27 CFR 30.24 - Specific gravity hydrometers.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 27 Alcohol, Tobacco Products and Firearms 1 2011-04-01 2011-04-01 false Specific gravity... BUREAU, DEPARTMENT OF THE TREASURY LIQUORS GAUGING MANUAL Gauging Instruments § 30.24 Specific gravity hydrometers. (a) The specific gravity hydrometers furnished by proprietors to appropriate TTB officers shall...

27 CFR 30.24 - Specific gravity hydrometers.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 27 Alcohol, Tobacco Products and Firearms 1 2014-04-01 2014-04-01 false Specific gravity... BUREAU, DEPARTMENT OF THE TREASURY ALCOHOL GAUGING MANUAL Gauging Instruments § 30.24 Specific gravity hydrometers. (a) The specific gravity hydrometers furnished by proprietors to appropriate TTB officers shall...

27 CFR 30.24 - Specific gravity hydrometers.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 27 Alcohol, Tobacco Products and Firearms 1 2013-04-01 2013-04-01 false Specific gravity... BUREAU, DEPARTMENT OF THE TREASURY ALCOHOL GAUGING MANUAL Gauging Instruments § 30.24 Specific gravity hydrometers. (a) The specific gravity hydrometers furnished by proprietors to appropriate TTB officers shall...

Ultrasonic hydrometer. [Specific gravity of electrolyte

DOEpatents

Swoboda, C.A.

1982-03-09

The disclosed ultrasonic hydrometer determines the specific gravity (density) of the electrolyte of a wet battery, such as a lead-acid battery. The hydrometer utilizes a transducer that when excited emits an ultrasonic impulse that traverses through the electrolyte back and forth between spaced sonic surfaces. The transducer detects the returning impulse, and means measures the time t between the initial and returning impulses. Considering the distance d between the spaced sonic surfaces and the measured time t, the sonic velocity V is calculated with the equation V = 2d/t. The hydrometer also utilizes a thermocouple to measure the electrolyte temperature. A hydrometer database correlates three variable parameters including sonic velocity in and temperature and specific gravity of the electrolyte, for temperature values between 0 and 40/sup 0/C and for specific gravity values between 1.05 and 1.30. Upon knowing two parameters (the calculated sonic velocity and the measured temperature), the third parameter (specific gravity) can be uniquely found in the database. The hydrometer utilizes a microprocessor for data storage and manipulation.

Calibration of hydrometers

NASA Astrophysics Data System (ADS)

Lorefice, Salvatore; Malengo, Andrea

2006-10-01

After a brief description of the different methods employed in periodic calibration of hydrometers used in most cases to measure the density of liquids in the range between 500 kg m-3 and 2000 kg m-3, particular emphasis is given to the multipoint procedure based on hydrostatic weighing, known as well as Cuckow's method. The features of the calibration apparatus and the procedure used at the INRiM (formerly IMGC-CNR) density laboratory have been considered to assess all relevant contributions involved in the calibration of different kinds of hydrometers. The uncertainty is strongly dependent on the kind of hydrometer; in particular, the results highlight the importance of the density of the reference buoyant liquid, the temperature of calibration and the skill of operator in the reading of the scale in the whole assessment of the uncertainty. It is also interesting to realize that for high-resolution hydrometers (division of 0.1 kg m-3), the uncertainty contribution of the density of the reference liquid is the main source of the total uncertainty, but its importance falls under about 50% for hydrometers with a division of 0.5 kg m-3 and becomes somewhat negligible for hydrometers with a division of 1 kg m-3, for which the reading uncertainty is the predominant part of the total uncertainty. At present the best INRiM result is obtained with commercially available hydrometers having a scale division of 0.1 kg m-3, for which the relative uncertainty is about 12 × 10-6.

Test Operations Procedure (TOP) 02-2-603A Vehicle Fuel Consumption

DTIC Science & Technology

2012-05-10

API) Hydrometer . The API Hydrometer is used for accurate determination of the density, relative density (specific gravity), or API gravity of... Hydrometer Method. 5. TOP 02-2-505, Inspection and Preliminary Operation of Vehicles, 4 February 1987. 6. TOP 02-1-003, Hybrid Electric

27 CFR 30.62 - Table 2, showing wine gallons and proof gallons by weight.

Code of Federal Regulations, 2010 CFR

2010-04-01

... spirituous liquor containing dissolved solids where the weight, apparent proof (hydrometer indication... table, from the weight of the liquid and the uncorrected reading of the hydrometer stem. An application... spirits having an uncorrected hydrometer reading of 113.0°. The full capacity of the package, 51.5 wine...

Automatic alignment method for calibration of hydrometers

NASA Astrophysics Data System (ADS)

Lee, Y. J.; Chang, K. H.; Chon, J. C.; Oh, C. Y.

2004-04-01

This paper presents a new method to automatically align specific scale-marks for the calibration of hydrometers. A hydrometer calibration system adopting the new method consists of a vision system, a stepping motor, and software to control the system. The vision system is composed of a CCD camera and a frame grabber, and is used to acquire images. The stepping motor moves the camera, which is attached to the vessel containing a reference liquid, along the hydrometer. The operating program has two main functions: to process images from the camera to find the position of the horizontal plane and to control the stepping motor for the alignment of the horizontal plane with a particular scale-mark. Any system adopting this automatic alignment method is a convenient and precise means of calibrating a hydrometer. The performance of the proposed method is illustrated by comparing the calibration results using the automatic alignment method with those obtained using the manual method.

Conflicts of Shared Resources: A Case Study of River Nile

DTIC Science & Technology

2012-03-22

as Lake Kivu. Rwanda joined the earlier Nile basin project, Hydromet , in 1967, with the support on the UNDP. 18 Although the country does not...operation Hydromet . In 1967, with the assistance of the United Nations Development Program (UNDP) and the World Meteorological Organization (WMO), Egypt...Kenya, Sudan, Tanzania and Uganda launched the Hydromet Survey project to regulate the water level of the Nile.”30 Rwanda joined later while Ethiopia

Demonstration of an In-Situ Friction-Sound Probe for Mapping Particle Size at Contaminated Sediment Sites

DTIC Science & Technology

2014-04-01

sedimentation according to the Stokes Law through pipettes (Plumb, 1981) or hydrometer (ASTM, 1988). Various optical techniques, electro-resistance (Coulter...used by the contracting laboratory (ASTM, 1998) is a combined mechanical sieving and hydrometer method. The sieves are used to quantify particle sizes...in the sand range (> 63 µm) and larger, and a sedimentation- hydrometer technique is used to quantify the silt and clay size ranges (< 63 µm

Ultrasonic hydrometer

DOEpatents

Swoboda, Carl A.

1984-01-01

The disclosed ultrasonic hydrometer determines the specific gravity (density) of the electrolyte of a wet battery, such as a lead-acid battery. The hydrometer utilizes a transducer that when excited emits an ultrasonic impulse that traverses through the electrolyte back and forth between spaced sonic surfaces. The transducer detects the returning impulse, and means measures the time "t" between the initial and returning impulses. Considering the distance "d" between the spaced sonic surfaces and the measured time "t", the sonic velocity "V" is calculated with the equation "V=2d/t". The hydrometer also utilizes a thermocouple to measure the electrolyte temperature. A hydrometer database correlates three variable parameters including sonic velocity in and temperature and specific gravity of the electrolyte, for temperature values between 0.degree. and 40.degree. C. and for specific gravity values between 1.05 and 1.30. Upon knowing two parameters (the calculated sonic velocity and the measured temperature), the third parameter (specific gravity) can be uniquely found in the database. The hydrometer utilizes a microprocessor for data storage and manipulation. The disclosed modified battery has a hollow spacer nub on the battery side wall, the sonic surfaces being on the inside of the nub and the electrolyte filling between the surfaces to the exclusion of intervening structure. An accessible pad exposed on the nub wall opposite one sonic surface allows the reliable placement thereagainst of the transducer.

27 CFR 19.980 - Gauging.

Code of Federal Regulations, 2010 CFR

2010-04-01

... quantity of spirits. The proof of the spirits shall be determined using a glass cylinder, hydrometer, and... determine quantity by volume. The proprietor shall ensure that hydrometers, thermometers, and other...

American Recovery and Reinvestment Act -- U.S. Army Corps of Engineers Mobile District Contractor Performance and Reporting Controls Were Generally Effective

DTIC Science & Technology

2012-01-06

Figure 2 shows the Supervisory Control and Data Acquisition and Hydromet Equipment at the Stennis Lock and Dam in Columbus. 3 Figure 2...Supervisory Control and Data Acquisition and Hydromet Equipment for the Waterway at the Stennis Lock and Dam • Tinker Air Force Base Project...Tennessee-Tombigbee Waterway, AL & MS W91278-10-C-0051 Upgrade of Supervisory Control and Data Acquisition and Hydromet Equipment for the Waterway

27 CFR 30.1 - Gauging of distilled spirits.

Code of Federal Regulations, 2010 CFR

2010-04-01

... correcting hydrometer indications at temperatures between 0 and 100 degrees Fahrenheit to true proof. If distilled spirits contain dissolved solids, temperature correction of the hydrometer reading by the use of...

27 CFR 30.41 - Bulk spirits.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 600 milligrams per 100 milliliters shall be ascertained by: (a) Use of a precision hydrometer and... wine gallons per pound, or (b) Use of a specific gravity hydrometer, in accordance with the provisions...

The Great Hydrometer Construction Contest!

ERIC Educational Resources Information Center

McGinnis, James Randy; Padilla, Michael J.

1991-01-01

The relationship between specific gravity, salinity, and density in brine solutions is investigated. Students construct hydrometers to reinforce concepts learned in oceanography. Background information, salt requirements for the unknowns, directions, and reproducible worksheets are included. (KR)

Range Atmospheric and Oceanic Environmental Support Capabilities

DTIC Science & Technology

2011-12-01

Precipitation location/intensity, thunderstorm location/intensity, rainfall/flash flood warning, hydrometer characterization, wind warnings, and...intensity, lightning monitoring, rainfall and flash flood warning, hydrometer characterization, and wind warnings. b. Satellite: MTSAT, GOES-10

7 CFR 51.3417 - Optional test for specific gravity.

Code of Federal Regulations, 2010 CFR

2010-01-01

... be corrected for temperature variations using Table I. (2) A hydrometer specifically designed for determining the specific gravity of potatoes. 3 3 The hydrometer is available from the Potato Chip/Snack Food...

27 CFR 30.32 - Determination of proof obscuration.

Code of Federal Regulations, 2010 CFR

2010-04-01

... added to the temperature corrected hydrometer reading will give the true proof. (c) Distillation method... use of a precision hydrometer and thermometer in accordance with the provisions of § 13.23 to the...

SHORT COMMUNICATION: An image processing approach to calibration of hydrometers

NASA Astrophysics Data System (ADS)

Lorefice, S.; Malengo, A.

2004-06-01

The usual method adopted for multipoint calibration of glass hydrometers is based on the measurement of the buoyancy by hydrostatic weighing when the hydrometer is plunged in a reference liquid up to the scale mark to be calibrated. An image processing approach is proposed by the authors to align the relevant scale mark with the reference liquid surface level. The method uses image analysis with a data processing technique and takes into account the perspective error. For this purpose a CCD camera with a pixel matrix of 604H × 576V and a lens of 16 mm focal length were used. High accuracy in the hydrometer reading was obtained as the resulting reading uncertainty was lower than 0.02 mm, about a fifth of the usual figure with the visual reading made by an operator.

A novel approach for estimating sugar and alcohol concentrations in wines using refractometer and hydrometer.

PubMed

Son, H S; Hong, Y S; Park, W M; Yu, M A; Lee, C H

2009-03-01

To estimate true Brix and alcoholic strength of must and wines without distillation, a novel approach using a refractometer and a hydrometer was developed. Initial Brix (I.B.), apparent refractometer Brix (A.R.), and apparent hydrometer Brix (A.H.) of must were measured by refractometer and hydrometer, respectively. Alcohol content (A) was determined with a hydrometer after distillation and true Brix (T.B.) was measured in distilled wines using a refractometer. Strong proportional correlations among A.R., A.H., T.B., and A in sugar solutions containing varying alcohol concentrations were observed in preliminary experiments. Similar proportional relationships among the parameters were also observed in must, which is a far more complex system than the sugar solution. To estimate T.B. and A of must during alcoholic fermentation, a total of 6 planar equations were empirically derived from the relationships among the experimental parameters. The empirical equations were then tested to estimate T.B. and A in 17 wine products, and resulted in good estimations of both quality factors. This novel approach was rapid, easy, and practical for use in routine analyses or for monitoring quality of must during fermentation and final wine products in a winery and/or laboratory.

27 CFR 30.31 - Determination of proof.

Code of Federal Regulations, 2010 CFR

2010-04-01

... milligrams of solids per 100 milliliters of spirits shall be determined by the use of a hydrometer and...) By the use of a hydrometer and a thermometer after the spirits have been distilled in a small...

Alignment of the measurement scale mark during immersion hydrometer calibration using an image processing system.

PubMed

Peña-Perez, Luis Manuel; Pedraza-Ortega, Jesus Carlos; Ramos-Arreguin, Juan Manuel; Arriaga, Saul Tovar; Fernandez, Marco Antonio Aceves; Becerra, Luis Omar; Hurtado, Efren Gorrostieta; Vargas-Soto, Jose Emilio

2013-10-24

The present work presents an improved method to align the measurement scale mark in an immersion hydrometer calibration system of CENAM, the National Metrology Institute (NMI) of Mexico, The proposed method uses a vision system to align the scale mark of the hydrometer to the surface of the liquid where it is immersed by implementing image processing algorithms. This approach reduces the variability in the apparent mass determination during the hydrostatic weighing in the calibration process, therefore decreasing the relative uncertainty of calibration.

Alignment of the Measurement Scale Mark during Immersion Hydrometer Calibration Using an Image Processing System

PubMed Central

Peña-Perez, Luis Manuel; Pedraza-Ortega, Jesus Carlos; Ramos-Arreguin, Juan Manuel; Arriaga, Saul Tovar; Fernandez, Marco Antonio Aceves; Becerra, Luis Omar; Hurtado, Efren Gorrostieta; Vargas-Soto, Jose Emilio

2013-01-01

The present work presents an improved method to align the measurement scale mark in an immersion hydrometer calibration system of CENAM, the National Metrology Institute (NMI) of Mexico, The proposed method uses a vision system to align the scale mark of the hydrometer to the surface of the liquid where it is immersed by implementing image processing algorithms. This approach reduces the variability in the apparent mass determination during the hydrostatic weighing in the calibration process, therefore decreasing the relative uncertainty of calibration. PMID:24284770

Hydrometer calibration by hydrostatic weighing with automated liquid surface positioning

NASA Astrophysics Data System (ADS)

Aguilera, Jesus; Wright, John D.; Bean, Vern E.

2008-01-01

We describe an automated apparatus for calibrating hydrometers by hydrostatic weighing (Cuckow's method) in tridecane, a liquid of known, stable density, and with a relatively low surface tension and contact angle against glass. The apparatus uses a laser light sheet and a laser power meter to position the tridecane surface at the hydrometer scale mark to be calibrated with an uncertainty of 0.08 mm. The calibration results have an expanded uncertainty (with a coverage factor of 2) of 100 parts in 106 or less of the liquid density. We validated the apparatus by comparisons using water, toluene, tridecane and trichloroethylene, and found agreement within 40 parts in 106 or less. The new calibration method is consistent with earlier, manual calibrations performed by NIST. When customers use calibrated hydrometers, they may encounter uncertainties of 370 parts in 106 or larger due to surface tension, contact angle and temperature effects.

A Low-Cost, Precision Hydrometer for Classroom Use.

ERIC Educational Resources Information Center

Murphy, Michael D.

1983-01-01

Describes a low cost hydrometer which can be assembled by students using stock laboratory items with a total retail cost of 17 cents. Includes list of required materials (with supplies) and experimental results on the instrument's accuracy. (JM)

27 CFR 30.23 - Use of precision hydrometers and thermometers.

Code of Federal Regulations, 2011 CFR

2011-04-01

... observed. Bulk spirits should be thoroughly agitated so that the test samples will be representative of the... should be inserted in the liquid and the hydrometer bulb raised and lowered from top to bottom 5 or 6...

Z-M in Lightning Forecasting

DTIC Science & Technology

2009-03-01

hydrometers create a charge separation. Inductive processes rely on a preexisting external electric field to induce charges on polarized particles, which...frozen hydrometers . A. FLORIDA CLIMATE Florida is often referred to as the lightning capital of the United States (Hodanish et al. 1997) or

Device Comparison for Determining Field Soil Moisture Content

DTIC Science & Technology

2011-11-01

properties. Tests conducted on each soil included grain size distribution with hydrometer analysis for dissemination of silt and clay fractions, Atterberg...ER D C/G SL TR -11-42 43 Clay-G ravel (SP-SC) - --- U.S, SIEVE OPENING II’! INCHES US. STANDIIRD SIEVE NUMBERS HYDROMETER Rln 1...STANOAR!l S<Eiil: NUMBERS HYDROMETER 1~1n. ~ln. 3/8.., o\\ ’ll """ """ li14ll"""’ fH, . , .. ~in. • 100 I I I’ I I l I ~ _u I I II 0 I I ~’r- ’Ŕ

Quantitative Precipitation Nowcasting: A Lagrangian Pixel-Based Approach

DTIC Science & Technology

2012-01-01

Sorooshian, T. Bellerby, and G. Huffman, 2010: REFAME: Rain Estimation Using Forward-Adjusted Advection of Microwave Estimates. J. of Hydromet ., 11...precipitation forecasting using information from radar and Numerical Weather Prediction models. J. of Hydromet ., 4(6):1168-1180. Germann, U., and I

27 CFR 30.21 - Requirements.

Code of Federal Regulations, 2012 CFR

2012-04-01

... thermometers furnished by the Government. However, where this part requires the use of a specific gravity hydrometer, TTB officers shall use precision grade specific gravity hydrometers conforming to the provisions... determination of specific gravity and for gauging. From time to time appropriate TTB officers shall verify the...

27 CFR 30.21 - Requirements.

Code of Federal Regulations, 2014 CFR

2014-04-01

... thermometers furnished by the Government. However, where this part requires the use of a specific gravity hydrometer, TTB officers shall use precision grade specific gravity hydrometers conforming to the provisions... determination of specific gravity and for gauging. From time to time appropriate TTB officers shall verify the...

27 CFR 30.21 - Requirements.

Code of Federal Regulations, 2011 CFR

2011-04-01

... thermometers furnished by the Government. However, where this part requires the use of a specific gravity hydrometer, TTB officers shall use precision grade specific gravity hydrometers conforming to the provisions... determination of specific gravity and for gauging. From time to time appropriate TTB officers shall verify the...

27 CFR 30.21 - Requirements.

Code of Federal Regulations, 2013 CFR

2013-04-01

... thermometers furnished by the Government. However, where this part requires the use of a specific gravity hydrometer, TTB officers shall use precision grade specific gravity hydrometers conforming to the provisions... determination of specific gravity and for gauging. From time to time appropriate TTB officers shall verify the...

Evaluation of a Non-Nuclear Soil Density Gauge on Fine-Grained Soils

DTIC Science & Technology

2013-05-01

U.S. STANDARD SIEVE NUMBERS HYDROMETER fY, in o/. in. 318 in #140 6 in. 3 in. 2 in. 1 in. ’A in #4 ’" #20 #30 #40 ឬ #100 #200 100 J I ’ I I I I I...1 3-20 31 C L-2 U.S. SIEVE OPENING IN INCHES U.S. STANDARD SIEVE NUMBERS HYDROMETER 1Y,in. ’/.in Un~/8 in #140 6 in 3 in. 2 in. 1in. " #4...Particle Size Distribution Reoort Fine PL 14 HYDROMETER %Fines Silt -------,---- PI Project Non-Nuclear Gau_ge Proiect 27 Area Boring No. 3 Date

27 CFR 30.64 - Table 4, showing the fractional part of a gallon per pound at each percent and each tenth percent...

Code of Federal Regulations, 2010 CFR

2010-04-01

... of the liquid and its apparent proof (hydrometer indication, corrected to 60 degrees Fahrenheit). The... of blended whisky containing added solids Temperature °F 75.0° Hydrometer reading 92.0° Apparent...

Toward Better Intraseasonal and Seasonal Prediction: Verification and Evaluation of the NOGAPS Model Forecasts

DTIC Science & Technology

2012-09-30

package developed by the Cloud Feedback Model Intercomparison Project (CFMIP), COSP (BODAS- SALCEDO et al. 2011). COSP will convert the model hydrometers ...and infrared data at high spatial and temporal resolution. J. Hydromet ., 5, 487-503. Kay, J. E. et al., 2012: Exposing global cloud biases in the

Comparison on the calibrations of hydrometers for liquids density determination between SIM laboratories

NASA Astrophysics Data System (ADS)

Morales, Abed; Quiroga, Aldo; Daued, Arturo; Cantero, Diana; Sequeira, Francisco; Castro, Luis Carlos; Becerra, Luis Omar; Salazar, Manuel; Vega, Maria

2017-01-01

A supplementary comparison was made between SIM laboratories concerning the calibration of four hydrometers within the range of 600 kg/m3 to 2000 kg/m3. The main objectives of the comparison were to evaluate the degree of equivalences SIM NMIs in the calibration of hydrometers of high accuracy. The participant NMIs were: CENAM, IBMETRO, INEN, INDECOPI, INM, INTN and LACOMET. Main text To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database kcdb.bipm.org/. The final report has been peer-reviewed and approved for publication by the CCM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).

Comparison of four methods to assess colostral IgG concentration in dairy cows.

PubMed

Chigerwe, Munashe; Tyler, Jeff W; Middleton, John R; Spain, James N; Dill, Jeffrey S; Steevens, Barry J

2008-09-01

To determine sensitivity and specificity of 4 methods to assess colostral IgG concentration in dairy cows and determine the optimal cutpoint for each method. Cross-sectional study. 160 Holstein dairy cows. 171 composite colostrum samples collected within 2 hours after parturition were used in the study. Test methods used to estimate colostral IgG concentration consisted of weight of the first milking, 2 hydrometers, and an electronic refractometer. Results of the test methods were compared with colostral IgG concentration determined by means of radial immunodiffusion. For each method, sensitivity and specificity for detecting colostral IgG concentration < 50 g/L were calculated across a range of potential cutpoints, and the optimal cutpoint for each test was selected to maximize sensitivity and specificity. At the optimal cutpoint for each method, sensitivity for weight of the first milking (0.42) was significantly lower than sensitivity for each of the other 3 methods (hydrometer 1, 0.75; hydrometer 2, 0.76; refractometer, 0.75), but no significant differences were identified among the other 3 methods with regard to sensitivity. Specificities at the optimal cutpoint were similar for all 4 methods. Results suggested that use of either hydrometer or the electronic refractometer was an acceptable method of screening colostrum for low IgG concentration; however, the manufacturer-defined scale for both hydrometers overestimated colostral IgG concentration. Use of weight of the first milking as a screening test to identify bovine colostrum with inadequate IgG concentration could not be justified because of the low sensitivity.

Assessment of different methods to estimate bovine colostrum quality on farm.

PubMed

Bartens, M-C; Drillich, M; Rychli, K; Iwersen, M; Arnholdt, T; Meyer, L; Klein-Jöbstl, D

2016-09-01

To evaluate two different hydrometers and an optical and a digital Brix refractometer for the assessment of bovine colostrum quality, in terms of accuracy and precision compared with the measurement of IgG concentrations using radial immunodiffusion (RID), and to evaluate the reliability and repeatability of the Brix refractometers. To determine reliability and repeatability, 145 colostrum samples were tested by two independent observers twice, using the optical and digital Brix refractometers. A further 193 colostrum samples from Holstein cows were collected on one commercial dairy farm at first milking and tested with two hydrometers and an optical and digital Brix refractometer. An aliquot of each sample was frozen for RID measurement of IgG concentrations and samples were classified as poor (≤50 g IgG/L) or good (>50 g IgG/L) quality colostrum. Intraclass correlation coefficients (ICC) were used to determine inter- and intra-observer reliability and repeatability. Optimised cut-off values for the four devices were determined using receiver operating characteristics (ROC) analysis with the RID results as the reference. Using these cut-offs, sensitivities and specificities for determining good quality colostrum were calculated. The ICC for inter-observer reliability was 0.98 for the optical Brix refractometer, and for intra-observer repeatability was 0.97 and 0.98 for the optical and the digital Brix refractometers, respectively. For the 193 colostrum samples, 67 (34.7%) had concentrations of IgG ≤50 g/L determined by RID. Optimised cut-off values evaluated by ROC analysis were higher for all devices compared with manufacturer reference or previously published values. Using these values, the sensitivities for the two hydrometers, and the optical and the digital Brix refractometers were 0.73, 0.71, 0.56 and 0.79, respectively; specificities were 0.72, 0.61, 0.90 and 0.69, respectively. The Brix refractometers provided the most accurate assessment of colostrum quality of the devices evaluated, and demonstrated excellent precision in terms of repeatability. To provide optimal health for newborn calves, a sufficient intake of good quality colostrum is essential. The Brix refractometers provide rapid, convenient tools for classification of colostrum quality.

SUPPLEMENTARY COMPARISON: Report of the bilateral comparison of the calibrations of hydrometers for liquid density determination between CENAM-Mexico and INRIM-Italy: SIM.M.D-S1

NASA Astrophysics Data System (ADS)

Becerra, Luis Omar; Lorefice, Salvatore

2009-01-01

Hydrometers are instruments usually made of glass which are widely used for different levels of precision to measure liquid density and related quantities to control different products and processes. This bilateral comparison on the calibration of hydrometers shows that results reported by CENAM-Mexico and INRIM-Italy are consistent within the claimed uncertainty in the range of 800 kg/m3 to 1200 kg/m3. This bilateral comparison is intended to link the two regional comparisons SIM.M.D-K4 and EURAMET.D-K4. Main text. To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database kcdb.bipm.org/. The final report has been peer-reviewed and approved for publication by SIM, according to the provisions of the CIPM Mutual Recognition Arrangement (MRA).

A High Resolution Hydrometer Phase Classifier Based on Analysis of Cloud Radar Doppler Spectra.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Luke,E.; Kollias, P.

2007-08-06

The lifecycle and radiative properties of clouds are highly sensitive to the phase of their hydrometeors (i.e., liquid or ice). Knowledge of cloud phase is essential for specifying the optical properties of clouds, or else, large errors can be introduced in the calculation of the cloud radiative fluxes. Current parameterizations of cloud water partition in liquid and ice based on temperature are characterized by large uncertainty (Curry et al., 1996; Hobbs and Rangno, 1998; Intriery et al., 2002). This is particularly important in high geographical latitudes and temperature ranges where both liquid droplets and ice crystal phases can exist (mixed-phasemore » cloud). The mixture of phases has a large effect on cloud radiative properties, and the parameterization of mixed-phase clouds has a large impact on climate simulations (e.g., Gregory and Morris, 1996). Furthermore, the presence of both ice and liquid affects the macroscopic properties of clouds, including their propensity to precipitate. Despite their importance, mixed-phase clouds are severely understudied compared to the arguably simpler single-phase clouds. In-situ measurements in mixed-phase clouds are hindered due to aircraft icing, difficulties distinguishing hydrometeor phase, and discrepancies in methods for deriving physical quantities (Wendisch et al. 1996, Lawson et al. 2001). Satellite-based retrievals of cloud phase in high latitudes are often hindered by the highly reflecting ice-covered ground and persistent temperature inversions. From the ground, the retrieval of mixed-phase cloud properties has been the subject of extensive research over the past 20 years using polarization lidars (e.g., Sassen et al. 1990), dual radar wavelengths (e.g., Gosset and Sauvageot 1992; Sekelsky and McIntosh, 1996), and recently radar Doppler spectra (Shupe et al. 2004). Millimeter-wavelength radars have substantially improved our ability to observe non-precipitating clouds (Kollias et al., 2007) due to their excellent sensitivity that enables the detection of thin cloud layers and their ability to penetrate several non-precipitating cloud layers. However, in mixed-phase clouds conditions, the observed Doppler moments are dominated by the highly reflecting ice crystals and thus can not be used to identify the cloud phase. This limits our ability to identify the spatial distribution of cloud phase and our ability to identify the conditions under which mixed-phase clouds form.« less

Hydrometer in the mantle: dln(Vs)/dln(Vp)

NASA Astrophysics Data System (ADS)

Li, L.; Weidner, D. J.

2010-12-01

The absorption of water into nominally non-hydrous phases is the probable storage mechanism of hydrogen throughout most of the mantle. Thus the water capacity in the mantle is greatest in the transition zone owing to the large water-solubility of ringwoodite and wadsleyite. However, the actual amount of water that is stored there is highly uncertain. Since water is probably brought down by subduction activity, it’s abundance is probably laterally variable. Thus, a metric that is sensitive to variations of water content are good candidates for hydrometers. Here we evaluate the parameter, dln(Vs)/dln(Vp), as such a parameter. It is useful to detect lateral variations of water if the effects of hydration on the parameter are different than those of temperature or composition. We compare the value of dln(Vs)/dln(Vp) due to the temperature with that due to the water content as a function of depth for the upper mantle. We have calculated dln(Vs)/dln(Vp) due to both water and temperature using a density functional theory approach, and available experimental data. Our results indicate that dln(Vs)/dln(Vp) due to water is distinguishable from dln(Vs)/dln(Vp) due to temperature or variations in iron content, particularly in ringwoodite. The difference increases with depth and making the lower part of the transition zone most identifiable as a water reservoir.

Settling characteristics of nursery pig manure and nutrient estimation by the hydrometer method.

PubMed

Zhu, Jun; Ndegwa, Pius M; Zhang, Zhijian

2003-05-01

The hydrometer method to measure manure specific gravity and subsequently relate it to manure nutrient contents was examined in this study. It was found that this method might be improved in estimation accuracy if only manure from a single growth stage of pigs was used (e.g., nursery pig manure used here). The total solids (TS) content of the test manure was well correlated with the total nitrogen (TN) and total phosphorus (TP) concentrations in the manure, with highly significant correlation coefficients of 0.9944 and 0.9873, respectively. Also observed were good linear correlations between the TN and TP contents and the manure specific gravity (correlation coefficients: 0.9836 and 0.9843, respectively). These correlations were much better than those reported by past researchers, in which lumped data for pigs at different growing stages were used. It may therefore be inferred that developing different linear equations for pigs at different ages should improve the accuracy in manure nutrient estimation using a hydrometer. Also, the error of using the hydrometer method to estimate manure TN and TP was found to increase, from +/- 10% to +/- 50%, with the decrease in TN (from 700 ppm to 100 ppm) and TP (from 130 ppm to 30 ppm) concentrations in the manure. The estimation errors for TN and TP may be larger than 50% if the total solids content is below 0.5%. In addition, the rapid settling of solids has long been considered characteristic of swine manure; however, in this study, the solids settling property appeared to be quite poor for nursery pig manure in that no conspicuous settling occurred after the manure was left statically for 5 hours. This information has not been reported elsewhere in the literature and may need further research to verify.

Wavelet-based image analysis system for soil texture analysis

NASA Astrophysics Data System (ADS)

Sun, Yun; Long, Zhiling; Jang, Ping-Rey; Plodinec, M. John

2003-05-01

Soil texture is defined as the relative proportion of clay, silt and sand found in a given soil sample. It is an important physical property of soil that affects such phenomena as plant growth and agricultural fertility. Traditional methods used to determine soil texture are either time consuming (hydrometer), or subjective and experience-demanding (field tactile evaluation). Considering that textural patterns observed at soil surfaces are uniquely associated with soil textures, we propose an innovative approach to soil texture analysis, in which wavelet frames-based features representing texture contents of soil images are extracted and categorized by applying a maximum likelihood criterion. The soil texture analysis system has been tested successfully with an accuracy of 91% in classifying soil samples into one of three general categories of soil textures. In comparison with the common methods, this wavelet-based image analysis approach is convenient, efficient, fast, and objective.

Manure sampling procedures and nutrient estimation by the hydrometer method for gestation pigs.

PubMed

Zhu, Jun; Ndegwa, Pius M; Zhang, Zhijian

2004-05-01

Three manure agitation procedures were examined in this study (vertical mixing, horizontal mixing, and no mixing) to determine the efficacy of producing a representative manure sample. The total solids content for manure from gestation pigs was found to be well correlated with the total nitrogen (TN) and total phosphorus (TP) concentrations in the manure, with highly significant correlation coefficients of 0.988 and 0.994, respectively. Linear correlations were observed between the TN and TP contents and the manure specific gravity (correlation coefficients: 0.991 and 0.987, respectively). Therefore, it may be inferred that the nutrients in pig manure can be estimated with reasonable accuracy by measuring the liquid manure specific gravity. A rapid testing method for manure nutrient contents (TN and TP) using a soil hydrometer was also evaluated. The results showed that the estimating error increased from +/-10% to +/-30% with the decrease in TN (from 1000 to 100 ppm) and TP (from 700 to 50 ppm) concentrations in the manure. Data also showed that the hydrometer readings had to be taken within 10 s after mixing to avoid reading drift in specific gravity due to the settling of manure solids.

Three-dimensional aspects of radiative transfer in remote sensing of precipitation: Application to the 1986 COHMEX storm

NASA Technical Reports Server (NTRS)

Haferman, J. L.; Krajewski, W. F.; Smith, T. F.

1994-01-01

Several multifrequency techniques for passive microwave estimation of precipitation based on the absorption and scattering properties of hydrometers have been proposed in the literature. In the present study, plane-parallel limitations are overcome by using a model based on the discrete-ordinates method to solve the radiative transfer equation in three-dimensional rectangular domains. This effectively accounts for the complexity and variety of radiation problems encountered in the atmosphere. This investigation presents result for plane-parallel and three-dimensional radiative transfer for a precipitating system, discusses differences between these results, and suggests possible explanations for these differences. Microphysical properties were obtained from the Colorado State University Regional Atmospehric Modeling System and represent a hailstorm observed during the 1986 Cooperative Huntsville Meteorological Experiment. These properties are used as input to a three-dimensional radiative transfer model in order to simulate satellite observation of the storm. The model output consists of upwelling brightness temperatures at several of the frequencies on the Special Sensor Microwave/Imager. The radiative transfer model accounts for scattering and emission of atmospheric gases and hydrometers in liquid and ice phases. Brightness temperatures obtained from the three-dimensional model of this investigation indicate that horizontal inhomogeneities give rise to brightness temperature fields that can be quite different from fields obtained using plane-parallel radiative transfer theory. These differences are examined for various resolutions of the satellite sensor field of view. In adddition, the issue of boundary conditions for three-dimensional atmospheric radiative transfer is addressed.

Supplement to CCM.D-K4 'Hydrometer' report: linkage of EURAMET.M.D-K4 comparison, SIM.M.D-K4 comparison and the supplementary SIM.M.D-S2 to CCM.D-K4 'Hydrometer'

NASA Astrophysics Data System (ADS)

Lorefice, S.; Becerra, L. O.

2017-01-01

Evaluation of different types of comparisons to a common set of reference values of a CIPM key comparison is essential to satisfy the concept of the CIPM Mutual Recognition Arrangement (CIPM MRA), where the DoEs of any participant who took part in comparisons should be within the Calibration and Measurement Capability (CMC) section of the CIPM MRA Key Comparison Data Base. The subject of this supplementary report is therefore to present the equivalence of each National Metrological Institute (NMI) participant in the CCM.D-K4 'Hydrometer' key comparison, which was performed in the density range 600 kg/m3 to 2000 kg/m3 at the temperature of 20 °C, and the linkage of the European and Inter-American NMI results performed in the RMO.M.D-K4 comparisons as well as those of the supplementary SIM.M.D-S2 to the common set of KCRVs of the CCM.D-K4 'Hydrometer'. The linking procedure has been obtained by numerical simulation, based on the Monte Carlo method, in which the differences in the results of the different comparison between the intended laboratory and one or more linking laboratory/ies, which took part in both comparisons, are correlated with a continuous function describing the DoEs of the linking laboratory/ies with respect to the common set of KCRVs of the CCM.D-K4. Main text To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database kcdb.bipm.org/. The final report has been peer-reviewed and approved for publication by the CCM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).

The role of updraft velocity in temporal variability of cloud hydrometeor number

NASA Astrophysics Data System (ADS)

Sullivan, Sylvia; Nenes, Athanasios; Lee, Dong Min; Oreopoulos, Lazaros

2016-04-01

Significant effort has been dedicated to incorporating direct aerosol-cloud links, through parameterization of liquid droplet activation and ice crystal nucleation, within climate models. This significant accomplishment has generated the need for understanding which parameters affecting hydrometer formation drives its variability in coupled climate simulations, as it provides the basis for optimal parameter estimation as well as robust comparison with data, and other models. Sensitivity analysis alone does not address this issue, given that the importance of each parameter for hydrometer formation depends on its variance and sensitivity. To address the above issue, we develop and use a series of attribution metrics defined with adjoint sensitivities to attribute the temporal variability in droplet and crystal number to important aerosol and dynamical parameters. This attribution analysis is done both for the NASA Global Modeling and Assimilation Office Goddard Earth Observing System Model, Version 5 and the National Center for Atmospheric Research Community Atmosphere Model Version 5.1. Within the GEOS simulation, up to 48% of temporal variability in output ice crystal number and 61% in droplet number can be attributed to input updraft velocity fluctuations, while for the CAM simulation, they explain as much as 89% of the ice crystal number variability. This above results suggest that vertical velocity in both model frameworks is seen to be a very important (or dominant) driver of hydrometer variability. Yet, observations of vertical velocity are seldomly available (or used) to evaluate the vertical velocities in simulations; this strikingly contrasts the amount and quality of data available for aerosol-related parameters. Consequentially, there is a strong need for retrievals or measurements of vertical velocity for addressing this important knowledge gap that requires a significant investment and effort by the atmospheric community. The attribution metrics as a tool of understanding for hydrometer variability can be instrumental for understanding the source of differences between models used for aerosol-cloud-climate interaction studies.

The structure and phase of cloud tops as observed by polarization lidar

NASA Technical Reports Server (NTRS)

Spinhirne, J. D.; Hansen, M. Z.; Simpson, J.

1983-01-01

High-resolution observations of the structure of cloud tops have been obtained with polarization lidar operated from a high altitude aircraft. Case studies of measurements acquired from cumuliform cloud systems are presented, two from September 1979 observations in the area of Florida and adjacent waters and a third during the May 1981 CCOPE experiment in southeast Montana. Accurate cloud top height structure and relative density of hydrometers are obtained from the lidar return signal intensity. Correlation between the signal return intensity and active updrafts was noted. Thin cirrus overlying developing turrets was observed in some cases. Typical values of the observed backscatter cross section were 0.1-5 (km/sr) for cumulonimbus tops. The depolarization ratio of the lidar signals was a function of the thermodynamic phase of cloud top areas. An increase of the cloud top depolarization with decreasing temperature was found for temperatures above and below -40 C.

Qualitative identification of rigid gas permeable contact lens materials by densitometry.

PubMed

Arce, C G; Schuman, P D; Schuman, W P

1999-10-01

We describe a practical method to qualitatively identify polymethylmethacrylate (PMMA) and rigid gas permeable (RGP) contact lens materials. By progressive dilution of a saturated saline solution made with distilled or tap water and sodium chloride, we recorded comparative densitometry of rigid contact lens materials using a small hydrometer or by liquid displacement. The method was sensitive enough to separate the polymethylmethacrylate, all silicon-methacrylates, and all but two fluorine-containing silicon-methacrylates. The hydrometer had a precision of three decimals rounded to the nearest 0.005. There was only one RGP product that could have been confused with the PMMA material. Most silicon-methacrylates had lower densities than fluorine containing silicon-methacrylates. Only four of 25 products under 1.117 gm/cm3 contained fluorine. Densitometry with a hydrometer is an effective non-destructive method to identify RGP materials and to verify their quality. The method is easier when lens blanks are tested, but in spite of differences in shape, size, and weight, densitometry may also be used with new or used contact lenses. Its simplicity and low cost makes densitometry feasible for any contact lens laboratory or clinic to use on a routine basis. Only silicon-methacrylates had an inverse relationship between density and oxygen permeability. As the silicon content of the contact lens increases, the Dk increases and the density decreases.

Comparison of 3 Methods to Assess Urine Specific Gravity in Collegiate Wrestlers.

PubMed

Stuempfle, Kristin J.; Drury, Daniel G.

2003-12-01

OBJECTIVE: To investigate the reliability and validity of refractometry, hydrometry, and reagent strips in assessing urine specific gravity in collegiate wrestlers. DESIGN AND SETTING: We assessed the reliability of refractometry, hydrometry, and reagent strips between 2 trials and among 4 testers. The validity of hydrometry and reagent strips was assessed by comparison with refractometry, the criterion measure for urine specific gravity. SUBJECTS: Twenty-one National Collegiate Athletic Association Division III collegiate wrestlers provided fresh urine samples. MEASUREMENTS: Four testers measured the specific gravity of each urine sample 6 times: twice by refractometry, twice by hydrometry, and twice by reagent strips. RESULTS: Refractometer measurements were consistent between trials (R =.998) and among testers; hydrometer measurements were consistent between trials (R =.987) but not among testers; and reagent-strip measurements were not consistent between trials or among testers. Hydrometer (1.018 +/- 0.006) and reagent-strip (1.017 +/- 0.007) measurements were significantly higher than refractometer (1.015 +/- 0.006) measurements. Intraclass correlation coefficients were moderate between refractometry and hydrometry (R =.869) and low between refractometry and reagent strips (R =.573). The hydrometer produced 28% false positives and 2% false negatives, and reagent strips produced 15% false positives and 9% false negatives. CONCLUSIONS: Only the refractometer should be used to determine urine specific gravity in collegiate wrestlers during the weight-certification process.

Comparison of 3 Methods to Assess Urine Specific Gravity in Collegiate Wrestlers

PubMed Central

Drury, Daniel G.

2003-01-01

Objective: To investigate the reliability and validity of refractometry, hydrometry, and reagent strips in assessing urine specific gravity in collegiate wrestlers. Design and Setting: We assessed the reliability of refractometry, hydrometry, and reagent strips between 2 trials and among 4 testers. The validity of hydrometry and reagent strips was assessed by comparison with refractometry, the criterion measure for urine specific gravity. Subjects: Twenty-one National Collegiate Athletic Association Division III collegiate wrestlers provided fresh urine samples. Measurements: Four testers measured the specific gravity of each urine sample 6 times: twice by refractometry, twice by hydrometry, and twice by reagent strips. Results: Refractometer measurements were consistent between trials (R = .998) and among testers; hydrometer measurements were consistent between trials (R = .987) but not among testers; and reagent-strip measurements were not consistent between trials or among testers. Hydrometer (1.018 ± 0.006) and reagent-strip (1.017 ± 0.007) measurements were significantly higher than refractometer (1.015 ± 0.006) measurements. Intraclass correlation coefficients were moderate between refractometry and hydrometry (R = .869) and low between refractometry and reagent strips (R = .573). The hydrometer produced 28% false positives and 2% false negatives, and reagent strips produced 15% false positives and 9% false negatives. Conclusions: Only the refractometer should be used to determine urine specific gravity in collegiate wrestlers during the weight-certification process. PMID:14737213

40 CFR 92.5 - Reference materials.

Code of Federal Regulations, 2012 CFR

2012-07-01

..., or at http://www.ansi.org. (1) ANSI B109.1-1992, Diaphragm Type Gas Displacment Meters, IBR approved..., Standard Test Method for API Gravity of Crude Petroleum and Petroleum Products (Hydrometer Method), IBR...

40 CFR 92.5 - Reference materials.

Code of Federal Regulations, 2013 CFR

2013-07-01

..., or at http://www.ansi.org. (1) ANSI B109.1-1992, Diaphragm Type Gas Displacment Meters, IBR approved..., Standard Test Method for API Gravity of Crude Petroleum and Petroleum Products (Hydrometer Method), IBR...

40 CFR 92.5 - Reference materials.

Code of Federal Regulations, 2014 CFR

2014-07-01

..., or at http://www.ansi.org. (1) ANSI B109.1-1992, Diaphragm Type Gas Displacment Meters, IBR approved..., Standard Test Method for API Gravity of Crude Petroleum and Petroleum Products (Hydrometer Method), IBR...

KEY COMPARISON: Final report of comparison of the calibrations of hydrometers for liquid density determination between SIM laboratories: SIM.M.D-K4

NASA Astrophysics Data System (ADS)

Becerra, Luis Omar

2009-01-01

This SIM comparison on the calibration of high accuracy hydrometers was carried out within fourteen laboratories in the density range from 600 kg/m3 to 1300 kg/m3 in order to evaluate the degree of equivalence among participant laboratories. This key comparison anticipates the planned key comparison CCM.D-K4, and is intended to be linked with CCM.D-K4 when results are available. Main text. To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database kcdb.bipm.org/. The final report has been peer-reviewed and approved for publication by the CCM, according to the provisions of the CIPM Mutual Recognition Arrangement (MRA).

SUPPLEMENTARY COMPARISON Bilateral comparison on the calibrations of hydrometers for liquid density between INRIM-Italy and INMETRO-Brazil: SIM.M.D-S2

NASA Astrophysics Data System (ADS)

Lorefice, Salvatore; Malta, Dalni; Julio Pinheiro, José; Marteleto, Paulo Roberto

2010-01-01

The results of the SIM.M.D-S2 bilateral comparison between INRIM-Italy and INMETRO-Brazil are summarized in this report. The aims of this comparison were to check the stated uncertainty levels and the degrees of equivalence between the two institutes on the calibration of hydrometers for liquid density in the range of 800 kg m-3 to 1000 kg m-3 at 20 ºC, by means of two transfer standards of excellent metrological characteristics. Main text. To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database kcdb.bipm.org/. The final report has been peer-reviewed and approved for publication by SIM, according to the provisions of the CIPM Mutual Recognition Arrangement (MRA).

Evaluation of Minimum Asphalt Concrete Thickness Criteria

DTIC Science & Technology

2008-10-01

9 Figure 6. Dry density versus moisture content for CH material... density measurements. ............................ 24 Figure 18. EPC installation in a crushed gravel base course layer...Construction Materials Materials Characterization Laboratory Testing Field Testing Test Section Construction Hydrometer, Modified Proctor , Specific

Cloud Ice: A Climate Model Challenge With Signs and Expectations of Progress

NASA Astrophysics Data System (ADS)

Li, F.; Waliser, D.; Bacmeister, J.; Chern, J.; Del Genio, T.; Jiang, J.; Kharitondov, M.; Liou, K.; Meng, H.; Minnis, P.; Rossow, B.; Stephens, G.; Sun-Mack, S.; Tao, W.; Vane, D.; Woods, C.; Tompkins, A.; Wu, D.

2007-12-01

Global climate models (GCMs), including those assessed in the IPCC AR4, exhibit considerable disagreement in the amount of cloud ice - both in terms of the annual global mean as well as their spatial variability. Global measurements of cloud ice have been difficult due to the challenges involved in remotely sensing ice water content (IWC) and its vertical profile - including complications associated with multi-level clouds, mixed-phases and multiple hydrometer types, the uncertainty in classifying ice particle size and shape for remote retrievals, and the relatively small time and space scales associated with deep convection. Together, these measurement difficulties make it a challenge to characterize and understand the mechanisms of ice cloud formation and dissipation. Fortunately, there are new observational resources recently established that can be expected to lead to considerable reduction in the observational uncertainties of cloud ice, and in turn improve the fidelity of model representations. Specifically, these include the Microwave Limb Sounder (MLS) on the Earth Observing System (EOS) Aura satellite, and the CloudSat and Calipso satellite missions, all of which fly in formation in what is referred to as the A-Train. Based on radar and limb-sounding techniques, these new satellite measurements provide a considerable leap forward in terms of the information gathered regarding upper-tropospheric cloud IWC as well as other macrophysical and microphysical properties. In this presentation, we describe the current state of GCM representations of cloud ice and their associated uncertainties, the nature of the new observational resources for constraining cloud ice values in GCMs, the challenges in making model-data comparisons with these data resources, and prospects for near-term improvements in model representations.

KEY COMPARISON: EUROMET.M.D-K4/EUROMET Project 702: Comparison of the calibrations of high-resolution hydrometers for liquid density determinations

NASA Astrophysics Data System (ADS)

Lorefice, S.; Malengo, A.; Vámossy, C.; Bettin, H.; Toth, H.; do Céu Ferreira, M.; Gosset, A.; Madec, T.; Heinonen, M.; Buchner, C.; Lenard, E.; Spurny, R.; Akcadag, U.; Domostroeva, N.

2008-01-01

The main objective of the EUROMET project 702 was to compare the extent of comparability among eleven participating European national metrology institutes (INRIM (IT), OMH (HU), PTB (DE), BEV (AT), IPQ (PT), LNE (FR), MIKES (FI), GUM (PL), SMU (SK), UME (TR) and VNIIM (RU)) in performing calibrations of high-resolution hydrometers for liquid density determination in the range between 600 kg m-3 and 1300 kg m-3. By means of two groups of four similar transfer standards of excellent metrological characteristics, the participating laboratories were initially divided into two groups (petals) linked by the three density laboratories of INRIM, OMH and PTB. The results of the participating laboratories have been analyzed in this report and a good agreement was found between the results provided by most of the participants. These results allowed also determination of the degrees of equivalence of each NMI participating with the EUROMET_key comparison reference values (EU_KCRV); they will provide a basis for the review of the Calibration Measurement Capabilities (CMC) entries on hydrometer calibration, and they allowed the degree of equivalence between pairs of NMIs to be established. The Istitituto Nazionale di Ricerca Metrologica (INRIM), Italy, formerly IMGC-CNR, coordinated the project. Main text. To reach the main text of this Paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database kcdb.bipm.org/. The final report has been peer-reviewed and approved for publication by the CCM, according to the provisions of the CIPM Mutual Recognition Arrangement (MRA).

On-farm quick tests for estimating nitrogen in dairy manure.

PubMed

Van Kessel, J S; Reeves, J B

2000-08-01

Manure nutrient analyses performed rapidly on the farm could be useful for nutrient management programs. The objective of this experiment was to evaluate six quick tests for their accuracy in estimating total manure N or NH4+-N. The quick tests included the hydrometer, electrical conductivity meter and pen, reflectometer, Agros N Meter, and Quantofix-N-Volumeter. The hydrometer was used to estimate total N, while the remaining tests were used to estimate NH4+-N. Samples (107) were collected from dairy farms in five northeastern states. Samples were analyzed for total N and NH4+-N by traditional laboratory methods and using each of the quick tests. Manure compositions ranged from 1.4 to 38.6% dry matter (DM), 0.9 to 9.5 kg/m3 total N, and 0.3 to 4.7 kg/m3 NH4+-N. The estimated concentration of total N or NH4+-N determined by each quick test was regressed against laboratory-determined values. The hydrometer did not estimate total N accurately. The strongest relationship for estimation of NH4+-N was with the Quantofix-N-Volumeter followed by the Agros N Meter, the reflectometer, and the electrical conductivity meter and pen. When the samples were split into high (>12%) and low (< or =12%) DM groups, in all cases the r2 for the regression equation was higher for the low DM group than for the high DM group. The Agros N Meter, the reflectometer, and the conductivity meter and pen did not perform well for the high DM group. These data indicate that several quick tests are viable options for measuring NH4+-N concentrations in dairy slurries and solids.

27 CFR 30.1 - Gauging of distilled spirits.

Code of Federal Regulations, 2011 CFR

2011-04-01

... “Gauging Manual Embracing Instructions and Tables for Determining Quantity of Distilled Spirits by Proof... tables, together with their instructions, shall be used, wherever applicable, in making the necessary... distilled spirits contain dissolved solids, temperature correction of the hydrometer reading by the use of...

Soil texture classification algorithm using RGB characteristics of soil images

USDA-ARS?s Scientific Manuscript database

Soil texture has an important influence on agriculture, affecting crop selection, movement of nutrients and water, soil electrical conductivity, and crop growth. Soil texture has traditionally been determined in the laboratory using pipette and hydrometer methods that require a considerable amount o...

National Forecast Charts

Science.gov Websites

Summaries Heat Index Tropical Products Daily Weather Map GIS Products Current Watches/ Warnings Satellite and Training WPC HydroMet Testbed Development Experimental Products WPC Overview About the WPC Mission and Vision Staff WPC History About Our Products Accomplishments Other Sites FAQs Meteorological

A simple formula for predicting claw volume of cattle.

PubMed

Scott, T D; Naylor, J M; Greenough, P R

1999-11-01

The object of this study was to develop a simple method for accurately calculating the volume of bovine claws under field conditions. The digits of 30 slaughterhouse beef cattle were examined and the following four linear measurements taken from each pair of claws: (1) the length of the dorsal surface of the claw (Toe); (2) the length of the coronary band (CorBand); (3) the length of the bearing surface (Base); and (4) the height of the claw at the abaxial groove (AbaxGr). Measurements of claw volume using a simple hydrometer were highly repeatable (r(2)= 0.999) and could be calculated from linear measurements using the formula:Claw Volume (cm(3)) = (17.192 x Base) + (7.467 x AbaxGr) + 45.270 x (CorBand) - 798.5This formula was found to be accurate (r(2)= 0.88) when compared to volume data derived from a hydrometer displacement procedure. The front claws occupied 54% of the total volume compared to 46% for the hind claws. Copyright 1999 Harcourt Publishers Ltd.

Correlation of rapid hydrometer analysis for select material to existing procedure LDH-TR-407-66 : final report.

DOT National Transportation Integrated Search

1968-05-01

Conditions arise during construction of bases with Portland cement stabilized soils which require close programming of work. Therefore, time is of significant importance. : That is the objective of this report; to evaluate a method by which considera...

27 CFR 30.22 - Hydrometers and thermometers.

Code of Federal Regulations, 2013 CFR

2013-04-01

... subdivisions of degrees as follows: Type Range Subdivision Pencil type 10° to 100° 1° V-back 10° to 100° 1° Glass shell (earlier model) 40° to 100° 1/2° Glass shell (later model) 40° to 100° 1/4° (Sec. 201, Pub...

27 CFR 30.22 - Hydrometers and thermometers.

Code of Federal Regulations, 2012 CFR

2012-04-01

... subdivisions of degrees as follows: Type Range Subdivision Pencil type 10° to 100° 1° V-back 10° to 100° 1° Glass shell (earlier model) 40° to 100° 1/2° Glass shell (later model) 40° to 100° 1/4° (Sec. 201, Pub...

27 CFR 30.22 - Hydrometers and thermometers.

Code of Federal Regulations, 2014 CFR

2014-04-01

... subdivisions of degrees as follows: Type Range Subdivision Pencil type 10° to 100° 1° V-back 10° to 100° 1° Glass shell (earlier model) 40° to 100° 1/2° Glass shell (later model) 40° to 100° 1/4° (Sec. 201, Pub...

27 CFR 30.41 - Bulk spirits.

Code of Federal Regulations, 2012 CFR

2012-04-01

... specific gravity at the temperature of the spirits is not more than 1.0) and reference to Table 4 for the wine gallons per pound, or (b) Use of a specific gravity hydrometer, in accordance with the provisions of § 30.25, to determine the specific gravity of the spirits (if the specific gravity at the...

27 CFR 30.41 - Bulk spirits.

Code of Federal Regulations, 2011 CFR

2011-04-01

... specific gravity at the temperature of the spirits is not more than 1.0) and reference to Table 4 for the wine gallons per pound, or (b) Use of a specific gravity hydrometer, in accordance with the provisions of § 30.25, to determine the specific gravity of the spirits (if the specific gravity at the...

27 CFR 30.41 - Bulk spirits.

Code of Federal Regulations, 2014 CFR

2014-04-01

... specific gravity at the temperature of the spirits is not more than 1.0) and reference to Table 4 for the wine gallons per pound, or (b) Use of a specific gravity hydrometer, in accordance with the provisions of § 30.25, to determine the specific gravity of the spirits (if the specific gravity at the...

27 CFR 30.41 - Bulk spirits.

Code of Federal Regulations, 2013 CFR

2013-04-01

... specific gravity at the temperature of the spirits is not more than 1.0) and reference to Table 4 for the wine gallons per pound, or (b) Use of a specific gravity hydrometer, in accordance with the provisions of § 30.25, to determine the specific gravity of the spirits (if the specific gravity at the...

Dairy manure nutrient analysis using quick tests.

PubMed

Singh, A; Bicudo, J R

2005-05-01

Rapid on-farm assessment of manure nutrient content can be achieved with the use of quick tests. These tests can be used to indirectly measure the nutrient content in animal slurries immediately before manure is applied on agricultural fields. The objective of this study was to assess the reliability of hydrometers, electrical conductivity meter and pens, and Agros N meter against standard laboratory methods. Manure samples were collected from 34 dairy farms in the Mammoth Cave area in central Kentucky. Regression equations were developed for combined and individual counties located In the area (Barren, Hart and Monroe). Our results indicated that accuracy in nutrient estimation could be improved if separate linear regressions were developed for farms with similar facilities in a county. Direct hydrometer estimates of total nitrogen were among the most accurate when separate regression equations were developed for each county (R2 = 0.61, 0.93, and 0.74 for Barren, Hart and Monroe county, respectively). Reasonably accurate estimates (R2 > 0.70) were also obtained for total nitrogen and total phosphorus using hydrometers, either by relating specific gravity to nutrient content or to total solids content. Estimation of ammoniacal nitrogen with Agros N meter and electrical conductivity meter/pens correlated well with standard laboratory determinations, especially while using the individual data sets from Hart County (R2 = 0.70 to 0.87). This study indicates that the use of quick test calibration equations developed for a small area or region where farms are similar in terms of manure handling and management, housing, and feed ration are more appropriate than using "universal" equations usually developed with combined data sets. Accuracy is expected to improve if individual farms develop their own calibration curves. Nevertheless, we suggest confidence intervals always be specified for nutrients estimated through quick testing for any specific region, county, or farm.

Termite infestation associated with type of soil in pulau pinang, malaysia (isoptera: rhinotermitidae).

PubMed

Majid, Abdul Hafiz Ab; Ahmad, Abu Hassan

2013-12-01

Nine soil samples from nine buildings infested with Coptotermes gestroi in Pulau Pinang, Malaysia, were tested for the type of soil texture. The soil texture analysis procedures used the hydrometer method. Four of nine buildings (44%) yielded loamy sand-type soil, whereas five of nine buildings (56%) contained sandy loam-type soil.

Termite Infestation Associated with Type of Soil in Pulau Pinang, Malaysia (Isoptera: Rhinotermitidae)

PubMed Central

Majid, Abdul Hafiz Ab; Ahmad, Abu Hassan

2013-01-01

Nine soil samples from nine buildings infested with Coptotermes gestroi in Pulau Pinang, Malaysia, were tested for the type of soil texture. The soil texture analysis procedures used the hydrometer method. Four of nine buildings (44%) yielded loamy sand-type soil, whereas five of nine buildings (56%) contained sandy loam-type soil. PMID:24575252

Use of combined radar and radiometer systems in space for precipitation measurement: Some ideas

NASA Technical Reports Server (NTRS)

Moore, R. K.

1981-01-01

A brief survey is given of some fundamental physical concepts of optimal polarization characteristics of a transmission path or scatter ensemble of hydrometers. It is argued that, based on this optimization concept, definite advances in remote atmospheric sensing are to be expected. Basic properties of Kennaugh's optimal polarization theory are identified.

A Quality Control study of the distribution of NOAA MIRS Cloudy retrievals during Hurricane Sandy

NASA Astrophysics Data System (ADS)

Fletcher, S. J.

2013-12-01

Cloudy radiance present a difficult challenge to data assimilation (DA) systems, through both the radiative transfer system as well the hydrometers required to resolve the cloud and precipitation. In most DA systems the hydrometers are not control variables due to many limitations. The National Oceanic and Atmospheric Administration's (NOAA) Microwave Integrated Retrieval System (MIRS) is producing products from the NPP-ATMS satellite where the scene is cloud and precipitation affected. The test case that we present here is the life time of Hurricane and then Superstorm Sandy in October 2012. As a quality control study we shall compare the retrieved water vapor content during the lifetime of Sandy with the first guess and the analysis from the NOAA Gridpoint Statistical Interpolation (GSI) system. The assessment involves the gross error check system against the first guess with different values for the observational error's variance to see if the difference is within three standard deviations. We shall also compare against the final analysis at the relevant cycles to see if the products which have been retrieved through a cloudy radiance are similar, given that the DA system does not assimilate cloudy radiances yet.

Consequences of using different soil texture determination methodologies for soil physical quality and unsaturated zone time lag estimates

NASA Astrophysics Data System (ADS)

Fenton, O.; Vero, S.; Ibrahim, T. G.; Murphy, P. N. C.; Sherriff, S. C.; Ó hUallacháin, D.

2015-11-01

Elucidation of when the loss of pollutants, below the rooting zone in agricultural landscapes, affects water quality is important when assessing the efficacy of mitigation measures. Investigation of this inherent time lag (tT) is divided into unsaturated (tu) and saturated (ts) components. The duration of these components relative to each other differs depending on soil characteristics and the landscape position. The present field study focuses on tu estimation in a scenario where the saturated zone is likely to constitute a higher proportion of tT. In such instances, or where only initial breakthrough (IBT) or centre of mass (COM) is of interest, utilisation of site and depth specific "simple" textural class or actual sand-silt-clay percentages to generate soil water characteristic curves with associated soil hydraulic parameters is acceptable. With the same data it is also possible to estimate a soil physical quality (S) parameter for each soil layer which can be used to infer many other physical, chemical and biological quality indicators. In this study, hand texturing in the field was used to determine textural classes of a soil profile. Laboratory methods, including hydrometer, pipette and laser diffraction methods were used to determine actual sand-silt-clay percentages of sections of the same soil profile. Results showed that in terms of S, hand texturing resulted in a lower index value (inferring a degraded soil) than that of pipette, hydrometer and laser equivalents. There was no difference between S index values determined using the pipette, hydrometer and laser diffraction methods. The difference between the three laboratory methods on both the IBT and COM stages of tu were negligible, and in this instance were unlikely to affect either groundwater monitoring decisions, or to be of consequence from a policy perspective. When tu estimates are made over the full depth of the vadose zone, which may extend to several metres, errors resulting from the use of hydraulic parameters generated from hand texture data will be resultantly greater, and may lead to flawed predictions regarding the achievability of water policy targets. For this reason laboratory analysis, regardless of method, should be preferred to simple field assessments.

Aerosol Attenuation in the 2-4 Micrometer Region

DTIC Science & Technology

1975-03-01

Company Model 911ir dew point hydrometer. The lithium chloride sensors will be placed on the roof where the aerosol is sampled and at the entrance...Extinction Measurement il External View of 400 Meter White Cell 13 Primary Aerosol and Gas Handlinfe Systems 14 Calibration for Extinction...Massacusetts. Aerosol-laden air will be drawn into the experimental apparatus from a point 10 ft above the roof of the building. A continuoush

Radar volume reflectivity estimation using an array of ground-based rainfall drop size detectors

NASA Astrophysics Data System (ADS)

Lane, John; Merceret, Francis; Kasparis, Takis; Roy, D.; Muller, Brad; Jones, W. Linwood

2000-08-01

Rainfall drop size distribution (DSD) measurements made by single disdrometers at isolated ground sites have traditionally been used to estimate the transformation between weather radar reflectivity Z and rainfall rate R. Despite the immense disparity in sampling geometries, the resulting Z-R relation obtained by these single point measurements has historically been important in the study of applied radar meteorology. Simultaneous DSD measurements made at several ground sites within a microscale area may be used to improve the estimate of radar reflectivity in the air volume surrounding the disdrometer array. By applying the equations of motion for non-interacting hydrometers, a volume estimate of Z is obtained from the array of ground based disdrometers by first calculating a 3D drop size distribution. The 3D-DSD model assumes that only gravity and terminal velocity due to atmospheric drag within the sampling volume influence hydrometer dynamics. The sampling volume is characterized by wind velocities, which are input parameters to the 3D-DSD model, composed of vertical and horizontal components. Reflectivity data from four consecutive WSR-88D volume scans, acquired during a thunderstorm near Melbourne, FL on June 1, 1997, are compared to data processed using the 3D-DSD model and data form three ground based disdrometers of a microscale array.

Immunoglobulin concentration, specific gravity, and nitrogen fractions of colostrum from Jersey cattle.

PubMed

Quigley, J D; Martin, K R; Dowlen, H H; Wallis, L B; Lamar, K

1994-01-01

Colostrum samples from 88 Jersey cows were analyzed for concentrations of IgG, IgM, IgA, total solids, specific gravity, and N fractions. Colostrum (50 ml) was sampled from each cow as soon as possible after parturition, and specific gravity was determined immediately using a hydrometer. Samples then were frozen prior to analysis of Ig, fat, and N fractions. Mean concentrations of IgG, IgM, and IgA were 65.8, 2.4, and 1.7 g/L, respectively. Concentration of IgG was lower, and IgA was higher, in colostrum from second lactation cows than from first lactation cows or from cows in third or later lactations; IgM increased linearly as lactation number increased. Total N, protein N, noncasein N, and fat contents also were lower in second lactation cows. Regression of total Ig (grams per liter) on specific gravity was -1172 + 1180 x specific gravity (r2 = .38). Relationship of total Ig to specific gravity differed from colostrum of Holstein cattle and may have been related to differences in fat and noncasein N concentrations. Use of specific gravity hydrometer to estimate Ig concentration using equations derived from Holstein cattle appears to underestimate Ig concentration in colostrum from Jersey cattle.

A Neural Network-Based Gait Phase Classification Method Using Sensors Equipped on Lower Limb Exoskeleton Robots

PubMed Central

Jung, Jun-Young; Heo, Wonho; Yang, Hyundae; Park, Hyunsub

2015-01-01

An exact classification of different gait phases is essential to enable the control of exoskeleton robots and detect the intentions of users. We propose a gait phase classification method based on neural networks using sensor signals from lower limb exoskeleton robots. In such robots, foot sensors with force sensing registers are commonly used to classify gait phases. We describe classifiers that use the orientation of each lower limb segment and the angular velocities of the joints to output the current gait phase. Experiments to obtain the input signals and desired outputs for the learning and validation process are conducted, and two neural network methods (a multilayer perceptron and nonlinear autoregressive with external inputs (NARX)) are used to develop an optimal classifier. Offline and online evaluations using four criteria are used to compare the performance of the classifiers. The proposed NARX-based method exhibits sufficiently good performance to replace foot sensors as a means of classifying gait phases. PMID:26528986

A Neural Network-Based Gait Phase Classification Method Using Sensors Equipped on Lower Limb Exoskeleton Robots.

PubMed

Jung, Jun-Young; Heo, Wonho; Yang, Hyundae; Park, Hyunsub

2015-10-30

An exact classification of different gait phases is essential to enable the control of exoskeleton robots and detect the intentions of users. We propose a gait phase classification method based on neural networks using sensor signals from lower limb exoskeleton robots. In such robots, foot sensors with force sensing registers are commonly used to classify gait phases. We describe classifiers that use the orientation of each lower limb segment and the angular velocities of the joints to output the current gait phase. Experiments to obtain the input signals and desired outputs for the learning and validation process are conducted, and two neural network methods (a multilayer perceptron and nonlinear autoregressive with external inputs (NARX)) are used to develop an optimal classifier. Offline and online evaluations using four criteria are used to compare the performance of the classifiers. The proposed NARX-based method exhibits sufficiently good performance to replace foot sensors as a means of classifying gait phases.

Improved adaptive splitting and selection: the hybrid training method of a classifier based on a feature space partitioning.

PubMed

Jackowski, Konrad; Krawczyk, Bartosz; Woźniak, Michał

2014-05-01

Currently, methods of combined classification are the focus of intense research. A properly designed group of combined classifiers exploiting knowledge gathered in a pool of elementary classifiers can successfully outperform a single classifier. There are two essential issues to consider when creating combined classifiers: how to establish the most comprehensive pool and how to design a fusion model that allows for taking full advantage of the collected knowledge. In this work, we address the issues and propose an AdaSS+, training algorithm dedicated for the compound classifier system that effectively exploits local specialization of the elementary classifiers. An effective training procedure consists of two phases. The first phase detects the classifier competencies and adjusts the respective fusion parameters. The second phase boosts classification accuracy by elevating the degree of local specialization. The quality of the proposed algorithms are evaluated on the basis of a wide range of computer experiments that show that AdaSS+ can outperform the original method and several reference classifiers.

Creep and Sliding in Clay Slopes: Mutual Effects of Interlayer Swelling and Ice Jacking.

DTIC Science & Technology

1983-08-24

project, swelling and freezing, have been treated as well. The extent of swell heave of the montmorillonite clay under investigation depends on the...the amount of clay size particles: up to 70% and the amount of montmorillonite : up to 35%. 1.2. Grain Size Distribution Twelve hydrometer tests were...in physical conditions and exhibit swelling again upon subsequent wetting. Another important swelling parameter is the montmorillonite content, that

Managing Loblolly Pine (Pinus taeda) Stands for the Restoration of Red-cockaded Woodpecker (Picoides borealis) Habitat

DTIC Science & Technology

2014-03-01

hydrometer method (Milford 1997). Climate data from the study period was obtained from the National Climatic Data Center web service, with data for...season after treatment. Throughout this paper , the term “seedling” is used to refer to any loblolly pine individual that established following site... Paper land in southwestern Georgia and found that longleaf pine stands had significantly higher herbaceous richness and diversity than the other

SUNRAYCE 1995: Working safely with lead-acid batteries and photovoltaic power systems

NASA Astrophysics Data System (ADS)

Dephillips, M. P.; Moskowitz, P. D.; Fthenakis, V. M.

1994-05-01

This document is a power system and battery safety handbook for participants in the SUNRAYCE 95 solar powered electric vehicle program. The topics of the handbook include batteries, photovoltaic modules, safety equipment needed for working with sulfuric acid electrolyte and batteries, battery transport, accident response, battery recharging and ventilation, electrical risks on-board vehicle, external electrical risks, electrical risk management strategies, and general maintenance including troubleshooting, hydrometer check and voltmeter check.

27 CFR 30.22 - Hydrometers and thermometers.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 105 to 125 0.2° N 125 to 145 0.2° P 145 to 165 0.2° Q 165 to 185 0.2° R 185 to 206 0.2° Thermometers are designated by type according to range of degrees Fahrenheit and are provided in ranges and subdivisions of degrees as follows: Type Range Subdivision Pencil type 10° to 100° 1° V-back 10° to 100° 1...

Consequences of using different soil texture determination methodologies for soil physical quality and unsaturated zone time lag estimates.

PubMed

Fenton, O; Vero, S; Ibrahim, T G; Murphy, P N C; Sherriff, S C; Ó hUallacháin, D

2015-11-01

Elucidation of when the loss of pollutants, below the rooting zone in agricultural landscapes, affects water quality is important when assessing the efficacy of mitigation measures. Investigation of this inherent time lag (t(T)) is divided into unsaturated (t(u)) and saturated (t(s)) components. The duration of these components relative to each other differs depending on soil characteristics and the landscape position. The present field study focuses on tu estimation in a scenario where the saturated zone is likely to constitute a higher proportion of t(T). In such instances, or where only initial breakthrough (IBT) or centre of mass (COM) is of interest, utilisation of site and depth specific "simple" textural class or actual sand-silt-clay percentages to generate soil water characteristic curves with associated soil hydraulic parameters is acceptable. With the same data it is also possible to estimate a soil physical quality (S) parameter for each soil layer which can be used to infer many other physical, chemical and biological quality indicators. In this study, hand texturing in the field was used to determine textural classes of a soil profile. Laboratory methods, including hydrometer, pipette and laser diffraction methods were used to determine actual sand-silt-clay percentages of sections of the same soil profile. Results showed that in terms of S, hand texturing resulted in a lower index value (inferring a degraded soil) than that of pipette, hydrometer and laser equivalents. There was no difference between S index values determined using the pipette, hydrometer and laser diffraction methods. The difference between the three laboratory methods on both the IBT and COM stages of t(u) were negligible, and in this instance were unlikely to affect either groundwater monitoring decisions, or to be of consequence from a policy perspective. When t(u) estimates are made over the full depth of the vadose zone, which may extend to several metres, errors resulting from the use of hydraulic parameters generated from hand texture data will be resultantly greater, and may lead to flawed predictions regarding the achievability of water policy targets. For this reason laboratory analysis, regardless of method, should be preferred to simple field assessments. Copyright © 2015 Elsevier B.V. All rights reserved.

CCM key comparison CCM.D-K4 'Hydrometer'

NASA Astrophysics Data System (ADS)

Lorefice, S.; Becerra, L. O.; Lenard, E.; Lee, Y. J.; Lee, W. G.; Madec, T.; Meury, P. A.; Caceres, J.; Santos, C.; Vamossy, C.; Man, J.; Fen, K.; Toda, K.; Wright, J.; Bettin, H.; Toth, H.

2016-01-01

This report presents the comparison philosophy, methodology, analysis and the results of the designed CCM.D-K4 key comparison that covered the calibration of high resolution hydrometers for liquid and alcoholometers in the density range 600 kg/m3 to 2000 kg/m3 at the temperature of 20°C. The main purpose of this comparison was not only to evaluate the degree of equivalence in the calibration of high accuracy hydrometers between NMI participants, but also to link, were it is possible, the results of previous comparisons to Key Comparison Reference Values (KCRVs) of CCM.D-K4. Eleven NMI laboratories took part in the CCM.D-K4 divided in two groups (petals). With the CCM.D-K4 purpose, two similar sets consisting of three hydrometers for liquid density determinations and an alcoholometer were circulated to the NMI participants as a travelling standard in the time interval from January 2011 to April 2012. Twelve Key Comparison Reference Values (KCRVs) for each petal have been obtained at the density values related to the tested density marks of the transfer standards by the results of participants. The KCRVs and corresponding uncertainties were calculated by the weighted mean in the case of consistent results, otherwise the median was used. The degree of equivalence (DoE) with respect to the corresponding KCRV was determined for each participant and, in this particular comparison, the Weighted Least Squares (WLS) method was used to link the individual DoE of each participant by a continuous function. Significant drift of the transfer standards was not detected. This report also gives instructions on calculating pair-wise degrees of equivalence, with the addition of any information on correlations that may be necessary to estimate more accurately as well as the procedure for linking international comparisons to the CCM.D-K4. Finally an example of linkage to the CCM.D-K4 is given by dealing with the results of the bilateral comparison between INRiM and NMIA, which was added to this comparison so that all participants were engaged after the breakage of the 9340171 artefact. A particularly good agreement was found among the results provided by most of the participants, even if some systematic differences and either underestimated or overestimated uncertainties of the submitted results can be identified with respect to the KCRVs. In general the deviations of the laboratory results to the KCRVs are within of 1/3rd to 1/4th of a scale division and the uncertainty at 95% is usually within half a division. During the analysis of the submitted results, a systematic difference between the first and last immersed mark was also noted, possibly due to a temperature gradient along the stem and/or wetting of the stem around the tested mark, and therefore a corrected claimed uncertainty from each laboratory is expected. However this comparison may help the laboratories to solve some residual or marginal problems as well as to better understand the uncertainty components. The comparison fully supports the calibration measurement capabilities table in the BIPM key comparison database (KCDB). The results can be used to link regional comparisons to this CCM key comparison Main text To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database kcdb.bipm.org/. The final report has been peer-reviewed and approved for publication by the CCM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).

A New Inversion-Based Algorithm for Retrieval of Over-Water Rain Rate from SSM/I Multichannel Imagery

NASA Technical Reports Server (NTRS)

Petty, Grant W.; Stettner, David R.

1994-01-01

This paper discusses certain aspects of a new inversion based algorithm for the retrieval of rain rate over the open ocean from the special sensor microwave/imager (SSM/I) multichannel imagery. This algorithm takes a more detailed physical approach to the retrieval problem than previously discussed algorithms that perform explicit forward radiative transfer calculations based on detailed model hydrometer profiles and attempt to match the observations to the predicted brightness temperature.

New methods of subcooled water recognition in dew point hygrometers

NASA Astrophysics Data System (ADS)

Weremczuk, Jerzy; Jachowicz, Ryszard

2001-08-01

Two new methods of sub-cooled water recognition in dew point hygrometers are presented in this paper. The first one- impedance method use a new semiconductor mirror in which the dew point detector, the thermometer and the heaters were integrated all together. The second one an optical method based on a multi-section optical detector is discussed in the report. Experimental results of both methods are shown. New types of dew pont hydrometers of ability to recognized sub-cooled water were proposed.

Abstracts of papers presented at the Eleventh International Laser Radar Conference

NASA Technical Reports Server (NTRS)

1982-01-01

Abstracts of 39 papers discuss measurements of properties from the Earth's ocean surface to the mesosphere, made with techniques ranging from elastic and inelastic scattering to Doppler shifts and differential absorption. Topics covered include: (1) middle atmospheric measurements; (2) meteorological parameters: temperature, density, humidity; (3) trace gases by Raman and DIAL techniques; (4) techniques and technology; (5) plume dispersion; (6) boundary layer dynamics; (7) wind measurements; visibility and aerosol properties; and (9) multiple scattering, clouds, and hydrometers.

Ice Nucleation in Deep Convection

NASA Technical Reports Server (NTRS)

Jensen, Eric; Ackerman, Andrew; Stevens, David; Gore, Warren J. (Technical Monitor)

2001-01-01

The processes controlling production of ice crystals in deep, rapidly ascending convective columns are poorly understood due to the difficulties involved with either modeling or in situ sampling of these violent clouds. A large number of ice crystals are no doubt generated when droplets freeze at about -40 C. However, at higher levels, these crystals are likely depleted due to precipitation and detrainment. As the ice surface area decreases, the relative humidity can increase well above ice saturation, resulting in bursts of ice nucleation. We will present simulations of these processes using a large-eddy simulation model with detailed microphysics. Size bins are included for aerosols, liquid droplets, ice crystals, and mixed-phase (ice/liquid) hydrometers. Microphysical processes simulated include droplet activation, freezing, melting, homogeneous freezing of sulfate aerosols, and heterogeneous ice nucleation. We are focusing on the importance of ice nucleation events in the upper part of the cloud at temperatures below -40 C. We will show that the ultimate evolution of the cloud in this region (and the anvil produced by the convection) is sensitive to these ice nucleation events, and hence to the composition of upper tropospheric aerosols that get entrained into the convective column.

Brain metabolic pattern analysis using a magnetic resonance spectra classification software in experimental stroke.

PubMed

Jiménez-Xarrié, Elena; Davila, Myriam; Candiota, Ana Paula; Delgado-Mederos, Raquel; Ortega-Martorell, Sandra; Julià-Sapé, Margarida; Arús, Carles; Martí-Fàbregas, Joan

2017-01-13

Magnetic resonance spectroscopy (MRS) provides non-invasive information about the metabolic pattern of the brain parenchyma in vivo. The SpectraClassifier software performs MRS pattern-recognition by determining the spectral features (metabolites) which can be used objectively to classify spectra. Our aim was to develop an Infarct Evolution Classifier and a Brain Regions Classifier in a rat model of focal ischemic stroke using SpectraClassifier. A total of 164 single-voxel proton spectra obtained with a 7 Tesla magnet at an echo time of 12 ms from non-infarcted parenchyma, subventricular zones and infarcted parenchyma were analyzed with SpectraClassifier ( http://gabrmn.uab.es/?q=sc ). The spectra corresponded to Sprague-Dawley rats (healthy rats, n = 7) and stroke rats at day 1 post-stroke (acute phase, n = 6 rats) and at days 7 ± 1 post-stroke (subacute phase, n = 14). In the Infarct Evolution Classifier, spectral features contributed by lactate + mobile lipids (1.33 ppm), total creatine (3.05 ppm) and mobile lipids (0.85 ppm) distinguished among non-infarcted parenchyma (100% sensitivity and 100% specificity), acute phase of infarct (100% sensitivity and 95% specificity) and subacute phase of infarct (78% sensitivity and 100% specificity). In the Brain Regions Classifier, spectral features contributed by myoinositol (3.62 ppm) and total creatine (3.04/3.05 ppm) distinguished among infarcted parenchyma (100% sensitivity and 98% specificity), non-infarcted parenchyma (84% sensitivity and 84% specificity) and subventricular zones (76% sensitivity and 93% specificity). SpectraClassifier identified candidate biomarkers for infarct evolution (mobile lipids accumulation) and different brain regions (myoinositol content).

Estimation of Microphysical and Radiative Parameters of Precipitating Cloud Systems Using mm-Wavelength Radars

NASA Astrophysics Data System (ADS)

Matrosov, Sergey Y.

2009-03-01

A remote sensing approach is described to retrieve cloud and rainfall parameters within the same precipitating system. This approach is based on mm-wavelength radar signal attenuation effects which are observed in a layer of liquid precipitation containing clouds and rainfall. The parameters of ice clouds in the upper part of startiform precipitating systems are then retrieved using the absolute measurements of radar reflectivity. In case of the ground-based radar location, these measurements are corrected for attenuation in the intervening layer of liquid hydrometers.

Self-reports of induced abortion: an empathetic setting can improve the quality of data.

PubMed Central

Rasch, V; Muhammad, H; Urassa, E; Bergström, S

2000-01-01

OBJECTIVES: This study estimated the proportion of incomplete abortions that are induced in hospital-based settings in Tanzania. METHODS: A cross-sectional questionnaire study was conducted in 2 phases at 3 hospitals in Tanzania. Phase 1 included 302 patients with a diagnosis of incomplete abortion, and phase 2 included 823 such patients. RESULTS: In phase 1, in which cases were classified by clinical criteria and information from the patient, 3.9% to 16.1% of the cases were classified as induced abortion. In phase 2, in which the structured interview was changed to an empathetic dialogue and previously used clinical criteria were omitted, 30.9% to 60.0% of the cases were classified as induced abortion. CONCLUSIONS: An empathetic dialogue improves the quality of data collected among women with induced abortion. PMID:10897196

A novel HMM distributed classifier for the detection of gait phases by means of a wearable inertial sensor network.

PubMed

Taborri, Juri; Rossi, Stefano; Palermo, Eduardo; Patanè, Fabrizio; Cappa, Paolo

2014-09-02

In this work, we decided to apply a hierarchical weighted decision, proposed and used in other research fields, for the recognition of gait phases. The developed and validated novel distributed classifier is based on hierarchical weighted decision from outputs of scalar Hidden Markov Models (HMM) applied to angular velocities of foot, shank, and thigh. The angular velocities of ten healthy subjects were acquired via three uni-axial gyroscopes embedded in inertial measurement units (IMUs) during one walking task, repeated three times, on a treadmill. After validating the novel distributed classifier and scalar and vectorial classifiers-already proposed in the literature, with a cross-validation, classifiers were compared for sensitivity, specificity, and computational load for all combinations of the three targeted anatomical segments. Moreover, the performance of the novel distributed classifier in the estimation of gait variability in terms of mean time and coefficient of variation was evaluated. The highest values of specificity and sensitivity (>0.98) for the three classifiers examined here were obtained when the angular velocity of the foot was processed. Distributed and vectorial classifiers reached acceptable values (>0.95) when the angular velocity of shank and thigh were analyzed. Distributed and scalar classifiers showed values of computational load about 100 times lower than the one obtained with the vectorial classifier. In addition, distributed classifiers showed an excellent reliability for the evaluation of mean time and a good/excellent reliability for the coefficient of variation. In conclusion, due to the better performance and the small value of computational load, the here proposed novel distributed classifier can be implemented in the real-time application of gait phases recognition, such as to evaluate gait variability in patients or to control active orthoses for the recovery of mobility of lower limb joints.

Validation of Inter-Subject Training for Hidden Markov Models Applied to Gait Phase Detection in Children with Cerebral Palsy.

PubMed

Taborri, Juri; Scalona, Emilia; Palermo, Eduardo; Rossi, Stefano; Cappa, Paolo

2015-09-23

Gait-phase recognition is a necessary functionality to drive robotic rehabilitation devices for lower limbs. Hidden Markov Models (HMMs) represent a viable solution, but they need subject-specific training, making data processing very time-consuming. Here, we validated an inter-subject procedure to avoid the intra-subject one in two, four and six gait-phase models in pediatric subjects. The inter-subject procedure consists in the identification of a standardized parameter set to adapt the model to measurements. We tested the inter-subject procedure both on scalar and distributed classifiers. Ten healthy children and ten hemiplegic children, each equipped with two Inertial Measurement Units placed on shank and foot, were recruited. The sagittal component of angular velocity was recorded by gyroscopes while subjects performed four walking trials on a treadmill. The goodness of classifiers was evaluated with the Receiver Operating Characteristic. The results provided a goodness from good to optimum for all examined classifiers (0 < G < 0.6), with the best performance for the distributed classifier in two-phase recognition (G = 0.02). Differences were found among gait partitioning models, while no differences were found between training procedures with the exception of the shank classifier. Our results raise the possibility of avoiding subject-specific training in HMM for gait-phase recognition and its implementation to control exoskeletons for the pediatric population.

Validation of Inter-Subject Training for Hidden Markov Models Applied to Gait Phase Detection in Children with Cerebral Palsy

PubMed Central

Taborri, Juri; Scalona, Emilia; Palermo, Eduardo; Rossi, Stefano; Cappa, Paolo

2015-01-01

Gait-phase recognition is a necessary functionality to drive robotic rehabilitation devices for lower limbs. Hidden Markov Models (HMMs) represent a viable solution, but they need subject-specific training, making data processing very time-consuming. Here, we validated an inter-subject procedure to avoid the intra-subject one in two, four and six gait-phase models in pediatric subjects. The inter-subject procedure consists in the identification of a standardized parameter set to adapt the model to measurements. We tested the inter-subject procedure both on scalar and distributed classifiers. Ten healthy children and ten hemiplegic children, each equipped with two Inertial Measurement Units placed on shank and foot, were recruited. The sagittal component of angular velocity was recorded by gyroscopes while subjects performed four walking trials on a treadmill. The goodness of classifiers was evaluated with the Receiver Operating Characteristic. The results provided a goodness from good to optimum for all examined classifiers (0 < G < 0.6), with the best performance for the distributed classifier in two-phase recognition (G = 0.02). Differences were found among gait partitioning models, while no differences were found between training procedures with the exception of the shank classifier. Our results raise the possibility of avoiding subject-specific training in HMM for gait-phase recognition and its implementation to control exoskeletons for the pediatric population. PMID:26404309

Quantum adiabatic machine learning

NASA Astrophysics Data System (ADS)

Pudenz, Kristen L.; Lidar, Daniel A.

2013-05-01

We develop an approach to machine learning and anomaly detection via quantum adiabatic evolution. This approach consists of two quantum phases, with some amount of classical preprocessing to set up the quantum problems. In the training phase we identify an optimal set of weak classifiers, to form a single strong classifier. In the testing phase we adiabatically evolve one or more strong classifiers on a superposition of inputs in order to find certain anomalous elements in the classification space. Both the training and testing phases are executed via quantum adiabatic evolution. All quantum processing is strictly limited to two-qubit interactions so as to ensure physical feasibility. We apply and illustrate this approach in detail to the problem of software verification and validation, with a specific example of the learning phase applied to a problem of interest in flight control systems. Beyond this example, the algorithm can be used to attack a broad class of anomaly detection problems.

Evaluation of the Ott Hydromet Qliner for measuring discharge in laboratory and field conditions

USGS Publications Warehouse

McVay, Jason C.

2015-01-01

The U.S. Geological Survey, in collaboration with the University of Iowa IIHR – Hydroscience and Engineering, evaluated the use of the Ott Hydromet Qliner using laboratory flume tests along with field validation tests. Analysis of the flume testing indicates the velocities measured by the Qliner at a 40-second exposure time results in higher dispersion of velocities from the mean velocity of data collected with a 5-minute exposure time. The percent data spread from the mean of a 100-minute mean of Qliner velocities for a 40-second exposure time averaged 16.6 percent for the entire vertical, and a 5-minute mean produced a 6.2 percent data spread from the 100-minute mean. This 16.6 percent variation in measured velocity would result in a 3.32 percent variation in computed discharge assuming 25 verticals while averaging 4 bins in each vertical. The flume testing also provided results that indicate the blanking distance of 0.20 meters is acceptable when using beams 1 and 2, however beam 3 is negatively biased near the transducer and the 0.20-meter blanking distance is not sufficient. Field testing included comparing the measured discharge by the Qliner to the discharge measured by a Price AA mechanical current meter and a Teledyne RDI Rio Grande 1200 kilohertz acoustic Doppler current profiler. The field tests indicated a difference between the discharges measured with the Qliner and the field reference discharge between -14.0 and 8.0 percent; however the average percent difference for all 22 field comparisons was 0.22, which was not statistically significant.

Security authentication with a three-dimensional optical phase code using random forest classifier: an overview

NASA Astrophysics Data System (ADS)

Markman, Adam; Carnicer, Artur; Javidi, Bahram

2017-05-01

We overview our recent work [1] on utilizing three-dimensional (3D) optical phase codes for object authentication using the random forest classifier. A simple 3D optical phase code (OPC) is generated by combining multiple diffusers and glass slides. This tag is then placed on a quick-response (QR) code, which is a barcode capable of storing information and can be scanned under non-uniform illumination conditions, rotation, and slight degradation. A coherent light source illuminates the OPC and the transmitted light is captured by a CCD to record the unique signature. Feature extraction on the signature is performed and inputted into a pre-trained random-forest classifier for authentication.

Towards More Nuanced Classification of NGOs and Their Services to Improve Integrated Planning across Disaster Phases

PubMed Central

Towe, Vivian L.; Acosta, Joie D.; Chandra, Anita

2017-01-01

Nongovernmental organizations (NGOs) are being integrated into U.S. strategies to expand the services that are available during health security threats like disasters. Identifying better ways to classify NGOs and their services could optimize disaster planning. We surveyed NGOs about the types of services they provided during different disaster phases. Survey responses were used to categorize NGO services as core—critical to fulfilling their organizational mission—or adaptive—services implemented during a disaster based on community need. We also classified NGOs as being core or adaptive types of organizations by calculating the percentage of each NGO’s services classified as core. Service types classified as core were mainly social services, while adaptive service types were those typically relied upon during disasters (e.g., warehousing, food services, etc.). In total, 120 NGOs were classified as core organizations, meaning they mainly provided the same services across disaster phases, while 100 NGOs were adaptive organizations, meaning their services changed. Adaptive NGOs were eight times more likely to report routinely participating in disaster planning as compared to core NGOs. One reason for this association may be that adaptive NGOs are more aware of the changing needs in their communities across disaster phases because of their involvement in disaster planning. PMID:29160810

Intercomparison of microphysical datasets collected from CAIPEEX observations and WRF simulation

NASA Astrophysics Data System (ADS)

Pattnaik, S.; Goswami, B.; Kulkarni, J.

2009-12-01

In the first phase of ongoing Cloud Aerosol Interaction and Precipitation Enhancement Experiment (CAIPEEX) program of Indian Institute of Tropical Meteorology (IITM), intensive cloud microphysical datasets are collected over India during the May through September, 2009. This study is designed to evaluate the forecast skills of existing cloud microphysical parameterization schemes (i.e. single moment/double moments) within the WRF-ARW model (Version 3.1.1) during different intensive observation periods (IOP) over the targeted regions spreading all across India. Basic meteorological and cloud microphysical parameters obtained from the model simulations are validated against the observed data set collected during CAIPEEX program. For this study, we have considered three IOP phases (i.e. May 23-27, June 11-15, July 3-7) carried out over northern, central and western India respectively. This study emphasizes the thrust to understand the mechanism of evolution, intensification and distribution of simulated precipitation forecast upto day four (i.e. 96 hour forecast). Efforts have also been made to carryout few important microphysics sensitivity experiments within the explicit schemes to investigate their respective impact on the formation and distribution of vital cloud parameters (e.g. cloud liquid water, frozen hydrometeors) and model rainfall forecast over the IOP regions. The characteristic features of liquid and frozen hydrometers in the pre-monsoon and monsoon regimes are examined from model forecast as well as from CAIPEEX observation data set for different IOPs. The model is integrated in a triply nested fashion with an innermost nest explicitly resolved at a horizontal resolution of 4km.In this presentation preliminary results from aforementioned research initiatives will be introduced.

Dual-Polarization Radar Observations of Upward Lightning-Producing Storms

NASA Astrophysics Data System (ADS)

Lueck, R.; Helsdon, J. H.; Warner, T.

2013-12-01

The Upward Lightning Triggering Study (UPLIGHTS) seeks to determine how upward lightning, which originates from the tips of tall objects, is triggered by nearby flash activity. As a component of this study we analyze standard and dual-polarization weather radar data. The Correlation Coefficient (CC) in particular can be used to identify and quantify the melting layer associated with storms that produce upward lightning. It has been proposed that positive charge generation due to aggregate shedding at the melting layer results in a positive charge region just above the cloud base. This positive charge region may serve as a positive potential well favorable for negative leader propagation, which initiate upward positive leaders from tall objects. We characterize the horizontal coverage, thickness and height of the melting layer in addition to cloud base heights when upward lightning occurs to determine trends and possible threshold criteria relating to upward lightning production. Furthermore, we characterize storm type and morphology using relevant schemes as well as precipitation type using the Hydrometer Classification Algorithm (HCA) for upward lightning-producing storms. Ice-phase hydrometeors have been shown to be a significant factor in thunderstorm electrification. Only a small fraction of storms produce upward lightning, so null cases will be examined and compared as well.

Hydrometer test for estimation of immunoglobulin concentration in bovine colostrum.

PubMed

Fleenor, W A; Stott, G H

1980-06-01

A practical field method for measuring immunoglobulin concentration in bovine colostrum has been developed from the linear relationship between colostral specific gravity and immunoglobulin concentration. Fourteen colostrums were collected within 24 h postpartum from nursed and unnursed cows and were assayed for specific gravity and major colostral constituents. Additionally, 15 colostrums were collected immediately postpartum prior to suckling and assayed for specific gravity and immunoglobulin concentration. Regression analysis provided an equation to estimate colostral immunoglobulin concentration from the specific gravity of fresh whole colostrum. From this, a colostrometer was developed for practical field use.

Measurement of particle size distribution of soil and selected aggregate sizes using the hydrometer method and laser diffractometry

NASA Astrophysics Data System (ADS)

Guzmán, G.; Gómez, J. A.; Giráldez, J. V.

2010-05-01

Soil particle size distribution has been traditionally determined by the hydrometer or the sieve-pipette methods, both of them time consuming and requiring a relatively large soil sample. This might be a limitation in situations, such as for instance analysis of suspended sediment, when the sample is small. A possible alternative to these methods are the optical techniques such as laser diffractometry. However the literature indicates that the use of this technique as an alternative to traditional methods is still limited, because the difficulty in replicating the results obtained with the standard methods. In this study we present the percentages of soil grain size determined using laser diffractometry within ranges set between 0.04 - 2000 μm. A Beckman-Coulter ® LS-230 with a 750 nm laser beam and software version 3.2 in five soils, representative of southern Spain: Alameda, Benacazón, Conchuela, Lanjarón and Pedrera. In three of the studied soils (Alameda, Benacazón and Conchuela) the particle size distribution of each aggregate size class was also determined. Aggregate size classes were obtained by dry sieve analysis using a Retsch AS 200 basic ®. Two hundred grams of air dried soil were sieved during 150 s, at amplitude 2 mm, getting nine different sizes between 2000 μm and 10 μm. Analyses were performed by triplicate. The soil sample preparation was also adapted to our conditions. A small amount each soil sample (less than 1 g) was transferred to the fluid module full of running water and disaggregated by ultrasonication at energy level 4 and 80 ml of sodium hexametaphosphate solution during 580 seconds. Two replicates of each sample were performed. Each measurement was made for a 90 second reading at a pump speed of 62. After the laser diffractometry analysis, each soil and its aggregate classes were processed calibrating its own optical model fitting the optical parameters that mainly depends on the color and the shape of the analyzed particle. As a second alternative a unique optical model valid for a broad range of soils developed by the Department of Soil, Water, and Environmental Science of the University of Arizona (personal communication, already submitted) was tested. The results were compared with the particle size distribution measured in the same soils and aggregate classes using the hydrometer method. Preliminary results indicate a better calibration of the technique using the optical model of the Department of Soil, Water, and Environmental Science of the University of Arizona, which obtained a good correlations (r2>0.85). This result suggests that with an appropriate calibration of the optical model laser diffractometry might provide a reliable soil particle characterization.

A Novel HMM Distributed Classifier for the Detection of Gait Phases by Means of a Wearable Inertial Sensor Network

PubMed Central

Taborri, Juri; Rossi, Stefano; Palermo, Eduardo; Patanè, Fabrizio; Cappa, Paolo

2014-01-01

In this work, we decided to apply a hierarchical weighted decision, proposed and used in other research fields, for the recognition of gait phases. The developed and validated novel distributed classifier is based on hierarchical weighted decision from outputs of scalar Hidden Markov Models (HMM) applied to angular velocities of foot, shank, and thigh. The angular velocities of ten healthy subjects were acquired via three uni-axial gyroscopes embedded in inertial measurement units (IMUs) during one walking task, repeated three times, on a treadmill. After validating the novel distributed classifier and scalar and vectorial classifiers-already proposed in the literature, with a cross-validation, classifiers were compared for sensitivity, specificity, and computational load for all combinations of the three targeted anatomical segments. Moreover, the performance of the novel distributed classifier in the estimation of gait variability in terms of mean time and coefficient of variation was evaluated. The highest values of specificity and sensitivity (>0.98) for the three classifiers examined here were obtained when the angular velocity of the foot was processed. Distributed and vectorial classifiers reached acceptable values (>0.95) when the angular velocity of shank and thigh were analyzed. Distributed and scalar classifiers showed values of computational load about 100 times lower than the one obtained with the vectorial classifier. In addition, distributed classifiers showed an excellent reliability for the evaluation of mean time and a good/excellent reliability for the coefficient of variation. In conclusion, due to the better performance and the small value of computational load, the here proposed novel distributed classifier can be implemented in the real-time application of gait phases recognition, such as to evaluate gait variability in patients or to control active orthoses for the recovery of mobility of lower limb joints. PMID:25184488

On the phase form of a deformation quantization with separation of variables

NASA Astrophysics Data System (ADS)

Karabegov, Alexander

2016-06-01

Given a star product with separation of variables on a pseudo-Kähler manifold, we obtain a new formal (1, 1)-form from its classifying form and call it the phase form of the star product. The cohomology class of a star product with separation of variables equals the class of its phase form. We show that the phase forms can be arbitrary and they bijectively parametrize the star products with separation of variables. We also describe the action of a change of the formal parameter on a star product with separation of variables, its formal Berezin transform, classifying form, phase form, and canonical trace density.

Identifying hidden voice and video streams

NASA Astrophysics Data System (ADS)

Fan, Jieyan; Wu, Dapeng; Nucci, Antonio; Keralapura, Ram; Gao, Lixin

2009-04-01

Given the rising popularity of voice and video services over the Internet, accurately identifying voice and video traffic that traverse their networks has become a critical task for Internet service providers (ISPs). As the number of proprietary applications that deliver voice and video services to end users increases over time, the search for the one methodology that can accurately detect such services while being application independent still remains open. This problem becomes even more complicated when voice and video service providers like Skype, Microsoft, and Google bundle their voice and video services with other services like file transfer and chat. For example, a bundled Skype session can contain both voice stream and file transfer stream in the same layer-3/layer-4 flow. In this context, traditional techniques to identify voice and video streams do not work. In this paper, we propose a novel self-learning classifier, called VVS-I , that detects the presence of voice and video streams in flows with minimum manual intervention. Our classifier works in two phases: training phase and detection phase. In the training phase, VVS-I first extracts the relevant features, and subsequently constructs a fingerprint of a flow using the power spectral density (PSD) analysis. In the detection phase, it compares the fingerprint of a flow to the existing fingerprints learned during the training phase, and subsequently classifies the flow. Our classifier is not only capable of detecting voice and video streams that are hidden in different flows, but is also capable of detecting different applications (like Skype, MSN, etc.) that generate these voice/video streams. We show that our classifier can achieve close to 100% detection rate while keeping the false positive rate to less that 1%.

The Impact of Assimilating Precipitation-affected Radiance on Cloud and Precipitation in Goddard WRF-EDAS Analyses

NASA Technical Reports Server (NTRS)

Lin, Xin; Zhang, Sara Q.; Zupanski, M.; Hou, Arthur Y.; Zhang, J.

2015-01-01

High-frequency TMI and AMSR-E radiances, which are sensitive to precipitation over land, are assimilated into the Goddard Weather Research and Forecasting Model- Ensemble Data Assimilation System (WRF-EDAS) for a few heavy rain events over the continental US. Independent observations from surface rainfall, satellite IR brightness temperatures, as well as ground-radar reflectivity profiles are used to evaluate the impact of assimilating rain-sensitive radiances on cloud and precipitation within WRF-EDAS. The evaluations go beyond comparisons of forecast skills and domain-mean statistics, and focus on studying the cloud and precipitation features in the jointed rainradiance and rain-cloud space, with particular attentions on vertical distributions of height-dependent cloud types and collective effect of cloud hydrometers. Such a methodology is very helpful to understand limitations and sources of errors in rainaffected radiance assimilations. It is found that the assimilation of rain-sensitive radiances can reduce the mismatch between model analyses and observations by reasonably enhancing/reducing convective intensity over areas where the observation indicates precipitation, and suppressing convection over areas where the model forecast indicates rain but the observation does not. It is also noted that instead of generating sufficient low-level warmrain clouds as in observations, the model analysis tends to produce many spurious upperlevel clouds containing small amount of ice water content. This discrepancy is associated with insufficient information in ice-water-sensitive radiances to address the vertical distribution of clouds with small amount of ice water content. Such a problem will likely be mitigated when multi-channel multi-frequency radiances/reflectivity are assimilated over land along with sufficiently accurate surface emissivity information to better constrain the vertical distribution of cloud hydrometers.

Three learning phases for radial-basis-function networks.

PubMed

Schwenker, F; Kestler, H A; Palm, G

2001-05-01

In this paper, learning algorithms for radial basis function (RBF) networks are discussed. Whereas multilayer perceptrons (MLP) are typically trained with backpropagation algorithms, starting the training procedure with a random initialization of the MLP's parameters, an RBF network may be trained in many different ways. We categorize these RBF training methods into one-, two-, and three-phase learning schemes. Two-phase RBF learning is a very common learning scheme. The two layers of an RBF network are learnt separately; first the RBF layer is trained, including the adaptation of centers and scaling parameters, and then the weights of the output layer are adapted. RBF centers may be trained by clustering, vector quantization and classification tree algorithms, and the output layer by supervised learning (through gradient descent or pseudo inverse solution). Results from numerical experiments of RBF classifiers trained by two-phase learning are presented in three completely different pattern recognition applications: (a) the classification of 3D visual objects; (b) the recognition hand-written digits (2D objects); and (c) the categorization of high-resolution electrocardiograms given as a time series (ID objects) and as a set of features extracted from these time series. In these applications, it can be observed that the performance of RBF classifiers trained with two-phase learning can be improved through a third backpropagation-like training phase of the RBF network, adapting the whole set of parameters (RBF centers, scaling parameters, and output layer weights) simultaneously. This, we call three-phase learning in RBF networks. A practical advantage of two- and three-phase learning in RBF networks is the possibility to use unlabeled training data for the first training phase. Support vector (SV) learning in RBF networks is a different learning approach. SV learning can be considered, in this context of learning, as a special type of one-phase learning, where only the output layer weights of the RBF network are calculated, and the RBF centers are restricted to be a subset of the training data. Numerical experiments with several classifier schemes including k-nearest-neighbor, learning vector quantization and RBF classifiers trained through two-phase, three-phase and support vector learning are given. The performance of the RBF classifiers trained through SV learning and three-phase learning are superior to the results of two-phase learning, but SV learning often leads to complex network structures, since the number of support vectors is not a small fraction of the total number of data points.

Integrated Sensing Processor, Phase 2

DTIC Science & Technology

2005-12-01

performance analysis for several baseline classifiers including neural nets, linear classifiers, and kNN classifiers. Use of CCDR as a preprocessing step...below the level of the benchmark non-linear classifier for this problem ( kNN ). Furthermore, the CCDR preconditioned kNN achieved a 10% improvement over...the benchmark kNN without CCDR. Finally, we found an important connection between intrinsic dimension estimation via entropic graphs and the optimal

Comparison of cloud boundaries measured with 8.6 mm radar and 10.6 micrometer lidar

NASA Technical Reports Server (NTRS)

Uttal, Taneil; Intrieri, Janet M.

1993-01-01

One of the most basic cloud properties is location; the height of cloud base and the height of cloud top. The glossary of meteorology defines cloud base (top) as follows: 'For a given cloud or cloud layer, that lowest (highest) level in the atmosphere at which the air contains a perceptible quantity of cloud particles.' Our studies show that for a 8.66 mm radar, and a 10.6 micrometer lidar, the level at which cloud hydrometers become 'perceptible' can vary significantly as a function of the different wavelengths, powers, beamwidths and sampling rates of the two remote sensors.

Quantification of texture match of the skin graft: function and morphology of the stratum corneum.

PubMed

Inoue, K; Matsumoto, K

1986-01-01

In an attempt to analyze the "texture match" of grafted skin, functional and morphological aspects of the stratum corneum were studied using the Skin Surface Hydrometer (IBS Inc.) and the scanning electron microscope. The results showed that hygroscopicity and water holding capacity of the stratum corneum played a crucial role in making the skin surface soft and smooth. Morphologically there were regional differences in the surface pattern and the mean area of corneocytes, suggesting that these differences affect skin texture. It is suggested that the present functional and morphological studies of the stratum corneum can provide a quantitative measure of the "texture match".

Ultrasonic Sensor Signals and Optimum Path Forest Classifier for the Microstructural Characterization of Thermally-Aged Inconel 625 Alloy

PubMed Central

de Albuquerque, Victor Hugo C.; Barbosa, Cleisson V.; Silva, Cleiton C.; Moura, Elineudo P.; Rebouças Filho, Pedro P.; Papa, João P.; Tavares, João Manuel R. S.

2015-01-01

Secondary phases, such as laves and carbides, are formed during the final solidification stages of nickel-based superalloy coatings deposited during the gas tungsten arc welding cold wire process. However, when aged at high temperatures, other phases can precipitate in the microstructure, like the γ” and δ phases. This work presents an evaluation of the powerful optimum path forest (OPF) classifier configured with six distance functions to classify background echo and backscattered ultrasonic signals from samples of the inconel 625 superalloy thermally aged at 650 and 950 °C for 10, 100 and 200 h. The background echo and backscattered ultrasonic signals were acquired using transducers with frequencies of 4 and 5 MHz. The potentiality of ultrasonic sensor signals combined with the OPF to characterize the microstructures of an inconel 625 thermally aged and in the as-welded condition were confirmed by the results. The experimental results revealed that the OPF classifier is sufficiently fast (classification total time of 0.316 ms) and accurate (accuracy of 88.75% and harmonic mean of 89.52) for the application proposed. PMID:26024416

Ultrasonic sensor signals and optimum path forest classifier for the microstructural characterization of thermally-aged inconel 625 alloy.

PubMed

de Albuquerque, Victor Hugo C; Barbosa, Cleisson V; Silva, Cleiton C; Moura, Elineudo P; Filho, Pedro P Rebouças; Papa, João P; Tavares, João Manuel R S

2015-05-27

Secondary phases, such as laves and carbides, are formed during the final solidification stages of nickel-based superalloy coatings deposited during the gas tungsten arc welding cold wire process. However, when aged at high temperatures, other phases can precipitate in the microstructure, like the γ'' and δ phases. This work presents an evaluation of the powerful optimum path forest (OPF) classifier configured with six distance functions to classify background echo and backscattered ultrasonic signals from samples of the inconel 625 superalloy thermally aged at 650 and 950 °C for 10, 100 and 200 h. The background echo and backscattered ultrasonic signals were acquired using transducers with frequencies of 4 and 5 MHz. The potentiality of ultrasonic sensor signals combined with the OPF to characterize the microstructures of an inconel 625 thermally aged and in the as-welded condition were confirmed by the results. The experimental results revealed that the OPF classifier is sufficiently fast (classification total time of 0.316 ms) and accurate (accuracy of 88.75%" and harmonic mean of 89.52) for the application proposed.

Monitoring Snow Using Geostationary Satellite Retrievals During the SAAWSO Project

NASA Astrophysics Data System (ADS)

Rabin, Robert M.; Gultepe, Ismail; Kuligowski, Robert J.; Heidinger, Andrew K.

2016-09-01

The SAAWSO (Satellite Applications for Arctic Weather and SAR (Search And Rescue) Operations) field programs were conducted by Environment Canada near St. Johns, NL and Goose Bay, NL in the winters of 2012-13 and 2013-14, respectively. The goals of these programs were to validate satellite-based nowcasting products, including snow amount, wind intensity, and cloud physical parameters (e.g., cloud cover), over northern latitudes with potential applications to Search And Rescue (SAR) operations. Ground-based in situ sensors and remote sensing platforms were used to measure microphysical properties of precipitation, clouds and fog, radiation, temperature, moisture and wind profiles. Multi-spectral infrared observations obtained from Geostationary Operational Environmental Satellite (GOES)-13 provided estimates of cloud top temperature and height, phase (water, ice), hydrometer size, extinction, optical depth, and horizontal wind patterns at 15 min intervals. In this work, a technique developed for identifying clouds capable of producing high snowfall rates and incorporating wind information from the satellite observations is described. The cloud top physical properties retrieved from operational satellite observations are validated using measurements obtained from the ground-based in situ and remote sensing platforms collected during two precipitation events: a blizzard heavy snow storm case and a moderate snow event. The retrieved snow precipitation rates are found to be comparable to those of ground-based platform measurements in the heavy snow event.

Learning disordered topological phases by statistical recovery of symmetry

NASA Astrophysics Data System (ADS)

Yoshioka, Nobuyuki; Akagi, Yutaka; Katsura, Hosho

2018-05-01

We apply the artificial neural network in a supervised manner to map out the quantum phase diagram of disordered topological superconductors in class DIII. Given the disorder that keeps the discrete symmetries of the ensemble as a whole, translational symmetry which is broken in the quasiparticle distribution individually is recovered statistically by taking an ensemble average. By using this, we classify the phases by the artificial neural network that learned the quasiparticle distribution in the clean limit and show that the result is totally consistent with the calculation by the transfer matrix method or noncommutative geometry approach. If all three phases, namely the Z2, trivial, and thermal metal phases, appear in the clean limit, the machine can classify them with high confidence over the entire phase diagram. If only the former two phases are present, we find that the machine remains confused in a certain region, leading us to conclude the detection of the unknown phase which is eventually identified as the thermal metal phase.

Correcting Classifiers for Sample Selection Bias in Two-Phase Case-Control Studies

PubMed Central

Theis, Fabian J.

2017-01-01

Epidemiological studies often utilize stratified data in which rare outcomes or exposures are artificially enriched. This design can increase precision in association tests but distorts predictions when applying classifiers on nonstratified data. Several methods correct for this so-called sample selection bias, but their performance remains unclear especially for machine learning classifiers. With an emphasis on two-phase case-control studies, we aim to assess which corrections to perform in which setting and to obtain methods suitable for machine learning techniques, especially the random forest. We propose two new resampling-based methods to resemble the original data and covariance structure: stochastic inverse-probability oversampling and parametric inverse-probability bagging. We compare all techniques for the random forest and other classifiers, both theoretically and on simulated and real data. Empirical results show that the random forest profits from only the parametric inverse-probability bagging proposed by us. For other classifiers, correction is mostly advantageous, and methods perform uniformly. We discuss consequences of inappropriate distribution assumptions and reason for different behaviors between the random forest and other classifiers. In conclusion, we provide guidance for choosing correction methods when training classifiers on biased samples. For random forests, our method outperforms state-of-the-art procedures if distribution assumptions are roughly fulfilled. We provide our implementation in the R package sambia. PMID:29312464

Evaluation of a colorimetric reagent strip assay for urine specific gravity.

PubMed

Kirschbaum, B B

1983-06-01

N-Multistix SG provides a convenient colorimetric assay for the determination of the specific gravity (sp. gr.) of freshly voided urine. When compared with results obtained by standard hydrometry, the colorimetric assay sp. gr. was observed to decrease by as much as 0.010 units as urine pH increased from 5 to 7. Moderate levels of proteinuria that did not alter hydrometer readings effectively raised the colorimetric sp. gr. by 0.005-0.010 units. The colorimetric assay was almost completely insensitive to clinically encountered concentrations of glucose and urea but responded appropriately to monovalent salts. The magnitude of these observed discrepancies places serious limitations on the value of the colorimetric sp. gr. measurement.

A Nongraded Phase Elective Senior High English Curriculum.

ERIC Educational Resources Information Center

South Bend Community School Corp., IN.

The course content in this nongraded phase elective curriculum is classified into Phase 1, designed for students who find reading, writing, and speaking difficult, Phase 2 for students who need to improve and refine basic skills at a somewhat slower pace, Phase 3 for those who have an average command of basic language skills and want to advance at…

Evaluation of quick tests for phosphorus determination in dairy manures.

PubMed

Lugo-Ospina, A; Dao, Thanh H; Van Kessel, J A; Reeves, J B

2005-05-01

Nutrients in animal manure are valuable inputs in agronomic crop production. Rapid and timely information about manure nutrient content are needed to minimize the risks of phosphorus (P) over-application and losses of dissolved P (DP) in runoff from fields treated with manure. We evaluated the suitability of a commercial hand-held reflectometer, a hydrometer, and an electrical conductivity (EC) meter for determining DP and total P (TP) in dairy manures. Bulk samples (n = 107) collected from farms across CT, MD, NY, PA, and VA were highly variable in total solids (TS) concentration, ranging from 11 to 213gL(-1), in suspensions' pH (6.3-9.2), and EC (6.2-53.3 dS m(-1)). Manure DP concentrations measured using the RQFlex reflectometer (RQFlex-DP(s)) were related to molybdate-reactive P (MRP(s)) concentrations as follows: RQFlex-DP(s) = 0.471 x MRP(s) + 1102 (r2 = 0.29). Inclusion of pH and squared-pH terms improved the prediction of manure DP from RQFlex results (r2 = 0.66). Excluding five outlier samples that had pH < or = 6.9 the coefficient of determination (r2) for the MRP(s) and RQFlex-DP(s) relationship was 0.83 for 95% of the samples. Manure TS were related to hydrometer specific gravity readings (r2 = 0.53) that were in turn related to TP (r2 = 0.34), but not to either RQFlex-DP or MRP. Relationships between suspensions' EC and DP or TP were non-significant. Therefore, the RQFlex method is the only viable option for on-site quick estimates of DP that can be made more robust when complemented with TS and pH measurements. The DP quick test can provide near real-time information on soluble manure nutrient content across a wide range of handling and storage conditions on dairy farms and quick estimates of potential soluble P losses in runoff following land applications of manure.

Tennessee DUI probation followup demonstration project

DOT National Transportation Integrated Search

1981-04-01

This project was funded in 1975 for a 1 year planning phase, a 2 year operational phase, and a 221 year follow up period. During the operational phase, 4,148 clients were classified by drinker type using Mortimer-Filkins, and randomly assigned to tre...

RAWS: The spaceborne radar wind sounder

NASA Technical Reports Server (NTRS)

Moore, Richard K.

1991-01-01

The concept of the Radar Wind Sounder (RAWS) is discussed. The goals of the RAWS is to estimate the following three qualities: the echo power, to determine rain rate and surface wind velocity; the mean Doppler frequency, to determine the wind velocity in hydrometers; and the spread of the Doppler frequency, to determine the turbulent spread of the wind velocity. Researchers made significant progress during the first year. The feasibility of the concept seems certain. Studies indicate that a reasonably sized system can measure in the presence of ice clouds and dense water clouds. No sensitivity problems exist in rainy environments. More research is needed on the application of the radar to the measurement of rain rates and winds at the sea surface.

Total Lightning and Radar Storm Characteristics Associated with Severe Storms in Central Florida

NASA Technical Reports Server (NTRS)

Goodman, Steven J.; Raghavan, Ravi; Ramachandran, Rahul; Buechler, Dennis; Hodanish, Stephen; Sharp, David; Williams, Earle; Boldi, Bob; Matlin, Anne; Weber, Mark

1998-01-01

A number of prior studies have examined the association of lightning activity with the occurrence of severe weather and tornadoes, in particular. High flash rates are often observed in tornadic storms (Taylor, 1973; Johnson, 1980; Goodman and Knupp, 1993) but not always. Taylor found that 23% of nontornadic storms and 1% of non-severe storms had sferics rates comparable to the tornadic storms. MacGorman (1993) found that storms with mesocyclones produced more frequent intracloud (IC) lightning than cloud-to-ground (CG) lightning. MacGorman (1993) and others suggest that the lightning activity accompanying tomadic storms will be dominated by intracloud lightning-with an increase in intracloud and total flash rates as the updraft increases in depth, size, and velocity. In a recent study, Perez et al. (1998) found that CG flash rates alone are too variable to be a useful predictor of (F4, F5) tornado formation. Studies of non-tomadic storms have also shown that total lightning flash rates track the updraft, with rates increasing as the updraft intensities and decreasing rapidly with cessation of vertical growth or downburst onset (Goodman et al., 1988; Williams et al., 1989). Such relationships result from the development of mixed phase precipitation and increased hydrometer collisions that lead to the efficient separation of charge. Correlations between updraft strength and other variables such as cloud-top height, cloud water mass, and hail size have also been observed.

Detection of mass regions in mammograms by bilateral analysis adapted to breast density using similarity indexes and convolutional neural networks.

PubMed

Bandeira Diniz, João Otávio; Bandeira Diniz, Pedro Henrique; Azevedo Valente, Thales Levi; Corrêa Silva, Aristófanes; de Paiva, Anselmo Cardoso; Gattass, Marcelo

2018-03-01

The processing of medical image is an important tool to assist in minimizing the degree of uncertainty of the specialist, while providing specialists with an additional source of detect and diagnosis information. Breast cancer is the most common type of cancer that affects the female population around the world. It is also the most deadly type of cancer among women. It is the second most common type of cancer among all others. The most common examination to diagnose breast cancer early is mammography. In the last decades, computational techniques have been developed with the purpose of automatically detecting structures that maybe associated with tumors in mammography examination. This work presents a computational methodology to automatically detection of mass regions in mammography by using a convolutional neural network. The materials used in this work is the DDSM database. The method proposed consists of two phases: training phase and test phase. The training phase has 2 main steps: (1) create a model to classify breast tissue into dense and non-dense (2) create a model to classify regions of breast into mass and non-mass. The test phase has 7 step: (1) preprocessing; (2) registration; (3) segmentation; (4) first reduction of false positives; (5) preprocessing of regions segmented; (6) density tissue classification (7) second reduction of false positives where regions will be classified into mass and non-mass. The proposed method achieved 95.6% of accuracy in classify non-dense breasts tissue and 97,72% accuracy in classify dense breasts. To detect regions of mass in non-dense breast, the method achieved a sensitivity value of 91.5%, and specificity value of 90.7%, with 91% accuracy. To detect regions in dense breasts, our method achieved 90.4% of sensitivity and 96.4% of specificity, with accuracy of 94.8%. According to the results achieved by CNN, we demonstrate the feasibility of using convolutional neural networks on medical image processing techniques for classification of breast tissue and mass detection. Copyright © 2018 Elsevier B.V. All rights reserved.

Automated detection of heart ailments from 12-lead ECG using complex wavelet sub-band bi-spectrum features.

PubMed

Tripathy, Rajesh Kumar; Dandapat, Samarendra

2017-04-01

The complex wavelet sub-band bi-spectrum (CWSB) features are proposed for detection and classification of myocardial infarction (MI), heart muscle disease (HMD) and bundle branch block (BBB) from 12-lead ECG. The dual tree CW transform of 12-lead ECG produces CW coefficients at different sub-bands. The higher-order CW analysis is used for evaluation of CWSB. The mean of the absolute value of CWSB, and the number of negative phase angle and the number of positive phase angle features from the phase of CWSB of 12-lead ECG are evaluated. Extreme learning machine and support vector machine (SVM) classifiers are used to evaluate the performance of CWSB features. Experimental results show that the proposed CWSB features of 12-lead ECG and the SVM classifier are successful for classification of various heart pathologies. The individual accuracy values for MI, HMD and BBB classes are obtained as 98.37, 97.39 and 96.40%, respectively, using SVM classifier and radial basis function kernel function. A comparison has also been made with existing 12-lead ECG-based cardiac disease detection techniques.

A Predictive Model for Toxicity Effects Assessment of Biotransformed Hepatic Drugs Using Iterative Sampling Method.

PubMed

Tharwat, Alaa; Moemen, Yasmine S; Hassanien, Aboul Ella

2016-12-09

Measuring toxicity is one of the main steps in drug development. Hence, there is a high demand for computational models to predict the toxicity effects of the potential drugs. In this study, we used a dataset, which consists of four toxicity effects:mutagenic, tumorigenic, irritant and reproductive effects. The proposed model consists of three phases. In the first phase, rough set-based methods are used to select the most discriminative features for reducing the classification time and improving the classification performance. Due to the imbalanced class distribution, in the second phase, different sampling methods such as Random Under-Sampling, Random Over-Sampling and Synthetic Minority Oversampling Technique are used to solve the problem of imbalanced datasets. ITerative Sampling (ITS) method is proposed to avoid the limitations of those methods. ITS method has two steps. The first step (sampling step) iteratively modifies the prior distribution of the minority and majority classes. In the second step, a data cleaning method is used to remove the overlapping that is produced from the first step. In the third phase, Bagging classifier is used to classify an unknown drug into toxic or non-toxic. The experimental results proved that the proposed model performed well in classifying the unknown samples according to all toxic effects in the imbalanced datasets.

Hindrance Velocity Model for Phase Segregation in Suspensions of Poly-dispersed Randomly Oriented Spheroids

NASA Astrophysics Data System (ADS)

Faroughi, S. A.; Huber, C.

2015-12-01

Crystal settling and bubbles migration in magmas have significant effects on the physical and chemical evolution of magmas. The rate of phase segregation is controlled by the force balance that governs the migration of particles suspended in the melt. The relative velocity of a single particle or bubble in a quiescent infinite fluid (melt) is well characterized; however, the interplay between particles or bubbles in suspensions and emulsions and its effect on their settling/rising velocity remains poorly quantified. We propose a theoretical model for the hindered velocity of non-Brownian emulsions of nondeformable droplets, and suspensions of spherical solid particles in the creeping flow regime. The model is based on three sets of hydrodynamic corrections: two on the drag coefficient experienced by each particle to account for both return flow and Smoluchowski effects and a correction on the mixture rheology to account for nonlocal interactions between particles. The model is then extended for mono-disperse non-spherical solid particles that are randomly oriented. The non-spherical particles are idealized as spheroids and characterized by their aspect ratio. The poly-disperse nature of natural suspensions is then taken into consideration by introducing an effective volume fraction of particles for each class of mono-disperse particles sizes. Our model is tested against new and published experimental data over a wide range of particle volume fraction and viscosity ratios between the constituents of dispersions. We find an excellent agreement between our model and experiments. We also show two significant applications for our model: (1) We demonstrate that hindered settling can increase mineral residence time by up to an order of magnitude in convecting magma chambers. (2) We provide a model to correct for particle interactions in the conventional hydrometer test to estimate the particle size distribution in soils. Our model offers a greatly improved agreement with the results obtained with direct measurement methods such as laser diffraction.

Vesicle deformation by microtubules: A phase diagram

NASA Astrophysics Data System (ADS)

Emsellem, Virginie; Cardoso, Olivier; Tabeling, Patrick

1998-10-01

The experimental investigation of vesicles deformed by the growth of encapsulated microtubules shows that the axisymmetric morphologies can be classified into ovals, lemons, φ, cherries, dumbbells, and pearls. A geometrical phase diagram is established. Numerical minimization of the elastic energy of the membrane reproduces satisfactorily well the observed morphologies and the corresponding phase diagram.

Statistical Methods for Passive Vehicle Classification in Urban Traffic Surveillance and Control

DOT National Transportation Integrated Search

1980-01-01

A statistical approach to passive vehicle classification using the phase-shift signature from electromagnetic presence-type vehicle detectors is developed with digitized samples of the analog phase-shift signature, the problem of classifying vehicle ...

Sensitivity of snow process simulations to precipitation-phase transition method in forested and open areas

NASA Astrophysics Data System (ADS)

Lundberg, A.; Gustafsson, D.

2009-04-01

Modeling of forest snow processes is complicated and especially problematic seems to be the separation of precipitation phase in climates where a large part of the precipitation falls at temperatures near zero degrees Celsius. When the precipitation is classified as snow, the tree crowns can carry an order of magnitude more canopy storage as compared to when the precipitation is classified as rain, and snow in the trees also alters the albedo of the forest while rain does not. Many different schemes for the precipitation phase separation are used by various snow models. Some models use just one air temperature threshold (TR/S) below which all precipitation is assumed to be snow and above which all precipitation is classified as rain. A more common approach for forest snow models is to use two temperature thresholds. The snow fraction (SF) is then set to one below the snow threshold (TS) and to zero above the rain threshold (TR) and SF is assumed to decrease linearly between these two thresholds. Also more sophisticated schemes exist, but three seems to be a lack of agreement on how the precipitation phase separations should be performed. The aim with this study is to use a hydrological model including canopy snow processes to illustrate the sensitivity for different formulations of the precipitation phase separation on a) the simulated maximum snow pack storage b) the interception evaporation loss and c) snow melt runoff. In other words, to investigate of the choice of precipitation phase separation has an impact on the simulated wintertime water balance. Simulations are made for sites in different climates and for both open fields and forest sites in different regions of Sweden from north to south. In general, precipitation phase separation methods that classified snowfall at higher temperatures resulted in a larger proportion of the precipitation lost by interception evaporation as a result of the increased interception capacity. However, the maximum snow accumulation was also increased in some cases due to the overall increased snowfall, depending on canopy density and precipitation and temperature regimes. Results show that the choice of precipitation phase separation method can have an significant impact on the simulated wintertime water balance, especially in forested regions.

MIDAS, prototype Multivariate Interactive Digital Analysis System, phase 1. Volume 3: Wiring diagrams

NASA Technical Reports Server (NTRS)

Kriegler, F. J.; Christenson, D.; Gordon, M.; Kistler, R.; Lampert, S.; Marshall, R.; Mclaughlin, R.

1974-01-01

The Midas System is a third-generation, fast, multispectral recognition system able to keep pace with the large quantity and high rates of data acquisition from present and projected sensors. A principal objective of the MIDAS Program is to provide a system well interfaced with the human operator and thus to obtain large overall reductions in turn-around time and significant gains in throughput. The hardware and software generated in Phase I of the overall program are described. The system contains a mini-computer to control the various high-speed processing elements in the data path and a classifier which implements an all-digital prototype multivariate-Gaussian maximum likelihood decision algorithm operating at 2 x 100,000 pixels/sec. Sufficient hardware was developed to perform signature extraction from computer-compatible tapes, compute classifier coefficients, control the classifier operation, and diagnose operation. The MIDAS construction and wiring diagrams are given.

MIDAS, prototype Multivariate Interactive Digital Analysis System, Phase 1. Volume 2: Diagnostic system

NASA Technical Reports Server (NTRS)

Kriegler, F. J.; Christenson, D.; Gordon, M.; Kistler, R.; Lampert, S.; Marshall, R.; Mclaughlin, R.

1974-01-01

The MIDAS System is a third-generation, fast, multispectral recognition system able to keep pace with the large quantity and high rates of data acquisition from present and projected sensors. A principal objective of the MIDAS Program is to provide a system well interfaced with the human operator and thus to obtain large overall reductions in turn-around time and significant gains in throughout. The hardware and software generated in Phase I of the over-all program are described. The system contains a mini-computer to control the various high-speed processing elements in the data path and a classifier which implements an all-digital prototype multivariate-Gaussian maximum likelihood decision algorithm operating 2 x 105 pixels/sec. Sufficient hardware was developed to perform signature extraction from computer-compatible tapes, compute classifier coefficients, control the classifier operation, and diagnose operation. Diagnostic programs used to test MIDAS' operations are presented.

Classifying the auditory P300 using mobile EEG recordings without calibration phase.

PubMed

Zink, R; Hunyádi, B; Van Huffel, S; De Vos, M

2015-08-01

One of the major drawbacks in mobile EEG Brain Computer Interfaces (BCI) is the need for subject specific training data to train a classifier. By removing the need for supervised classification and calibration phase, new users could start immediate interaction with a BCI. We propose a solution to exploit the structural difference by means of canonical polyadic decomposition (CPD) for three-class auditory oddball data without the need for subject-specific information. We achieve this by adding average event-related-potential (ERP) templates to the CPD model. This constitutes a novel similarity measure between single-trial pairs and known-templates, which results in a fast and interpretable classifier. These results have similar accuracy to those of the supervised and cross-validated stepwise LDA approach but without the need for having subject-dependent data. Therefore the described CPD method has a significant practical advantage over the traditional and widely used approach.

Influence of multiple scattering on CloudSat measurements in snow: A model study

NASA Astrophysics Data System (ADS)

Matrosov, Sergey Y.; Battaglia, Alessandro

2009-06-01

The effects of multiple scattering on larger precipitating hydrometers have an influence on measurements of the spaceborne W-band (94 GHz) CloudSat radar. This study presents initial quantitative estimates of these effects in “dry” snow using radiative transfer calculations for appropriate snowfall models. It is shown that these effects become significant (i.e., greater than approximately 1 dB) when snowfall radar reflectivity factors are greater than about 10-15 dBZ. Reflectivity enhancement due to multiple scattering can reach 4-5 dB in heavier stratiform snowfalls. Multiple scattering effects counteract signal attenuation, so the observed CloudSat reflectivity factors in snowfall could be relatively close to the values that would be observed in the case of single scattering and the absence of attenuation.

An intelligent classifier for prognosis of cardiac resynchronization therapy based on speckle-tracking echocardiograms.

PubMed

Chao, Pei-Kuang; Wang, Chun-Li; Chan, Hsiao-Lung

2012-03-01

Predicting response after cardiac resynchronization therapy (CRT) has been a challenge of cardiologists. About 30% of selected patients based on the standard selection criteria for CRT do not show response after receiving the treatment. This study is aimed to build an intelligent classifier to assist in identifying potential CRT responders by speckle-tracking radial strain based on echocardiograms. The echocardiograms analyzed were acquired before CRT from 26 patients who have received CRT. Sequential forward selection was performed on the parameters obtained by peak-strain timing and phase space reconstruction on speckle-tracking radial strain to find an optimal set of features for creating intelligent classifiers. Support vector machine (SVM) with a linear, quadratic, and polynominal kernel were tested to build classifiers to identify potential responders and non-responders for CRT by selected features. Based on random sub-sampling validation, the best classification performance is correct rate about 95% with 96-97% sensitivity and 93-94% specificity achieved by applying SVM with a quadratic kernel on a set of 3 parameters. The selected 3 parameters contain both indexes extracted by peak-strain timing and phase space reconstruction. An intelligent classifier with an averaged correct rate, sensitivity and specificity above 90% for assisting in identifying CRT responders is built by speckle-tracking radial strain. The classifier can be applied to provide objective suggestion for patient selection of CRT. Copyright © 2011 Elsevier B.V. All rights reserved.

Discussion of Priorities

NASA Technical Reports Server (NTRS)

2003-01-01

The Microgravity Science Division identifies four priority ratings for microgravity research and technology issues: 1) Critical; 2) Severely Limiting; 3) Enhancements; 4) Communication. Reduced gravity instabilities are critical, while severely limiting issues include phase separation, phase change, and flow through components. Enhancements are listed for passive phase separation and phase change. This viewgraph presentation also classifies microgravity issues as spaceflight, ground-based, or other for the time periods 2003-2008, 2009-2015, and beyond.

Automated detection of heart ailments from 12-lead ECG using complex wavelet sub-band bi-spectrum features

PubMed Central

Dandapat, Samarendra

2017-01-01

The complex wavelet sub-band bi-spectrum (CWSB) features are proposed for detection and classification of myocardial infarction (MI), heart muscle disease (HMD) and bundle branch block (BBB) from 12-lead ECG. The dual tree CW transform of 12-lead ECG produces CW coefficients at different sub-bands. The higher-order CW analysis is used for evaluation of CWSB. The mean of the absolute value of CWSB, and the number of negative phase angle and the number of positive phase angle features from the phase of CWSB of 12-lead ECG are evaluated. Extreme learning machine and support vector machine (SVM) classifiers are used to evaluate the performance of CWSB features. Experimental results show that the proposed CWSB features of 12-lead ECG and the SVM classifier are successful for classification of various heart pathologies. The individual accuracy values for MI, HMD and BBB classes are obtained as 98.37, 97.39 and 96.40%, respectively, using SVM classifier and radial basis function kernel function. A comparison has also been made with existing 12-lead ECG-based cardiac disease detection techniques. PMID:28894589

Learning accurate very fast decision trees from uncertain data streams

NASA Astrophysics Data System (ADS)

Liang, Chunquan; Zhang, Yang; Shi, Peng; Hu, Zhengguo

2015-12-01

Most existing works on data stream classification assume the streaming data is precise and definite. Such assumption, however, does not always hold in practice, since data uncertainty is ubiquitous in data stream applications due to imprecise measurement, missing values, privacy protection, etc. The goal of this paper is to learn accurate decision tree models from uncertain data streams for classification analysis. On the basis of very fast decision tree (VFDT) algorithms, we proposed an algorithm for constructing an uncertain VFDT tree with classifiers at tree leaves (uVFDTc). The uVFDTc algorithm can exploit uncertain information effectively and efficiently in both the learning and the classification phases. In the learning phase, it uses Hoeffding bound theory to learn from uncertain data streams and yield fast and reasonable decision trees. In the classification phase, at tree leaves it uses uncertain naive Bayes (UNB) classifiers to improve the classification performance. Experimental results on both synthetic and real-life datasets demonstrate the strong ability of uVFDTc to classify uncertain data streams. The use of UNB at tree leaves has improved the performance of uVFDTc, especially the any-time property, the benefit of exploiting uncertain information, and the robustness against uncertainty.

Disambiguating ambiguous biomedical terms in biomedical narrative text: an unsupervised method.

PubMed

Liu, H; Lussier, Y A; Friedman, C

2001-08-01

With the growing use of Natural Language Processing (NLP) techniques for information extraction and concept indexing in the biomedical domain, a method that quickly and efficiently assigns the correct sense of an ambiguous biomedical term in a given context is needed concurrently. The current status of word sense disambiguation (WSD) in the biomedical domain is that handcrafted rules are used based on contextual material. The disadvantages of this approach are (i) generating WSD rules manually is a time-consuming and tedious task, (ii) maintenance of rule sets becomes increasingly difficult over time, and (iii) handcrafted rules are often incomplete and perform poorly in new domains comprised of specialized vocabularies and different genres of text. This paper presents a two-phase unsupervised method to build a WSD classifier for an ambiguous biomedical term W. The first phase automatically creates a sense-tagged corpus for W, and the second phase derives a classifier for W using the derived sense-tagged corpus as a training set. A formative experiment was performed, which demonstrated that classifiers trained on the derived sense-tagged corpora achieved an overall accuracy of about 97%, with greater than 90% accuracy for each individual ambiguous term.

Non-invasive classification of gas-liquid two-phase horizontal flow regimes using an ultrasonic Doppler sensor and a neural network

NASA Astrophysics Data System (ADS)

Musa Abbagoni, Baba; Yeung, Hoi

2016-08-01

The identification of flow pattern is a key issue in multiphase flow which is encountered in the petrochemical industry. It is difficult to identify the gas-liquid flow regimes objectively with the gas-liquid two-phase flow. This paper presents the feasibility of a clamp-on instrument for an objective flow regime classification of two-phase flow using an ultrasonic Doppler sensor and an artificial neural network, which records and processes the ultrasonic signals reflected from the two-phase flow. Experimental data is obtained on a horizontal test rig with a total pipe length of 21 m and 5.08 cm internal diameter carrying air-water two-phase flow under slug, elongated bubble, stratified-wavy and, stratified flow regimes. Multilayer perceptron neural networks (MLPNNs) are used to develop the classification model. The classifier requires features as an input which is representative of the signals. Ultrasound signal features are extracted by applying both power spectral density (PSD) and discrete wavelet transform (DWT) methods to the flow signals. A classification scheme of ‘1-of-C coding method for classification’ was adopted to classify features extracted into one of four flow regime categories. To improve the performance of the flow regime classifier network, a second level neural network was incorporated by using the output of a first level networks feature as an input feature. The addition of the two network models provided a combined neural network model which has achieved a higher accuracy than single neural network models. Classification accuracies are evaluated in the form of both the PSD and DWT features. The success rates of the two models are: (1) using PSD features, the classifier missed 3 datasets out of 24 test datasets of the classification and scored 87.5% accuracy; (2) with the DWT features, the network misclassified only one data point and it was able to classify the flow patterns up to 95.8% accuracy. This approach has demonstrated the success of a clamp-on ultrasound sensor for flow regime classification that would be possible in industry practice. It is considerably more promising than other techniques as it uses a non-invasive and non-radioactive sensor.

External risk factors affecting construction costs

NASA Astrophysics Data System (ADS)

Mubarak, Husin, Saiful; Oktaviati, Mutia

2017-11-01

Some risk factors can have impacts on the cost, time, and performance. Results of previous studies indicated that the external conditions are among the factors which give effect to the contractor in the completion of the project. The analysis in the study carried out by considering the conditions of the project in the last 15 years in Aceh province, divided into military conflict phase (2000-2004), post tsunami disaster rehabilitation and reconstruction phase (2005-2009), and post-rehabilitation and reconstruction phase (2010-present). This study intended to analyze the impact of external risk factors, primarily related to the impact on project costs and to investigate the influence of the risk factors and construction phases impacted the project cost. Data was collected by using a questionnaire distributed in 15 large companies qualification contractors in Aceh province. Factors analyzed consisted of socio-political, government policies, natural disasters, and monetary conditions. Data were analyzed using statistical application of severity index to measure the level of risk impact. The analysis results presented the tendency of impact on cost can generally be classified as low. There is only one variable classified as high-impact, variable `fuel price increases', which appear on the military conflict and post tsunami disaster rehabilitation and reconstruction periods. The risk impact on costs from the factors and variables classified with high intensity needs a serious attention, especially when the high level impact is followed by the high frequency of occurrences.

Water: from the source to the treatment plan

NASA Astrophysics Data System (ADS)

Baude, I.; Marquet, V.

2012-04-01

Isabelle BAUDE isa.baude@free.fr Lycee français de Vienne Liechtensteinstrasse 37AVienna As a physics and chemistry teacher, I have worked on water from the source to the treatment plant with 27 pupils between 14 and 15 years old enrolled in the option "Science and laboratory". The objectives of this option are to interest students in science, to introduce them to practical methods of laboratory analyses, and let them use computer technology. Teaching takes place every two weeks and lasts 1.5 hours. The theme of water is a common project with the biology and geology teacher, Mrs. Virginie Marquet. Lesson 1: Introduction: The water in Vienna The pupils have to consider why the water is so important in Vienna (history, economy etc.) and where tap water comes from. Activities: Brainstorming about where and why we use water every day and why the water is different in Vienna. Lesson 2: Objectives of the session: What are the differences between mineral waters? Activities: Compare water from different origins (France: Evian, Vittel, Contrex. Austria: Vöslauer, Juvina, Gasteiner and tap water from Vienna) by tasting and finding the main ions they contain. Testing ions: Calcium, magnesium, sulphate, chloride, sodium, and potassium Lesson 3: Objectives of the session: Build a hydrometer Activities: Producing a range of calibration solutions, build and calibrate the hydrometer with different salt-water solutions. Measure the density of the Dead Sea's water and other mineral waters. Lesson 4: Objectives of the session: How does a fountain work? Activities: Construction of a fountain as Heron of Alexandria with simple equipment and try to understand the hydrostatic principles. Lesson 5: Objectives of the session: Study of the physical processes of water treatment (decantation, filtration, screening) Activities: Build a natural filter with sand, stone, carbon, and cotton wool. Retrieve the filtered water to test it during lesson 7. Lesson 6: Visit of the biggest treatment plant of Europe in Vienna. Lesson 7: Objectives of the session: Water Quality Monitoring: Biochemical Oxygen Demand (chemical analysis) in common with my colleague.

Soy sauce classification by geographic region and fermentation based on artificial neural network and genetic algorithm.

PubMed

Xu, Libin; Li, Yang; Xu, Ning; Hu, Yong; Wang, Chao; He, Jianjun; Cao, Yueze; Chen, Shigui; Li, Dongsheng

2014-12-24

This work demonstrated the possibility of using artificial neural networks to classify soy sauce from China. The aroma profiles of different soy sauce samples were differentiated using headspace solid-phase microextraction. The soy sauce samples were analyzed by gas chromatography-mass spectrometry, and 22 and 15 volatile aroma compounds were selected for sensitivity analysis to classify the samples by fermentation and geographic region, respectively. The 15 selected samples can be classified by fermentation and geographic region with a prediction success rate of 100%. Furans and phenols represented the variables with the greatest contribution in classifying soy sauce samples by fermentation and geographic region, respectively.

Multi-Sensor Data Fusion Project

DTIC Science & Technology

2000-02-28

seismic network by detecting T phases generated by underground events ( generally earthquakes ) and associating these phases to seismic events. The...between underwater explosions (H), underground sources, mostly earthquake - generated (7), and noise detections (N). The phases classified as H are the only...processing for infrasound sensors is most similar to seismic array processing with the exception that the detections are based on a more sophisticated

Shape based segmentation of MRIs of the bones in the knee using phase and intensity information

NASA Astrophysics Data System (ADS)

Fripp, Jurgen; Bourgeat, Pierrick; Crozier, Stuart; Ourselin, Sébastien

2007-03-01

The segmentation of the bones from MR images is useful for performing subsequent segmentation and quantitative measurements of cartilage tissue. In this paper, we present a shape based segmentation scheme for the bones that uses texture features derived from the phase and intensity information in the complex MR image. The phase can provide additional information about the tissue interfaces, but due to the phase unwrapping problem, this information is usually discarded. By using a Gabor filter bank on the complex MR image, texture features (including phase) can be extracted without requiring phase unwrapping. These texture features are then analyzed using a support vector machine classifier to obtain probability tissue matches. The segmentation of the bone is fully automatic and performed using a 3D active shape model based approach driven using gradient and texture information. The 3D active shape model is automatically initialized using a robust affine registration. The approach is validated using a database of 18 FLASH MR images that are manually segmented, with an average segmentation overlap (Dice similarity coefficient) of 0.92 compared to 0.9 obtained using the classifier only.

Topological phases protected by point group symmetry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Song, Hao; Huang, Sheng -Jie; Fu, Liang

We consider symmetry-protected topological (SPT) phases with crystalline point group symmetry, dubbed point group SPT (pgSPT) phases. We show that such phases can be understood in terms of lower-dimensional topological phases with on-site symmetry and that they can be constructed as stacks and arrays of these lower-dimensional states. This provides the basis for a general framework to classify and characterize bosonic and fermionic pgSPT phases, which can be applied for arbitrary crystalline point group symmetry and in arbitrary spatial dimensions. We develop and illustrate this framework by means of a few examples, focusing on three-dimensional states. We classify bosonic pgSPTmore » phases and fermionic topological crystalline superconductors with Z P 2 (reflection) symmetry, electronic topological crystalline insulators (TCIs) with U(1)×Z P 2 symmetry, and bosonic pgSPT phases with C 2v symmetry, which is generated by two perpendicular mirror reflections. We also study surface properties, with a focus on gapped, topologically ordered surface states. For electronic TCIs, we find a Z 8 × Z 2 classification, where the Z 8 corresponds to known states obtained from noninteracting electrons, and the Z 2 corresponds to a “strongly correlated” TCI that requires strong interactions in the bulk. Lastly, our approach may also point the way toward a general theory of symmetry-enriched topological phases with crystalline point group symmetry.« less

New Baxter phase in the Ashkin-Teller model on a cubic lattice

NASA Astrophysics Data System (ADS)

Santos, J. P.; Rosa, D. S.; Sá Barreto, F. C.

2018-02-01

The mean field theory results are obtained from the Bogoliubov inequality for the spin-1/2 Ashkin-Teller model on a cubic lattice for different cluster sizes. The phase diagram, magnetization and free energy are obtained. From those expressions we observed a new phase in the model. Denoted in the course of this work by Baxter(2) this new phase presents 〈 S 〉 ≠ 〈 σ 〉 ≠ 0. The phase transitions between the Baxter(2) and the others well known phases for the model are studied and classified.

Interaction geometry: an ecological perspective.

Treesearch

Rolfe A. Leary

1976-01-01

A new mathematical coordinate system results from a unique combination of two frameworks long used by ecologists: the phase plane and coaction cross-tabulation. The resulting construct combines the classifying power of the cross-tabulation and discriminating power of the phase plane. It may be used for analysis and synthesis.

Determination of precipitation profiles from airborne passive microwave radiometric measurements

NASA Technical Reports Server (NTRS)

Kummerow, Christian; Hakkarinen, Ida M.; Pierce, Harold F.; Weinman, James A.

1991-01-01

This study presents the first quantitative retrievals of vertical profiles of precipitation derived from multispectral passive microwave radiometry. Measurements of microwave brightness temperature (Tb) obtained by a NASA high-altitude research aircraft are related to profiles of rainfall rate through a multichannel piecewise-linear statistical regression procedure. Statistics for Tb are obtained from a set of cloud radiative models representing a wide variety of convective, stratiform, and anvil structures. The retrieval scheme itself determines which cloud model best fits the observed meteorological conditions. Retrieved rainfall rate profiles are converted to equivalent radar reflectivity for comparison with observed reflectivities from a ground-based research radar. Results for two case studies, a stratiform rain situation and an intense convective thunderstorm, show that the radiometrically derived profiles capture the major features of the observed vertical structure of hydrometer density.

The energy requirements of an aircraft triggered discharge

NASA Astrophysics Data System (ADS)

Bicknell, J. A.; Shelton, R. W.

The corona produced at aircraft surfaces requires an energy input before the corona can develop into a high current discharge and, thus, a possible lightning stroke. This energy must be drawn from the space charge field of the thundercloud and, since this is of low density, the unique propagation characteristics of positive corona streamers may be important. Estimates of the energy made available by the propagation are compared with laboratory measurements of the minimum energy input required to trigger a breakdown. The comparison indicates a minimum streamer range for breakdown of several tens of meters. Also estimated is the energy released as a consequence of streamer-hydrometer interactions; this is shown to be significant so that breakdown could depend upon the precipitation rate within the cloud. Inhibiting streamer production may therefore provide an aircraft with a degree of corona protection.

Evaluation of an Algorithm to Predict Menstrual-Cycle Phase at the Time of Injury.

PubMed

Tourville, Timothy W; Shultz, Sandra J; Vacek, Pamela M; Knudsen, Emily J; Bernstein, Ira M; Tourville, Kelly J; Hardy, Daniel M; Johnson, Robert J; Slauterbeck, James R; Beynnon, Bruce D

2016-01-01

Women are 2 to 8 times more likely to sustain an anterior cruciate ligament (ACL) injury than men, and previous studies indicated an increased risk for injury during the preovulatory phase of the menstrual cycle (MC). However, investigations of risk rely on retrospective classification of MC phase, and no tools for this have been validated. To evaluate the accuracy of an algorithm for retrospectively classifying MC phase at the time of a mock injury based on MC history and salivary progesterone (P4) concentration. Descriptive laboratory study. Research laboratory. Thirty-one healthy female collegiate athletes (age range, 18-24 years) provided serum or saliva (or both) samples at 8 visits over 1 complete MC. Self-reported MC information was obtained on a randomized date (1-45 days) after mock injury, which is the typical timeframe in which researchers have access to ACL-injured study participants. The MC phase was classified using the algorithm as applied in a stand-alone computational fashion and also by 4 clinical experts using the algorithm and additional subjective hormonal history information to help inform their decision. To assess algorithm accuracy, phase classifications were compared with the actual MC phase at the time of mock injury (ascertained using urinary luteinizing hormone tests and serial serum P4 samples). Clinical expert and computed classifications were compared using κ statistics. Fourteen participants (45%) experienced anovulatory cycles. The algorithm correctly classified MC phase for 23 participants (74%): 22 (76%) of 29 who were preovulatory/anovulatory and 1 (50%) of 2 who were postovulatory. Agreement between expert and algorithm classifications ranged from 80.6% (κ = 0.50) to 93% (κ = 0.83). Classifications based on same-day saliva sample and optimal P4 threshold were the same as those based on MC history alone (87.1% correct). Algorithm accuracy varied during the MC but at no time were both sensitivity and specificity levels acceptable. These findings raise concerns about the accuracy of previous retrospective MC-phase classification systems, particularly in a population with a high occurrence of anovulatory cycles.

Classification of earth terrain using polarimetric synthetic aperture radar images

NASA Technical Reports Server (NTRS)

Lim, H. H.; Swartz, A. A.; Yueh, H. A.; Kong, J. A.; Shin, R. T.; Van Zyl, J. J.

1989-01-01

Supervised and unsupervised classification techniques are developed and used to classify the earth terrain components from SAR polarimetric images of San Francisco Bay and Traverse City, Michigan. The supervised techniques include the Bayes classifiers, normalized polarimetric classification, and simple feature classification using discriminates such as the absolute and normalized magnitude response of individual receiver channel returns and the phase difference between receiver channels. An algorithm is developed as an unsupervised technique which classifies terrain elements based on the relationship between the orientation angle and the handedness of the transmitting and receiving polariation states. It is found that supervised classification produces the best results when accurate classifier training data are used, while unsupervised classification may be applied when training data are not available.

Integrated Emergy and Economic Evaluation of Tea Production Chains in Anxi, China

EPA Science Inventory

Emergy and economic methods were used to evaluate and compare tea production systems in Anxi, China. Tea production was classified into three phases, i.e., the nursery, the plantation and tea processing, and each phase was evaluated. The results showed that the nursery subsystems...

Clinical application of modified bag-of-features coupled with hybrid neural-based classifier in dengue fever classification using gene expression data.

PubMed

Chatterjee, Sankhadeep; Dey, Nilanjan; Shi, Fuqian; Ashour, Amira S; Fong, Simon James; Sen, Soumya

2018-04-01

Dengue fever detection and classification have a vital role due to the recent outbreaks of different kinds of dengue fever. Recently, the advancement in the microarray technology can be employed for such classification process. Several studies have established that the gene selection phase takes a significant role in the classifier performance. Subsequently, the current study focused on detecting two different variations, namely, dengue fever (DF) and dengue hemorrhagic fever (DHF). A modified bag-of-features method has been proposed to select the most promising genes in the classification process. Afterward, a modified cuckoo search optimization algorithm has been engaged to support the artificial neural (ANN-MCS) to classify the unknown subjects into three different classes namely, DF, DHF, and another class containing convalescent and normal cases. The proposed method has been compared with other three well-known classifiers, namely, multilayer perceptron feed-forward network (MLP-FFN), artificial neural network (ANN) trained with cuckoo search (ANN-CS), and ANN trained with PSO (ANN-PSO). Experiments have been carried out with different number of clusters for the initial bag-of-features-based feature selection phase. After obtaining the reduced dataset, the hybrid ANN-MCS model has been employed for the classification process. The results have been compared in terms of the confusion matrix-based performance measuring metrics. The experimental results indicated a highly statistically significant improvement with the proposed classifier over the traditional ANN-CS model.

Improving Classification of Cancer and Mining Biomarkers from Gene Expression Profiles Using Hybrid Optimization Algorithms and Fuzzy Support Vector Machine

PubMed Central

Moteghaed, Niloofar Yousefi; Maghooli, Keivan; Garshasbi, Masoud

2018-01-01

Background: Gene expression data are characteristically high dimensional with a small sample size in contrast to the feature size and variability inherent in biological processes that contribute to difficulties in analysis. Selection of highly discriminative features decreases the computational cost and complexity of the classifier and improves its reliability for prediction of a new class of samples. Methods: The present study used hybrid particle swarm optimization and genetic algorithms for gene selection and a fuzzy support vector machine (SVM) as the classifier. Fuzzy logic is used to infer the importance of each sample in the training phase and decrease the outlier sensitivity of the system to increase the ability to generalize the classifier. A decision-tree algorithm was applied to the most frequent genes to develop a set of rules for each type of cancer. This improved the abilities of the algorithm by finding the best parameters for the classifier during the training phase without the need for trial-and-error by the user. The proposed approach was tested on four benchmark gene expression profiles. Results: Good results have been demonstrated for the proposed algorithm. The classification accuracy for leukemia data is 100%, for colon cancer is 96.67% and for breast cancer is 98%. The results show that the best kernel used in training the SVM classifier is the radial basis function. Conclusions: The experimental results show that the proposed algorithm can decrease the dimensionality of the dataset, determine the most informative gene subset, and improve classification accuracy using the optimal parameters of the classifier with no user interface. PMID:29535919

Machine learning vortices at the Kosterlitz-Thouless transition

NASA Astrophysics Data System (ADS)

Beach, Matthew J. S.; Golubeva, Anna; Melko, Roger G.

2018-01-01

Efficient and automated classification of phases from minimally processed data is one goal of machine learning in condensed-matter and statistical physics. Supervised algorithms trained on raw samples of microstates can successfully detect conventional phase transitions via learning a bulk feature such as an order parameter. In this paper, we investigate whether neural networks can learn to classify phases based on topological defects. We address this question on the two-dimensional classical XY model which exhibits a Kosterlitz-Thouless transition. We find significant feature engineering of the raw spin states is required to convincingly claim that features of the vortex configurations are responsible for learning the transition temperature. We further show a single-layer network does not correctly classify the phases of the XY model, while a convolutional network easily performs classification by learning the global magnetization. Finally, we design a deep network capable of learning vortices without feature engineering. We demonstrate the detection of vortices does not necessarily result in the best classification accuracy, especially for lattices of less than approximately 1000 spins. For larger systems, it remains a difficult task to learn vortices.

Classifier Subset Selection for the Stacked Generalization Method Applied to Emotion Recognition in Speech

PubMed Central

Álvarez, Aitor; Sierra, Basilio; Arruti, Andoni; López-Gil, Juan-Miguel; Garay-Vitoria, Nestor

2015-01-01

In this paper, a new supervised classification paradigm, called classifier subset selection for stacked generalization (CSS stacking), is presented to deal with speech emotion recognition. The new approach consists of an improvement of a bi-level multi-classifier system known as stacking generalization by means of an integration of an estimation of distribution algorithm (EDA) in the first layer to select the optimal subset from the standard base classifiers. The good performance of the proposed new paradigm was demonstrated over different configurations and datasets. First, several CSS stacking classifiers were constructed on the RekEmozio dataset, using some specific standard base classifiers and a total of 123 spectral, quality and prosodic features computed using in-house feature extraction algorithms. These initial CSS stacking classifiers were compared to other multi-classifier systems and the employed standard classifiers built on the same set of speech features. Then, new CSS stacking classifiers were built on RekEmozio using a different set of both acoustic parameters (extended version of the Geneva Minimalistic Acoustic Parameter Set (eGeMAPS)) and standard classifiers and employing the best meta-classifier of the initial experiments. The performance of these two CSS stacking classifiers was evaluated and compared. Finally, the new paradigm was tested on the well-known Berlin Emotional Speech database. We compared the performance of single, standard stacking and CSS stacking systems using the same parametrization of the second phase. All of the classifications were performed at the categorical level, including the six primary emotions plus the neutral one. PMID:26712757

Topological Band Theory for Non-Hermitian Hamiltonians

NASA Astrophysics Data System (ADS)

Shen, Huitao; Zhen, Bo; Fu, Liang

2018-04-01

We develop the topological band theory for systems described by non-Hermitian Hamiltonians, whose energy spectra are generally complex. After generalizing the notion of gapped band structures to the non-Hermitian case, we classify "gapped" bands in one and two dimensions by explicitly finding their topological invariants. We find nontrivial generalizations of the Chern number in two dimensions, and a new classification in one dimension, whose topology is determined by the energy dispersion rather than the energy eigenstates. We then study the bulk-edge correspondence and the topological phase transition in two dimensions. Different from the Hermitian case, the transition generically involves an extended intermediate phase with complex-energy band degeneracies at isolated "exceptional points" in momentum space. We also systematically classify all types of band degeneracies.

Adiabatic Quantum Anomaly Detection and Machine Learning

NASA Astrophysics Data System (ADS)

Pudenz, Kristen; Lidar, Daniel

2012-02-01

We present methods of anomaly detection and machine learning using adiabatic quantum computing. The machine learning algorithm is a boosting approach which seeks to optimally combine somewhat accurate classification functions to create a unified classifier which is much more accurate than its components. This algorithm then becomes the first part of the larger anomaly detection algorithm. In the anomaly detection routine, we first use adiabatic quantum computing to train two classifiers which detect two sets, the overlap of which forms the anomaly class. We call this the learning phase. Then, in the testing phase, the two learned classification functions are combined to form the final Hamiltonian for an adiabatic quantum computation, the low energy states of which represent the anomalies in a binary vector space.

Identification and characterization of plastid-type proteins from sequence-attributed features using machine learning

PubMed Central

2013-01-01

Background Plastids are an important component of plant cells, being the site of manufacture and storage of chemical compounds used by the cell, and contain pigments such as those used in photosynthesis, starch synthesis/storage, cell color etc. They are essential organelles of the plant cell, also present in algae. Recent advances in genomic technology and sequencing efforts is generating a huge amount of DNA sequence data every day. The predicted proteome of these genomes needs annotation at a faster pace. In view of this, one such annotation need is to develop an automated system that can distinguish between plastid and non-plastid proteins accurately, and further classify plastid-types based on their functionality. We compared the amino acid compositions of plastid proteins with those of non-plastid ones and found significant differences, which were used as a basis to develop various feature-based prediction models using similarity-search and machine learning. Results In this study, we developed separate Support Vector Machine (SVM) trained classifiers for characterizing the plastids in two steps: first distinguishing the plastid vs. non-plastid proteins, and then classifying the identified plastids into their various types based on their function (chloroplast, chromoplast, etioplast, and amyloplast). Five diverse protein features: amino acid composition, dipeptide composition, the pseudo amino acid composition, Nterminal-Center-Cterminal composition and the protein physicochemical properties are used to develop SVM models. Overall, the dipeptide composition-based module shows the best performance with an accuracy of 86.80% and Matthews Correlation Coefficient (MCC) of 0.74 in phase-I and 78.60% with a MCC of 0.44 in phase-II. On independent test data, this model also performs better with an overall accuracy of 76.58% and 74.97% in phase-I and phase-II, respectively. The similarity-based PSI-BLAST module shows very low performance with about 50% prediction accuracy for distinguishing plastid vs. non-plastids and only 20% in classifying various plastid-types, indicating the need and importance of machine learning algorithms. Conclusion The current work is a first attempt to develop a methodology for classifying various plastid-type proteins. The prediction modules have also been made available as a web tool, PLpred available at http://bioinfo.okstate.edu/PLpred/ for real time identification/characterization. We believe this tool will be very useful in the functional annotation of various genomes. PMID:24266945

Wireless sensor node for surface seawater density measurements.

PubMed

Baronti, Federico; Fantechi, Gabriele; Roncella, Roberto; Saletti, Roberto

2012-01-01

An electronic meter to measure surface seawater density is presented. It is based on the measurement of the difference in displacements of a surface level probe and a weighted float, which according to Archimedes' law depends on the density of the water. The displacements are simultaneously measured using a high-accuracy magnetostrictive sensor, to which a custom electronic board provides a wireless connection and power supply so that it can become part of a wireless sensor network. The electronics are designed so that different kinds of wireless networks can be used, by simply changing the wireless module and the relevant firmware of the microcontroller. Lastly, laboratory and at-sea tests are presented and discussed in order to highlight the functionality and the performance of a prototype of the wireless density meter node in a Bluetooth radio network. The experimental results show a good agreement of the values of the calculated density compared to reference hydrometer readings.

Wireless Sensor Node for Surface Seawater Density Measurements

PubMed Central

Baronti, Federico; Fantechi, Gabriele; Roncella, Roberto; Saletti, Roberto

2012-01-01

An electronic meter to measure surface seawater density is presented. It is based on the measurement of the difference in displacements of a surface level probe and a weighted float, which according to Archimedes’ law depends on the density of the water. The displacements are simultaneously measured using a high-accuracy magnetostrictive sensor, to which a custom electronic board provides a wireless connection and power supply so that it can become part of a wireless sensor network. The electronics are designed so that different kinds of wireless networks can be used, by simply changing the wireless module and the relevant firmware of the microcontroller. Lastly, laboratory and at-sea tests are presented and discussed in order to highlight the functionality and the performance of a prototype of the wireless density meter node in a Bluetooth radio network. The experimental results show a good agreement of the values of the calculated density compared to reference hydrometer readings. PMID:22736986

Use of High-Resolution Satellite Observations to Evaluate Cloud and Precipitation Statistics from Cloud-Resolving Model Simulations

NASA Astrophysics Data System (ADS)

Zhou, Y.; Tao, W.; Hou, A. Y.; Zeng, X.; Shie, C.

2007-12-01

The cloud and precipitation statistics simulated by 3D Goddard Cumulus Ensemble (GCE) model for different environmental conditions, i.e., the South China Sea Monsoon Experiment (SCSMEX), CRYSTAL-FACE, and KAWJEX are compared with Tropical Rainfall Measuring Mission (TRMM) TMI and PR rainfall measurements and as well as cloud observations from the Earth's Radiant Energy System (CERES) and the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments. It is found that GCE is capable of simulating major convective system development and reproducing total surface rainfall amount as compared with rainfall estimated from the soundings. The model presents large discrepancies in rain spectrum and vertical hydrometer profiles. The discrepancy in the precipitation field is also consistent with the cloud and radiation observations. The study will focus on the effects of large scale forcing and microphysics to the simulated model- observation discrepancies.

Quantitative estimation of Tropical Rainfall Mapping Mission precipitation radar signals from ground-based polarimetric radar observations

NASA Astrophysics Data System (ADS)

Bolen, Steven M.; Chandrasekar, V.

2003-06-01

The Tropical Rainfall Mapping Mission (TRMM) is the first mission dedicated to measuring rainfall from space using radar. The precipitation radar (PR) is one of several instruments aboard the TRMM satellite that is operating in a nearly circular orbit with nominal altitude of 350 km, inclination of 35°, and period of 91.5 min. The PR is a single-frequency Ku-band instrument that is designed to yield information about the vertical storm structure so as to gain insight into the intensity and distribution of rainfall. Attenuation effects on PR measurements, however, can be significant and as high as 10-15 dB. This can seriously impair the accuracy of rain rate retrieval algorithms derived from PR signal returns. Quantitative estimation of PR attenuation is made along the PR beam via ground-based polarimetric observations to validate attenuation correction procedures used by the PR. The reflectivity (Zh) at horizontal polarization and specific differential phase (Kdp) are found along the beam from S-band ground radar measurements, and theoretical modeling is used to determine the expected specific attenuation (k) along the space-Earth path at Ku-band frequency from these measurements. A theoretical k-Kdp relationship is determined for rain when Kdp ≥ 0.5°/km, and a power law relationship, k = a Zhb, is determined for light rain and other types of hydrometers encountered along the path. After alignment and resolution volume matching is made between ground and PR measurements, the two-way path-integrated attenuation (PIA) is calculated along the PR propagation path by integrating the specific attenuation along the path. The PR reflectivity derived after removing the PIA is also compared against ground radar observations.

Skin temperature changes induced by strong static magnetic field exposure.

PubMed

Ichioka, Shigeru; Minegishi, Masayuki; Iwasaka, Masakazu; Shibata, Masahiro; Nakatsuka, Takashi; Ando, Joji; Ueno, Shoogo

2003-09-01

High intensity static magnetic fields, when applied to the whole body of the anesthetized rat, have previously been reported to decrease skin temperature. The hypothesis of the present study was that in diamagnetic water, molecules in the air play significant roles in the mechanism of skin temperature decrease. We used a horizontal cylindrical superconducting magnet. The magnet produced 8 T at its center. A thermistor probe was inserted in a subcutaneous pocket of the anesthetized rats to measure skin temperature. Animals (n=10) were placed in an open plastic holder in which the ambient air was free to move in any direction (group I). Animals (n=10) were placed in a closed holder in which the air circulation toward the direction of weak magnetic field was restricted (group II). Each holder was connected to a hydrometer to measure humidity around the animal in the holder. The data acquisition phase consisted of a 5 min baseline interval, followed by inserting the animal together with the holder into the center of the magnet bore for a 5 min exposure and a 5 min postexposure period outside the bore. In group I, skin temperature and humidity around the animal significantly decreased during exposure, followed by recovery after exposure. In group II, skin temperature and humidity did not decrease during the measurement. The skin temperature decrease was closely related to the decrease in humidity around the body of the animal in the holder, and the changes were completely blocked by restricting the air circulation in the direction of the bore entrance. Possible mechanisms responsible for the decrease in skin temperature may be associated with magnetically induced movement of water vapor at the skin surface, leading to skin temperature decrease. Copyright 2003 Wiley-Liss, Inc.

Classification and mensuration of LACIE segments

NASA Technical Reports Server (NTRS)

Heydorn, R. P.; Bizzell, R. M.; Quirein, J. A.; Abotteen, K. M.; Sumner, C. A. (Principal Investigator)

1979-01-01

The theory of classification methods and the functional steps in the manual training process used in the three phases of LACIE are discussed. The major problems that arose in using a procedure for manually training a classifier and a method of machine classification are discussed to reveal the motivation that led to a redesign for the third LACIE phase.

Minimizing calibration time using inter-subject information of single-trial recognition of error potentials in brain-computer interfaces.

PubMed

Iturrate, Iñaki; Montesano, Luis; Chavarriaga, Ricardo; del R Millán, Jose; Minguez, Javier

2011-01-01

One of the main problems of both synchronous and asynchronous EEG-based BCIs is the need of an initial calibration phase before the system can be used. This phase is necessary due to the high non-stationarity of the EEG, since it changes between sessions and users. The calibration process limits the BCI systems to scenarios where the outputs are very controlled, and makes these systems non-friendly and exhausting for the users. Although it has been studied how to reduce calibration time for asynchronous signals, it is still an open issue for event-related potentials. Here, we propose the minimization of the calibration time on single-trial error potentials by using classifiers based on inter-subject information. The results show that it is possible to have a classifier with a high performance from the beginning of the experiment, and which is able to adapt itself making the calibration phase shorter and transparent to the user.

Phase retrieval based wavefront sensing experimental implementation and wavefront sensing accuracy calibration

NASA Astrophysics Data System (ADS)

Mao, Heng; Wang, Xiao; Zhao, Dazun

2009-05-01

As a wavefront sensing (WFS) tool, Baseline algorithm, which is classified as the iterative-transform algorithm of phase retrieval, estimates the phase distribution at pupil from some known PSFs at defocus planes. By using multiple phase diversities and appropriate phase unwrapping methods, this algorithm can accomplish reliable unique solution and high dynamic phase measurement. In the paper, a Baseline algorithm based wavefront sensing experiment with modification of phase unwrapping has been implemented, and corresponding Graphical User Interfaces (GUI) software has also been given. The adaptability and repeatability of Baseline algorithm have been validated in experiments. Moreover, referring to the ZYGO interferometric results, the WFS accuracy of this algorithm has been exactly calibrated.

Are Some Pre-Cataclysmic Variables also Post-Cataclysmic Variables?

NASA Astrophysics Data System (ADS)

Sarna, M. J.; Marks, P. B.; Smith, R. C.

1995-10-01

We propose an evolutionary scenario in which post-common-envelope binaries (PCEBs) with secondary component masses between 0.8 Msun and 1.2 M0 start semi-detached evolution almost immediately after the common-envelope (CE) phase. These systems detach due to unstable mass transfer when the secondary develops a thick convective envelope. The duration of the detached phase is a few times 108 yr, depending on the efficiency of magnetic braking and gravitational radiation. We suggest that some of the systems that have been classified as PCEBs may be in this stage of evolution and hence would be more realistically classified as pre-cataclysmic variables (PreCVs). We also propose an observational test based on measurements of the carbon and oxygen isotopic ratios from the infrared CO bands.

A new method for recognizing hand configurations of Brazilian gesture language.

PubMed

Costa Filho, C F F; Dos Santos, B L; de Souza, R S; Dos Santos, J R; Costa, M G F

2016-08-01

This paper describes a new method for recognizing hand configurations of the Brazilian Gesture Language - LIBRAS - using depth maps obtained with a Kinect® camera. The proposed method comprised three phases: hand segmentation, feature extraction, and classification. The segmentation phase is independent from the background and depends only on pixel depth information. Using geometric operations and numerical normalization, the feature extraction process was done independent from rotation and translation. The features are extracted employing two techniques: (2D)2LDA and (2D)2PCA. The classification is made with a novelty classifier. A robust database was constructed for classifier evaluation, with 12,200 images of LIBRAS and 200 gestures of each hand configuration. The best accuracy obtained was 95.41%, which was greater than previous values obtained in the literature.

Quantum Hooke's Law to classify pulse laser induced ultrafast melting

DOE PAGES

Hu, Hao; Ding, Hepeng; Liu, Feng

2015-02-03

Ultrafast crystal-to-liquid phase transition induced by femtosecond pulse laser excitation is an interesting material's behavior manifesting the complexity of light-matter interaction. There exist two types of such phase transitions: one occurs at a time scale shorter than a picosecond via a nonthermal process mediated by electron-hole plasma formation; the other at a longer time scale via a thermal melting process mediated by electron-phonon interaction. However, it remains unclear what material would undergo which process and why? Here, by exploiting the property of quantum electronic stress (QES) governed by quantum Hooke's law, we classify the transitions by two distinct classes ofmore » materials: the faster nonthermal process can only occur in materials like ice having an anomalous phase diagram characterized with dT m/dP < 0, where T m is the melting temperature and P is pressure, above a high threshold laser fluence; while the slower thermal process may occur in all materials. Especially, the nonthermal transition is shown to be induced by the QES, acting like a negative internal pressure, which drives the crystal into a “super pressing” state to spontaneously transform into a higher-density liquid phase. Our findings significantly advance fundamental understanding of ultrafast crystal-to-liquid phase transitions, enabling quantitative a priori predictions.« less

Quantum Hooke's Law to Classify Pulse Laser Induced Ultrafast Melting

NASA Astrophysics Data System (ADS)

Hu, Hao; Ding, Hepeng; Liu, Feng

2015-02-01

Ultrafast crystal-to-liquid phase transition induced by femtosecond pulse laser excitation is an interesting material's behavior manifesting the complexity of light-matter interaction. There exist two types of such phase transitions: one occurs at a time scale shorter than a picosecond via a nonthermal process mediated by electron-hole plasma formation; the other at a longer time scale via a thermal melting process mediated by electron-phonon interaction. However, it remains unclear what material would undergo which process and why? Here, by exploiting the property of quantum electronic stress (QES) governed by quantum Hooke's law, we classify the transitions by two distinct classes of materials: the faster nonthermal process can only occur in materials like ice having an anomalous phase diagram characterized with dTm/dP < 0, where Tm is the melting temperature and P is pressure, above a high threshold laser fluence; while the slower thermal process may occur in all materials. Especially, the nonthermal transition is shown to be induced by the QES, acting like a negative internal pressure, which drives the crystal into a ``super pressing'' state to spontaneously transform into a higher-density liquid phase. Our findings significantly advance fundamental understanding of ultrafast crystal-to-liquid phase transitions, enabling quantitative a priori predictions.

Quantum Hooke's Law to Classify Pulse Laser Induced Ultrafast Melting

PubMed Central

Hu, Hao; Ding, Hepeng; Liu, Feng

2015-01-01

Ultrafast crystal-to-liquid phase transition induced by femtosecond pulse laser excitation is an interesting material's behavior manifesting the complexity of light-matter interaction. There exist two types of such phase transitions: one occurs at a time scale shorter than a picosecond via a nonthermal process mediated by electron-hole plasma formation; the other at a longer time scale via a thermal melting process mediated by electron-phonon interaction. However, it remains unclear what material would undergo which process and why? Here, by exploiting the property of quantum electronic stress (QES) governed by quantum Hooke's law, we classify the transitions by two distinct classes of materials: the faster nonthermal process can only occur in materials like ice having an anomalous phase diagram characterized with dTm/dP < 0, where Tm is the melting temperature and P is pressure, above a high threshold laser fluence; while the slower thermal process may occur in all materials. Especially, the nonthermal transition is shown to be induced by the QES, acting like a negative internal pressure, which drives the crystal into a “super pressing” state to spontaneously transform into a higher-density liquid phase. Our findings significantly advance fundamental understanding of ultrafast crystal-to-liquid phase transitions, enabling quantitative a priori predictions. PMID:25645258

Quantum Hooke's law to classify pulse laser induced ultrafast melting.

PubMed

Hu, Hao; Ding, Hepeng; Liu, Feng

2015-02-03

Ultrafast crystal-to-liquid phase transition induced by femtosecond pulse laser excitation is an interesting material's behavior manifesting the complexity of light-matter interaction. There exist two types of such phase transitions: one occurs at a time scale shorter than a picosecond via a nonthermal process mediated by electron-hole plasma formation; the other at a longer time scale via a thermal melting process mediated by electron-phonon interaction. However, it remains unclear what material would undergo which process and why? Here, by exploiting the property of quantum electronic stress (QES) governed by quantum Hooke's law, we classify the transitions by two distinct classes of materials: the faster nonthermal process can only occur in materials like ice having an anomalous phase diagram characterized with dTm/dP < 0, where Tm is the melting temperature and P is pressure, above a high threshold laser fluence; while the slower thermal process may occur in all materials. Especially, the nonthermal transition is shown to be induced by the QES, acting like a negative internal pressure, which drives the crystal into a "super pressing" state to spontaneously transform into a higher-density liquid phase. Our findings significantly advance fundamental understanding of ultrafast crystal-to-liquid phase transitions, enabling quantitative a priori predictions.

Open Scenario Study, Phase I. Volume 3. Questionnaire Response

DTIC Science & Technology

2008-03-01

a conceptual framework to assist users to grasp new ideas. As the concepts are used by a broad community and internationally, classified scenarios are...framework to assist users to grasp new ideas. As the concepts are used by a broad community and internationally, classified scenarios are not necessary for...from other sources Comment: Normally have an old version that we can update. Occasionally we’ve had to develop new scenarios - the SSSP for example - we

Multiscale Symbolic Phase Transfer Entropy in Financial Time Series Classification

NASA Astrophysics Data System (ADS)

Zhang, Ningning; Lin, Aijing; Shang, Pengjian

We address the challenge of classifying financial time series via a newly proposed multiscale symbolic phase transfer entropy (MSPTE). Using MSPTE method, we succeed to quantify the strength and direction of information flow between financial systems and classify financial time series, which are the stock indices from Europe, America and China during the period from 2006 to 2016 and the stocks of banking, aviation industry and pharmacy during the period from 2007 to 2016, simultaneously. The MSPTE analysis shows that the value of symbolic phase transfer entropy (SPTE) among stocks decreases with the increasing scale factor. It is demonstrated that MSPTE method can well divide stocks into groups by areas and industries. In addition, it can be concluded that the MSPTE analysis quantify the similarity among the stock markets. The symbolic phase transfer entropy (SPTE) between the two stocks from the same area is far less than the SPTE between stocks from different areas. The results also indicate that four stocks from America and Europe have relatively high degree of similarity and the stocks of banking and pharmaceutical industry have higher similarity for CA. It is worth mentioning that the pharmaceutical industry has weaker particular market mechanism than banking and aviation industry.

AHA classification of coronary and carotid atherosclerotic plaques by grating-based phase-contrast computed tomography.

PubMed

Hetterich, Holger; Webber, Nicole; Willner, Marian; Herzen, Julia; Birnbacher, Lorenz; Hipp, Alexander; Marschner, Mathias; Auweter, Sigrid D; Habbel, Christopher; Schüller, Ulrich; Bamberg, Fabian; Ertl-Wagner, Birgit; Pfeiffer, Franz; Saam, Tobias

2016-09-01

To evaluate the potential of grating-based phase-contrast computed-tomography (gb-PCCT) to classify human carotid and coronary atherosclerotic plaques according to modified American Heart Association (AHA) criteria. Experiments were carried out at a laboratory-based set-up consisting of X-ray tube (40 kVp), grating-interferometer and detector. Eighteen human carotid and coronary artery specimens were examined. Histopathology served as the standard of reference. Vessel cross-sections were classified as AHA lesion type I/II, III, IV/V, VI, VII or VIII plaques by two independent reviewers blinded to histopathology. Conservative measurements of diagnostic accuracies for the detection and differentiation of plaque types were evaluated. A total of 127 corresponding gb-PCCT/histopathology sections were analyzed. Based on histopathology, lesion type I/II was present in 12 (9.5 %), III in 18 (14.2 %), IV/V in 38 (29.9 %), VI in 16 (12.6 %), VII in 34 (26.8 %) and VIII in 9 (7.0 %) cross-sections. Sensitivity, specificity and positive and negative predictive value were ≥0.88 for most analyzed plaque types with a good level of agreement (Cohen's kappa = 0.90). Overall, results were better in carotid (kappa = 0.97) than in coronary arteries (kappa = 0.85). Inter-observer agreement was high with kappa = 0.85, p < 0.0001. These results indicate that gb-PCCT can reliably classify atherosclerotic plaques according to modified AHA criteria with excellent agreement to histopathology. • Different atherosclerotic plaque types display distinct morphological features in phase-contrast CT. • Phase-contrast CT can detect and differentiate AHA plaque types. • Calcifications caused streak artefacts and reduced sensitivity in type VI lesions. • Overall agreement was higher in carotid than in coronary arteries.

RECIST response and variation of circulating tumour cells in phase 1 trials: A prospective multicentric study.

PubMed

Massard, Christophe; Borget, Isabelle; Farace, Françoise; Aspeslagh, Sandrine; Le Deley, Marie-Cécile; Le Tourneau, Christophe; Bidard, François-Clement; Pierga, Jean-Yves; Dieras, Veronique; Hofman, Paul; Spano, Jean-Philippe; Ferte, Charles; Lacroix, Ludovic; Soria, Jean-Charles

2017-09-01

Circulating tumour cell (CTC) counting could be a new biomarker for better evaluation of tumour response to molecules tested in phase I trials. Consenting patients with advanced metastatic cancer referred to various phase I units were enrolled prospectively in this study. CTCs from 7.5 ml of whole blood drawn at baseline and after starting experimental therapy were counted using the CellSearch system, and tumour response was assessed using RECIST 1.1 criteria at baseline and 2 months after treatment initiation. Between March 2010 and May 2013, a total of 326 patients were enrolled, among whom 214 were evaluable (49% male, median age = 56; main cancer types: lung [28], colon [53], ovarian [18], breast [28]). At baseline, we detected ≥1 CTC/7.5 ml in 113/214 patients (53%), and at day 30, we observed ≥1 CTC/7.5 ml in 103/214 patients (48%). Two months after treatment initiation, 11 (5%) of the 214 patients were classified as having a partial response, with no CTCs in 9 of them or a decrease in the CTC count after therapy. In contrast, among the 104 patients (49%) classified as having progressive disease, 38 patients had a higher CTC count. The remaining 99 patients (49%), 33 of whom (33%) had a lower CTC count, were classified as having stable disease. The sensitivity and specificity of CTC variation for predicting progressive disease were 41% (32-51%) and 80% (73-88%) respectively. An early CTC change following therapy does not correlate with RECIST response in patients with advanced cancer enrolled in phase I trials. Copyright © 2017 Elsevier Ltd. All rights reserved.

32 CFR 2004.20 - National Industrial Security Program Operating Manual (NISPOM) [201(a)].

Code of Federal Regulations, 2011 CFR

2011-07-01

... phases of the contracting process. (b) As a general rule, procedures for safeguarding classified information by contractors and recommendations for changes shall be addressed through the NISPOM coordination...

Thermodynamic model of social influence on two-dimensional square lattice: Case for two features

NASA Astrophysics Data System (ADS)

Genzor, Jozef; Bužek, Vladimír; Gendiar, Andrej

2015-02-01

We propose a thermodynamic multi-state spin model in order to describe equilibrial behavior of a society. Our model is inspired by the Axelrod model used in social network studies. In the framework of the statistical mechanics language, we analyze phase transitions of our model, in which the spin interaction J is interpreted as a mutual communication among individuals forming a society. The thermal fluctuations introduce a noise T into the communication, which suppresses long-range correlations. Below a certain phase transition point Tt, large-scale clusters of the individuals, who share a specific dominant property, are formed. The measure of the cluster sizes is an order parameter after spontaneous symmetry breaking. By means of the Corner transfer matrix renormalization group algorithm, we treat our model in the thermodynamic limit and classify the phase transitions with respect to inherent degrees of freedom. Each individual is chosen to possess two independent features f = 2 and each feature can assume one of q traits (e.g. interests). Hence, each individual is described by q2 degrees of freedom. A single first-order phase transition is detected in our model if q > 2, whereas two distinct continuous phase transitions are found if q = 2 only. Evaluating the free energy, order parameters, specific heat, and the entanglement von Neumann entropy, we classify the phase transitions Tt(q) in detail. The permanent existence of the ordered phase (the large-scale cluster formation with a non-zero order parameter) is conjectured below a non-zero transition point Tt(q) ≈ 0.5 in the asymptotic regime q → ∞.

Tensor-based classification of an auditory mobile BCI without a subject-specific calibration phase

NASA Astrophysics Data System (ADS)

Zink, Rob; Hunyadi, Borbála; Van Huffel, Sabine; De Vos, Maarten

2016-04-01

Objective. One of the major drawbacks in EEG brain-computer interfaces (BCI) is the need for subject-specific training of the classifier. By removing the need for a supervised calibration phase, new users could potentially explore a BCI faster. In this work we aim to remove this subject-specific calibration phase and allow direct classification. Approach. We explore canonical polyadic decompositions and block term decompositions of the EEG. These methods exploit structure in higher dimensional data arrays called tensors. The BCI tensors are constructed by concatenating ERP templates from other subjects to a target and non-target trial and the inherent structure guides a decomposition that allows accurate classification. We illustrate the new method on data from a three-class auditory oddball paradigm. Main results. The presented approach leads to a fast and intuitive classification with accuracies competitive with a supervised and cross-validated LDA approach. Significance. The described methods are a promising new way of classifying BCI data with a forthright link to the original P300 ERP signal over the conventional and widely used supervised approaches.

A Smartphone Indoor Localization Algorithm Based on WLAN Location Fingerprinting with Feature Extraction and Clustering.

PubMed

Luo, Junhai; Fu, Liang

2017-06-09

With the development of communication technology, the demand for location-based services is growing rapidly. This paper presents an algorithm for indoor localization based on Received Signal Strength (RSS), which is collected from Access Points (APs). The proposed localization algorithm contains the offline information acquisition phase and online positioning phase. Firstly, the AP selection algorithm is reviewed and improved based on the stability of signals to remove useless AP; secondly, Kernel Principal Component Analysis (KPCA) is analyzed and used to remove the data redundancy and maintain useful characteristics for nonlinear feature extraction; thirdly, the Affinity Propagation Clustering (APC) algorithm utilizes RSS values to classify data samples and narrow the positioning range. In the online positioning phase, the classified data will be matched with the testing data to determine the position area, and the Maximum Likelihood (ML) estimate will be employed for precise positioning. Eventually, the proposed algorithm is implemented in a real-world environment for performance evaluation. Experimental results demonstrate that the proposed algorithm improves the accuracy and computational complexity.

Tensor-based classification of an auditory mobile BCI without a subject-specific calibration phase.

PubMed

Zink, Rob; Hunyadi, Borbála; Huffel, Sabine Van; Vos, Maarten De

2016-04-01

One of the major drawbacks in EEG brain-computer interfaces (BCI) is the need for subject-specific training of the classifier. By removing the need for a supervised calibration phase, new users could potentially explore a BCI faster. In this work we aim to remove this subject-specific calibration phase and allow direct classification. We explore canonical polyadic decompositions and block term decompositions of the EEG. These methods exploit structure in higher dimensional data arrays called tensors. The BCI tensors are constructed by concatenating ERP templates from other subjects to a target and non-target trial and the inherent structure guides a decomposition that allows accurate classification. We illustrate the new method on data from a three-class auditory oddball paradigm. The presented approach leads to a fast and intuitive classification with accuracies competitive with a supervised and cross-validated LDA approach. The described methods are a promising new way of classifying BCI data with a forthright link to the original P300 ERP signal over the conventional and widely used supervised approaches.

Hierarchical Leak Detection and Localization Method in Natural Gas Pipeline Monitoring Sensor Networks

PubMed Central

Wan, Jiangwen; Yu, Yang; Wu, Yinfeng; Feng, Renjian; Yu, Ning

2012-01-01

In light of the problems of low recognition efficiency, high false rates and poor localization accuracy in traditional pipeline security detection technology, this paper proposes a type of hierarchical leak detection and localization method for use in natural gas pipeline monitoring sensor networks. In the signal preprocessing phase, original monitoring signals are dealt with by wavelet transform technology to extract the single mode signals as well as characteristic parameters. In the initial recognition phase, a multi-classifier model based on SVM is constructed and characteristic parameters are sent as input vectors to the multi-classifier for initial recognition. In the final decision phase, an improved evidence combination rule is designed to integrate initial recognition results for final decisions. Furthermore, a weighted average localization algorithm based on time difference of arrival is introduced for determining the leak point’s position. Experimental results illustrate that this hierarchical pipeline leak detection and localization method could effectively improve the accuracy of the leak point localization and reduce the undetected rate as well as false alarm rate. PMID:22368464

Hierarchical leak detection and localization method in natural gas pipeline monitoring sensor networks.

PubMed

Wan, Jiangwen; Yu, Yang; Wu, Yinfeng; Feng, Renjian; Yu, Ning

2012-01-01

In light of the problems of low recognition efficiency, high false rates and poor localization accuracy in traditional pipeline security detection technology, this paper proposes a type of hierarchical leak detection and localization method for use in natural gas pipeline monitoring sensor networks. In the signal preprocessing phase, original monitoring signals are dealt with by wavelet transform technology to extract the single mode signals as well as characteristic parameters. In the initial recognition phase, a multi-classifier model based on SVM is constructed and characteristic parameters are sent as input vectors to the multi-classifier for initial recognition. In the final decision phase, an improved evidence combination rule is designed to integrate initial recognition results for final decisions. Furthermore, a weighted average localization algorithm based on time difference of arrival is introduced for determining the leak point's position. Experimental results illustrate that this hierarchical pipeline leak detection and localization method could effectively improve the accuracy of the leak point localization and reduce the undetected rate as well as false alarm rate.

Application of phase-change materials in memory taxonomy.

PubMed

Wang, Lei; Tu, Liang; Wen, Jing

2017-01-01

Phase-change materials are suitable for data storage because they exhibit reversible transitions between crystalline and amorphous states that have distinguishable electrical and optical properties. Consequently, these materials find applications in diverse memory devices ranging from conventional optical discs to emerging nanophotonic devices. Current research efforts are mostly devoted to phase-change random access memory, whereas the applications of phase-change materials in other types of memory devices are rarely reported. Here we review the physical principles of phase-change materials and devices aiming to help researchers understand the concept of phase-change memory. We classify phase-change memory devices into phase-change optical disc, phase-change scanning probe memory, phase-change random access memory, and phase-change nanophotonic device, according to their locations in memory hierarchy. For each device type we discuss the physical principles in conjunction with merits and weakness for data storage applications. We also outline state-of-the-art technologies and future prospects.

Treating Patients with High-Risk Smoldering Myeloma

Cancer.gov

In this phase III clinical trial, patients with smoldering myeloma classified as high risk for progression will be randomly assigned to undergo standard observation or six 4-week courses of treatment with the drug lenalidomide.

Automated analysis of individual sperm cells using stain-free interferometric phase microscopy and machine learning.

PubMed

Mirsky, Simcha K; Barnea, Itay; Levi, Mattan; Greenspan, Hayit; Shaked, Natan T

2017-09-01

Currently, the delicate process of selecting sperm cells to be used for in vitro fertilization (IVF) is still based on the subjective, qualitative analysis of experienced clinicians using non-quantitative optical microscopy techniques. In this work, a method was developed for the automated analysis of sperm cells based on the quantitative phase maps acquired through use of interferometric phase microscopy (IPM). Over 1,400 human sperm cells from 8 donors were imaged using IPM, and an algorithm was designed to digitally isolate sperm cell heads from the quantitative phase maps while taking into consideration both the cell 3D morphology and contents, as well as acquire features describing sperm head morphology. A subset of these features was used to train a support vector machine (SVM) classifier to automatically classify sperm of good and bad morphology. The SVM achieves an area under the receiver operating characteristic curve of 88.59% and an area under the precision-recall curve of 88.67%, as well as precisions of 90% or higher. We believe that our automatic analysis can become the basis for objective and automatic sperm cell selection in IVF. © 2017 International Society for Advancement of Cytometry. © 2017 International Society for Advancement of Cytometry.

Multiple-instance ensemble learning for hyperspectral images

NASA Astrophysics Data System (ADS)

Ergul, Ugur; Bilgin, Gokhan

2017-10-01

An ensemble framework for multiple-instance (MI) learning (MIL) is introduced for use in hyperspectral images (HSIs) by inspiring the bagging (bootstrap aggregation) method in ensemble learning. Ensemble-based bagging is performed by a small percentage of training samples, and MI bags are formed by a local windowing process with variable window sizes on selected instances. In addition to bootstrap aggregation, random subspace is another method used to diversify base classifiers. The proposed method is implemented using four MIL classification algorithms. The classifier model learning phase is carried out with MI bags, and the estimation phase is performed over single-test instances. In the experimental part of the study, two different HSIs that have ground-truth information are used, and comparative results are demonstrated with state-of-the-art classification methods. In general, the MI ensemble approach produces more compact results in terms of both diversity and error compared to equipollent non-MIL algorithms.

A target recognition method for maritime surveillance radars based on hybrid ensemble selection

NASA Astrophysics Data System (ADS)

Fan, Xueman; Hu, Shengliang; He, Jingbo

2017-11-01

In order to improve the generalisation ability of the maritime surveillance radar, a novel ensemble selection technique, termed Optimisation and Dynamic Selection (ODS), is proposed. During the optimisation phase, the non-dominated sorting genetic algorithm II for multi-objective optimisation is used to find the Pareto front, i.e. a set of ensembles of classifiers representing different tradeoffs between the classification error and diversity. During the dynamic selection phase, the meta-learning method is used to predict whether a candidate ensemble is competent enough to classify a query instance based on three different aspects, namely, feature space, decision space and the extent of consensus. The classification performance and time complexity of ODS are compared against nine other ensemble methods using a self-built full polarimetric high resolution range profile data-set. The experimental results clearly show the effectiveness of ODS. In addition, the influence of the selection of diversity measures is studied concurrently.

Thermogram breast cancer prediction approach based on Neutrosophic sets and fuzzy c-means algorithm.

PubMed

Gaber, Tarek; Ismail, Gehad; Anter, Ahmed; Soliman, Mona; Ali, Mona; Semary, Noura; Hassanien, Aboul Ella; Snasel, Vaclav

2015-08-01

The early detection of breast cancer makes many women survive. In this paper, a CAD system classifying breast cancer thermograms to normal and abnormal is proposed. This approach consists of two main phases: automatic segmentation and classification. For the former phase, an improved segmentation approach based on both Neutrosophic sets (NS) and optimized Fast Fuzzy c-mean (F-FCM) algorithm was proposed. Also, post-segmentation process was suggested to segment breast parenchyma (i.e. ROI) from thermogram images. For the classification, different kernel functions of the Support Vector Machine (SVM) were used to classify breast parenchyma into normal or abnormal cases. Using benchmark database, the proposed CAD system was evaluated based on precision, recall, and accuracy as well as a comparison with related work. The experimental results showed that our system would be a very promising step toward automatic diagnosis of breast cancer using thermograms as the accuracy reached 100%.

Classification of Odours for Mobile Robots Using an Ensemble of Linear Classifiers

NASA Astrophysics Data System (ADS)

Trincavelli, Marco; Coradeschi, Silvia; Loutfi, Amy

2009-05-01

This paper investigates the classification of odours using an electronic nose mounted on a mobile robot. The samples are collected as the robot explores the environment. Under such conditions, the sensor response differs from typical three phase sampling processes. In this paper, we focus particularly on the classification problem and how it is influenced by the movement of the robot. To cope with these influences, an algorithm consisting of an ensemble of classifiers is presented. Experimental results show that this algorithm increases classification performance compared to other traditional classification methods.

Kinematic and Hydrometer Data Products from Scanning Radars during MC3E

DOE Data Explorer

matthews, Alyssa; Dolan, Brenda; Rutledge, Steven

2016-02-29

Recently the Radar Meteorology Group at Colorado State University has completed major case studies of some top cases from MC3E including 25 April, 20 May and 23 May 2011. A discussion on the analysis methods as well as radar quality control methods is included. For each case, a brief overview is first provided. Then, multiple Doppler (using available X-SAPR and C-SAPR data) analyses are presented including statistics on vertical air motions, sub-divided by convective and stratiform precipitation. Mean profiles and CFAD's of vertical motion are included to facilitate comparison with ASR model simulations. Retrieved vertical motion has also been verified with vertically pointing profiler data. Finally for each case, hydrometeor types are included derived from polarimetric radar observations. The latter can be used to provide comparisons to model-generated hydrometeor fields. Instructions for accessing all the data fields are also included. The web page can be found at: http://radarmet.atmos.colostate.edu/mc3e/research/

A statistical technique for determining rainfall over land employing Nimbus-6 ESMR measurements

NASA Technical Reports Server (NTRS)

Rodgers, E.; Siddalingaiah, H.; Chang, A. T. C.; Wilheit, T. T.

1978-01-01

At 37 GHz, the frequency at which the Nimbus 6 Electrically Scanning Microwave Radiometer (ESMR 6) measures upwelling radiance, it was shown theoretically that the atmospheric scattering and the relative independence on electromagnetic polarization of the radiances emerging from hydrometers make it possible to monitor remotely active rainfall over land. In order to verify experimentally these theoretical findings and to develop an algorithm to monitor rainfall over land, the digitized ESMR 6 measurements were examined statistically. Horizontally and vertically polarized brightness temperature pairs (TH, TV) from ESMR 6 were sampled for areas of rainfall over land as determined from the rain recording stations and the WSR 57 radar, and areas of wet and dry ground (whose thermodynamic temperatures were greater than 5 C) over the Southeastern United States. These three categories of brightness temperatures were found to be significantly different in the sense that the chances that the mean vectors of any two populations coincided were less than 1 in 100.

Millimeter wave radiative transfer studies for precipitation measurements

NASA Technical Reports Server (NTRS)

Vivekanandan, J.; Evans, Frank

1989-01-01

Scattering calculations using the discrete dipole approximation and vector radiative transfer calculations were performed to model multiparameter radar return and passive microwave emission for a simple model of a winter storm. The issue of dendrite riming was addressed by computing scattering properties of thin ice disks with varying bulk density. It was shown that C-band multiparameter radar contains information about particle density and the number concentration of the ice particles. The radiative transfer modeling indicated that polarized multifrequency passive microwave emission may be used to infer some properties of ice hydrometers. Detailed radar modeling and vector radiative transfer modeling is in progress to enhance the understanding of simultaneous radar and radiometer measurements, as in the case of the proposed TRMM field program. A one-dimensional cloud model will be used to simulate the storm structure in detail and study the microphysics, such as size and density. Multifrequency polarized radiometer measurements from the SSMI satellite instrument will be analyzed in relation to dual-frequency and dual-polarization radar measurements.

Inference of precipitation through thermal infrared measurements of soil moisture

NASA Technical Reports Server (NTRS)

Wetzel, P. J.; Atlas, D.

1981-01-01

The physics of microwave radiative transfer is well understood so that causal models can be assembled which relate the observed brightness temperatures to assumed distributions of hydrometeors (both liquid and ice), non-precipitating clouds, water vapor oxygen, and surface conditions. Present models assume a Marshall Palmer size distribution of liquid hydrometers from the surface to the freezing level (near the 0 C isotherm) and a variable thickness of frozen hydrometeors above that with various reasonable distribution of the other relevant constituents. The validity of such models is discussed. All uncertainties in the rain rate retrieval algorithms can be expressed in terms of specific model uncertainties which can be addressed through appropriate measurements. Those factors which must be known to achieve umambiguous results can be identified so that rainfall measuring algorithms can be developed and improved. The emissivity of the underlying surface significantly affects the contrast that may be measured between areas covered by rain and those which are dry. Sensing strategies for measuring rain over the ocean and rain over land are reviewed.

Multi-Angle Snowflake Camera Instrument Handbook

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stuefer, Martin; Bailey, J.

2016-07-01

The Multi-Angle Snowflake Camera (MASC) takes 9- to 37-micron resolution stereographic photographs of free-falling hydrometers from three angles, while simultaneously measuring their fall speed. Information about hydrometeor size, shape orientation, and aspect ratio is derived from MASC photographs. The instrument consists of three commercial cameras separated by angles of 36º. Each camera field of view is aligned to have a common single focus point about 10 cm distant from the cameras. Two near-infrared emitter pairs are aligned with the camera’s field of view within a 10-angular ring and detect hydrometeor passage, with the lower emitters configured to trigger the MASCmore » cameras. The sensitive IR motion sensors are designed to filter out slow variations in ambient light. Fall speed is derived from successive triggers along the fall path. The camera exposure times are extremely short, in the range of 1/25,000th of a second, enabling the MASC to capture snowflake sizes ranging from 30 micrometers to 3 cm.« less

Monitoring the battery status for photovoltaic systems

NASA Astrophysics Data System (ADS)

Kim, Myungsoo; Hwang, Euijin

Photovoltaic power systems in Korea have been installed in remote islands where it is difficult to connect the utilities. Lead/acid batteries are used as an energy storage device for the stand-alone photovoltaic system. Hence, monitoring the battery status of photovoltaic systems is quite important to extend the total system service life. To monitor the state-of-charge of batteries, we adopted a current interrupt technique to measure the internal resistance of the battery. The internal resistance increases at the end of charge/discharge steps and also with cycles. The specific gravity of the electrolyte was measured in relation to the state-of-charge. A home-made optical hydrometer was utilized for automatic monitoring of the specific gravity. It is shown that the specific gravity and stratification increase with cycle number. One of the photovoltaic systems in a remote island, Ho-do, which has 90 kW peak power was checked for actual operational conditions such as solar generation, load, and battery status.

Geology and evolution of lakes in north-central Florida

USGS Publications Warehouse

Kindinger, J.L.; Davis, J.B.; Flocks, J.G.

1999-01-01

Fluid exchange between surficial waters and groundwater in karst environments, and the processes that control exchange, are of critical concern to water management districts and planners. High-resolution seismic data were collected from 30 lakes of north-central Florida. In each case study, lake structure and geomorphology were controlled by solution and/or mechanical processes. Processes that control lake development are twofold: (1) karstification or dissolution of the underlying limestone, and (2) the collapse, subsidence, or slumping of overburden to form sinkholes. Initial lake formation is directly related to the karst topography of the underlying host limestone. Case studies have shown that lakes can be divided by geomorphic types into progressive developmental phases: (1) active subsidence or collapse phase (young); (2) transitional phase (middle age); (3) baselevel phase (mature); and (4) polje (drowned prairie) - broad flat-bottom that have one or all phases of sinkhole. Using these criteria, Florida lakes can be classified by size, fill, subsurface features, and geomorphology.Fluid exchange between surficial waters and groundwater in karst environments, and the processes that control exchange, are of critical concern to water management districts and planners. High-resolution seismic data were collected from 30 lakes of north-central Florida. In each case study, lake structure and geomorphology were controlled by solution and/or mechanical processes. Processes that control lake development are twofold: (1) karstification or dissolution of the underlying limestone, and (2) the collapse, subsidence, or slumping of overburden to form sinkholes. Initial lake formation is directly related to the karst topography of the underlying host limestone. Case studies have shown that lakes can be divided by geomorphic types into progressive developmental phased: (1) active subsidence or collapse phase (young); (2) transitional phase (middle age); (3) baselevel phase (mature); and (4) polje (drowned prairie) - broad flat-bottom that have one or all phases of sinkhole. Using these criteria, Florida lakes can be classified by size, fill, subsurface features, and geomorphology.

Identification of terrain cover using the optimum polarimetric classifier

NASA Technical Reports Server (NTRS)

Kong, J. A.; Swartz, A. A.; Yueh, H. A.; Novak, L. M.; Shin, R. T.

1988-01-01

A systematic approach for the identification of terrain media such as vegetation canopy, forest, and snow-covered fields is developed using the optimum polarimetric classifier. The covariance matrices for various terrain cover are computed from theoretical models of random medium by evaluating the scattering matrix elements. The optimal classification scheme makes use of a quadratic distance measure and is applied to classify a vegetation canopy consisting of both trees and grass. Experimentally measured data are used to validate the classification scheme. Analytical and Monte Carlo simulated classification errors using the fully polarimetric feature vector are compared with classification based on single features which include the phase difference between the VV and HH polarization returns. It is shown that the full polarimetric results are optimal and provide better classification performance than single feature measurements.

What Are Clinical Trials? | NIH MedlinePlus the Magazine

MedlinePlus

... of this page please turn Javascript on. Feature: Clinical Trials What Are Clinical Trials? Past Issues / Fall 2010 Table of Contents ... conducted all the time. The Different Phases of Clinical Trials Clinical trials related to drugs are classified ...

Low-complexity approximations to maximum likelihood MPSK modulation classification

NASA Technical Reports Server (NTRS)

Hamkins, Jon

2004-01-01

We present a new approximation to the maximum likelihood classifier to discriminate between M-ary and M'-ary phase-shift-keying transmitted on an additive white Gaussian noise (AWGN) channel and received noncoherentl, partially coherently, or coherently.

NON-COMMUNITY WATER SYSTEMS DATABASE

EPA Science Inventory

Resource Purpose:Virtually every SIC code has some establishments which are classified as public water supplies under the SDWA. The survey (entering its design phase) will provide information on drinking water utilization and production at these establishments. With such...

Testing for significance of phase synchronisation dynamics in the EEG.

PubMed

Daly, Ian; Sweeney-Reed, Catherine M; Nasuto, Slawomir J

2013-06-01

A number of tests exist to check for statistical significance of phase synchronisation within the Electroencephalogram (EEG); however, the majority suffer from a lack of generality and applicability. They may also fail to account for temporal dynamics in the phase synchronisation, regarding synchronisation as a constant state instead of a dynamical process. Therefore, a novel test is developed for identifying the statistical significance of phase synchronisation based upon a combination of work characterising temporal dynamics of multivariate time-series and Markov modelling. We show how this method is better able to assess the significance of phase synchronisation than a range of commonly used significance tests. We also show how the method may be applied to identify and classify significantly different phase synchronisation dynamics in both univariate and multivariate datasets.

Classification of symmetry-protected phases for interacting fermions in two dimensions

NASA Astrophysics Data System (ADS)

Cheng, Meng; Bi, Zhen; You, Yi-Zhuang; Gu, Zheng-Cheng

2018-05-01

Recently, it has been established that two-dimensional bosonic symmetry-protected topological (SPT) phases with on-site unitary symmetry G can be completely classified by the group cohomology H3( G ,U (1 ) ) . Later, group supercohomology was proposed as a partial classification for SPT phases of interacting fermions. In this work, we revisit this problem based on the algebraic theory of symmetry and defects in two-dimensional topological phases. We reproduce the partial classifications given by group supercohomology, and we also show that with an additional H1(G ,Z2) structure, a complete classification of SPT phases for two-dimensional interacting fermion systems with a total symmetry group G ×Z2f is obtained. We also discuss the classification of interacting fermionic SPT phases protected by time-reversal symmetry.

The phase topology of a special case of Goryachev integrability in rigid body dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ryabov, P. E., E-mail: orelryabov@mail.ru

2014-07-31

The phase topology of a special case of Goryachev integrability in the problem of motion of a rigid body in a fluid is investigated using the method of Boolean functions, which was developed by Kharlamov for algebraically separated systems. The bifurcation diagram of the moment map is found and the Fomenko invariant, which classifies the systems up to rough Liouville equivalence, is specified. Bibliography: 15 titles. (paper)

Installation Restoration Program Records Search for Westover Air Force Base, Massachusetts.

DTIC Science & Technology

1982-04-01

Phase III (not part of this contract) consists of a technology base development study to support the development of project plans for controlling...determine the extent and magnitude of the contaminant migration. Phase III (not part of this contract) consists of a technology base development study to...number of vegetation studies have attempted to classify the potential climax vegetation within the region of Westover AFB (Braun, 1972; Kuchler, 1975

Hepatocellular Adenoma: Evaluation with Contrast-Enhanced Ultrasound and MRI and Correlation with Pathologic and Phenotypic Classification in 26 Lesions

PubMed Central

Manichon, Anne-Frédérique; Bancel, Brigitte; Durieux-Millon, Marion; Ducerf, Christian; Mabrut, Jean-Yves; Lepogam, Marie-Annick; Rode, Agnès

2012-01-01

Purpose. To review the contrast-enhanced ultrasonographic (CEUS) and magnetic resonance (MR) imaging findings in 25 patients with 26 hepatocellular adenomas (HCAs) and to compare imaging features with histopathologic results from resected specimen considering the new immunophenotypical classification. Material and Methods. Two abdominal radiologists reviewed retrospectively CEUS cineloops and MR images in 26 HCA. All pathological specimens were reviewed and classified into four subgroups (steatotic or HNF 1α mutated, inflammatory, atypical or β-catenin mutated, and unspecified). Inflammatory infiltrates were scored, steatosis, and telangiectasia semiquantitatively evaluated. Results. CEUS and MRI features are well correlated: among the 16 inflammatory HCA, 7/16 presented typical imaging features: hypersignal T2, strong arterial enhancement with a centripetal filling, persistent on delayed phase. 6 HCA were classified as steatotic with typical imaging features: a drop out signal, slight arterial enhancement, vanishing on late phase. Four HCA were classified as atypical with an HCC developed in one. Five lesions displayed important steatosis (>50%) without belonging to the HNF1α group. Conclusion. In half cases, inflammatory HCA have specific imaging features well correlated with the amount of telangiectasia and inflammatory infiltrates. An HCA with important amount of steatosis noticed on chemical shift images does not always belong to the HNF1α group. PMID:22811588

There is not yet strong evidence that exercise regimens other than pelvic floor muscle training can reduce stress urinary incontinence in women: a systematic review.

PubMed

Bø, Kari; Herbert, Robert D

2013-09-01

What evidence is there for alternative exercises to specific pelvic floor muscle training for treatment of stress urinary incontinence in women? A systematic review was conducted with searches of PubMed and PEDro to January 2013. The quality of randomised trials was evaluated using the PEDro scale. Each type of exercise was classified as being in a Development Phase, Testing Phase, or Refinement and Dissemination Phase. Women with stress or mixed urinary incontinence with predominantly stress urinary incontinence. Exercise regimens other than pelvic floor muscle training. The primary outcome was urinary leakage. Seven randomised controlled trials were found: three on abdominal training, two on the Paula method, and two on Pilates exercise. The methodological quality score ranged between 4 and 8 with a mean of 5.7. There was no convincing evidence for the effect of these exercise regimens so they remain in the Testing Phase. Because no randomised trials were found for posture correction, breathing exercise, yoga, Tai Chi, and general fitness training, these were classified as being in the Development Phase. There is not yet strong evidence that alternative exercise regimens can reduce urinary leakage in women with stress urinary incontinence. Alternative exercise regimens should not yet be recommended for use in clinical practice for women with stress urinary incontinence. Copyright © 2013 Australian Physiotherapy Association. Published by .. All rights reserved.

Automated identification of best-quality coronary artery segments from multiple-phase coronary CT angiography (cCTA) for vessel analysis

NASA Astrophysics Data System (ADS)

Zhou, Chuan; Chan, Heang-Ping; Hadjiiski, Lubomir M.; Chughtai, Aamer; Wei, Jun; Kazerooni, Ella A.

2016-03-01

We are developing an automated method to identify the best quality segment among the corresponding segments in multiple-phase cCTA. The coronary artery trees are automatically extracted from different cCTA phases using our multi-scale vessel segmentation and tracking method. An automated registration method is then used to align the multiple-phase artery trees. The corresponding coronary artery segments are identified in the registered vessel trees and are straightened by curved planar reformation (CPR). Four features are extracted from each segment in each phase as quality indicators in the original CT volume and the straightened CPR volume. Each quality indicator is used as a voting classifier to vote the corresponding segments. A newly designed weighted voting ensemble (WVE) classifier is finally used to determine the best-quality coronary segment. An observer preference study is conducted with three readers to visually rate the quality of the vessels in 1 to 6 rankings. Six and 10 cCTA cases are used as training and test set in this preliminary study. For the 10 test cases, the agreement between automatically identified best-quality (AI-BQ) segments and radiologist's top 2 rankings is 79.7%, and between AI-BQ and the other two readers are 74.8% and 83.7%, respectively. The results demonstrated that the performance of our automated method was comparable to those of experienced readers for identification of the best-quality coronary segments.

Quantum trajectory phase transitions in the micromaser.

PubMed

Garrahan, Juan P; Armour, Andrew D; Lesanovsky, Igor

2011-08-01

We study the dynamics of the single-atom maser, or micromaser, by means of the recently introduced method of thermodynamics of quantum jump trajectories. We find that the dynamics of the micromaser displays multiple space-time phase transitions, i.e., phase transitions in ensembles of quantum jump trajectories. This rich dynamical phase structure becomes apparent when trajectories are classified by dynamical observables that quantify dynamical activity, such as the number of atoms that have changed state while traversing the cavity. The space-time transitions can be either first order or continuous, and are controlled not just by standard parameters of the micromaser but also by nonequilibrium "counting" fields. We discuss how the dynamical phase behavior relates to the better known stationary-state properties of the micromaser.

Urine cell-based DNA methylation classifier for monitoring bladder cancer.

PubMed

van der Heijden, Antoine G; Mengual, Lourdes; Ingelmo-Torres, Mercedes; Lozano, Juan J; van Rijt-van de Westerlo, Cindy C M; Baixauli, Montserrat; Geavlete, Bogdan; Moldoveanud, Cristian; Ene, Cosmin; Dinney, Colin P; Czerniak, Bogdan; Schalken, Jack A; Kiemeney, Lambertus A L M; Ribal, Maria J; Witjes, J Alfred; Alcaraz, Antonio

2018-01-01

Current standard methods used to detect and monitor bladder cancer (BC) are invasive or have low sensitivity. This study aimed to develop a urine methylation biomarker classifier for BC monitoring and validate this classifier in patients in follow-up for bladder cancer (PFBC). Voided urine samples ( N  = 725) from BC patients, controls, and PFBC were prospectively collected in four centers. Finally, 626 urine samples were available for analysis. DNA was extracted from the urinary cells and bisulfite modificated, and methylation status was analyzed using pyrosequencing. Cytology was available from a subset of patients ( N  = 399). In the discovery phase, seven selected genes from the literature ( CDH13 , CFTR , NID2 , SALL3 , TMEFF2 , TWIST1 , and VIM2 ) were studied in 111 BC and 57 control samples. This training set was used to develop a gene classifier by logistic regression and was validated in 458 PFBC samples (173 with recurrence). A three-gene methylation classifier containing CFTR , SALL3 , and TWIST1 was developed in the training set (AUC 0.874). The classifier achieved an AUC of 0.741 in the validation series. Cytology results were available for 308 samples from the validation set. Cytology achieved AUC 0.696 whereas the classifier in this subset of patients reached an AUC 0.768. Combining the methylation classifier with cytology results achieved an AUC 0.86 in the validation set, with a sensitivity of 96%, a specificity of 40%, and a positive and negative predictive value of 56 and 92%, respectively. The combination of the three-gene methylation classifier and cytology results has high sensitivity and high negative predictive value in a real clinical scenario (PFBC). The proposed classifier is a useful test for predicting BC recurrence and decrease the number of cystoscopies in the follow-up of BC patients. If only patients with a positive combined classifier result would be cystoscopied, 36% of all cystoscopies can be prevented.

Just-in-time adaptive classifiers-part II: designing the classifier.

PubMed

Alippi, Cesare; Roveri, Manuel

2008-12-01

Aging effects, environmental changes, thermal drifts, and soft and hard faults affect physical systems by changing their nature and behavior over time. To cope with a process evolution adaptive solutions must be envisaged to track its dynamics; in this direction, adaptive classifiers are generally designed by assuming the stationary hypothesis for the process generating the data with very few results addressing nonstationary environments. This paper proposes a methodology based on k-nearest neighbor (NN) classifiers for designing adaptive classification systems able to react to changing conditions just-in-time (JIT), i.e., exactly when it is needed. k-NN classifiers have been selected for their computational-free training phase, the possibility to easily estimate the model complexity k and keep under control the computational complexity of the classifier through suitable data reduction mechanisms. A JIT classifier requires a temporal detection of a (possible) process deviation (aspect tackled in a companion paper) followed by an adaptive management of the knowledge base (KB) of the classifier to cope with the process change. The novelty of the proposed approach resides in the general framework supporting the real-time update of the KB of the classification system in response to novel information coming from the process both in stationary conditions (accuracy improvement) and in nonstationary ones (process tracking) and in providing a suitable estimate of k. It is shown that the classification system grants consistency once the change targets the process generating the data in a new stationary state, as it is the case in many real applications.

Nested Tracer Studies In Catchment Hydrology: Towards A Multiscale Understanding of Runoff Generation and Catchment Funtioning

NASA Astrophysics Data System (ADS)

Soulsby, C.; Rodgers, P.; Malcolm, I. A.; Dunn, S.

Geochemical and isotopic tracers have been shown to have widespread utility in catch- ment hydrology in terms of identifying hydrological source areas and characterising residence time distributions. In many cases application of tracer techniques has pro- vided insights into catchment functioning that could not be obtained from hydromet- ric and/or modelling studies alone. This paper will show how the use of tracers has contributed to an evolving perceptual model of hydrological pathways and runoff gen- eration processes in catchments in the Scottish highlands. In particular the paper will focus on the different insights that are gained at three different scales of analysis; (a) nested sub-catchments within a mesoscale (ca. 200 square kilometers) experimen- tal catchment; (b) hillslope-riparian interactions and (c) stream bed fluxes. Nested hydrometric and hydrochemical monitoring within the mesoscale Feugh catchment identified three main hydrological response units: (i) plateau peatlands which gener- ated saturation overland flow in the catchment headwaters, (ii) steep valley hillslopes which drain from the plateaux into (iii) alluvial and drift aquifers in the valley bottoms. End Member Mixing Analysis (EMMA) in 8 nested sub-catchments indicated that that stream water tracer concentrations can be modelled in terms of 2 dominant runoff pro- cesses; overland flow from the peat and groundwater from the drift aquifers. Ground- water contributions generally increased with catchment size, though this was moder- ated by the characteristics of individual sub-basins, with drift cover being particularly important. Hillslope riparian interactions were also examined using tracers, hydromet- ric data and a semi-distributed hydrological model. This revealed that in the glaciated, drift covered terrain of the Scottish highlands, extensive valley bottom aquifers effec- tively de-couple hillslope waters from the river channel. Thus, riparian groundwater appears to significantly contribute to storm runoff as well as sustain base flows. Water from steeper hillslopes appears to primarily recharge valley bottom aquifers. Fluxes from the drift aquifers into the stream bed were investigated using hydrometric and tracer techniques. Groundwater fluxes through the stream bed appear to be relatively localized relating to geological boundaries or changes in drift characteristics. How- ever, these fluxes are also controlled by morphological features in the river channel which exert a strong control on localized groundwater U surface water interactions. 1 If catchment hydrology is to contribute to a functional understanding of freshwater ecosystems it is argued that integrated tracer studies, at different scales and incorpo- rating both observations from field work and modelling applications, have a key role to play. 2

Occurrence and toxicity of Microcystis aeruginosa (Cyanobacteria) in the Paraná River, downstream of the Yacyretá dam (Argentina).

PubMed

Forastier, Marina Elizabet; Zalocar, Yolanda; Andrinolo, Dario; Domitrovic, Hugo Alberto

2016-03-01

Cyanobacteria constitute the main toxin producers in inland water ecosystems and have extensive global distribution. The presence of hepatotoxins in aquatic environments is hazardous to human and animal health; even though the presence and identification of hepatotoxic microcystins in rivers and reservoirs of the world have been confirmed by several studies in the last few years. Herein, we studied the abundance and toxicity of Microcystis aeruginosa in the Argentine section of the Paraná River at the beginning of the Middle Paraná (Corrientes Hydrometer), near Corrientes city (27º28´ S - 58º51´ W) and approximately 220 km downstream of the Yacyretá dam (High Paraná). The Paraná River basin, with a drainage area of 3.1 x 10(6) km(2) and 3 965 km in length, is the second largest catchment of South America, after that of the Amazon. The Paraná River is the main source of drinking water supply for the Northeastern Argentine region. Phytoplankton samples were collected and environmental variables were measured in a monthly basis (exceptionally fortnightly), from March 2004 to June 2008. Fifty-eight samples were analyzed for phytoplankton density and biomass. Five samples were used for toxicity testing; the latter were obtained during the cyanobacteria blooms from 2005 to 2008. Phytoplankton counts were performed with an inverted microscope, and biomass was expressed as biovolume. Bioassays with mice and high-performance liquid chromatography (HPLC) analysis were performed to evaluate the presence of cyanotoxins. Phytoplankton mainly consisted of Cryptophyta, Chlorophyta and Bacillariophyta. Microcystis aeruginosa was identified during the warmer months each year (November to March). Density varied between 189 and 25 027 cells/mL (1-10 colonies/mL) and biomass from 0.34 to 44 mm(3)/L. Taking into account the number of cells, the highest abundance occurred in April 2004 (25 027 cells/mL), coinciding with the largest biovolume (44 mm(3)/L). All mice subjected to intraperitoneal injections with samples obtained during bloom episodes showed positive results for the presence of hepatotoxins. Three microcystins variants: LR, RR and [D-Leu(1)] Mcyst-LR were detected by analysis with semi-preparative high-performance liquid chromatography with diode array detector system (HPLC-PDA). This constitutes the first report of microcystins recorded during M. aeruginosa blooms in the Argentine stretch of the Paraná River at the beginning of the Middle Paraná (Corrientes Hydrometer), approximately 220 km downstream of the Yacyretá dam (High Paraná).

Practical methodological guide for hydrometric inter-laboratory organisation

NASA Astrophysics Data System (ADS)

Besson, David; Bertrand, Xavier

2015-04-01

Discharge measurements performed by the French governmental hydrometer team feed a national database. This data is available for general river flows knowkedge, flood forecasting, low water survey, statistical calculations flow, control flow regulatory and many other uses. Regularly checking the measurements quality and better quantifying its accuracy is therefore an absolute need. The practice of inter-laboratory comparison in hydrometry particularly developed during the last decade. Indeed, discharge measurement can not easily be linked to a standard. Therefore, on-site measurement accuracy control is very difficult. Inter-laboratory comparison is thus a practical solution to this issue. However, it needs some regulations in order to ease its practice and legitimize its results. To do so, the French government hydrometrics teams produced a practical methodological guide for hydrometric inter-laboratory organisation in destination of hydrometers community in view of ensure the harmonization of inter-laboratory comparison practices for different materials (ADCP, current meter on wadind rod or gauging van, tracer dilution, surface speed) and flow range (flood, low water). Ensure the results formalization and banking. The realisation of this practice guide is grounded on the experience of the governmental teams & their partners (or fellows), following existing approaches (Doppler group especially). The guide is designated to validate compliance measures and identify outliers : Hardware, methodological, environmental, or human. Inter-laboratory comparison provides the means to verify the compliance of the instruments (devices + methods + operators) and provides methods to determine an experimental uncertainty of the tested measurement method which is valid only for the site and the measurement conditions but does not address the calibration or periodic monitoring of the few materials. After some conceptual definitions, the guide describes the different stages of an inter-comparison campaign: the campaing creation: targets, participants ( instruments type and number) and site preparation of test protocols and schedule; the campaign set-up (organization): invitation and pre-information of the participants, logistics, field preparation; the campaign conduct: participants reception and information, sequences of tests, results analysis and communication, balance sheet; post-campaign work: further analysis, dissemination and periodic verification of the instruments. This guide is associated with measurement instruments forms, reminding their limits and conditions for use, land forms, used to record all the necessary information during the inter-comparison campaign (site description and measurement conditions, equipment and its settings, and the set of measurements or intermediate calculations to the final results) as well as a calculation tool and banking measures and results.

Categorization and Characterization of American Driving Conditions (Phase I)

DOT National Transportation Integrated Search

1978-11-01

The objectives of the study were: (1) to develop a multidimensional matrix as an analysis framework to classify travel of personal motor vehicles according to fuel consumption, (2) to identify and assess available information on travel and fuel consu...

Application of phase-change materials in memory taxonomy

PubMed Central

Wang, Lei; Tu, Liang; Wen, Jing

2017-01-01

Abstract Phase-change materials are suitable for data storage because they exhibit reversible transitions between crystalline and amorphous states that have distinguishable electrical and optical properties. Consequently, these materials find applications in diverse memory devices ranging from conventional optical discs to emerging nanophotonic devices. Current research efforts are mostly devoted to phase-change random access memory, whereas the applications of phase-change materials in other types of memory devices are rarely reported. Here we review the physical principles of phase-change materials and devices aiming to help researchers understand the concept of phase-change memory. We classify phase-change memory devices into phase-change optical disc, phase-change scanning probe memory, phase-change random access memory, and phase-change nanophotonic device, according to their locations in memory hierarchy. For each device type we discuss the physical principles in conjunction with merits and weakness for data storage applications. We also outline state-of-the-art technologies and future prospects. PMID:28740557

Reanalysis of porous chondritic cosmic dust particles

NASA Astrophysics Data System (ADS)

Kapisinsky, I.; Figusch, V.; Ivan, J.; Izdinsky, K.; Zemankova, M.

2001-10-01

The particles reanalysed in this study were obtained from the NASA Johnson Space Center (JSC) Cosmic Dust Collection. The reanalysis of the particle L2008 P9 indicates typical assemblage of olivine - pyroxene. This sample can be classified as a chondritic porous IDP with the metallic phase grain containing essential amount of nickel and copper (the latter element is most probably due to instrumental artefact). The chemical composition of the particle L2011 S5 corresponds mostly to an assemblage of pyroxene phase - (Mg,Fe,Ni)SiO_3 roughly 75 wt.% and a sulphide phase - probably pyrrhotite (Fe,Ni)S about 25 wt.%.

Unifying hydrotropy under Gibbs phase rule.

PubMed

Shimizu, Seishi; Matubayasi, Nobuyuki

2017-09-13

The task of elucidating the mechanism of solubility enhancement using hydrotropes has been hampered by the wide variety of phase behaviour that hydrotropes can exhibit, encompassing near-ideal aqueous solution, self-association, micelle formation, and micro-emulsions. Instead of taking a field guide or encyclopedic approach to classify hydrotropes into different molecular classes, we take a rational approach aiming at constructing a unified theory of hydrotropy based upon the first principles of statistical thermodynamics. Achieving this aim can be facilitated by the two key concepts: (1) the Gibbs phase rule as the basis of classifying the hydrotropes in terms of the degrees of freedom and the number of variables to modulate the solvation free energy; (2) the Kirkwood-Buff integrals to quantify the interactions between the species and their relative contributions to the process of solubilization. We demonstrate that the application of the two key concepts can in principle be used to distinguish the different molecular scenarios at work under apparently similar solubility curves observed from experiments. In addition, a generalization of our previous approach to solutes beyond dilution reveals the unified mechanism of hydrotropy, driven by a strong solute-hydrotrope interaction which overcomes the apparent per-hydrotrope inefficiency due to hydrotrope self-clustering.

A phased SNP-based classification of sickle cell anemia HBB haplotypes.

PubMed

Shaikho, Elmutaz M; Farrell, John J; Alsultan, Abdulrahman; Qutub, Hatem; Al-Ali, Amein K; Figueiredo, Maria Stella; Chui, David H K; Farrer, Lindsay A; Murphy, George J; Mostoslavsky, Gustavo; Sebastiani, Paola; Steinberg, Martin H

2017-08-11

Sickle cell anemia causes severe complications and premature death. Five common β-globin gene cluster haplotypes are each associated with characteristic fetal hemoglobin (HbF) levels. As HbF is the major modulator of disease severity, classifying patients according to haplotype is useful. The first method of haplotype classification used restriction fragment length polymorphisms (RFLPs) to detect single nucleotide polymorphisms (SNPs) in the β-globin gene cluster. This is labor intensive, and error prone. We used genome-wide SNP data imputed to the 1000 Genomes reference panel to obtain phased data distinguishing parental alleles. We successfully haplotyped 813 sickle cell anemia patients previously classified by RFLPs with a concordance >98%. Four SNPs (rs3834466, rs28440105, rs10128556, and rs968857) marking four different restriction enzyme sites unequivocally defined most haplotypes. We were able to assign a haplotype to 86% of samples that were either partially or misclassified using RFLPs. Phased data using only four SNPs allowed unequivocal assignment of a haplotype that was not always possible using a larger number of RFLPs. Given the availability of genome-wide SNP data, our method is rapid and does not require high computational resources.

Full Phase Multi-Band Study of Eclipsing Binaries 1SWASP J061850.43+220511.9 and 2MASSJ07095549+3643564

NASA Astrophysics Data System (ADS)

Terheide, Rachel; Zhang, Liyun; Han, Xianming; Lu, Hongpeng

2018-01-01

We present full-phase VRI-band light curves for eclipsing binary 1SWASP J061850.43+220511.9, and full-phase BVRI-band light curves for eclipsing binary 2MASS J07095549+3643564. The observations were conducted using the 0.94-m Holcomb Observatory telescope located on Butler University Campus in Indianapolis, Indiana, and the 0.6-m SARA telescope located at the Cerro Tololo Inter-American Observatory in Chile. We obtained key system parameters for both eclipsing binaries. For 1SWASP J061850.43+220511.9, the period is 0.21482 ±0.00053 days compared to 0.21439 days from an older study (Lohr et. al), the system mass ratio is found as 2.50 and the system is classified as EW type. Similarly, for 2MASS J07095549+3643564, we obtained a linear ephemeris and a physical model for the first time. We found its period to be 0.22297 ±0.00032 days, as compared to 0.446092 days and 0.11152 days from previous research (Drake et. al 2014, Hartman et. al 2011). 2MASS J07095549+3643564 is classified as a W Uma type eclipsing binary.

A possible role of a cerebral energy gene in alcoholism.

PubMed

Ribeiro, A F; Correia, D; Boerngen-Lacerda, R; Brunialti-Godard, A L

2012-02-17

We examined a possible relationship between genes responsible for energy metabolism of the brain and addictive behavior in an animal model. We used non-inbred, Swiss mice exposed to a three-bottle free-choice model [water, 5% (v/v) ethanol, and 10% (v/v) ethanol] over a 16-week period, consisting of four phases: acquisition, withdrawal, reexposure, and quinine-adulteration. The mice were then behaviorally classified into three groups: loss-of-control-drinker (preference for ethanol and high levels of consumption during all phases, N = 6), heavy-drinker (preference for ethanol and high levels of consumption during acquisition and reduction during quinine-adulteration, N = 7), and light-drinker (preference for water during all phases, N = 10). Another group only received tap water (ethanol-naive control mice, N = 9). Further analysis using quantitative real-time PCR showed that in mice behaviorally classified as loss-of-control-drinkers, there was a significant inverse correlation between transcript levels of the Hadh gene and those of other energy metabolism genes in the nucleus of the amygdala, suggesting that this pathway may contribute to ethanol consumption in these mice. We conclude that cerebral energy metabolism is involved with ethanol addiction, meriting further study.

Data fusion with artificial neural networks (ANN) for classification of earth surface from microwave satellite measurements

NASA Technical Reports Server (NTRS)

Lure, Y. M. Fleming; Grody, Norman C.; Chiou, Y. S. Peter; Yeh, H. Y. Michael

1993-01-01

A data fusion system with artificial neural networks (ANN) is used for fast and accurate classification of five earth surface conditions and surface changes, based on seven SSMI multichannel microwave satellite measurements. The measurements include brightness temperatures at 19, 22, 37, and 85 GHz at both H and V polarizations (only V at 22 GHz). The seven channel measurements are processed through a convolution computation such that all measurements are located at same grid. Five surface classes including non-scattering surface, precipitation over land, over ocean, snow, and desert are identified from ground-truth observations. The system processes sensory data in three consecutive phases: (1) pre-processing to extract feature vectors and enhance separability among detected classes; (2) preliminary classification of Earth surface patterns using two separate and parallely acting classifiers: back-propagation neural network and binary decision tree classifiers; and (3) data fusion of results from preliminary classifiers to obtain the optimal performance in overall classification. Both the binary decision tree classifier and the fusion processing centers are implemented by neural network architectures. The fusion system configuration is a hierarchical neural network architecture, in which each functional neural net will handle different processing phases in a pipelined fashion. There is a total of around 13,500 samples for this analysis, of which 4 percent are used as the training set and 96 percent as the testing set. After training, this classification system is able to bring up the detection accuracy to 94 percent compared with 88 percent for back-propagation artificial neural networks and 80 percent for binary decision tree classifiers. The neural network data fusion classification is currently under progress to be integrated in an image processing system at NOAA and to be implemented in a prototype of a massively parallel and dynamically reconfigurable Modular Neural Ring (MNR).

MIDAS, prototype Multivariate Interactive Digital Analysis System, phase 1. Volume 1: System description

NASA Technical Reports Server (NTRS)

Kriegler, F. J.

1974-01-01

The MIDAS System is described as a third-generation fast multispectral recognition system able to keep pace with the large quantity and high rates of data acquisition from present and projected sensors. A principal objective of the MIDAS program is to provide a system well interfaced with the human operator and thus to obtain large overall reductions in turnaround time and significant gains in throughput. The hardware and software are described. The system contains a mini-computer to control the various high-speed processing elements in the data path, and a classifier which implements an all-digital prototype multivariate-Gaussian maximum likelihood decision algorithm operating at 200,000 pixels/sec. Sufficient hardware was developed to perform signature extraction from computer-compatible tapes, compute classifier coefficients, control the classifier operation, and diagnose operation.

The Oxygen Isotopic Composition of MIL 090001: A CR2 Chondrite with Abundant Refractory Inclusions

NASA Technical Reports Server (NTRS)

Keller, Lindsay P.; McKeegan, K. D.; Sharp, Z. D.

2012-01-01

MIL 090001 is a large (>6 kg) carbonaceous chondrite that was classified as a member of the CV reduced subgroup (CVred) that was recovered during the 2009-2010 ANSMET field season [1]. Based on the abundance of refractory inclusions and the extent of aqueous alteration, Keller [2] suggested a CV2 classification. Here we report additional mineralogical and petrographic data for MIL 090001, its whole-rock oxygen isotopic composition and ion microprobe analyses of individual phases. The whole rock oxygen isotopic analyses show that MIL 090001 should be classified as a CR chondrite.

Liquid Crystals for Laser Applications

DTIC Science & Technology

1992-07-01

336. Zei’dovich, B . Ya. and Tabiryan, N. V., Induced light scattering in the mesophase of a nematic liquid crystal (NLC), JETP Lett., 30, 478- 482 ...and devices. ADVANCES IN MATERIALS I Ferroelectric LC’s Ferroelectricity in liquid crystals was first suggested in 1974 by R. B . Meyer2 3 who, by means...most recently, 2 4 the M* phase. These tilted chiral smectic phases are classified according to the nature of the intermolecular I I packing within

Design of a hybrid model for cardiac arrhythmia classification based on Daubechies wavelet transform.

PubMed

Rajagopal, Rekha; Ranganathan, Vidhyapriya

2018-06-05

Automation in cardiac arrhythmia classification helps medical professionals make accurate decisions about the patient's health. The aim of this work was to design a hybrid classification model to classify cardiac arrhythmias. The design phase of the classification model comprises the following stages: preprocessing of the cardiac signal by eliminating detail coefficients that contain noise, feature extraction through Daubechies wavelet transform, and arrhythmia classification using a collaborative decision from the K nearest neighbor classifier (KNN) and a support vector machine (SVM). The proposed model is able to classify 5 arrhythmia classes as per the ANSI/AAMI EC57: 1998 classification standard. Level 1 of the proposed model involves classification using the KNN and the classifier is trained with examples from all classes. Level 2 involves classification using an SVM and is trained specifically to classify overlapped classes. The final classification of a test heartbeat pertaining to a particular class is done using the proposed KNN/SVM hybrid model. The experimental results demonstrated that the average sensitivity of the proposed model was 92.56%, the average specificity 99.35%, the average positive predictive value 98.13%, the average F-score 94.5%, and the average accuracy 99.78%. The results obtained using the proposed model were compared with the results of discriminant, tree, and KNN classifiers. The proposed model is able to achieve a high classification accuracy.

Phase behavior of charged colloids at a fluid interface

NASA Astrophysics Data System (ADS)

Kelleher, Colm P.; Guerra, Rodrigo E.; Hollingsworth, Andrew D.; Chaikin, Paul M.

2017-02-01

We study the phase behavior of a system of charged colloidal particles that are electrostatically bound to an almost flat interface between two fluids. We show that, despite the fact that our experimental system consists of only 103-104 particles, the phase behavior is consistent with the theory of melting due to Kosterlitz, Thouless, Halperin, Nelson, and Young. Using spatial and temporal correlations of the bond-orientational order parameter, we classify our samples into solid, isotropic fluid, and hexatic phases. We demonstrate that the topological defect structure we observe in each phase corresponds to the predictions of Kosterlitz-Thouless-Halperin-Nelson-Young theory. By measuring the dynamic Lindemann parameter γL(τ ) and the non-Gaussian parameter α2(τ ) of the displacements of the particles relative to their neighbors, we show that each of the phases displays distinctive dynamical behavior.

Learning phase transitions by confusion

NASA Astrophysics Data System (ADS)

van Nieuwenburg, Evert P. L.; Liu, Ye-Hua; Huber, Sebastian D.

2017-02-01

Classifying phases of matter is key to our understanding of many problems in physics. For quantum-mechanical systems in particular, the task can be daunting due to the exponentially large Hilbert space. With modern computing power and access to ever-larger data sets, classification problems are now routinely solved using machine-learning techniques. Here, we propose a neural-network approach to finding phase transitions, based on the performance of a neural network after it is trained with data that are deliberately labelled incorrectly. We demonstrate the success of this method on the topological phase transition in the Kitaev chain, the thermal phase transition in the classical Ising model, and the many-body-localization transition in a disordered quantum spin chain. Our method does not depend on order parameters, knowledge of the topological content of the phases, or any other specifics of the transition at hand. It therefore paves the way to the development of a generic tool for identifying unexplored phase transitions.

Performance profile of NCAA Division I men's basketball games and training sessions.

PubMed

Conte, D; Tessitore, A; Smiley, K; Thomas, C; Favero, T G

2016-06-01

This study aimed to analyse live and stoppage time phases, their ratio, and action played on half and full court in college basketball games. Differences were assessed for the entire games and between halves. Moreover, differences of the live/stoppage time ratio were analysed between games and game-based conditioning drills. Ten games as well as fifteen defensive, fourteen offensive and six scrimmage-type drills of the same division I men's college team (13 players) were analysed using time-motion analysis technique. Live and stoppage time were classified in five classes of duration: 1-20, 21-40, 41-60, 61-80, >80 seconds. Half court actions started and finished in the same half court. Full court actions were classified as transfer (TR) phases when at least 3 teammates crossed the mid-court line. TR phases were then classified in 5 classes of frequency: 1TR, 2TR, 3TR, 4TR, and >4TR. The results revealed no statistically significant differences between games or between halves for the considered parameters. The only significant difference was observed for live/stoppage time ratio between halves (p<0.001). Furthermore, a significant difference of the live/stoppage ratio was found between games and game-based drills (p<0.01). Post-hoc analysis demonstrated significant differences of scrimmage-type drills in comparison to games, and defensive and offensive drills (p<0.05), whereas no differences emerged for the other pairwise comparisons. The absence of differences between games in the analysed parameters might be important to characterize the model of performance in division I men's college games. Furthermore, these results encourage coaches to use game-based conditioning drills to replicate the LT/ST ratio documented during games.

Using X-Ray In-Line Phase-Contrast Imaging for the Investigation of Nude Mouse Hepatic Tumors

PubMed Central

Zhang, Lu; Luo, Shuqian

2012-01-01

The purpose of this paper is to report the noninvasive imaging of hepatic tumors without contrast agents. Both normal tissues and tumor tissues can be detected, and tumor tissues in different stages can be classified quantitatively. We implanted BEL-7402 human hepatocellular carcinoma cells into the livers of nude mice and then imaged the livers using X-ray in-line phase-contrast imaging (ILPCI). The projection images' texture feature based on gray level co-occurrence matrix (GLCM) and dual-tree complex wavelet transforms (DTCWT) were extracted to discriminate normal tissues and tumor tissues. Different stages of hepatic tumors were classified using support vector machines (SVM). Images of livers from nude mice sacrificed 6 days after inoculation with cancer cells show diffuse distribution of the tumor tissue, but images of livers from nude mice sacrificed 9, 12, or 15 days after inoculation with cancer cells show necrotic lumps in the tumor tissue. The results of the principal component analysis (PCA) of the texture features based on GLCM of normal regions were positive, but those of tumor regions were negative. The results of PCA of the texture features based on DTCWT of normal regions were greater than those of tumor regions. The values of the texture features in low-frequency coefficient images increased monotonically with the growth of the tumors. Different stages of liver tumors can be classified using SVM, and the accuracy is 83.33%. Noninvasive and micron-scale imaging can be achieved by X-ray ILPCI. We can observe hepatic tumors and small vessels from the phase-contrast images. This new imaging approach for hepatic cancer is effective and has potential use in the early detection and classification of hepatic tumors. PMID:22761929

An investigation of Hebbian phase sequences as assembly graphs

PubMed Central

Almeida-Filho, Daniel G.; Lopes-dos-Santos, Vitor; Vasconcelos, Nivaldo A. P.; Miranda, José G. V.; Tort, Adriano B. L.; Ribeiro, Sidarta

2014-01-01

Hebb proposed that synapses between neurons that fire synchronously are strengthened, forming cell assemblies and phase sequences. The former, on a shorter scale, are ensembles of synchronized cells that function transiently as a closed processing system; the latter, on a larger scale, correspond to the sequential activation of cell assemblies able to represent percepts and behaviors. Nowadays, the recording of large neuronal populations allows for the detection of multiple cell assemblies. Within Hebb's theory, the next logical step is the analysis of phase sequences. Here we detected phase sequences as consecutive assembly activation patterns, and then analyzed their graph attributes in relation to behavior. We investigated action potentials recorded from the adult rat hippocampus and neocortex before, during and after novel object exploration (experimental periods). Within assembly graphs, each assembly corresponded to a node, and each edge corresponded to the temporal sequence of consecutive node activations. The sum of all assembly activations was proportional to firing rates, but the activity of individual assemblies was not. Assembly repertoire was stable across experimental periods, suggesting that novel experience does not create new assemblies in the adult rat. Assembly graph attributes, on the other hand, varied significantly across behavioral states and experimental periods, and were separable enough to correctly classify experimental periods (Naïve Bayes classifier; maximum AUROCs ranging from 0.55 to 0.99) and behavioral states (waking, slow wave sleep, and rapid eye movement sleep; maximum AUROCs ranging from 0.64 to 0.98). Our findings agree with Hebb's view that assemblies correspond to primitive building blocks of representation, nearly unchanged in the adult, while phase sequences are labile across behavioral states and change after novel experience. The results are compatible with a role for phase sequences in behavior and cognition. PMID:24782715

Blue intensity matters for cell cycle profiling in fluorescence DAPI-stained images.

PubMed

Ferro, Anabela; Mestre, Tânia; Carneiro, Patrícia; Sahumbaiev, Ivan; Seruca, Raquel; Sanches, João M

2017-05-01

In the past decades, there has been an amazing progress in the understanding of the molecular mechanisms of the cell cycle. This has been possible largely due to a better conceptualization of the cycle itself, but also as a consequence of technological advances. Herein, we propose a new fluorescence image-based framework targeted at the identification and segmentation of stained nuclei with the purpose to determine DNA content in distinct cell cycle stages. The method is based on discriminative features, such as total intensity and area, retrieved from in situ stained nuclei by fluorescence microscopy, allowing the determination of the cell cycle phase of both single and sub-population of cells. The analysis framework was built on a modified k-means clustering strategy and refined with a Gaussian mixture model classifier, which enabled the definition of highly accurate classification clusters corresponding to G1, S and G2 phases. Using the information retrieved from area and fluorescence total intensity, the modified k-means (k=3) cluster imaging framework classified 64.7% of the imaged nuclei, as being at G1 phase, 12.0% at G2 phase and 23.2% at S phase. Performance of the imaging framework was ascertained with normal murine mammary gland cells constitutively expressing the Fucci2 technology, exhibiting an overall sensitivity of 94.0%. Further, the results indicate that the imaging framework has a robust capacity to both identify a given DAPI-stained nucleus to its correct cell cycle phase, as well as to determine, with very high probability, true negatives. Importantly, this novel imaging approach is a non-disruptive method that allows an integrative and simultaneous quantitative analysis of molecular and morphological parameters, thus awarding the possibility of cell cycle profiling in cytological and histological samples.

Managing Florida's fracture critical bridges - phases 1 and 2 : final report.

DOT National Transportation Integrated Search

2016-05-01

Based on the definition given in the AASHTO LRFD Bridge Design Specifications, twin steel box-girder bridges are : classified as bridges with fracture critical members (FCMs), in which a failure of a tension member is expected to : lead to a collapse...

ToxRefDB: Classifying ToxCast™ Phase I Chemicals Utilizing Structured Toxicity Information

EPA Science Inventory

There is an essential need for highly detailed chemicals classifications within the ToxCast™ research program. In order to develop predictive models and biological signatures utilizing high-throughput screening (HTS) and in vitro genomic data, relevant endpoints and toxicities m...

Multimodal Neurodiagnostic Tool for Exploration Missions

NASA Technical Reports Server (NTRS)

Lee, Yong Jin

2015-01-01

Linea Research Corporation has developed a neurodiagnostic tool that detects behavioral stress markers for astronauts on long-duration space missions. Lightweight and compact, the device is unobtrusive and requires minimal time and effort for the crew to use. The system provides a real-time functional imaging of cortical activity during normal activities. In Phase I of the project, Linea Research successfully monitored cortical activity using multiparameter sensor modules. Using electroencephalography (EEG) and functional near-infrared spectroscopy signals, the company obtained photoplethysmography and electrooculography signals to compute the heart rate and frequency of eye movement. The company also demonstrated the functionality of an algorithm that automatically classifies the varying degrees of cognitive loading based on physiological parameters. In Phase II, Linea Research developed the flight-capable neurodiagnostic device. Worn unobtrusively on the head, the device detects and classifies neurophysiological markers associated with decrements in behavior state and cognition. An automated algorithm identifies key decrements and provides meaningful and actionable feedback to the crew and ground-based medical staff.

Quantitative change of EEG and respiration signals during mindfulness meditation.

PubMed

Ahani, Asieh; Wahbeh, Helane; Nezamfar, Hooman; Miller, Meghan; Erdogmus, Deniz; Oken, Barry

2014-05-14

This study investigates measures of mindfulness meditation (MM) as a mental practice, in which a resting but alert state of mind is maintained. A population of older people with high stress level participated in this study, while electroencephalographic (EEG) and respiration signals were recorded during a MM intervention. The physiological signals during meditation and control conditions were analyzed with signal processing. EEG and respiration data were collected and analyzed on 34 novice meditators after a 6-week meditation intervention. Collected data were analyzed with spectral analysis, phase analysis and classification to evaluate an objective marker for meditation. Different frequency bands showed differences in meditation and control conditions. Furthermore, we established a classifier using EEG and respiration signals with a higher accuracy (85%) at discriminating between meditation and control conditions than a classifier using the EEG signal only (78%). Support vector machine (SVM) classifier with EEG and respiration feature vector is a viable objective marker for meditation ability. This classifier should be able to quantify different levels of meditation depth and meditation experience in future studies.

Quantitative change of EEG and respiration signals during mindfulness meditation

PubMed Central

2014-01-01

Background This study investigates measures of mindfulness meditation (MM) as a mental practice, in which a resting but alert state of mind is maintained. A population of older people with high stress level participated in this study, while electroencephalographic (EEG) and respiration signals were recorded during a MM intervention. The physiological signals during meditation and control conditions were analyzed with signal processing. Methods EEG and respiration data were collected and analyzed on 34 novice meditators after a 6-week meditation intervention. Collected data were analyzed with spectral analysis, phase analysis and classification to evaluate an objective marker for meditation. Results Different frequency bands showed differences in meditation and control conditions. Furthermore, we established a classifier using EEG and respiration signals with a higher accuracy (85%) at discriminating between meditation and control conditions than a classifier using the EEG signal only (78%). Conclusion Support vector machine (SVM) classifier with EEG and respiration feature vector is a viable objective marker for meditation ability. This classifier should be able to quantify different levels of meditation depth and meditation experience in future studies. PMID:24939519

Prediction of heterotrimeric protein complexes by two-phase learning using neighboring kernels

PubMed Central

2014-01-01

Background Protein complexes play important roles in biological systems such as gene regulatory networks and metabolic pathways. Most methods for predicting protein complexes try to find protein complexes with size more than three. It, however, is known that protein complexes with smaller sizes occupy a large part of whole complexes for several species. In our previous work, we developed a method with several feature space mappings and the domain composition kernel for prediction of heterodimeric protein complexes, which outperforms existing methods. Results We propose methods for prediction of heterotrimeric protein complexes by extending techniques in the previous work on the basis of the idea that most heterotrimeric protein complexes are not likely to share the same protein with each other. We make use of the discriminant function in support vector machines (SVMs), and design novel feature space mappings for the second phase. As the second classifier, we examine SVMs and relevance vector machines (RVMs). We perform 10-fold cross-validation computational experiments. The results suggest that our proposed two-phase methods and SVM with the extended features outperform the existing method NWE, which was reported to outperform other existing methods such as MCL, MCODE, DPClus, CMC, COACH, RRW, and PPSampler for prediction of heterotrimeric protein complexes. Conclusions We propose two-phase prediction methods with the extended features, the domain composition kernel, SVMs and RVMs. The two-phase method with the extended features and the domain composition kernel using SVM as the second classifier is particularly useful for prediction of heterotrimeric protein complexes. PMID:24564744

High pressure air compressor valve fault diagnosis using feedforward neural networks

NASA Astrophysics Data System (ADS)

James Li, C.; Yu, Xueli

1995-09-01

Feedforward neural networks (FNNs) are developed and implemented to classify a four-stage high pressure air compressor into one of the following conditions: baseline, suction or exhaust valve faults. These FNNs are used for the compressor's automatic condition monitoring and fault diagnosis. Measurements of 39 variables are obtained under different baseline conditions and third-stage suction and exhaust valve faults. These variables include pressures and temperatures at all stages, voltage between phase aand phase b, voltage between phase band phase c, total three-phase real power, cooling water flow rate, etc. To reduce the number of variables, the amount of their discriminatory information is quantified by scattering matrices to identify statistical significant ones. Measurements of the selected variables are then used by a fully automatic structural and weight learning algorithm to construct three-layer FNNs to classify the compressor's condition. This learning algorithm requires neither guesses of initial weight values nor number of neurons in the hidden layer of an FNN. It takes an incremental approach in which a hidden neuron is trained by exemplars and then augmented to the existing network. These exemplars are then made orthogonal to the newly identified hidden neuron. They are subsequently used for the training of the next hidden neuron. The betterment continues until a desired accuracy is reached. After the neural networks are established, novel measurements from various conditions that haven't been previously seen by the FNNs are then used to evaluate their ability in fault diagnosis. The trained neural networks provide very accurate diagnosis for suction and discharge valve defects.

Evolutionary and Neural Computing Based Decision Support System for Disease Diagnosis from Clinical Data Sets in Medical Practice.

PubMed

Sudha, M

2017-09-27

As a recent trend, various computational intelligence and machine learning approaches have been used for mining inferences hidden in the large clinical databases to assist the clinician in strategic decision making. In any target data the irrelevant information may be detrimental, causing confusion for the mining algorithm and degrades the prediction outcome. To address this issue, this study attempts to identify an intelligent approach to assist disease diagnostic procedure using an optimal set of attributes instead of all attributes present in the clinical data set. In this proposed Application Specific Intelligent Computing (ASIC) decision support system, a rough set based genetic algorithm is employed in pre-processing phase and a back propagation neural network is applied in training and testing phase. ASIC has two phases, the first phase handles outliers, noisy data, and missing values to obtain a qualitative target data to generate appropriate attribute reduct sets from the input data using rough computing based genetic algorithm centred on a relative fitness function measure. The succeeding phase of this system involves both training and testing of back propagation neural network classifier on the selected reducts. The model performance is evaluated with widely adopted existing classifiers. The proposed ASIC system for clinical decision support has been tested with breast cancer, fertility diagnosis and heart disease data set from the University of California at Irvine (UCI) machine learning repository. The proposed system outperformed the existing approaches attaining the accuracy rate of 95.33%, 97.61%, and 93.04% for breast cancer, fertility issue and heart disease diagnosis.

On the application of neural networks to the classification of phase modulated waveforms

NASA Astrophysics Data System (ADS)

Buchenroth, Anthony; Yim, Joong Gon; Nowak, Michael; Chakravarthy, Vasu

2017-04-01

Accurate classification of phase modulated radar waveforms is a well-known problem in spectrum sensing. Identification of such waveforms aids situational awareness enabling radar and communications spectrum sharing. While various feature extraction and engineering approaches have sought to address this problem, the use of a machine learning algorithm that best utilizes these features is becomes foremost. In this effort, a comparison of a standard shallow and a deep learning approach are explored. Experiments provide insights into classifier architecture, training procedure, and performance.

Thermal Engineering Issues in Hydrogen Storage for Mobile and Portable Applications

DTIC Science & Technology

2010-09-01

hydride beds Effective thermal conductivity measurement cell ::.·: .·:.·.·.·.·.·.·.·.·.·.·.·.·.·.·.·.·.·.·:. Insulation ...generally classified as micropores (< 2 nm), mesopores (between 2 and 50 nm), and macropores (> 50 nm). •Above critical point, adsorption takes place in... micropores only and the density of adsorbed phase (in micropores ) is much greater than that of unadsorbed gaseous phase (in macropores and slit volumes

MOLECULAR CLASSIFICATION OF OUTCOMES FROM DENGUE VIRUS -3 INFECTIONS

PubMed Central

Brasier, Allan R.; Zhao, Yingxin; Wiktorowicz, John E.; Spratt, Heidi M.; Nascimento, Eduardo J. M.; Cordeiro, Marli T.; Soman, Kizhake V.; Ju, Hyunsu; Recinos, Adrian; Stafford, Susan; Wu, Zheng; Marques, Ernesto T.A.; Vasilakis, Nikos

2015-01-01

Objectives Dengue virus (DENV) infection is a significant risk to over a third of the human population that causes a wide spectrum of illness, ranging from sub-clinical disease to intermediate syndrome of vascular complications called Dengue Fever Complicated (DFC) and severe, dengue hemorrhagic fever (DHF). Methods for discriminating outcomes will impact clinical trials and understanding disease pathophysiology. Study Design We integrated a proteomics discovery pipeline with a heuristics to develop a molecular classifier to identify an intermediate phenotype of DENV-3 infectious outcome. Results 121 differentially expressed proteins were identified in plasma from DHF vs dengue fever (DF), and informative candidates were selected using nonparametric statistics. These were combined with markers that measure complement activation, acute phase response, cellular leak, granulocyte differentiation and viral load. From this, we applied quantitative proteomics to select a 15 member panel of proteins that accurately predicted DF, DHF, and DFC using a Random Forest Classifier. The classifier primarily relied on acute phase (A2M), complement (CFD), platelet counts and cellular leak (TPM4) to produce an 86% accuracy of prediction with an area under the receiver operating curve of >0.9 for DHF and DFC vs DF. Conclusions Integrating discovery and heuristic approaches to sample distinct pathophysiological processes is a powerful approach in infectious disease. Early detection of intermediate outcomes of DENV-3 will speed clinical trials evaluating vaccines or drug interventions. PMID:25728087

Molecular classification of outcomes from dengue virus -3 infections.

PubMed

Brasier, Allan R; Zhao, Yingxin; Wiktorowicz, John E; Spratt, Heidi M; Nascimento, Eduardo J M; Cordeiro, Marli T; Soman, Kizhake V; Ju, Hyunsu; Recinos, Adrian; Stafford, Susan; Wu, Zheng; Marques, Ernesto T A; Vasilakis, Nikos

2015-03-01

Dengue virus (DENV) infection is a significant risk to over a third of the human population that causes a wide spectrum of illness, ranging from sub-clinical disease to intermediate syndrome of vascular complications called dengue fever complicated (DFC) and severe, dengue hemorrhagic fever (DHF). Methods for discriminating outcomes will impact clinical trials and understanding disease pathophysiology. We integrated a proteomics discovery pipeline with a heuristics approach to develop a molecular classifier to identify an intermediate phenotype of DENV-3 infectious outcome. 121 differentially expressed proteins were identified in plasma from DHF vs dengue fever (DF), and informative candidates were selected using nonparametric statistics. These were combined with markers that measure complement activation, acute phase response, cellular leak, granulocyte differentiation and viral load. From this, we applied quantitative proteomics to select a 15 member panel of proteins that accurately predicted DF, DHF, and DFC using a random forest classifier. The classifier primarily relied on acute phase (A2M), complement (CFD), platelet counts and cellular leak (TPM4) to produce an 86% accuracy of prediction with an area under the receiver operating curve of >0.9 for DHF and DFC vs DF. Integrating discovery and heuristic approaches to sample distinct pathophysiological processes is a powerful approach in infectious disease. Early detection of intermediate outcomes of DENV-3 will speed clinical trials evaluating vaccines or drug interventions. Copyright © 2015 Elsevier B.V. All rights reserved.

Least Squares Neural Network-Based Wireless E-Nose System Using an SnO₂ Sensor Array.

PubMed

Shahid, Areej; Choi, Jong-Hyeok; Rana, Abu Ul Hassan Sarwar; Kim, Hyun-Seok

2018-05-06

Over the last few decades, the development of the electronic nose (E-nose) for detection and quantification of dangerous and odorless gases, such as methane (CH₄) and carbon monoxide (CO), using an array of SnO₂ gas sensors has attracted considerable attention. This paper addresses sensor cross sensitivity by developing a classifier and estimator using an artificial neural network (ANN) and least squares regression (LSR), respectively. Initially, the ANN was implemented using a feedforward pattern recognition algorithm to learn the collective behavior of an array as the signature of a particular gas. In the second phase, the classified gas was quantified by minimizing the mean square error using LSR. The combined approach produced 98.7% recognition probability, with 95.5 and 94.4% estimated gas concentration accuracies for CH₄ and CO, respectively. The classifier and estimator parameters were deployed in a remote microcontroller for the actualization of a wireless E-nose system.

Bayes classification of terrain cover using normalized polarimetric data

NASA Technical Reports Server (NTRS)

Yueh, H. A.; Swartz, A. A.; Kong, J. A.; Shin, R. T.; Novak, L. M.

1988-01-01

The normalized polarimetric classifier (NPC) which uses only the relative magnitudes and phases of the polarimetric data is proposed for discrimination of terrain elements. The probability density functions (PDFs) of polarimetric data are assumed to have a complex Gaussian distribution, and the marginal PDF of the normalized polarimetric data is derived by adopting the Euclidean norm as the normalization function. The general form of the distance measure for the NPC is also obtained. It is demonstrated that for polarimetric data with an arbitrary PDF, the distance measure of NPC will be independent of the normalization function selected even when the classifier is mistrained. A complex Gaussian distribution is assumed for the polarimetric data consisting of grass and tree regions. The probability of error for the NPC is compared with those of several other single-feature classifiers. The classification error of NPCs is shown to be independent of the normalization function.

A Classroom Learning Cycle: Using Diagrams to Classify Matter.

ERIC Educational Resources Information Center

James, Helen J.; Nelson, Samuel L.

1981-01-01

A learning cycle involves the active participation of students in exploration, invention, and application phases. Describes one such learning cycle dealing with classification of matter and designed to provide students with an understanding of the terms: atom, molecule, element, compound, solution, and heterogeneous matter. (Author/JN)

REQUIREMENTS FOR GRAPHIC TEACHING MACHINES.

ERIC Educational Resources Information Center

HICKEY, ALBERT; AND OTHERS

AN EXPERIMENT WAS REPORTED WHICH DEMONSTRATES THAT GRAPHICS ARE MORE EFFECTIVE THAN SYMBOLS IN ACQUIRING ALGEBRA CONCEPTS. THE SECOND PHASE OF THE STUDY DEMONSTRATED THAT GRAPHICS IN HIGH SCHOOL TEXTBOOKS WERE RELIABLY CLASSIFIED IN A MATRIX OF 480 FUNCTIONAL STIMULUS-RESPONSE CATEGORIES. SUGGESTIONS WERE MADE FOR EXTENDING THE CLASSIFICATION…

Analysis of Fluvial Bed Sediments Along the Apalachicola River, Florida through Field Reconnaissance Studies

NASA Astrophysics Data System (ADS)

Passeri, D.; Hagen, S. C.; Daranpob, A.; Smar, D. E.

2011-12-01

River competence is an important parameter in understanding sediment transport in fluvial systems. Competence is defined as the measure of a stream's ability to transport a certain maximum grain size of sediment. Studies have shown that bed sediment particle size in rivers and streams tends to vary spatially along the direction of stream flow. Over a river section several reaches long, variability of sediment particle sizes can be seen, often becoming finer downstream. This phenomenon is attributed to mechanisms such as local control of stream gradient, coarse tributary sediment supply or particle breakdown. Average particle size may also be smaller in tributary sections of rivers due to river morphology. The relationship between river mean velocity and particle size that can be transported has also been explored. The Hjulstrom curve classifies this relationship by relating particle size to velocity, dividing the regions of sedimentation, transportation, and erosion. The curve can also be used to find values such as the critical erosion velocity (the velocity required to transport particles of various sizes in suspension) and settling velocity (the velocity at which particles of a given size become too heavy to be transported and fall out of suspension, consequently causing deposition). The purpose of this research is to explore the principles of river competence through field reconnaissance collection and laboratory analysis of fluvial sediment core samples along the Apalachicola River, FL and its distributaries. Sediment core samples were collected in the wetlands and estuarine regions of the Apalachicola River. Sieve and hydrometer analyses were performed to determine the spatial distribution of particle sizes along the river. An existing high resolution hydrodynamic model of the study domain was used to simulate tides and generate river velocities. The Hjulstrom curve and the generated river velocities were used to define whether sediment was being transported, eroded or deposited at the different locations in the river and its distributaries. Parameters such as critical erosion velocity and settling velocity were also calculated to describe sediment transport along the channel. This research provides a better understanding of the fluvial geomorphic system, particularly sediment transport in channels. It also provides excellent validation data for future sediment transport studies in similar fluvial study domains.

Simulation of a Multidimensional Input Quantum Perceptron

NASA Astrophysics Data System (ADS)

Yamamoto, Alexandre Y.; Sundqvist, Kyle M.; Li, Peng; Harris, H. Rusty

2018-06-01

In this work, we demonstrate the improved data separation capabilities of the Multidimensional Input Quantum Perceptron (MDIQP), a fundamental cell for the construction of more complex Quantum Artificial Neural Networks (QANNs). This is done by using input controlled alterations of ancillary qubits in combination with phase estimation and learning algorithms. The MDIQP is capable of processing quantum information and classifying multidimensional data that may not be linearly separable, extending the capabilities of the classical perceptron. With this powerful component, we get much closer to the achievement of a feedforward multilayer QANN, which would be able to represent and classify arbitrary sets of data (both quantum and classical).

Automated high resolution full-field spatial coherence tomography for quantitative phase imaging of human red blood cells

NASA Astrophysics Data System (ADS)

Singla, Neeru; Dubey, Kavita; Srivastava, Vishal; Ahmad, Azeem; Mehta, D. S.

2018-02-01

We developed an automated high-resolution full-field spatial coherence tomography (FF-SCT) microscope for quantitative phase imaging that is based on the spatial, rather than the temporal, coherence gating. The Red and Green color laser light was used for finding the quantitative phase images of unstained human red blood cells (RBCs). This study uses morphological parameters of unstained RBCs phase images to distinguish between normal and infected cells. We recorded the single interferogram by a FF-SCT microscope for red and green color wavelength and average the two phase images to further reduced the noise artifacts. In order to characterize anemia infected from normal cells different morphological features were extracted and these features were used to train machine learning ensemble model to classify RBCs with high accuracy.

Epileptic seizure detection from EEG signals with phase-amplitude cross-frequency coupling and support vector machine

NASA Astrophysics Data System (ADS)

Liu, Yang; Wang, Jiang; Cai, Lihui; Chen, Yingyuan; Qin, Yingmei

2018-03-01

As a pattern of cross-frequency coupling (CFC), phase-amplitude coupling (PAC) depicts the interaction between the phase and amplitude of distinct frequency bands from the same signal, and has been proved to be closely related to the brain’s cognitive and memory activities. This work utilized PAC and support vector machine (SVM) classifier to identify the epileptic seizures from electroencephalogram (EEG) data. The entropy-based modulation index (MI) matrixes are used to express the strength of PAC, from which we extracted features as the input for classifier. Based on the Bonn database, which contains five datasets of EEG segments obtained from healthy volunteers and epileptic subjects, a 100% classification accuracy is achieved for identifying seizure ictal from healthy data, and an accuracy of 97.67% is reached in the classification of ictal EEG signals from inter-ictal EEGs. Based on the CHB-MIT database which is a group of continuously recorded epileptic EEGs by scalp electrodes, a 97.50% classification accuracy is obtained and a raising sign of MI value is found at 6s before seizure onset. The classification performance in this work is effective, and PAC can be considered as a useful tool for detecting and predicting the epileptic seizures and providing reference for clinical diagnosis.

A Novel Multi-Class Ensemble Model for Classifying Imbalanced Biomedical Datasets

NASA Astrophysics Data System (ADS)

Bikku, Thulasi; Sambasiva Rao, N., Dr; Rao, Akepogu Ananda, Dr

2017-08-01

This paper mainly focuseson developing aHadoop based framework for feature selection and classification models to classify high dimensionality data in heterogeneous biomedical databases. Wide research has been performing in the fields of Machine learning, Big data and Data mining for identifying patterns. The main challenge is extracting useful features generated from diverse biological systems. The proposed model can be used for predicting diseases in various applications and identifying the features relevant to particular diseases. There is an exponential growth of biomedical repositories such as PubMed and Medline, an accurate predictive model is essential for knowledge discovery in Hadoop environment. Extracting key features from unstructured documents often lead to uncertain results due to outliers and missing values. In this paper, we proposed a two phase map-reduce framework with text preprocessor and classification model. In the first phase, mapper based preprocessing method was designed to eliminate irrelevant features, missing values and outliers from the biomedical data. In the second phase, a Map-Reduce based multi-class ensemble decision tree model was designed and implemented in the preprocessed mapper data to improve the true positive rate and computational time. The experimental results on the complex biomedical datasets show that the performance of our proposed Hadoop based multi-class ensemble model significantly outperforms state-of-the-art baselines.

Pretest probability of a normal echocardiography: validation of a simple and practical algorithm for routine use.

PubMed

Hammoudi, Nadjib; Duprey, Matthieu; Régnier, Philippe; Achkar, Marc; Boubrit, Lila; Preud'homme, Gisèle; Healy-Brucker, Aude; Vignalou, Jean-Baptiste; Pousset, Françoise; Komajda, Michel; Isnard, Richard

2014-02-01

Management of increased referrals for transthoracic echocardiography (TTE) examinations is a challenge. Patients with normal TTE examinations take less time to explore than those with heart abnormalities. A reliable method for assessing pretest probability of a normal TTE may optimize management of requests. To establish and validate, based on requests for examinations, a simple algorithm for defining pretest probability of a normal TTE. In a retrospective phase, factors associated with normality were investigated and an algorithm was designed. In a prospective phase, patients were classified in accordance with the algorithm as being at high or low probability of having a normal TTE. In the retrospective phase, 42% of 618 examinations were normal. In multivariable analysis, age and absence of cardiac history were associated to normality. Low pretest probability of normal TTE was defined by known cardiac history or, in case of doubt about cardiac history, by age>70 years. In the prospective phase, the prevalences of normality were 72% and 25% in high (n=167) and low (n=241) pretest probability of normality groups, respectively. The mean duration of normal examinations was significantly shorter than abnormal examinations (13.8 ± 9.2 min vs 17.6 ± 11.1 min; P=0.0003). A simple algorithm can classify patients referred for TTE as being at high or low pretest probability of having a normal examination. This algorithm might help to optimize management of requests in routine practice. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

29 CFR Appendix A to Part 510 - Manufacturing Industries Eligible for Minimum Wage Phase-In

Code of Federal Regulations, 2010 CFR

2010-07-01

.... 286 1 Industrial organic chemicals. 2865 1 Cyclic organic crudes and intermediates, and organic dyes and pigments. 2869 a Industrial organic chemicals, not elsewhere classified. 287 1 Agricultural chemicals. 2873 1 Nitrogenous fertilizers. 2879 1 Pesticides and agricultural chemicals, not elsewhere...

28 CFR 42.303 - Evaluation of employment opportunities.

Code of Federal Regulations, 2014 CFR

2014-07-01

...'s employment phases (e.g., recruitment, selection, and promotion) and the evaluation of employment... recruitment and selection of entrance candidates and selection of candidates for promotion. (c) In making the... requirements of this section should be cross classified by sex to ascertain the extent to which minority women...

28 CFR 42.303 - Evaluation of employment opportunities.

Code of Federal Regulations, 2012 CFR

2012-07-01

...'s employment phases (e.g., recruitment, selection, and promotion) and the evaluation of employment... recruitment and selection of entrance candidates and selection of candidates for promotion. (c) In making the... requirements of this section should be cross classified by sex to ascertain the extent to which minority women...

28 CFR 42.303 - Evaluation of employment opportunities.

Code of Federal Regulations, 2013 CFR

2013-07-01

...'s employment phases (e.g., recruitment, selection, and promotion) and the evaluation of employment... recruitment and selection of entrance candidates and selection of candidates for promotion. (c) In making the... requirements of this section should be cross classified by sex to ascertain the extent to which minority women...

Sociocultural Beliefs Related to Sex among Mexican American Adolescents.

ERIC Educational Resources Information Center

Flores, Elena; Millstein, Susan G.; Eyre, Stephen L.

1998-01-01

In a two-phase study, Mexican American male and female adolescents listed positive and negative elements related to preferred partner qualities and engaging in sexual activity; then other Mexican American adolescents classified the items. Results suggest that adolescents' partner preferences and reasons to have sex reflected Mexican American…

To Prevent Harm.

ERIC Educational Resources Information Center

Insurance Inst. for Highway Safety, Washington, DC.

Since 1969 the Insurance Institute of Highway Safety has concentrated on researching, demonstrating, and communicating to the public methods of reducing highway losses. The Institute has established a framework to classify the nature of each kind of loss (human, vehicle and equipment, and environment) in relation to the three phases of the crash…

A Systematic Review of Part C Early Identification Studies

ERIC Educational Resources Information Center

Barger, Brian; Rice, Catherine; Simmons, Christina Anne; Wolf, Rebecca

2018-01-01

Authors conducted a systematic literature review on early identification steps leading at-risk young children to connect with Part C services. Authors classified data collection settings as primary (settings for general population) or specialized (settings for children at risk of developmental delay) and according to the phases of early…

Estimation of nutrients and organic matter in Korean swine slurry using multiple regression analysis of physical and chemical properties.

PubMed

Suresh, Arumuganainar; Choi, Hong Lim

2011-10-01

Swine waste land application has increased due to organic fertilization, but excess application in an arable system can cause environmental risk. Therefore, in situ characterizations of such resources are important prior to application. To explore this, 41 swine slurry samples were collected from Korea, and wide differences were observed in the physico-biochemical properties. However, significant (P<0.001) multiple property correlations (R²) were obtained between nutrients with specific gravity (SG), electrical conductivity (EC), total solids (TS) and pH. The different combinations of hydrometer, EC meter, drying oven and pH meter were found useful to estimate Mn, Fe, Ca, K, Al, Na, N and 5-day biochemical oxygen demands (BOD₅) at improved R² values of 0.83, 0.82, 0.77, 0.75, 0.67, 0.47, 0.88 and 0.70, respectively. The results from this study suggest that multiple property regressions can facilitate the prediction of micronutrients and organic matter much better than a single property regression for livestock waste. Copyright © 2011 Elsevier Ltd. All rights reserved.

Analysis of the Water Resources on Baseflow River Basin in Jeju Island, Korea

NASA Astrophysics Data System (ADS)

Yang, S.-K.; Jung, W.-Y.; Kang, M.-S.

2012-04-01

Jeju Island is a volcanic island located at the southernmost of Korea, and is the heaviest raining area in Korea, but due to its hydrological / geological characteristics different from those of inland areas, most streams are of the dry form, and it relies on groundwater for water resources. As for some streams, however, springwater is discharged at a point near the downstream of the final discharge to maintain the flow of the stream; this has been developed as the source for water supply since the past, but the studies on detail observations and analysis are yet inadequate. This study utilizes the ADCP (Acoustic Doppler Current Profiler) hydrometer to regularly observe the flow amount of base run-off stream, and the water resources of base discharge basin of Jeju Island were analyzed using the SWAT (Soil & Water Assessment Tool) model. The detail water resource analysis study using modeling and site observation with high precision for Jeju Island water resources is expected to become the foundation for efficient usage and security of water resources against future climate changes.

Orbit and sampling requirements: TRMM experience

NASA Technical Reports Server (NTRS)

North, Gerald

1993-01-01

The Tropical Rainfall Measuring Mission (TRMM) concept originated in 1984. Its overall goal is to produce datasets that can be used in the improvement of general circulation models. A primary objective is a multi-year data stream of monthly averages of rain rate over 500 km boxes over the tropical oceans. Vertical distributions of the hydrometers, related to latent heat profiles, and the diurnal cycle of rainrates are secondary products believed to be accessible. The mission is sponsored jointly by the U.S. and Japan. TRMM is an approved mission with launch set for 1997. There are many retrieval and ground truth issues still being studied for TRMM, but here we concentrate on sampling since it is the single largest term in the error budget. The TRMM orbit plane is inclined by 35 degrees to the equator, which leads to a precession of the visits to a given grid box through the local hours of the day, requiring three to six weeks to complete the diurnal cycle, depending on latitude. For sampling studies we can consider the swath width to be about 700 km.

Permeability and compressibility of resedimented Gulf of Mexico mudrock

NASA Astrophysics Data System (ADS)

Betts, W. S.; Flemings, P. B.; Schneider, J.

2011-12-01

We use a constant-rate-of strain consolidation test on resedimented Gulf of Mexico mudrock to determine the compression index (Cc) to be 0.618 and the expansion index (Ce) to be 0.083. We used crushed, homogenized Pliocene and Pleistocene mudrock extracted from cored wells in the Eugene Island block 330 oil field. This powdered material has a liquid limit (LL) of 87, a plastic limit (PL) of 24, and a plasticity index (PI) of 63. The particle size distribution from hydrometer analyses is approximately 65% clay-sized particles (<2 μm) with the remainder being less than 70 microns in diameter. Resedimented specimens have been used to characterize the geotechnical and geophysical behavior of soils and mudstones independent of the variability of natural samples and without the effects of sampling disturbance. Previous investigations of resedimented offshore Gulf of Mexico sediments (e.g. Mazzei, 2008) have been limited in scope. This is the first test of the homogenized Eugene Island core material. These results will be compared to in situ measurements to determine the controls on consolidation over large stress ranges.

DNA unzipping phase diagram calculated via replica theory.

PubMed

Roland, C Brian; Hatch, Kristi Adamson; Prentiss, Mara; Shakhnovich, Eugene I

2009-05-01

We show how single-molecule unzipping experiments can provide strong evidence that the zero-force melting transition of long molecules of natural dsDNA should be classified as a phase transition of the higher-order type (continuous). Toward this end, we study a statistical-mechanics model for the fluctuating structure of a long molecule of dsDNA, and compute the equilibrium phase diagram for the experiment in which the molecule is unzipped under applied force. We consider a perfect-matching dsDNA model, in which the loops are volume-excluding chains with arbitrary loop exponent c . We include stacking interactions, hydrogen bonds, and main-chain entropy. We include sequence heterogeneity at the level of random sequences; in particular, there is no correlation in the base-pairing (bp) energy from one sequence position to the next. We present heuristic arguments to demonstrate that the low-temperature macrostate does not exhibit degenerate ergodicity breaking. We use this claim to understand the results of our replica-theoretic calculation of the equilibrium properties of the system. As a function of temperature, we obtain the minimal force at which the molecule separates completely. This critical-force curve is a line in the temperature-force phase diagram that marks the regions where the molecule exists primarily as a double helix versus the region where the molecule exists as two separate strands. We compare our random-sequence model to magnetic tweezer experiments performed on the 48 502 bp genome of bacteriophage lambda . We find good agreement with the experimental data, which is restricted to temperatures between 24 and 50 degrees C . At higher temperatures, the critical-force curve of our random-sequence model is very different for that of the homogeneous-sequence version of our model. For both sequence models, the critical force falls to zero at the melting temperature T_{c} like |T-T_{c}|;{alpha} . For the homogeneous-sequence model, alpha=1/2 almost exactly, while for the random-sequence model, alpha approximately 0.9 . Importantly, the shape of the critical-force curve is connected, via our theory, to the manner in which the helix fraction falls to zero at T_{c} . The helix fraction is the property that is used to classify the melting transition as a type of phase transition. In our calculation, the shape of the critical-force curve holds strong evidence that the zero-force melting transition of long natural dsDNA should be classified as a higher-order (continuous) phase transition. Specifically, the order is 3rd or greater.

Effects of mid-foot contact area ratio on lower body kinetics/kinematics in sagittal plane during stair descent in women.

PubMed

Lee, Jinkyu; Hong, Yoon No Gregory; Shin, Choongsoo S

2016-07-01

The mid-foot contact area relative to the total foot contact area can facilitate foot arch structure evaluation. A stair descent motion consistently provides initial fore-foot contact and utilizes the foot arch more actively for energy absorption. The purpose of this study was to compare ankle and knee joint angle, moment, and work in sagittal plane during stair descending between low and high Mid-Foot-Contact-Area (MFCA) ratio group. The twenty-two female subjects were tested and classified into two groups (high MFCA and low MFCA) using their static MFCA ratios. The ground reaction force (GRF) and kinematics of ankle and knee joints were measured while stair descending. During the period between initial contact and the first peak in vertical GRF (early absorption phase), ankle negative work for the low MFCA ratio group was 33% higher than that for the high MFCA ratio group (p<0.05). However, ankle negative work was not significantly different between the two groups during the period between initial contact and peak dorsiflexion angle (early absorption phase+late absorption phase). The peak ankle dorsiflexion angle was smaller in the low MFCA ratio group (p<0.05). Our results suggest that strategy of energy absorption at the ankle and foot differs depending upon foot arch types classified by MFCA. The low MFCA ratio group seemed to absorb more impact energy using strain in the planar fascia during early absorption phase, whereas the high MFCA ratio group absorbed more impact energy using increased dorsiflexion during late absorption phase. Copyright © 2016 Elsevier B.V. All rights reserved.

Movement coordination patterns between the foot joints during walking.

PubMed

Arnold, John B; Caravaggi, Paolo; Fraysse, François; Thewlis, Dominic; Leardini, Alberto

2017-01-01

In 3D gait analysis, kinematics of the foot joints are usually reported via isolated time histories of joint rotations and no information is provided on the relationship between rotations at different joints. The aim of this study was to identify movement coordination patterns in the foot during walking by expanding an existing vector coding technique according to an established multi-segment foot and ankle model. A graphical representation is also described to summarise the coordination patterns of joint rotations across multiple patients. Three-dimensional multi-segment foot kinematics were recorded in 13 adults during walking. A modified vector coding technique was used to identify coordination patterns between foot joints involving calcaneus, midfoot, metatarsus and hallux segments. According to the type and direction of joints rotations, these were classified as in-phase (same direction), anti-phase (opposite directions), proximal or distal joint dominant. In early stance, 51 to 75% of walking trials showed proximal-phase coordination between foot joints comprising the calcaneus, midfoot and metatarsus. In-phase coordination was more prominent in late stance, reflecting synergy in the simultaneous inversion occurring at multiple foot joints. Conversely, a distal-phase coordination pattern was identified for sagittal plane motion of the ankle relative to the midtarsal joint, highlighting the critical role of arch shortening to locomotor function in push-off. This study has identified coordination patterns between movement of the calcaneus, midfoot, metatarsus and hallux by expanding an existing vector cording technique for assessing and classifying coordination patterns of foot joints rotations during walking. This approach provides a different perspective in the analysis of multi-segment foot kinematics, and may be used for the objective quantification of the alterations in foot joint coordination patterns due to lower limb pathologies or following injuries.

Investigation of gastric cancers in nude mice using X-ray in-line phase contrast imaging.

PubMed

Tao, Qiang; Luo, Shuqian

2014-07-24

This paper is to report the new imaging of gastric cancers without the use of imaging agents. Both gastric normal regions and gastric cancer regions can be distinguished by using the principal component analysis (PCA) based on the gray level co-occurrence matrix (GLCM). Human gastric cancer BGC823 cells were implanted into the stomachs of nude mice. Then, 3, 5, 7, 9 or 11 days after cancer cells implantation, the nude mice were sacrificed and their stomachs were removed. X-ray in-line phase contrast imaging (XILPCI), an X-ray phase contrast imaging method, has greater soft tissue contrast than traditional absorption radiography and generates higher-resolution images. The gastric specimens were imaged by an XILPCIs' charge coupled device (CCD) of 9 μm image resolution. The PCA of the projective images' region of interests (ROIs) based on GLCM were extracted to discriminate gastric normal regions and gastric cancer regions. Different stages of gastric cancers were classified by using support vector machines (SVMs). The X-ray in-line phase contrast images of nude mice gastric specimens clearly show the gastric architectures and the details of the early gastric cancers. The phase contrast computed tomography (CT) images of nude mice gastric cancer specimens are better than the traditional absorption CT images without the use of imaging agents. The results of the PCA of the texture parameters based on GLCM of normal regions is (F1+F2) >8.5, but those of cancer regions is (F1+F2) <8.5. The classification accuracy is 83.3% that classifying gastric specimens into different stages using SVMs. This is a very preliminary feasibility study. With further researches, XILPCI could become a noninvasive method for future the early detection of gastric cancers or medical researches.

Enriched classification of parafermionic gapped phases with time-reversal symmetry

NASA Astrophysics Data System (ADS)

Xu, Wen-Tao; Zhang, Guang-Ming

2018-03-01

Based on the recently established parafermionic matrix product states, we study the classification of one-dimensional gapped phases of parafermions with time-reversal (TR) symmetry satisfying T2=1 . Without extra symmetry, it has been found that Zp parafermionic gapped phases can be classified as topological phases, spontaneous symmetry breaking (SSB) phases, and a trivial phase, which are uniquely labeled by the divisors n of p . In the presence of TR symmetry, however, the enriched classification is characterized by three indices n , κ , and μ , where κ ∈Z2 denotes the linear or projective TR actions on the edges, and μ ∈Z2 indicates the commutation relations between the TR and (fractionalized) charge operator. For the Zr-symmetric parafermionic ground states, where r =p for trivial or topological phases, and r =p /n for SSB phases, each original gapped phase with odd r is divided into two phases, while each phase with even r is further separated into four phases. The gapped parafermionic phases with the TR symmetry include the symmetry protected topological phases, symmetry enriched topological phases, and the SSB coexisting symmetry protected topological phases. From analyzing the structures and symmetries of their reduced density matrices of these resulting topological phases, we can obtain the topologically protected degeneracies of their entanglement spectra.

Online and unsupervised face recognition for continuous video stream

NASA Astrophysics Data System (ADS)

Huo, Hongwen; Feng, Jufu

2009-10-01

We present a novel online face recognition approach for video stream in this paper. Our method includes two stages: pre-training and online training. In the pre-training phase, our method observes interactions, collects batches of input data, and attempts to estimate their distributions (Box-Cox transformation is adopted here to normalize rough estimates). In the online training phase, our method incrementally improves classifiers' knowledge of the face space and updates it continuously with incremental eigenspace analysis. The performance achieved by our method shows its great potential in video stream processing.

Resource quality of a symmetry-protected topologically ordered phase for quantum computation.

PubMed

Miller, Jacob; Miyake, Akimasa

2015-03-27

We investigate entanglement naturally present in the 1D topologically ordered phase protected with the on-site symmetry group of an octahedron as a potential resource for teleportation-based quantum computation. We show that, as long as certain characteristic lengths are finite, all its ground states have the capability to implement any unit-fidelity one-qubit gate operation asymptotically as a key computational building block. This feature is intrinsic to the entire phase, in that perfect gate fidelity coincides with perfect string order parameters under a state-insensitive renormalization procedure. Our approach may pave the way toward a novel program to classify quantum many-body systems based on their operational use for quantum information processing.

Resource Quality of a Symmetry-Protected Topologically Ordered Phase for Quantum Computation

NASA Astrophysics Data System (ADS)

Miller, Jacob; Miyake, Akimasa

2015-03-01

We investigate entanglement naturally present in the 1D topologically ordered phase protected with the on-site symmetry group of an octahedron as a potential resource for teleportation-based quantum computation. We show that, as long as certain characteristic lengths are finite, all its ground states have the capability to implement any unit-fidelity one-qubit gate operation asymptotically as a key computational building block. This feature is intrinsic to the entire phase, in that perfect gate fidelity coincides with perfect string order parameters under a state-insensitive renormalization procedure. Our approach may pave the way toward a novel program to classify quantum many-body systems based on their operational use for quantum information processing.

Phase analysis of Košice meteorite: Preliminary results

NASA Astrophysics Data System (ADS)

Sitek, J.; Dekan, J.; Degmová, J.; Sedlačková, K.

2012-10-01

Meteorite fall was observed by the Košice town in Slovakia in February 2010 and it was classified as an ordinary chondrite H5. The samples were prepared in powder form scratched from the surface. Mossbauer spectra were measured at room temperature and liquid nitrogen temperature. Spectra consist of components related to iron-bearing phases with different content. Non-magnetic part was fitted with three quadrupole doublets. According to its parameters, we identified olivine, pyroxene, and traces of Fe3+ phases. Magnetic part consists of an iron-rich Fe-Ni alloy with hyperfine magnetic field similar to kamacite α-Fe(Ni,Co) and troilite. Main elements were also determined by X-ray fluorescence spectroscopy.

Study of Plasma Energization during Magnetic Reconnection in the FLARE (Facility for Laboratory Reconnection Experiments)

NASA Astrophysics Data System (ADS)

Ji, H.; Bhattacharjee, A.; Prager, S.; Daughton, W.; Bale, S.; Carter, T.; Crocker, N.; Drake, J.; Egedal, J.; Sarff, J.; Wallace, J.; Chen, Y.; Cutler, R.; Fox, W.; Heitzenroeder, P.; Kalish, M.; Jara-Almonte, J.; Myers, C.; Ren, Y.; Yamada, M.; Yoo, J.

2015-11-01

Various regimes or ``phases'' are identified in a magnetic reconnection ``phase diagram'' which classifies different coupling mechanisms from the global system scales to the local dissipation scales. The FLARE device (http://flare.pppl.gov) is a new intermediate-scale plasma experiment under construction at Princeton to provide access to all of these phases directly relevant to space, solar, astrophysical, and fusion plasmas. Study of plasma energization during magnetic reconnection is one of major topics for the FLARE facility, which is planned to be a user facility. The motivating major physics questions regarding plasma energization and the planned collaborative research on these topics will be presented and discussed. Supported by NSF.

Initial signatures of magnetic field and energetic particle fluxes at tail reconfiguration - Explosive growth phase

NASA Technical Reports Server (NTRS)

Ohtani, S.; Takahashi, K.; Zanetti, L. J.; Potemra, T. A.; Mcentire, R. W.; Iijima, T.

1992-01-01

The initial signatures of tail field reconfiguration observed in the near-earth magnetotail are examined using data obtained by the AMPTE/CCE magnetometer and the Medium Energy Particle Analyzer. It is found that the tail reconfiguration events could be classified as belonging to two types, Type I and Type II. In Type I events, a current disruption is immersed in a hot plasma region expanding from inward (earthward/equatorward) of the spacecraft; consequently, the spacecraft is immersed in a hot plasma region expanding from inward. The Type II reconfiguration event is characterized by a distinctive interval (explosive growth phase) just prior to the local commencement of tail phase.

Safety effects of exclusive and concurrent signal phasing for pedestrian crossing.

PubMed

Zhang, Yaohua; Mamun, Sha A; Ivan, John N; Ravishanker, Nalini; Haque, Khademul

2015-10-01

This paper describes the estimation of pedestrian crash count and vehicle interaction severity prediction models for a sample of signalized intersections in Connecticut with either concurrent or exclusive pedestrian phasing. With concurrent phasing, pedestrians cross at the same time as motor vehicle traffic in the same direction receives a green phase, while with exclusive phasing, pedestrians cross during their own phase when all motor vehicle traffic on all approaches is stopped. Pedestrians crossing at each intersection were observed and classified according to the severity of interactions with motor vehicles. Observation intersections were selected to represent both types of signal phasing while controlling for other physical characteristics. In the nonlinear mixed models for interaction severity, pedestrians crossing on the walk signal at an exclusive signal experienced lower interaction severity compared to those crossing on the green light with concurrent phasing; however, pedestrians crossing on a green light where an exclusive phase was available experienced higher interaction severity. Intersections with concurrent phasing have fewer total pedestrian crashes than those with exclusive phasing but more crashes at higher severity levels. It is recommended that exclusive pedestrian phasing only be used at locations where pedestrians are more likely to comply. Copyright © 2015. Published by Elsevier Ltd.

Determination of Minimum Training Sample Size for Microarray-Based Cancer Outcome Prediction–An Empirical Assessment

PubMed Central

Cheng, Ningtao; Wu, Leihong; Cheng, Yiyu

2013-01-01

The promise of microarray technology in providing prediction classifiers for cancer outcome estimation has been confirmed by a number of demonstrable successes. However, the reliability of prediction results relies heavily on the accuracy of statistical parameters involved in classifiers. It cannot be reliably estimated with only a small number of training samples. Therefore, it is of vital importance to determine the minimum number of training samples and to ensure the clinical value of microarrays in cancer outcome prediction. We evaluated the impact of training sample size on model performance extensively based on 3 large-scale cancer microarray datasets provided by the second phase of MicroArray Quality Control project (MAQC-II). An SSNR-based (scale of signal-to-noise ratio) protocol was proposed in this study for minimum training sample size determination. External validation results based on another 3 cancer datasets confirmed that the SSNR-based approach could not only determine the minimum number of training samples efficiently, but also provide a valuable strategy for estimating the underlying performance of classifiers in advance. Once translated into clinical routine applications, the SSNR-based protocol would provide great convenience in microarray-based cancer outcome prediction in improving classifier reliability. PMID:23861920

Point Clouds to Indoor/outdoor Accessibility Diagnosis

NASA Astrophysics Data System (ADS)

Balado, J.; Díaz-Vilariño, L.; Arias, P.; Garrido, I.

2017-09-01

This work presents an approach to automatically detect structural floor elements such as steps or ramps in the immediate environment of buildings, elements that may affect the accessibility to buildings. The methodology is based on Mobile Laser Scanner (MLS) point cloud and trajectory information. First, the street is segmented in stretches along the trajectory of the MLS to work in regular spaces. Next, the lower region of each stretch (the ground zone) is selected as the ROI and normal, curvature and tilt are calculated for each point. With this information, points in the ROI are classified in horizontal, inclined or vertical. Points are refined and grouped in structural elements using raster process and connected components in different phases for each type of previously classified points. At last, the trajectory data is used to distinguish between road and sidewalks. Adjacency information is used to classify structural elements in steps, ramps, curbs and curb-ramps. The methodology is tested in a real case study, consisting of 100 m of an urban street. Ground elements are correctly classified in an acceptable computation time. Steps and ramps also are exported to GIS software to enrich building models from Open Street Map with information about accessible/inaccessible entrances and their locations.

Cellular-automata-based learning network for pattern recognition

NASA Astrophysics Data System (ADS)

Tzionas, Panagiotis G.; Tsalides, Phillippos G.; Thanailakis, Adonios

1991-11-01

Most classification techniques either adopt an approach based directly on the statistical characteristics of the pattern classes involved, or they transform the patterns in a feature space and try to separate the point clusters in this space. An alternative approach based on memory networks has been presented, its novelty being that it can be implemented in parallel and it utilizes direct features of the patterns rather than statistical characteristics. This study presents a new approach for pattern classification using pseudo 2-D binary cellular automata (CA). This approach resembles the memory network classifier in the sense that it is based on an adaptive knowledge based formed during a training phase, and also in the fact that both methods utilize pattern features that are directly available. The main advantage of this approach is that the sensitivity of the pattern classifier can be controlled. The proposed pattern classifier has been designed using 1.5 micrometers design rules for an N-well CMOS process. Layout has been achieved using SOLO 1400. Binary pseudo 2-D hybrid additive CA (HACA) is described in the second section of this paper. The third section describes the operation of the pattern classifier and the fourth section presents some possible applications. The VLSI implementation of the pattern classifier is presented in the fifth section and, finally, the sixth section draws conclusions from the results obtained.

A case study of microphysical structures and hydrometeor phase in convection using radar Doppler spectra at Darwin, Australia

NASA Astrophysics Data System (ADS)

Riihimaki, L. D.; Comstock, J. M.; Luke, E.; Thorsen, T. J.; Fu, Q.

2017-07-01

To understand the microphysical processes that impact diabatic heating and cloud lifetimes in convection, we need to characterize the spatial distribution of supercooled liquid water. To address this observational challenge, ground-based vertically pointing active sensors at the Darwin Atmospheric Radiation Measurement site are used to classify cloud phase within a deep convective cloud. The cloud cannot be fully observed by a lidar due to signal attenuation. Therefore, we developed an objective method for identifying hydrometeor classes, including mixed-phase conditions, using k-means clustering on parameters that describe the shape of the Doppler spectra from vertically pointing Ka-band cloud radar. This approach shows that multiple, overlapping mixed-phase layers exist within the cloud, rather than a single region of supercooled liquid. Diffusional growth calculations show that the conditions for the Wegener-Bergeron-Findeisen process exist within one of these mixed-phase microstructures.

In situ attosecond pulse characterization techniques to measure the electromagnetic phase

NASA Astrophysics Data System (ADS)

Spanner, M.; Bertrand, J. B.; Villeneuve, D. M.

2016-08-01

A number of techniques have been developed to characterize the attosecond emission from high-order-harmonic sources. These techniques are broadly classified as ex situ, where the attosecond pulse train photoionizes a target gas in the presence of an infrared field, and in situ, where the measurement takes place in the medium in which the attosecond pulses are generated. It is accepted that ex situ techniques measure the characteristics of the electromagnetic field, including the phase of the recombination transition moment of the emitting atom or molecule, when the phase of the second medium is known. However, there is debate about whether in situ techniques measure the electromagnetic field, or only the characteristics of the recolliding electron before recombination occurs. We show numerically that in situ measurements are not sensitive to the recombination phase, when implemented in the perturbative regime as originally envisioned, and that they do not measure the electromagnetic phase of the emission.

Learning phase transitions by confusion

NASA Astrophysics Data System (ADS)

van Nieuwenburg, Evert; Liu, Ye-Hua; Huber, Sebastian

Classifying phases of matter is a central problem in physics. For quantum mechanical systems, this task can be daunting owing to the exponentially large Hilbert space. Thanks to the available computing power and access to ever larger data sets, classification problems are now routinely solved using machine learning techniques. Here, we propose to use a neural network based approach to find transitions depending on the performance of the neural network after training it with deliberately incorrectly labelled data. We demonstrate the success of this method on the topological phase transition in the Kitaev chain, the thermal phase transition in the classical Ising model, and the many-body-localization transition in a disordered quantum spin chain. Our method does not depend on order parameters, knowledge of the topological content of the phases, or any other specifics of the transition at hand. It therefore paves the way to a generic tool to identify unexplored transitions.

Characterization of retentivity of reversed phase liquid chromatography columns.

PubMed

Ying, P T; Dorsey, J G

1991-03-01

There are dozens of commercially available reversed phase columns, most marketed as C-8 or C-18 materials, but with no useful way of classifying their retentivity. A useful way of ranking these columns in terms of column "strength" or retentivity is presented. The method utilizes a value for ln k'(w), the estimated retention of a solute from a mobile phase of 100% water, and the slope of the plot of ln k' vsE(T)(30), the solvent polarity. The method is validated with 26 solutes varying in ln k'(w) from about 2 to over 20, on 14 different reversed phase columns. In agreement with previous work, it is found that the phase volume ratio of the column is the most important parameter in determining retentivity. It is strongly suggested that manufacturers adopt a uniform method of calculating this value and that it be made available in advertising, rather than the uninterpretable "% carbon".

The random field Blume-Capel model revisited

NASA Astrophysics Data System (ADS)

Santos, P. V.; da Costa, F. A.; de Araújo, J. M.

2018-04-01

We have revisited the mean-field treatment for the Blume-Capel model under the presence of a discrete random magnetic field as introduced by Kaufman and Kanner (1990). The magnetic field (H) versus temperature (T) phase diagrams for given values of the crystal field D were recovered in accordance to Kaufman and Kanner original work. However, our main goal in the present work was to investigate the distinct structures of the crystal field versus temperature phase diagrams as the random magnetic field is varied because similar models have presented reentrant phenomenon due to randomness. Following previous works we have classified the distinct phase diagrams according to five different topologies. The topological structure of the phase diagrams is maintained for both H - T and D - T cases. Although the phase diagrams exhibit a richness of multicritical phenomena we did not found any reentrant effect as have been seen in similar models.

The LCES HIRES/Keck Precision Radial Velocity Exoplanet Survey

NASA Astrophysics Data System (ADS)

Butler, R. Paul; Vogt, Steven S.; Laughlin, Gregory; Burt, Jennifer A.; Rivera, Eugenio J.; Tuomi, Mikko; Teske, Johanna; Arriagada, Pamela; Diaz, Matias; Holden, Brad; Keiser, Sandy

2017-05-01

We describe a 20 year survey carried out by the Lick-Carnegie Exoplanet Survey Team (LCES), using precision radial velocities from HIRES on the Keck I telescope to find and characterize extrasolar planetary systems orbiting nearby F, G, K, and M dwarf stars. We provide here 60,949 precision radial velocities for 1624 stars contained in that survey. We tabulate a list of 357 significant periodic signals that are of constant period and phase, and not coincident in period and/or phase with stellar activity indices. These signals are thus strongly suggestive of barycentric reflex motion of the star induced by one or more candidate exoplanets in Keplerian motion about the host star. Of these signals, 225 have already been published as planet claims, 60 are classified as significant unpublished planet candidates that await photometric follow-up to rule out activity-related causes, and 54 are also unpublished, but are classified as “significant” signals that require confirmation by additional data before rising to classification as planet candidates. Of particular interest is our detection of a candidate planet with M\\sin (I)=3.8 {M}\\oplus , and P = 9.9 days orbiting Lalande 21185, the fourth-closest main-sequence star to the Sun. For each of our exoplanetary candidate signals, we provide the period and semi-amplitude of the Keplerian orbital fit, and a likelihood ratio estimate of its statistical significance. We also tabulate 18 Keplerian-like signals that we classify as likely arising from stellar activity.

Determination of patellofemoral pain sub-groups and development of a method for predicting treatment outcome using running gait kinematics.

PubMed

Watari, Ricky; Kobsar, Dylan; Phinyomark, Angkoon; Osis, Sean; Ferber, Reed

2016-10-01

Not all patients with patellofemoral pain exhibit successful outcomes following exercise therapy. Thus, the ability to identify patellofemoral pain subgroups related to treatment response is important for the development of optimal therapeutic strategies to improve rehabilitation outcomes. The purpose of this study was to use baseline running gait kinematic and clinical outcome variables to classify patellofemoral pain patients on treatment response retrospectively. Forty-one individuals with patellofemoral pain that underwent a 6-week exercise intervention program were sub-grouped as treatment Responders (n=28) and Non-responders (n=13) based on self-reported measures of pain and function. Baseline three-dimensional running kinematics, and self-reported measures underwent a linear discriminant analysis of the principal components of the variables to retrospectively classify participants based on treatment response. The significance of the discriminant function was verified with a Wilk's lambda test (α=0.05). The model selected 2 gait principal components and had a 78.1% classification accuracy. Overall, Non-responders exhibited greater ankle dorsiflexion, knee abduction and hip flexion during the swing phase and greater ankle inversion during the stance phase, compared to Responders. This is the first study to investigate an objective method to use baseline kinematic and self-report outcome variables to classify on patellofemoral pain treatment outcome. This study represents a significant first step towards a method to help clinicians make evidence-informed decisions regarding optimal treatment strategies for patients with patellofemoral pain. Copyright © 2016 Elsevier Ltd. All rights reserved.

Comparison of two insulin assays for first-phase insulin release in type 1 diabetes prediction and prevention studies

PubMed Central

Mahon, Jeffrey L.; Beam, Craig A.; Marcovina, Santica M.; Boulware, David C.; Palmer, Jerry P.; Winter, William E.; Skyler, Jay S.; Krischer, Jeffrey P.

2018-01-01

Background Detection of below-threshold first-phase insulin release or FPIR (1 + 3 minute insulin concentrations during an intravenous glucose tolerance test [IVGTT]) is important in type 1 diabetes prediction and prevention studies including the TrialNet Oral Insulin Prevention Trial. We assessed whether an insulin immunoenzymometric assay (IEMA) could replace the less practical but current standard of a radioimmunoassay (RIA) for FPIR. Methods One hundred thirty-three islet autoantibody positive relatives of persons with type 1 diabetes underwent 161 IVGTTs. Insulin concentrations were measured by both assays in 1056 paired samples. A rule classifying FPIR (below-threshold, above-threshold, uncertain) by the IEMA was derived and validated against FPIR by the RIA. Results The insulin IEMA-based rule accurately classified below- and above-threshold FPIRs by the RIA in 110/161 (68%) IVGTTs, but was uncertain in 51/161 (32%) tests for which FPIR by RIA is needed. An uncertain FPIR by the IEMA was more likely among below-threshold vs above-threshold FPIRs by the RIA (64% [30/47] vs. 18% [21/114], respectively; p < 0.05). Conclusions An insulin IEMA for FPIR in subjects at risk for type 1 diabetes accurately determined below- and above-threshold FPIRs in 2/3 of tests relative to the current standard of the insulin RIA, but could not reliably classify the remaining FPIRs. TrialNet is limiting the insulin RIA for FPIR to the latter given the practical advantages of the more specific IEMA. PMID:21843518

Event Recognition for Contactless Activity Monitoring Using Phase-Modulated Continuous Wave Radar.

PubMed

Forouzanfar, Mohamad; Mabrouk, Mohamed; Rajan, Sreeraman; Bolic, Miodrag; Dajani, Hilmi R; Groza, Voicu Z

2017-02-01

The use of remote sensing technologies such as radar is gaining popularity as a technique for contactless detection of physiological signals and analysis of human motion. This paper presents a methodology for classifying different events in a collection of phase modulated continuous wave radar returns. The primary application of interest is to monitor inmates where the presence of human vital signs amidst different, interferences needs to be identified. A comprehensive set of features is derived through time and frequency domain analyses of the radar returns. The Bhattacharyya distance is used to preselect the features with highest class separability as the possible candidate features for use in the classification process. The uncorrelated linear discriminant analysis is performed to decorrelate, denoise, and reduce the dimension of the candidate feature set. Linear and quadratic Bayesian classifiers are designed to distinguish breathing, different human motions, and nonhuman motions. The performance of these classifiers is evaluated on a pilot dataset of radar returns that contained different events including breathing, stopped breathing, simple human motions, and movement of fan and water. Our proposed pattern classification system achieved accuracies of up to 93% in stationary subject detection, 90% in stop-breathing detection, and 86% in interference detection. Our proposed radar pattern recognition system was able to accurately distinguish the predefined events amidst interferences. Besides inmate monitoring and suicide attempt detection, this paper can be extended to other radar applications such as home-based monitoring of elderly people, apnea detection, and home occupancy detection.

Sediment and Phosphorus losses by Surface Runoff from a Catchment in the Humid Pampa Landscape, Argentina Republic

NASA Astrophysics Data System (ADS)

Méndez M., A.; Díaz E., L.; Lenzi M., L.; Lado, M.; Vidal-Vázquez, E.

2015-04-01

The estimation of sediment and phosphorus transfers from soil into watersheds as a result of agricultural activity is a key aspect for characterizing the sustainability of current land use systems. The objective of the present study was to quantify the temporal evolution of suspended sediment and dissolved phosphorus losses from the upper basin of the Gualeguaychú River. The studied catchment has an area of 483 Km2 and is located in the Entre Ríos province, Argentina Republic. The climate is subtropical humid with average annual rainfall of 1200 mm. Soils are characterized by very low infiltration rates. Land use was assessed by remote sensing and GIS tools, and consists of: 31% abandoned rice fields, 20% naturalized fields, 20% soybean (second cycle), 10% soybean (first cycle), 7% rice, 4% Pasture, and the remaining 7% is devoted to civil and road works, native forests and other crops. Low soil infiltration capacity, together with landscape geomorphological traits of the studied landscape and zonal rainfall regime, typically originates periods with high surface runoff volumes, mainly in autumn, spring and summer months. The study was conducted during a period of eight years. Instantaneous water flow measurements (discharge) were estimated in a control section of Gualeguaychú River from hydrometer reading and the rating curve of height-flow. In addition, 134 water samples of 2000 cm3 were collected during the study period to analyze the concentration of suspended sediments and dissolved phosphorus. The instantaneous flow was estimated with the hydrometer reading and the application of curve of height - flow. The discharge range was from 0.14 to 128 m3/sec, indicating a high variability in the response of the catchment to seasonal rainfall. On average suspended sediment and dissolved phosphorus losses of the experimental catchment were 1.42 Mg and 0.335 Kg per hectare/year, respectively. It was also shown that few events of high rainfall that generate excess runoff were responsible for the most of recorded losses of sediment and phosphorus. Moreover, the highest exportation of sediments and phosphorus from soil to streamflow occurred in the spring and summer period. The daily losses of phosphorus or sediments were mainly explained by the amount of precipitation accumulated during the five days prior to sampling, as shown by regression analysis, and a higher coefficient of determination was obtained for samples extracted during the summer season. This response mainly has been demonstrated to be produced in periods with higher amounts of precipitation equal or greater than 35 mm arising in this season, which are characteristic for summer storms with high rain intensities, and therefore greater erosive power.

The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models

EPA Science Inventory

The second phase of the MicroArray Quality Control (MAQC-II) project evaluated common practices for developing and validating microarray-based models aimed at predicting toxicological and clinical endpoints. Thirty-six teams developed classifiers for 13 endpoints - some easy, som...

Best Practices for Competency Development and Assessment in Higher Education

ERIC Educational Resources Information Center

Redondo Duarte, Sara; Learreta Ramos, Begoña; Ruiz Rosillo, María Auxiliadora; Alperstedt, Cristiane; Hazé, Emmanuël

2015-01-01

The main objective of this article is to present the results of a study aimed at determining, classifying and evaluating practices of interest for general competency development and assessment in undergraduate programmes. The study encompassed the following phases: (1) focus group in order to establish a starting point regarding competency…

Preliminary Bibliography on South Asia for Undergraduate Libraries.

ERIC Educational Resources Information Center

Hay, Stephen N.; And Others

This classified bibliography on South Asia and similar bibliographies on Africa south of the Sahara (LI 000 882) and East Asia (LI 000 881) have been compiled under the first phase of a three-year cooperative project to strengthen bibliographical resources for undergraduate libraries on "neglected" foreign areas. The bibliography in its…

Preliminary Bibliography on East Asia for Undergraduate Libraries.

ERIC Educational Resources Information Center

Ehrman, Edith; Morehouse, Ward

This classified bibliography on East Asia and similar bibliographies on Africa south of the Sahara (LI 000 882) and South Asia (LI 000 061) have been compiled under the first phase of a three-year cooperative project to strengthen bibliographical resources for undergraduate libraries on "neglected" foreign areas. The bibliography in its…

Preliminary Bibliography on Africa South of the Sahara for Undergraduate Libraries.

ERIC Educational Resources Information Center

Ehrman, Edith; Morehouse, Ward

This classified bibliography on Africa south of the Sahara and similar bibliographies on South Asia (LI 000 061) and East Asia (LI 000 881) have been compiled under the first phase of a three-year cooperative project to strengthen bibliographical resources for undergraduate libraries on "neglected" foreign areas. The bibliography in its…

Informatics approach using metabolic reactivity classifiers to link in vitro to in vivo data in application to the ToxCast Phase I dataset

EPA Science Inventory

Strategic combinations and tiered application of alternative testing methods to replace or minimize the use of animal models is attracting much attention. With the advancement of high throughput screening (HTS) assays and legacy databases providing in vivo testing results, suffic...

A Review of Content and Task Analysis Methodology. Technical Report No. 2.

ERIC Educational Resources Information Center

Gibbons, Andrew S.

A review of the literature related to methods for analyzing content or tasks prior to instructional development is presented. The review classifies methods according to a two-dimensional matrix. The first dimension differentiates phases of analysis, each dealing with content and tasks of a particular scope and each generating certain…

Using the Relevance Vector Machine Model Combined with Local Phase Quantization to Predict Protein-Protein Interactions from Protein Sequences.

PubMed

An, Ji-Yong; Meng, Fan-Rong; You, Zhu-Hong; Fang, Yu-Hong; Zhao, Yu-Jun; Zhang, Ming

2016-01-01

We propose a novel computational method known as RVM-LPQ that combines the Relevance Vector Machine (RVM) model and Local Phase Quantization (LPQ) to predict PPIs from protein sequences. The main improvements are the results of representing protein sequences using the LPQ feature representation on a Position Specific Scoring Matrix (PSSM), reducing the influence of noise using a Principal Component Analysis (PCA), and using a Relevance Vector Machine (RVM) based classifier. We perform 5-fold cross-validation experiments on Yeast and Human datasets, and we achieve very high accuracies of 92.65% and 97.62%, respectively, which is significantly better than previous works. To further evaluate the proposed method, we compare it with the state-of-the-art support vector machine (SVM) classifier on the Yeast dataset. The experimental results demonstrate that our RVM-LPQ method is obviously better than the SVM-based method. The promising experimental results show the efficiency and simplicity of the proposed method, which can be an automatic decision support tool for future proteomics research.

Fixed-interval performance and self-control in infants.

PubMed Central

Darcheville, J C; Rivière, V; Wearden, J H

1993-01-01

Twenty-six infants, 3 to 23 months old, were trained on fixed-interval schedules ranging from 10 s to 80 s. The operant response was touching an illuminated location on a touch-sensitive screen, and 20 s of cartoon presentation was the reinforcer. The subjects were also trained in a six-phase self-control procedure in which the critical phases involved choice between 20 s of cartoon available after a 0.5-s delay (impulsive choice) and 40 s of cartoon delayed for 40 s (self-controlled choice). All the youngest children (3 to 5 months) showed long postreinforcement pauses on the fixed-interval schedule, with most intervals involving the emission of a single, reinforced, response, and all made self-controlled choices. Older subjects (9 to 23 months) either produced the same pattern as the younger ones on the fixed-interval schedule (classified as pause-sensitive subjects) or produced short pauses and higher steady response rates (classified as pause-insensitive subjects). All pause-sensitive subjects made self-controlled choices in the self-control condition, and all pause-insensitive subjects made impulsive ones. PMID:8409821

Automatic Gleason grading of prostate cancer using SLIM and machine learning

NASA Astrophysics Data System (ADS)

Nguyen, Tan H.; Sridharan, Shamira; Marcias, Virgilia; Balla, Andre K.; Do, Minh N.; Popescu, Gabriel

2016-03-01

In this paper, we present an updated automatic diagnostic procedure for prostate cancer using quantitative phase imaging (QPI). In a recent report [1], we demonstrated the use of Random Forest for image segmentation on prostate cores imaged using QPI. Based on these label maps, we developed an algorithm to discriminate between regions with Gleason grade 3 and 4 prostate cancer in prostatectomy tissue. The Area-Under-Curve (AUC) of 0.79 for the Receiver Operating Curve (ROC) can be obtained for Gleason grade 4 detection in a binary classification between Grade 3 and Grade 4. Our dataset includes 280 benign cases and 141 malignant cases. We show that textural features in phase maps have strong diagnostic values since they can be used in combination with the label map to detect presence or absence of basal cells, which is a strong indicator for prostate carcinoma. A support vector machine (SVM) classifier trained on this new feature vector can classify cancer/non-cancer with an error rate of 0.23 and an AUC value of 0.83.

Classification of C2C12 cells at differentiation by convolutional neural network of deep learning using phase contrast images.

PubMed

Niioka, Hirohiko; Asatani, Satoshi; Yoshimura, Aina; Ohigashi, Hironori; Tagawa, Seiichi; Miyake, Jun

2018-01-01

In the field of regenerative medicine, tremendous numbers of cells are necessary for tissue/organ regeneration. Today automatic cell-culturing system has been developed. The next step is constructing a non-invasive method to monitor the conditions of cells automatically. As an image analysis method, convolutional neural network (CNN), one of the deep learning method, is approaching human recognition level. We constructed and applied the CNN algorithm for automatic cellular differentiation recognition of myogenic C2C12 cell line. Phase-contrast images of cultured C2C12 are prepared as input dataset. In differentiation process from myoblasts to myotubes, cellular morphology changes from round shape to elongated tubular shape due to fusion of the cells. CNN abstract the features of the shape of the cells and classify the cells depending on the culturing days from when differentiation is induced. Changes in cellular shape depending on the number of days of culture (Day 0, Day 3, Day 6) are classified with 91.3% accuracy. Image analysis with CNN has a potential to realize regenerative medicine industry.

Clinical implications of the titer of serum hepatitis B surface antigen during the natural history of hepatitis B virus infection.

PubMed

Suh, Sang Jun; Bae, Song-I; Kim, Ji Hoon; Kang, Keunhee; Yeon, Jong Eun; Byun, Kwan Soo

2014-01-01

Although there are some differences in hepatitis B surface antigen (HBsAg) titers in infection with different hepatitis B virus (HBV) genotypes, the HBsAg titers for each HBV genotype have not been evaluated extensively. The aim of this study was to investigate HBsAg titers during the natural history of patients infected with HBV in Korea, where the HBV genotype C is endemic exclusively. Four hundred fifteen patients were enrolled retrospectively and classified according to definitions of the natural phases of HBV infection. In total, 73, 118, 147, and 77 patients were classified in the immune tolerance, immune clearance, low replicative, and HBeAg-negative hepatitis phases, respectively. HBsAg titers (4.35 ± 0.67, 3.74 ± 0.68, 2.39 ± 1.23, and 3.29 ± 0.64 log(10)  IU/ml) were significantly different in the immune tolerance, immune clearance, low replicative, and HBeAg-negative hepatitis phases, respectively (P < 0.001). The ratio of HBsAg to HBV DNA was highest in the low replicative phase (1.13 ± 0.71, all P < 0.001) and second highest in the HBeAg-negative hepatitis phase (0.58 ± 0.18, all P < 0.05). In multivariate analysis of all patients, the HBsAg titers did not correlate with alanine aminotransferase. However, the HBsAg titers correlated with age (P = 0.038), platelet count (P < 0.001) and HBV DNA (P < 0.001). In subgroup analysis, the HBsAg titers correlated with HBV DNA in all phases (P < 0.001), except for the HBeAg-negative hepatitis phase. HBsAg titers were significantly different across the four phases of the natural history of the infection and correlated significantly with HBV DNA titer in genotype C chronic hepatitis B patients. The HBsAg titer could be used as a biomarker to differentiate the natural history of HBV infection. © 2013 Wiley Periodicals, Inc.

Unsupervised classification of cirrhotic livers using MRI data

NASA Astrophysics Data System (ADS)

Lee, Gobert; Kanematsu, Masayuki; Kato, Hiroki; Kondo, Hiroshi; Zhou, Xiangrong; Hara, Takeshi; Fujita, Hiroshi; Hoshi, Hiroaki

2008-03-01

Cirrhosis of the liver is a chronic disease. It is characterized by the presence of widespread nodules and fibrosis in the liver which results in characteristic texture patterns. Computerized analysis of hepatic texture patterns is usually based on regions-of-interest (ROIs). However, not all ROIs are typical representatives of the disease stage of the liver from which the ROIs originated. This leads to uncertainties in the ROI labels (diseased or non-diseased). On the other hand, supervised classifiers are commonly used in determining the assignment rule. This presents a problem as the training of a supervised classifier requires the correct labels of the ROIs. The main purpose of this paper is to investigate the use of an unsupervised classifier, the k-means clustering, in classifying ROI based data. In addition, a procedure for generating a receiver operating characteristic (ROC) curve depicting the classification performance of k-means clustering is also reported. Hepatic MRI images of 44 patients (16 cirrhotic; 28 non-cirrhotic) are used in this study. The MRI data are derived from gadolinium-enhanced equilibrium phase images. For each patient, 10 ROIs selected by an experienced radiologist and 7 texture features measured on each ROI are included in the MRI data. Results of the k-means classifier are depicted using an ROC curve. The area under the curve (AUC) has a value of 0.704. This is slightly lower than but comparable to that of LDA and ANN classifiers which have values 0.781 and 0.801, respectively. Methods in constructing ROC curve in relation to k-means clustering have not been previously reported in the literature.

Coronary artery analysis: Computer-assisted selection of best-quality segments in multiple-phase coronary CT angiography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Chuan, E-mail: chuan@umich.edu; Chan, Heang-

Purpose: The authors are developing an automated method to identify the best-quality coronary arterial segment from multiple-phase coronary CT angiography (cCTA) acquisitions, which may be used by either interpreting physicians or computer-aided detection systems to optimally and efficiently utilize the diagnostic information available in multiple-phase cCTA for the detection of coronary artery disease. Methods: After initialization with a manually identified seed point, each coronary artery tree is automatically extracted from multiple cCTA phases using our multiscale coronary artery response enhancement and 3D rolling balloon region growing vessel segmentation and tracking method. The coronary artery trees from multiple phases are thenmore » aligned by a global registration using an affine transformation with quadratic terms and nonlinear simplex optimization, followed by a local registration using a cubic B-spline method with fast localized optimization. The corresponding coronary arteries among the available phases are identified using a recursive coronary segment matching method. Each of the identified vessel segments is transformed by the curved planar reformation (CPR) method. Four features are extracted from each corresponding segment as quality indicators in the original computed tomography volume and the straightened CPR volume, and each quality indicator is used as a voting classifier for the arterial segment. A weighted voting ensemble (WVE) classifier is designed to combine the votes of the four voting classifiers for each corresponding segment. The segment with the highest WVE vote is then selected as the best-quality segment. In this study, the training and test sets consisted of 6 and 20 cCTA cases, respectively, each with 6 phases, containing a total of 156 cCTA volumes and 312 coronary artery trees. An observer preference study was also conducted with one expert cardiothoracic radiologist and four nonradiologist readers to visually rank vessel segment quality. The performance of our automated method was evaluated by comparing the automatically identified best-quality segments identified by the computer to those selected by the observers. Results: For the 20 test cases, 254 groups of corresponding vessel segments were identified after multiple phase registration and recursive matching. The AI-BQ segments agreed with the radiologist’s top 2 ranked segments in 78.3% of the 254 groups (Cohen’s kappa 0.60), and with the 4 nonradiologist observers in 76.8%, 84.3%, 83.9%, and 85.8% of the 254 groups. In addition, 89.4% of the AI-BQ segments agreed with at least two observers’ top 2 rankings, and 96.5% agreed with at least one observer’s top 2 rankings. In comparison, agreement between the four observers’ top ranked segment and the radiologist’s top 2 ranked segments were 79.9%, 80.7%, 82.3%, and 76.8%, respectively, with kappa values ranging from 0.56 to 0.68. Conclusions: The performance of our automated method for selecting the best-quality coronary segments from a multiple-phase cCTA acquisition was comparable to the selection made by human observers. This study demonstrates the potential usefulness of the automated method in clinical practice, enabling interpreting physicians to fully utilize the best available information in cCTA for diagnosis of coronary disease, without requiring manual search through the multiple phases and minimizing the variability in image phase selection for evaluation of coronary artery segments across the diversity of human readers with variations in expertise.« less

Phase information contained in meter-scale SAR images

NASA Astrophysics Data System (ADS)

Datcu, Mihai; Schwarz, Gottfried; Soccorsi, Matteo; Chaabouni, Houda

2007-10-01

The properties of single look complex SAR satellite images have already been analyzed by many investigators. A common belief is that, apart from inverse SAR methods or polarimetric applications, no information can be gained from the phase of each pixel. This belief is based on the assumption that we obtain uniformly distributed random phases when a sufficient number of small-scale scatterers are mixed in each image pixel. However, the random phase assumption does no longer hold for typical high resolution urban remote sensing scenes, when a limited number of prominent human-made scatterers with near-regular shape and sub-meter size lead to correlated phase patterns. If the pixel size shrinks to a critical threshold of about 1 meter, the reflectance of built-up urban scenes becomes dominated by typical metal reflectors, corner-like structures, and multiple scattering. The resulting phases are hard to model, but one can try to classify a scene based on the phase characteristics of neighboring image pixels. We provide a "cooking recipe" of how to analyze existing phase patterns that extend over neighboring pixels.

Symmetry-protected topological phases of one-dimensional interacting fermions with spin-charge separation

NASA Astrophysics Data System (ADS)

Montorsi, Arianna; Dolcini, Fabrizio; Iotti, Rita C.; Rossi, Fausto

2017-06-01

The low energy behavior of a huge variety of one-dimensional interacting spinful fermionic systems exhibits spin-charge separation, described in the continuum limit by two sine-Gordon models decoupled in the charge and spin channels. Interaction is known to induce, besides the gapless Luttinger liquid phase, eight possible gapped phases, among which are the Mott, Haldane, charge-/spin-density, and bond-ordered wave insulators, and the Luther Emery liquid. Here we prove that some of these physically distinct phases have nontrivial topological properties, notably the presence of degenerate protected edge modes with fractionalized charge/spin. Moreover, we show that the eight gapped phases are in one-to-one correspondence with the symmetry-protected topological (SPT) phases classified by group cohomology theory in the presence of particle-hole symmetry P. The latter result is also exploited to characterize SPT phases by measurable nonlocal order parameters which follow the system evolution to the quantum phase transition. The implications on the appearance of exotic orders in the class of microscopic Hubbard Hamiltonians, possibly without P symmetry at higher energies, are discussed.

Comparison of high-performance liquid chromatography separation of red wine anthocyanins on a mixed-mode ion-exchange reversed-phase and on a reversed-phase column.

PubMed

Vergara, Carola; Mardones, Claudia; Hermosín-Gutiérrez, Isidro; von Baer, Dietrich

2010-09-03

Anthocyanins, which confer the characteristic color to red wine, can be used as markers to classify wines according to the grape variety. It is a complex separation that requires very high chromatographic efficiency, especially in the case of aged red wines, due to the formation of pyranoanthocyanins. A coelution between these kinds of compounds can affect the R(ac/coum) ratio of aged wines, and might lead to false results when classifying the wine variety. In 2007, the use of a novel mixed-mode ion-exchange reversed-phase column was reported to separate anthocyanins extracted from grapes of Vitis labrusca with different selectivity than C-18 columns. In the present work, the separation of anthocyanins including pyranoanthocyanins in young and aged Cabernet Sauvignon wines and other varieties is evaluated. The most interesting contributions of this research are the different elution order and selectivity obtained for anthocyanins and pyranoanthocyanins (only formed in wine), compared with those observed in C-18 stationary phases. Also interesting is the separation of the polymeric fraction, which elutes as a clearly separated peak at the chromatogram's end. However, a comparison with a high efficiency C-18 column with the same dimensions and particle size demonstrated that the tested mixed-mode column shows broader peaks with a theoretical plate number below 8000, for malvidin-3-glucoside peak, while it can be up to 10 times higher for a high efficiency C-18 column, depending on the column manufacturer. Under the tested conditions, in mixed-mode phase, the analysis time is almost twice that of a C-18 column with the same dimensions and particle size. A mixed-mode phase with increased efficiency should provide an interesting perspective for separation of anthocyanins in wine, due to its improved selectivity, combined with a useful role in a second-dimension separation in preparative anthocyanin chromatography. 2010 Elsevier B.V. All rights reserved.

Improving ECG Classification Accuracy Using an Ensemble of Neural Network Modules

PubMed Central

Javadi, Mehrdad; Ebrahimpour, Reza; Sajedin, Atena; Faridi, Soheil; Zakernejad, Shokoufeh

2011-01-01

This paper illustrates the use of a combined neural network model based on Stacked Generalization method for classification of electrocardiogram (ECG) beats. In conventional Stacked Generalization method, the combiner learns to map the base classifiers' outputs to the target data. We claim adding the input pattern to the base classifiers' outputs helps the combiner to obtain knowledge about the input space and as the result, performs better on the same task. Experimental results support our claim that the additional knowledge according to the input space, improves the performance of the proposed method which is called Modified Stacked Generalization. In particular, for classification of 14966 ECG beats that were not previously seen during training phase, the Modified Stacked Generalization method reduced the error rate for 12.41% in comparison with the best of ten popular classifier fusion methods including Max, Min, Average, Product, Majority Voting, Borda Count, Decision Templates, Weighted Averaging based on Particle Swarm Optimization and Stacked Generalization. PMID:22046232

A Fuzzy Integral Ensemble Method in Visual P300 Brain-Computer Interface.

PubMed

Cavrini, Francesco; Bianchi, Luigi; Quitadamo, Lucia Rita; Saggio, Giovanni

2016-01-01

We evaluate the possibility of application of combination of classifiers using fuzzy measures and integrals to Brain-Computer Interface (BCI) based on electroencephalography. In particular, we present an ensemble method that can be applied to a variety of systems and evaluate it in the context of a visual P300-based BCI. Offline analysis of data relative to 5 subjects lets us argue that the proposed classification strategy is suitable for BCI. Indeed, the achieved performance is significantly greater than the average of the base classifiers and, broadly speaking, similar to that of the best one. Thus the proposed methodology allows realizing systems that can be used by different subjects without the need for a preliminary configuration phase in which the best classifier for each user has to be identified. Moreover, the ensemble is often capable of detecting uncertain situations and turning them from misclassifications into abstentions, thereby improving the level of safety in BCI for environmental or device control.

On-Line Detection and Segmentation of Sports Motions Using a Wearable Sensor.

PubMed

Kim, Woosuk; Kim, Myunggyu

2018-03-19

In sports motion analysis, observation is a prerequisite for understanding the quality of motions. This paper introduces a novel approach to detect and segment sports motions using a wearable sensor for supporting systematic observation. The main goal is, for convenient analysis, to automatically provide motion data, which are temporally classified according to the phase definition. For explicit segmentation, a motion model is defined as a sequence of sub-motions with boundary states. A sequence classifier based on deep neural networks is designed to detect sports motions from continuous sensor inputs. The evaluation on two types of motions (soccer kicking and two-handed ball throwing) verifies that the proposed method is successful for the accurate detection and segmentation of sports motions. By developing a sports motion analysis system using the motion model and the sequence classifier, we show that the proposed method is useful for observation of sports motions by automatically providing relevant motion data for analysis.

Energy-aware embedded classifier design for real-time emotion analysis.

PubMed

Padmanabhan, Manoj; Murali, Srinivasan; Rincon, Francisco; Atienza, David

2015-01-01

Detection and classification of human emotions from multiple bio-signals has a wide variety of applications. Though electronic devices are available in the market today that acquire multiple body signals, the classification of human emotions in real-time, adapted to the tight energy budgets of wearable embedded systems is a big challenge. In this paper we present an embedded classifier for real-time emotion classification. We propose a system that operates at different energy budgeted modes, depending on the available energy, where each mode is constrained by an operating energy bound. The classifier has an offline training phase where feature selection is performed for each operating mode, with an energy-budget aware algorithm that we propose. Across the different operating modes, the classification accuracy ranges from 95% - 75% and 89% - 70% for arousal and valence respectively. The accuracy is traded off for less power consumption, which results in an increased battery life of up to 7.7 times (from 146.1 to 1126.9 hours).

Needs of people with advanced dementia in their final phase of life: A multi-perspective qualitative study in nursing homes.

PubMed

Schmidt, Holger; Eisenmann, Yvonne; Golla, Heidrun; Voltz, Raymond; Perrar, Klaus Maria

2018-03-01

People with advanced dementia present an important target group for palliative care. They suffer a range of symptoms, and their verbal communication abilities are highly restricted. At present, little is known about their needs in the final phase of life. To identify the needs of people with advanced dementia in their final phase of life and to explore the aspects relevant to first recognize and then meet these needs. Multi-perspective qualitative study using grounded theory methodology conducting group discussions, individual interviews, and participant observation. The study encompassed nursing homes and involved health professionals, relatives, and residents with advanced dementia. Data were collected in six nursing homes. Nine group discussions and three individual interviews were conducted comprising 42 health professionals and 14 relatives. Participant observations aided in giving the perspective of 30 residents with advanced dementia. Data analysis generated a total of 25 physical, psychosocial, and spiritual needs divided into 10 categories. Physical needs were classified as follows: "food intake," "physical well-being," and "physical activity and recovery." Categories of psychosocial needs were classified as follows: "adaptation of stimuli," "communication," "personal attention," "participation," "familiarity and safety," as well as "self-determination." Spiritual needs addressed "religion." The results revealed a multitude of key aspects for recognizing and meeting these needs, stressing the importance of personhood. People with advanced dementia in their final phase of life have a multitude of individual and complex needs. This evidence contributes to narrowing the current research gap, offering an orientation framework for research and practice.

Bug Smash, Bug Splash: A Case Report of an Unusual Transmission of American Trypanosomiasis with a Brief Review of the Literature.

PubMed

Navarrete-Sandoval, Rafael Hernán; Servín-Rojas, Maximiliano

2016-12-29

BACKGROUND Chagas disease is a chronic parasitosis transmitted by the inoculation of infected triatomine feces into wounds or conjunctival sac, transfusion, congenitally, organ transplantation, and ingestion of contaminated food. The disease is classified into an acute and chronic phase; the latter is a life-long infection that can be asymptomatic or progress to cardiac or digestive complications. CASE REPORT We report a case of acute-phase Chagas disease, transmitted by the splash of gut content from an infected triatomine into the conjunctival mucosa. CONCLUSIONS The diagnosis of Chagas disease is made by the direct visualization of the parasite in blood smears during the acute phase of the disease; during the chronic phase of the disease the diagnosis is made by the detection of IgG antibodies. Parasitological cure can be achieved in up to 80% of the cases in acute phase of the disease, in contrast with less than 30% during the chronic phase.

Cathodoluminescence investigations on quartz cement in the sandstones of Khabour Formation from Iraqi Kurdistan Region, Northern Iraq

NASA Astrophysics Data System (ADS)

Omer, Muhamed F.; Friis, Henrik

2014-03-01

The Ordovician deltaic to shallow marine Khabour Formation in Northern Iraq consists mainly of sandstone with minor siltstone and interbedded shale. The sandstones are pervasively cemented by quartz that resulted in very little preserved primary porosity. Cathodoluminescence and petrographic studies showed that the silica cementation occurred in five successive phases which can be distinguished by their luminescence pattern. The precipitations of two phases have predated the major compaction process while the other phases are younger. The successive phases represent a sequence of changes in silica supply which were classified as very early and early, derived from dissolved biogenic silica that precipitated as opal/microquartz, possibly pre-compactional and of non-luminescent quartz overgrowth type. This was followed by phases whose silica supply derived from pressure solution of quartz, dissolution of feldspar, and hydrothermal fluids related to major thrust fault event. These successive quartz cement phases showed an increase in luminescence and the development of complicated zonation pattern in late-stage quartz cementation.

Holographic QCD phase diagram with critical point from Einstein-Maxwell-dilaton dynamics

NASA Astrophysics Data System (ADS)

Knaute, J.; Yaresko, R.; Kämpfer, B.

2018-03-01

Supplementing the holographic Einstein-Maxwell-dilaton model of [1,2] by input of lattice QCD data for 2 + 1 flavors and physical quark masses for the equation of state and quark number susceptibility at zero baryo-chemical potential we explore the resulting phase diagram over the temperature-chemical potential plane. A first-order phase transition sets in at a temperature of about 112 MeV and a baryo-chemical potential of 612 MeV. We estimate the accuracy of the critical point position in the order of approximately 5-8% by considering parameter variations and different low-temperature asymptotics for the second-order quark number susceptibility. The critical pressure as a function of the temperature has a positive slope, i.e. the entropy per baryon jumps up when crossing the phase border line from larger values of temperature/baryo-chemical potential, thus classifying the phase transition as a gas-liquid one. The updated holographic model exhibits in- and outgoing isentropes in the vicinity of the first-order phase transition.

Thermotropic phase behavior of choline soaps.

PubMed

Klein, Regina; Dutton, Helen; Diat, Olivier; Tiddy, Gordon J T; Kunz, Werner

2011-04-14

Choline carboxylates (ChCm with m = 12-18) are simple biocompatible anionic surfactants with very low Krafft temperatures, possessing a rich aqueous phase behavior. In the present work, we have investigated the thermotropic mesomorphism of anhydrous ChCm salts for m = 12-18. Transition temperatures and enthalpies determined by differential scanning calorimetry reveal that all investigated compounds exhibit three different phases between -20 and 95 °C. The phases were further characterized by optical polarizing microscopy, NMR spin-spin relaxation, and X-ray scattering measurements. The nature of the phases was identified with increasing temperature as crystalline, semicrystalline, and liquid-crystalline lamellar. Even long-chain choline carboxylates (m = 18) were found to melt into a lamellar liquid-crystalline phase below 100 °C. Accordingly, with choline as counterion in simple fatty acid soaps, not only the water solubility is considerably enhanced but also the melting points are substantially reduced, hence facilitating thermotropic mesomorphism at temperatures between 35 and 95 °C. Thus, simple choline soaps with m = 12-18 may be classified as ionic liquids.

Characterization of Xenorhabdus isolates from La Rioja (Northern Spain) and virulence with and without their symbiotic entomopathogenic nematodes (Nematoda: Steinernematidae).

PubMed

Campos-Herrera, R; Tailliez, P; Pagès, S; Ginibre, N; Gutiérrez, C; Boemare, N E

2009-10-01

Eighteen Xenorhabdus isolates associated with Spanish entomopathogenic nematodes of the genus Steinernema were characterized using a polyphasic approach including phenotypic and molecular methods. Two isolates were classified as Xenorhabdus nematophila and were associated with Steinernema carpocapsae. Sixteen isolates were classified as Xenorhabdus bovienii, of which fifteen were associated with Steinernema feltiae and one with Steinernema kraussei. Two X. bovienii Phase II were also isolated, one instable phase isolated from S. feltiae strain Rioja and one stable phase from S. feltiae strain BZ. Four representative bacterial isolates were chosen to study their pathogenicity against Spodoptera littoralis with and without the presence of their nematode host. The four bacterial isolates were pathogenic for S. littoralis leading to septicemia 24h post-injection and killing around 90% of the insect larvae 36 h post-injection, except for that isolated from S. kraussei. After 48 h of injection, this latter isolate showed a lower final population in the larval hemolymph (10(7) instead of 10(8)CFU per larvae) and a lower larval mortality (70% instead of 95-100%). The virulence of the nematode-bacteria complexes against S. littoralis showed similar traits with a significant insect larvae mortality (80-90%) 5 days post-infection except for S. kraussei, although this strain reached similar of larval mortality at 7 days after infection.

Topological superconductivity in the extended Kitaev-Heisenberg model

NASA Astrophysics Data System (ADS)

Schmidt, Johann; Scherer, Daniel D.; Black-Schaffer, Annica M.

2018-01-01

We study superconducting pairing in the doped Kitaev-Heisenberg model by taking into account the recently proposed symmetric off-diagonal exchange Γ . By performing a mean-field analysis, we classify all possible superconducting phases in terms of symmetry, explicitly taking into account effects of spin-orbit coupling. Solving the resulting gap equations self-consistently, we map out a phase diagram that involves several topologically nontrivial states. For Γ <0 , we find a competition between a time-reversal symmetry-breaking chiral phase with Chern number ±1 and a time-reversal symmetric nematic phase that breaks the rotational symmetry of the lattice. On the other hand, for Γ ≥0 we find a time-reversal symmetric phase that preserves all the lattice symmetries, thus yielding clearly distinguishable experimental signatures for all superconducting phases. Both of the time-reversal symmetric phases display a transition to a Z2 nontrivial phase at high doping levels. Finally, we also include a symmetry-allowed spin-orbit coupling kinetic energy and show that it destroys a tentative symmetry-protected topological order at lower doping levels. However, it can be used to tune the time-reversal symmetric phases into a Z2 nontrivial phase even at lower doping.

Classical topological paramagnetism

NASA Astrophysics Data System (ADS)

Bondesan, R.; Ringel, Z.

2017-05-01

Topological phases of matter are one of the hallmarks of quantum condensed matter physics. One of their striking features is a bulk-boundary correspondence wherein the topological nature of the bulk manifests itself on boundaries via exotic massless phases. In classical wave phenomena, analogous effects may arise; however, these cannot be viewed as equilibrium phases of matter. Here, we identify a set of rules under which robust equilibrium classical topological phenomena exist. We write simple and analytically tractable classical lattice models of spins and rotors in two and three dimensions which, at suitable parameter ranges, are paramagnetic in the bulk but nonetheless exhibit some unusual long-range or critical order on their boundaries. We point out the role of simplicial cohomology as a means of classifying, writing, and analyzing such models. This opens an experimental route for studying strongly interacting topological phases of spins.

Multi-Scale Long-Range Magnitude and Sign Correlations in Vertical Upward Oil-Gas-Water Three-Phase Flow

NASA Astrophysics Data System (ADS)

Zhao, An; Jin, Ning-de; Ren, Ying-yu; Zhu, Lei; Yang, Xia

2016-01-01

In this article we apply an approach to identify the oil-gas-water three-phase flow patterns in vertical upwards 20 mm inner-diameter pipe based on the conductance fluctuating signals. We use the approach to analyse the signals with long-range correlations by decomposing the signal increment series into magnitude and sign series and extracting their scaling properties. We find that the magnitude series relates to nonlinear properties of the original time series, whereas the sign series relates to the linear properties. The research shows that the oil-gas-water three-phase flows (slug flow, churn flow, bubble flow) can be classified by a combination of scaling exponents of magnitude and sign series. This study provides a new way of characterising linear and nonlinear properties embedded in oil-gas-water three-phase flows.

On the use of feature selection to improve the detection of sea oil spills in SAR images

NASA Astrophysics Data System (ADS)

Mera, David; Bolon-Canedo, Veronica; Cotos, J. M.; Alonso-Betanzos, Amparo

2017-03-01

Fast and effective oil spill detection systems are crucial to ensure a proper response to environmental emergencies caused by hydrocarbon pollution on the ocean's surface. Typically, these systems uncover not only oil spills, but also a high number of look-alikes. The feature extraction is a critical and computationally intensive phase where each detected dark spot is independently examined. Traditionally, detection systems use an arbitrary set of features to discriminate between oil spills and look-alikes phenomena. However, Feature Selection (FS) methods based on Machine Learning (ML) have proved to be very useful in real domains for enhancing the generalization capabilities of the classifiers, while discarding the existing irrelevant features. In this work, we present a generic and systematic approach, based on FS methods, for choosing a concise and relevant set of features to improve the oil spill detection systems. We have compared five FS methods: Correlation-based feature selection (CFS), Consistency-based filter, Information Gain, ReliefF and Recursive Feature Elimination for Support Vector Machine (SVM-RFE). They were applied on a 141-input vector composed of features from a collection of outstanding studies. Selected features were validated via a Support Vector Machine (SVM) classifier and the results were compared with previous works. Test experiments revealed that the classifier trained with the 6-input feature vector proposed by SVM-RFE achieved the best accuracy and Cohen's kappa coefficient (87.1% and 74.06% respectively). This is a smaller feature combination with similar or even better classification accuracy than previous works. The presented finding allows to speed up the feature extraction phase without reducing the classifier accuracy. Experiments also confirmed the significance of the geometrical features since 75.0% of the different features selected by the applied FS methods as well as 66.67% of the proposed 6-input feature vector belong to this category.

Detection and Identification: Instrumentation and Calibration for Air/Liquid/Surface-borne Nanoscale Particles

NASA Astrophysics Data System (ADS)

Ling, Tsz Yan; Zuo, Zhili; Pui, David Y. H.

2013-04-01

Nanoscale particles can be found in the air-borne, liquid-borne and surface-borne dispersed phases. Measurement techniques for nanoscale particles in all three dispersed phases are needed for the environmental, health and safety studies of nanomaterials. We present our studies on connecting the nanoparticle measurements in different phases to enhance the characterization capability. Microscopy analysis for particle morphology can be performed by depositing air-borne or liquid-borne nanoparticles on surfaces. Detection limit and measurement resolution of the liquid-borne nanoparticles can be enhanced by aerosolizing them and taking advantage of the well-developed air-borne particle analyzers. Sampling electrically classified air-borne virus particles with a gelatin filter provides higher collection efficiency than a liquid impinger.

Detection of different states of sleep in the rodents by the means of artificial neural networks

NASA Astrophysics Data System (ADS)

Musatov, Viacheslav; Dykin, Viacheslav; Pitsik, Elena; Pisarchik, Alexander

2018-04-01

This paper considers the possibility of classification of electroencephalogram (EEG) and electromyogram (EMG) signals corresponding to different phases of sleep and wakefulness of mice by the means of artificial neural networks. A feed-forward artificial neural network based on multilayer perceptron was created and trained on the data of one of the rodents. The trained network was used to read and classify the EEG and EMG data corresponding to different phases of sleep and wakefulness of the same mouse and other mouse. The results show a good recognition quality of all phases for the rodent on which the training was conducted (80-99%) and acceptable recognition quality for the data collected from the same mouse after a stroke.

Facial Emotions Recognition using Gabor Transform and Facial Animation Parameters with Neural Networks

NASA Astrophysics Data System (ADS)

Harit, Aditya; Joshi, J. C., Col; Gupta, K. K.

2018-03-01

The paper proposed an automatic facial emotion recognition algorithm which comprises of two main components: feature extraction and expression recognition. The algorithm uses a Gabor filter bank on fiducial points to find the facial expression features. The resulting magnitudes of Gabor transforms, along with 14 chosen FAPs (Facial Animation Parameters), compose the feature space. There are two stages: the training phase and the recognition phase. Firstly, for the present 6 different emotions, the system classifies all training expressions in 6 different classes (one for each emotion) in the training stage. In the recognition phase, it recognizes the emotion by applying the Gabor bank to a face image, then finds the fiducial points, and then feeds it to the trained neural architecture.

SBIR Phase I final report, Sensor for direct, rapid and complete elemental analysis of coal

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Chunyi

This Final Report is the result of the DOE SBIR Phase I assistance agreement No: DE-FOA-0001619 awarded to Applied Spectra, Inc. During the nine-month Phase I effort, we successfully demonstrated the ability to quantify rare-earth elements (REE) in coal using LIBS (Laser Induced Breakdown Spectroscopy) along with other elements of interest such as silicon (Si), aluminum (Al), magnesium (Mg), calcium (Ca), potassium (K), titanium (Ti) and iron (Fe). In addition to elemental quantification, eighteen different coal types could be classified with 100% certainty using their LIBS spectrum. High-resolution LA-ICP-MS surface mapping showed a correlation between REE and other prevalent elementsmore » such as aluminum, silicon, and titanium.« less

Pink-color sign in esophageal squamous neoplasia, and speculation regarding the underlying mechanism

PubMed Central

Ishihara, Ryu; Kanzaki, Hiromitsu; Iishi, Hiroyasu; Nagai, Kengo; Matsui, Fumi; Yamashina, Takeshi; Matsuura, Noriko; Ito, Takashi; Fujii, Mototsugu; Yamamoto, Sachiko; Hanaoka, Noboru; Takeuchi, Yoji; Higashino, Koji; Uedo, Noriya; Tatsuta, Masaharu; Tomita, Yasuhiko; Ishiguro, Shingo

2013-01-01

AIM: To investigate the reasons for the occurrence of the pink-color sign of iodine-unstained lesions. METHODS: In chromoendoscopy, the pink-color sign of iodine-unstained lesions is recognized as useful for the diagnosis of esophageal squamous cell carcinoma. Patients with superficial esophageal neoplasms treated by endoscopic resection were included in the study. Areas of mucosa with and without the pink-color sign were evaluated histologically. The following histologic features that were possibly associated with the pink-color sign were evaluated. The keratinous layer and basal cell layer were classified as present or absent. Cellular atypia was classified as high grade, moderate grade or low grade, based on nuclear irregularity, mitotic figures, loss of polarity, chromatin pattern and nuclear/cytoplasmic ratio. Vascular change was assessed based on dilatation, tortuosity, caliber change and variability in shape. Vessels with these four findings were classified as positive for vascular change. Endoscopic images of the lesions were captured immediately after iodine staining, 2-3 min after iodine staining and after complete fading of iodine staining. Quantitative analysis of color changes after iodine staining was also performed. RESULTS: A total of 61 superficial esophageal neoplasms in 54 patients were included in the study. The lesions were located in the cervical esophagus in one case, the upper thoracic esophagus in 10 cases, the mid-thoracic esophagus in 33 cases, and the lower thoracic esophagus in 17 cases. The median diameter of the lesions was 20 mm (range: 2-74 mm). Of the 61 lesions, 28 were classified as pink-color sign positive and 33 as pink-color sign negative. The histologic diagnosis was high-grade intraepithelial neoplasia (HGIN) or cancer invading into the lamina propria in 26 of the 28 pink-color sign positive lesions. There was a significant association between pink-color sign positive epithelium and HGIN or invasive cancer (P = 0.0001). Univariate analyses found that absence of the keratinous layer and cellular atypia were significantly associated with the pink-color sign. After Bonferroni correction, there were no significant associations between the pink-color sign and presence of the basal membrane or vascular change. Multivariate analyses found that only absence of the keratinous layer was independently associated with the pink-color sign (OR = 58.8, 95%CI: 5.5-632). Quantitative analysis was performed on 10 superficial esophageal neoplasms with both pink-color sign positive and negative areas in 10 patients. Pink-color sign positive mucosa had a lower mean color value in the late phase (pinkish color) than in the early phase (yellowish color), and had similar mean color values in the late and final phases. These findings suggest that pink-color positive mucosa underwent color fading from the color of the iodine (yellow) to the color of the mucosa (pink) within 2-3 min after iodine staining. Pink-color sign negative mucosa had similar mean color values in the late and early phases (yellowish color), and had a lower mean color value in the final phase (pinkish color) than in the late phase. These findings suggest that pink-color sign negative mucosa did not undergo color fading during the 2-3 min after iodine staining, and underwent color fading only after spraying of sodium thiosulfate. CONCLUSION: The pink-color sign was associated with absence of the keratinous layer. This sign may be caused by early fading of iodine staining. PMID:23885140

Disciplines. Course HP08b: Part Time BA Degree Programme.

ERIC Educational Resources Information Center

Griffith Univ., Brisbane (Australia). School of Humanities.

This course, one of 16 sequential courses comprising phase one of a part-time Bachelor of Arts degree program in Australian Studies, deals with the ways in which knowledge is historically classified into distinct fields. The example used is the 19th century demarcation between science and psuedo-science. The course is designed for independent…

Additive Relations Word Problems in the South African Curriculum and Assessment Policy Standard at Foundation Phase

ERIC Educational Resources Information Center

Roberts, Nicky

2016-01-01

Drawing on a literature review of classifications developed by each of Riley, Verschaffel and Carpenter and their respective research groups, a refined typology of additive relations word problems is proposed and then used as analytical tool to classify the additive relations word problems in South African Curriculum and Assessment Policy Standard…

Adsorption of halogens on metal surfaces

NASA Astrophysics Data System (ADS)

Andryushechkin, B. V.; Pavlova, T. V.; Eltsov, K. N.

2018-06-01

This paper presents a review of the experimental and theoretical investigations of halogen interaction with metal surfaces. The emphasis was placed on the recent measurements performed with a scanning tunneling microscope in combination with density functional theory calculations. The surface structures formed on metal surface after halogen interaction are classified into three groups: chemisorbed monolayer, surface halide, bulk-like halide. Formation of monolayer structures is described in terms of surface phase transitions. Surface halide phases are considered to be intermediates between chemisorbed halogen and bulk halide. The modern theoretical approaches in studying the dynamics of metal halogenation reactions are also presented.

Diagnostic value of gadobenate dimeglumine-enhanced hepatocyte-phase magnetic resonance imaging in evaluating hepatic fibrosis and hepatitis.

PubMed

Li, Xiu-Mei; Chen, Zhu; Xiao, En-Hua; Shang, Quan-Liang; Ma, Cong

2017-05-07

To evaluate the diagnostic value of gadobenate dimeglumine (Gd-BOPTA)-enhanced hepatocyte-phase magnetic resonance imaging (MRI) in evaluating hepatic fibrosis and hepatitis. Hepatocyte-phase images of Gd-BOPTA-enhanced MRI were retrospectively evaluated in 76 patients with chronic liver disease. These patients were classified into five groups according to either the histopathological fibrosis stage (S0-S4) or the histopathological hepatitis grade (G0-G4). The relative enhancement ratio (RE) of the liver parenchyma in the T1-vibe sequence was calculated by measuring the signal intensity before (SI pre) and 90 min after (SI post) intravenous injection of Gd-BOPTA using the following formula: RE = (SI post - SI pre)/SI pre. One-way analysis of variance was used to compare the difference between the relative RE in the hepatocyte phase (REh) and the stage of hepatic fibrosis and the grade of hepatitis. Pearson's product-moment correlation analysis was used to evaluate the relationship between the REh and the levels of serologic liver functional parameters. According to histopathological hepatic fibrosis stage, the 76 patients were classified into five groups: 16 in S0, 15 in S1, 21 in S2, 9 in S3, and 15 in S4 group. According to histopathological hepatitis grade, the 76 patients were also classified into five groups: 0 in G0, 44 in G1, 22 in G2, 8 in G3, and 2 in G3 group. With regard to the stage of hepatic fibrosis, REh showed significant differences between the S2 and S3 groups and between the S2 and S4 groups ( P < 0.05), but no significant difference was observed between the other groups. With regard to the grade of hepatitis, REh showed significant differences between the G1 and G2 groups and between the G1 and G4 groups ( P < 0.05), but no significant difference was observed between the other groups. Increased REh showed correlations with decreased serum levels of TB, ALT and AST ( P < 0.05). To some extent, measuring the REh using Gd-BOPTA-enhanced MRI might be a noninvasive technique for assessing the stage of hepatic fibrosis. This method is able to differentiate no/mild hepatitis from advanced hepatitis. TB, ALT and AST levels can predict the degree of liver enhancement in the hepatocyte phase of Gd-BOPTA-enhanced MRI.

Novel MRI-derived quantitative biomarker for cardiac function applied to classifying ischemic cardiomyopathy within a Bayesian rule learning framework

NASA Astrophysics Data System (ADS)

Menon, Prahlad G.; Morris, Lailonny; Staines, Mara; Lima, Joao; Lee, Daniel C.; Gopalakrishnan, Vanathi

2014-03-01

Characterization of regional left ventricular (LV) function may have application in prognosticating timely response and informing choice therapy in patients with ischemic cardiomyopathy. The purpose of this study is to characterize LV function through a systematic analysis of 4D (3D + time) endocardial motion over the cardiac cycle in an effort to define objective, clinically useful metrics of pathological remodeling and declining cardiac performance, using standard cardiac MRI data for two distinct patient cohorts accessed from CardiacAtlas.org: a) MESA - a cohort of asymptomatic patients; and b) DETERMINE - a cohort of symptomatic patients with a history of ischemic heart disease (IHD) or myocardial infarction. The LV endocardium was segmented and a signed phase-to-phase Hausdorff distance (HD) was computed at 3D uniformly spaced points tracked on segmented endocardial surface contours, over the cardiac cycle. An LV-averaged index of phase-to-phase endocardial displacement (P2PD) time-histories was computed at each tracked point, using the HD computed between consecutive cardiac phases. Average and standard deviation in P2PD over the cardiac cycle was used to prepare characteristic curves for the asymptomatic and IHD cohort. A novel biomarker of RMS error between mean patient-specific characteristic P2PD over the cardiac cycle for each individual patient and the cumulative P2PD characteristic of a cohort of asymptomatic patients was established as the RMS-P2PD marker. The novel RMS-P2PD marker was tested as a cardiac function based feature for automatic patient classification using a Bayesian Rule Learning (BRL) framework. The RMS-P2PD biomarker indices were significantly different for the symptomatic patient and asymptomatic control cohorts (p<0.001). BRL accurately classified 83.8% of patients correctly from the patient and control populations, with leave-one-out cross validation, using standard indices of LV ejection fraction (LV-EF) and LV end-systolic volume index (LV-ESVI). This improved to 91.9% with inclusion of the RMS-P2PD biomarker and was congruent with improvements in both sensitivity for classifying patients and specificity for identifying asymptomatic controls from 82.6% up to 95.7%. RMS-P2PD, when contrasted against a collective normal reference, is a promising biomarker to investigate further in its utility for identifying quantitative signs of pathological endocardial function which may boost standard image makers as precursors of declining cardiac performance.

Three-dimensional counting of morphologically normal human red blood cells via digital holographic microscopy

NASA Astrophysics Data System (ADS)

Yi, Faliu; Moon, Inkyu; Lee, Yeon H.

2015-01-01

Counting morphologically normal cells in human red blood cells (RBCs) is extremely beneficial in the health care field. We propose a three-dimensional (3-D) classification method of automatically determining the morphologically normal RBCs in the phase image of multiple human RBCs that are obtained by off-axis digital holographic microscopy (DHM). The RBC holograms are first recorded by DHM, and then the phase images of multiple RBCs are reconstructed by a computational numerical algorithm. To design the classifier, the three typical RBC shapes, which are stomatocyte, discocyte, and echinocyte, are used for training and testing. Nonmain or abnormal RBC shapes different from the three normal shapes are defined as the fourth category. Ten features, including projected surface area, average phase value, mean corpuscular hemoglobin, perimeter, mean corpuscular hemoglobin surface density, circularity, mean phase of center part, sphericity coefficient, elongation, and pallor, are extracted from each RBC after segmenting the reconstructed phase images by using a watershed transform algorithm. Moreover, four additional properties, such as projected surface area, perimeter, average phase value, and elongation, are measured from the inner part of each cell, which can give significant information beyond the previous 10 features for the separation of the RBC groups; these are verified in the experiment by the statistical method of Hotelling's T-square test. We also apply the principal component analysis algorithm to reduce the dimension number of variables and establish the Gaussian mixture densities using the projected data with the first eight principal components. Consequently, the Gaussian mixtures are used to design the discriminant functions based on Bayesian decision theory. To improve the performance of the Bayes classifier and the accuracy of estimation of its error rate, the leaving-one-out technique is applied. Experimental results show that the proposed method can yield good results for calculating the percentage of each typical normal RBC shape in a reconstructed phase image of multiple RBCs that will be favorable to the analysis of RBC-related diseases. In addition, we show that the discrimination performance for the counting of normal shapes of RBCs can be improved by using 3-D features of an RBC.

Development of LLNA:DAE: a new local lymph node assay that includes the elicitation phase, discriminates borderline-positive chemicals, and is useful for cross-sensitization testing.

PubMed

Yamashita, Kunihiko; Shinoda, Shinsuke; Hagiwara, Saori; Itagaki, Hiroshi

2014-02-01

We developed a new local lymph node assay (LLNA) that includes the elicitation phase termed LLNA:DAE for discrimination of borderline-positive chemicals as classified by the LLNA modified by Daicel based on ATP content (LLNA:DA) and for cross-sensitization testing. Although the LLNA:DA method could help identify skin sensitizers, some skin irritants classified as non-sensitizers by the LLNA were classified as borderline positive. In addition, the evaluation for the cross-sensitization potential between chemicals was impossible. In the LLNA:DAE procedure, test group of mice received four applications of chemicals on the dorsum of the right ear for induction and one application on the dorsum of the left ear for elicitation. Control group of mice received one chemical application on the dorsum of the left ear. We evaluated the sensitizing potential by comparing the weights of the lymph nodes from the left ears between the two groups. The results of using the LLNA:DAE method to examine 24 chemicals, which contained borderline-positive chemicals, were consistent with those from the LLNA method, except for nickel chloride (NiCl2). Two chemical pairs, 2,4-dinitrochlorobenzene (DNCB) with 2,4-dinitrofluorobenzene (DNFB) and hydroquinone (HQ) with p-benzoquinone (p-BQ), showed clear cross-sensitization with each other, while another chemical pair, DNFB with hexylcinnamic aldehyde (HCA) did not. Taken together, our results suggest that the LLNA:DAE method is useful for discriminating borderline-positive chemicals and for determining chemical cross-sensitization.

Comparison of two insulin assays for first-phase insulin release in type 1 diabetes prediction and prevention studies.

PubMed

Mahon, Jeffrey L; Beam, Craig A; Marcovina, Santica M; Boulware, David C; Palmer, Jerry P; Winter, William E; Skyler, Jay S; Krischer, Jeffrey P

2011-11-20

Detection of below-threshold first-phase insulin release or FPIR (1+3 minute insulin concentrations during an intravenous glucose tolerance test [IVGTT]) is important in type 1 diabetes prediction and prevention studies including the TrialNet Oral Insulin Prevention Trial. We assessed whether an insulin immunoenzymometric assay (IEMA) could replace the less practical but current standard of a radioimmunoassay (RIA) for FPIR. One hundred thirty-three islet autoantibody positive relatives of persons with type 1 diabetes underwent 161 IVGTTs. Insulin concentrations were measured by both assays in 1056 paired samples. A rule classifying FPIR (below-threshold, above-threshold, uncertain) by the IEMA was derived and validated against FPIR by the RIA. The insulin IEMA-based rule accurately classified below- and above-threshold FPIRs by the RIA in 110/161 (68%) IVGTTs, but was uncertain in 51/161 (32%) tests for which FPIR by RIA is needed. An uncertain FPIR by the IEMA was more likely among below-threshold vs above-threshold FPIRs by the RIA (64% [30/47] vs. 18% [21/114], respectively; p<0.05). An insulin IEMA for FPIR in subjects at risk for type 1 diabetes accurately determined below- and above-threshold FPIRs in 2/3 of tests relative to the current standard of the insulin RIA, but could not reliably classify the remaining FPIRs. TrialNet is limiting the insulin RIA for FPIR to the latter given the practical advantages of the more specific IEMA. Copyright © 2011 Elsevier B.V. All rights reserved.

Processing of Fear and Anger Facial Expressions: The Role of Spatial Frequency

PubMed Central

Comfort, William E.; Wang, Meng; Benton, Christopher P.; Zana, Yossi

2013-01-01

Spatial frequency (SF) components encode a portion of the affective value expressed in face images. The aim of this study was to estimate the relative weight of specific frequency spectrum bandwidth on the discrimination of anger and fear facial expressions. The general paradigm was a classification of the expression of faces morphed at varying proportions between anger and fear images in which SF adaptation and SF subtraction are expected to shift classification of facial emotion. A series of three experiments was conducted. In Experiment 1 subjects classified morphed face images that were unfiltered or filtered to remove either low (<8 cycles/face), middle (12–28 cycles/face), or high (>32 cycles/face) SF components. In Experiment 2 subjects were adapted to unfiltered or filtered prototypical (non-morphed) fear face images and subsequently classified morphed face images. In Experiment 3 subjects were adapted to unfiltered or filtered prototypical fear face images with the phase component randomized before classifying morphed face images. Removing mid frequency components from the target images shifted classification toward fear. The same shift was observed under adaptation condition to unfiltered and low- and middle-range filtered fear images. However, when the phase spectrum of the same adaptation stimuli was randomized, no adaptation effect was observed. These results suggest that medium SF components support the perception of fear more than anger at both low and high level of processing. They also suggest that the effect at high-level processing stage is related more to high-level featural and/or configural information than to the low-level frequency spectrum. PMID:23637687

Imaging gray matter with concomitant null point imaging from the phase sensitive inversion recovery sequence.

PubMed

Mougin, Olivier; Abdel-Fahim, Rasha; Dineen, Robert; Pitiot, Alain; Evangelou, Nikos; Gowland, Penny

2016-11-01

To present an improved three-dimensional (3D) interleaved phase sensitive inversion recovery (PSIR) sequence including a concomitantly acquired new contrast, null point imaging (NPI), to help detect and classify abnormalities in cortical gray matter. The 3D gradient echo PSIR images were acquired at 0.6 mm isotropic resolution on 11 multiple sclerosis (MS) patients and 9 controls subjects using a 7 Tesla (T) MRI scanner, and 2 MS patients at 3T. Cortical abnormalities were delineated on the NPI/PSIR data and later classified according to position in the cortex. The NPI helped detect cortical lesions within the cortical ribbon with increased, positive contrast compared with the PSIR. It also provided improved intrinsic delineation of the ribbon, increasing confidence in classifying the lesions' locations. The proposed PSIR facilitates the classification of cortical lesions by providing two T 1 -weighted 3D datasets with isotropic resolution, including the NPI showing cortical lesions with clear delineation of the gray/white matter boundary and minimal partial volume effects. Magn Reson Med 76:1512-1516, 2016. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.

Accelerometer and Camera-Based Strategy for Improved Human Fall Detection.

PubMed

Zerrouki, Nabil; Harrou, Fouzi; Sun, Ying; Houacine, Amrane

2016-12-01

In this paper, we address the problem of detecting human falls using anomaly detection. Detection and classification of falls are based on accelerometric data and variations in human silhouette shape. First, we use the exponentially weighted moving average (EWMA) monitoring scheme to detect a potential fall in the accelerometric data. We used an EWMA to identify features that correspond with a particular type of fall allowing us to classify falls. Only features corresponding with detected falls were used in the classification phase. A benefit of using a subset of the original data to design classification models minimizes training time and simplifies models. Based on features corresponding to detected falls, we used the support vector machine (SVM) algorithm to distinguish between true falls and fall-like events. We apply this strategy to the publicly available fall detection databases from the university of Rzeszow's. Results indicated that our strategy accurately detected and classified fall events, suggesting its potential application to early alert mechanisms in the event of fall situations and its capability for classification of detected falls. Comparison of the classification results using the EWMA-based SVM classifier method with those achieved using three commonly used machine learning classifiers, neural network, K-nearest neighbor and naïve Bayes, proved our model superior.

A comprehensive statistical classifier of foci in the cell transformation assay for carcinogenicity testing.

PubMed

Callegaro, Giulia; Malkoc, Kasja; Corvi, Raffaella; Urani, Chiara; Stefanini, Federico M

2017-12-01

The identification of the carcinogenic risk of chemicals is currently mainly based on animal studies. The in vitro Cell Transformation Assays (CTAs) are a promising alternative to be considered in an integrated approach. CTAs measure the induction of foci of transformed cells. CTAs model key stages of the in vivo neoplastic process and are able to detect both genotoxic and some non-genotoxic compounds, being the only in vitro method able to deal with the latter. Despite their favorable features, CTAs can be further improved, especially reducing the possible subjectivity arising from the last phase of the protocol, namely visual scoring of foci using coded morphological features. By taking advantage of digital image analysis, the aim of our work is to translate morphological features into statistical descriptors of foci images, and to use them to mimic the classification performances of the visual scorer to discriminate between transformed and non-transformed foci. Here we present a classifier based on five descriptors trained on a dataset of 1364 foci, obtained with different compounds and concentrations. Our classifier showed accuracy, sensitivity and specificity equal to 0.77 and an area under the curve (AUC) of 0.84. The presented classifier outperforms a previously published model. Copyright © 2017 Elsevier Ltd. All rights reserved.

Machinery Bearing Fault Diagnosis Using Variational Mode Decomposition and Support Vector Machine as a Classifier

NASA Astrophysics Data System (ADS)

Rama Krishna, K.; Ramachandran, K. I.

2018-02-01

Crack propagation is a major cause of failure in rotating machines. It adversely affects the productivity, safety, and the machining quality. Hence, detecting the crack’s severity accurately is imperative for the predictive maintenance of such machines. Fault diagnosis is an established concept in identifying the faults, for observing the non-linear behaviour of the vibration signals at various operating conditions. In this work, we find the classification efficiencies for both original and the reconstructed vibrational signals. The reconstructed signals are obtained using Variational Mode Decomposition (VMD), by splitting the original signal into three intrinsic mode functional components and framing them accordingly. Feature extraction, feature selection and feature classification are the three phases in obtaining the classification efficiencies. All the statistical features from the original signals and reconstructed signals are found out in feature extraction process individually. A few statistical parameters are selected in feature selection process and are classified using the SVM classifier. The obtained results show the best parameters and appropriate kernel in SVM classifier for detecting the faults in bearings. Hence, we conclude that better results were obtained by VMD and SVM process over normal process using SVM. This is owing to denoising and filtering the raw vibrational signals.

Four reversible and reconfigurable structures for three-phase emulsions: extended morphologies and applications

NASA Astrophysics Data System (ADS)

Ge, Xue-Hui; Geng, Yu-Hao; Zhang, Qiao-Chu; Shao, Meng; Chen, Jian; Luo, Guang-Sheng; Xu, Jian-Hong

2017-02-01

Here in this article, we classify and conclude the four morphologies of three-phase emulsions. Remarkably, we achieve the reversible transformations between every shape. Through theoretical analysis, we choose four liquid systems to form these four morphologies. Then monodispersed droplets with these four morphologies are formed through a microfluidic device and captured in a petri-dish. By replacing their ambient solution of the captured emulsions, in-situ morphology transformations between each shape are achieved. The process is well recorded through photographs and videos and they are systematical and reversible. Finally, we use the droplets structure to form an on-off switch to start and shut off the evaporation of one volatile phase to achieve the process monitoring. This could be used to initiate and quench a reaction, which offers a novel idea to achieve the switchable and reversible reaction control in multiple-phase reactions.

Topological Classification of Crystalline Insulators through Band Structure Combinatorics

NASA Astrophysics Data System (ADS)

Kruthoff, Jorrit; de Boer, Jan; van Wezel, Jasper; Kane, Charles L.; Slager, Robert-Jan

2017-10-01

We present a method for efficiently enumerating all allowed, topologically distinct, electronic band structures within a given crystal structure in all physically relevant dimensions. The algorithm applies to crystals without time-reversal, particle-hole, chiral, or any other anticommuting or anti-unitary symmetries. The results presented match the mathematical structure underlying the topological classification of these crystals in terms of K -theory and therefore elucidate this abstract mathematical framework from a simple combinatorial perspective. Using a straightforward counting procedure, we classify all allowed topological phases of spinless particles in crystals in class A . Employing this classification, we study transitions between topological phases within class A that are driven by band inversions at high-symmetry points in the first Brillouin zone. This enables us to list all possible types of phase transitions within a given crystal structure and to identify whether or not they give rise to intermediate Weyl semimetallic phases.

Friction phenomena and phase transition in the underdamped two-dimensional Frenkel-Kontorova model

NASA Astrophysics Data System (ADS)

Yang, Yang; Duan, Wen-Shan; Chen, Jian-Min; Yang, Lei; Tekić, Jasmina; Shao, Zhi-Gang; Wang, Cang-Long

2010-11-01

Locked-to-sliding phase transition has been studied in the driven two-dimensional Frenkel-Kontorova model with the square symmetric substrate potential. It is found that as the driving force increases, the system transfers from the locked state to the sliding state where the motion of particles is in the direction different from that of driving force. With the further increase in driving force, at some critical value, the particles start to move in the direction of driving force. These two critical forces, the static friction or depinning force, and the kinetic friction force for which particles move in the direction of driving force have been analyzed for different system parameters. Different scenarios of phase transitions have been examined and dynamical phases are classified. In the case of zero misfit angle, the analytical expressions for static and kinetic friction force have been obtained.

Web-search trends shed light on the nature of lunacy: relationship between moon phases and epilepsy information-seeking behavior.

PubMed

Otte, Willem M; van Diessen, Eric; Bell, Gail S; Sander, Josemir W

2013-12-01

In old and modern times and across cultures, recurrent seizures have been attributed to the lunar phase. It is unclear whether this relationship should be classified as a myth or whether a true connection exists between moon phases and seizures. We analyzed the worldwide aggregated search queries related to epilepsy health-seeking behavior between 2005 and 2012. Epilepsy-related Internet searches increased in periods with a high moon illumination. The overall association was weak (r=0.11, 95% confidence interval: 0.07 to 0.14) but seems to be higher than most control search queries not related to epilepsy. Increased sleep deprivation during periods of full moon might explain this positive association and warrants further study into epilepsy-related health-seeking behavior on the Internet, the lunar phase, and its contribution to nocturnal luminance. © 2013.

Multi-sensor measurements of mixed-phase clouds above Greenland

NASA Astrophysics Data System (ADS)

Stillwell, Robert A.; Shupe, Matthew D.; Thayer, Jeffrey P.; Neely, Ryan R.; Turner, David D.

2018-04-01

Liquid-only and mixed-phase clouds in the Arctic strongly affect the regional surface energy and ice mass budgets, yet much remains unknown about the nature of these clouds due to the lack of intensive measurements. Lidar measurements of these clouds are challenged by very large signal dynamic range, which makes even seemingly simple tasks, such as thermodynamic phase classification, difficult. This work focuses on a set of measurements made by the Clouds Aerosol Polarization and Backscatter Lidar at Summit, Greenland and its retrieval algorithms, which use both analog and photon counting as well as orthogonal and non-orthogonal polarization retrievals to extend dynamic range and improve overall measurement quality and quantity. Presented here is an algorithm for cloud parameter retrievals that leverages enhanced dynamic range retrievals to classify mixed-phase clouds. This best guess retrieval is compared to co-located instruments for validation.

A pilot study to determine whether combinations of objectively measured activity parameters can be used to differentiate between mixed states, mania, and bipolar depression.

PubMed

Scott, Jan; Vaaler, Arne E; Fasmer, Ole Bernt; Morken, Gunnar; Krane-Gartiser, Karoline

2017-12-01

Until recently, actigraphy studies in bipolar disorders focused on sleep rather than daytime activity in mania or depression, and have failed to analyse mixed episodes separately. Furthermore, even those studies that assessed activity parameters reported only mean levels rather than complexity or predictability of activity. We identified cases presenting in one of three acute phases of bipolar disorder and examined whether the application of non-linear dynamic models to the description of objectively measured activity can be used to predict case classification. The sample comprised 34 adults who were hospitalized with an acute episode of mania (n = 16), bipolar depression (n = 12), or a mixed state (n = 6), who agreed to wear an actiwatch for a continuous period of 24 h. Mean level, variability, regularity, entropy, and predictability of activity were recorded for a defined 64-min active morning and active evening period. Discriminant function analysis was used to determine the combination of variables that best classified cases based on phase of illness. The model identified two discriminant functions: the first was statistically significant and correlated with intra-individual fluctuation in activity and regularity of activity (sample entropy) in the active morning period; the second correlated with several measures of activity from the evening period (e.g. Fourier analysis, autocorrelation, sample entropy). A classification table generated from both functions correctly classified 79% of all cases based on phase of illness (χ 2  = 36.21; df 4; p = 0.001). However, 42% of bipolar depression cases were misclassified as being in manic phase. The findings should be treated with caution as this was a small-scale pilot study and we did not control for prescribed treatments, medication adherence, etc. However, the insights gained should encourage more widespread adoption of statistical approaches to the classification of cases alongside the application of more sophisticated modelling of activity patterns. The difficulty of accurately classifying cases of bipolar depression requires further research, as it is unclear whether the lower prediction rate reflects weaknesses in a model based only on actigraphy data, or if it reflects clinical reality i.e. the possibility that there may be more than one subtype of bipolar depression.

Anomalous Z2 antiferromagnetic topological phase in pressurized SmB6

NASA Astrophysics Data System (ADS)

Chang, Kai-Wei; Chen, Peng-Jen

2018-05-01

Antiferromagnetic materials, whose time-reversal symmetry is broken, can be classified into the Z2 topology if they respect some specific symmetry. Since the theoretical proposal, however, no materials have been found to host such Z2 antiferromagnetic topological (Z2-AFT ) phase to date. Here we demonstrate that the topological Kondo insulator SmB6 can be a Z2-AFT system when pressurized to undergo an antiferromagnetic phase transition. In addition to proposing the possible candidate for a Z2-AFT material, in this work we also illustrate the anomalous topological surface states of the Z2-AFT phase which have not been discussed before. Originating from the interplay between the topological properties and the antiferromagnetic surface magnetization, the topological surface states of the Z2-AFT phase behave differently as compared with those of a topological insulator. Besides, the Z2-AFT insulators are also found promising in the generation of tunable spin currents, which is an important application in spintronics.

A case study of microphysical structures and hydrometeor phase in convection using radar Doppler spectra at Darwin, Australia

DOE PAGES

Riihimaki, Laura D.; Comstock, J. M.; Luke, E.; ...

2017-07-12

To understand the microphysical processes that impact diabatic heating and cloud lifetimes in convection, we need to characterize the spatial distribution of supercooled liquid water. To address this observational challenge, ground-based vertically pointing active sensors at the Darwin Atmospheric Radiation Measurement site are used to classify cloud phase within a deep convective cloud. The cloud cannot be fully observed by a lidar due to signal attenuation. Therefore, we developed an objective method for identifying hydrometeor classes, including mixed-phase conditions, using k-means clustering on parameters that describe the shape of the Doppler spectra from vertically pointing Ka-band cloud radar. Furthermore, thismore » approach shows that multiple, overlapping mixed-phase layers exist within the cloud, rather than a single region of supercooled liquid. Diffusional growth calculations show that the conditions for the Wegener-Bergeron-Findeisen process exist within one of these mixed-phase microstructures.« less

A case study of microphysical structures and hydrometeor phase in convection using radar Doppler spectra at Darwin, Australia

DOE Office of Scientific and Technical Information (OSTI.GOV)

Riihimaki, Laura D.; Comstock, J. M.; Luke, E.

To understand the microphysical processes that impact diabatic heating and cloud lifetimes in convection, we need to characterize the spatial distribution of supercooled liquid water. To address this observational challenge, ground-based vertically pointing active sensors at the Darwin Atmospheric Radiation Measurement site are used to classify cloud phase within a deep convective cloud. The cloud cannot be fully observed by a lidar due to signal attenuation. Therefore, we developed an objective method for identifying hydrometeor classes, including mixed-phase conditions, using k-means clustering on parameters that describe the shape of the Doppler spectra from vertically pointing Ka-band cloud radar. Furthermore, thismore » approach shows that multiple, overlapping mixed-phase layers exist within the cloud, rather than a single region of supercooled liquid. Diffusional growth calculations show that the conditions for the Wegener-Bergeron-Findeisen process exist within one of these mixed-phase microstructures.« less

Motivation and participation in a phase III cardiac rehabilitation programme: an application of the health action process approach.

PubMed

Dohnke, Birte; Nowossadeck, Enno; Müller-Fahrnow, Werner

2010-10-01

This longitudinal study extends the previous research on low participation rates and high dropout rates in phase III cardiac rehabilitation (CR) exercise programmes. It examines the correlates of motivation and participation 6 months after inpatient phase II CR (T1) and the predictors of dropout 6 months later (T2) using the health action process approach (HAPA). Risk perception, outcome expectancies, self-efficacy, intention (at T1), and participation (at T1 and T2) in relation to phase III CR programmes was assessed in 456 patients. Based on intention and participation at T1, patients were classified as nonintenders (56%), intenders (13%), or actors (31%). Group differences were confirmed in outcome expectancies and self-efficacy. By T2, 21% of T1 actors had dropped out. Dropouts and maintainers differed in intention and self-efficacy (at T1). Results are in line with the HAPA and suggest a perspective for tailoring motivational counselling to improve participation in phase III CR programmes.

A Link between ORC-Origin Binding Mechanisms and Origin Activation Time Revealed in Budding Yeast

PubMed Central

Hoggard, Timothy; Shor, Erika; Müller, Carolin A.; Nieduszynski, Conrad A.; Fox, Catherine A.

2013-01-01

Eukaryotic DNA replication origins are selected in G1-phase when the origin recognition complex (ORC) binds chromosomal positions and triggers molecular events culminating in the initiation of DNA replication (a.k.a. origin firing) during S-phase. Each chromosome uses multiple origins for its duplication, and each origin fires at a characteristic time during S-phase, creating a cell-type specific genome replication pattern relevant to differentiation and genome stability. It is unclear whether ORC-origin interactions are relevant to origin activation time. We applied a novel genome-wide strategy to classify origins in the model eukaryote Saccharomyces cerevisiae based on the types of molecular interactions used for ORC-origin binding. Specifically, origins were classified as DNA-dependent when the strength of ORC-origin binding in vivo could be explained by the affinity of ORC for origin DNA in vitro, and, conversely, as ‘chromatin-dependent’ when the ORC-DNA interaction in vitro was insufficient to explain the strength of ORC-origin binding in vivo. These two origin classes differed in terms of nucleosome architecture and dependence on origin-flanking sequences in plasmid replication assays, consistent with local features of chromatin promoting ORC binding at ‘chromatin-dependent’ origins. Finally, the ‘chromatin-dependent’ class was enriched for origins that fire early in S-phase, while the DNA-dependent class was enriched for later firing origins. Conversely, the latest firing origins showed a positive association with the ORC-origin DNA paradigm for normal levels of ORC binding, whereas the earliest firing origins did not. These data reveal a novel association between ORC-origin binding mechanisms and the regulation of origin activation time. PMID:24068963

Classification of toxicity effects of biotransformed hepatic drugs using whale optimized support vector machines.

PubMed

Tharwat, Alaa; Moemen, Yasmine S; Hassanien, Aboul Ella

2017-04-01

Measuring toxicity is an important step in drug development. Nevertheless, the current experimental methods used to estimate the drug toxicity are expensive and time-consuming, indicating that they are not suitable for large-scale evaluation of drug toxicity in the early stage of drug development. Hence, there is a high demand to develop computational models that can predict the drug toxicity risks. In this study, we used a dataset that consists of 553 drugs that biotransformed in liver. The toxic effects were calculated for the current data, namely, mutagenic, tumorigenic, irritant and reproductive effect. Each drug is represented by 31 chemical descriptors (features). The proposed model consists of three phases. In the first phase, the most discriminative subset of features is selected using rough set-based methods to reduce the classification time while improving the classification performance. In the second phase, different sampling methods such as Random Under-Sampling, Random Over-Sampling and Synthetic Minority Oversampling Technique (SMOTE), BorderLine SMOTE and Safe Level SMOTE are used to solve the problem of imbalanced dataset. In the third phase, the Support Vector Machines (SVM) classifier is used to classify an unknown drug into toxic or non-toxic. SVM parameters such as the penalty parameter and kernel parameter have a great impact on the classification accuracy of the model. In this paper, Whale Optimization Algorithm (WOA) has been proposed to optimize the parameters of SVM, so that the classification error can be reduced. The experimental results proved that the proposed model achieved high sensitivity to all toxic effects. Overall, the high sensitivity of the WOA+SVM model indicates that it could be used for the prediction of drug toxicity in the early stage of drug development. Copyright © 2017 Elsevier Inc. All rights reserved.

The phase-space structure of nearby dark matter as constrained by the SDSS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Leclercq, Florent; Percival, Will; Jasche, Jens

Previous studies using numerical simulations have demonstrated that the shape of the cosmic web can be described by studying the Lagrangian displacement field. We extend these analyses, showing that it is now possible to perform a Lagrangian description of cosmic structure in the nearby Universe based on large-scale structure observations. Building upon recent Bayesian large-scale inference of initial conditions, we present a cosmographic analysis of the dark matter distribution and its evolution, referred to as the dark matter phase-space sheet, in the nearby universe as probed by the Sloan Digital Sky Survey main galaxy sample. We consider its stretchings andmore » foldings using a tetrahedral tessellation of the Lagrangian lattice. The method provides extremely accurate estimates of nearby density and velocity fields, even in regions of low galaxy density. It also measures the number of matter streams, and the deformation and parity reversals of fluid elements, which were previously thought inaccessible using observations. We illustrate the approach by showing the phase-space structure of known objects of the nearby Universe such as the Sloan Great Wall, the Coma cluster and the Boötes void. We dissect cosmic structures into four distinct components (voids, sheets, filaments, and clusters), using the Lagrangian classifiers DIVA, ORIGAMI, and a new scheme which we introduce and call LICH. Because these classifiers use information other than the sheer local density, identified structures explicitly carry physical information about their formation history. Accessing the phase-space structure of dark matter in galaxy surveys opens the way for new confrontations of observational data and theoretical models. We have made our data products publicly available.« less

The phase-space structure of nearby dark matter as constrained by the SDSS

NASA Astrophysics Data System (ADS)

Leclercq, Florent; Jasche, Jens; Lavaux, Guilhem; Wandelt, Benjamin; Percival, Will

2017-06-01

Previous studies using numerical simulations have demonstrated that the shape of the cosmic web can be described by studying the Lagrangian displacement field. We extend these analyses, showing that it is now possible to perform a Lagrangian description of cosmic structure in the nearby Universe based on large-scale structure observations. Building upon recent Bayesian large-scale inference of initial conditions, we present a cosmographic analysis of the dark matter distribution and its evolution, referred to as the dark matter phase-space sheet, in the nearby universe as probed by the Sloan Digital Sky Survey main galaxy sample. We consider its stretchings and foldings using a tetrahedral tessellation of the Lagrangian lattice. The method provides extremely accurate estimates of nearby density and velocity fields, even in regions of low galaxy density. It also measures the number of matter streams, and the deformation and parity reversals of fluid elements, which were previously thought inaccessible using observations. We illustrate the approach by showing the phase-space structure of known objects of the nearby Universe such as the Sloan Great Wall, the Coma cluster and the Boötes void. We dissect cosmic structures into four distinct components (voids, sheets, filaments, and clusters), using the Lagrangian classifiers DIVA, ORIGAMI, and a new scheme which we introduce and call LICH. Because these classifiers use information other than the sheer local density, identified structures explicitly carry physical information about their formation history. Accessing the phase-space structure of dark matter in galaxy surveys opens the way for new confrontations of observational data and theoretical models. We have made our data products publicly available.

Immune response phenotype of allergic versus clinically tolerant pigs in a neonatal swine model of allergy.

PubMed

Schmied, Julie; Rupa, Prithy; Garvie, Sarah; Wilkie, Bruce

2013-07-15

The prevalence of childhood food allergy and the duration of these allergies, particularly those considered to be transient, like egg and milk allergy, are increasing. The identification of allergic individuals using minimally invasive, non-anaphylaxis-threatening methods is therefore of increasing importance. In this experiment, correlates were sought of an allergic immune response (IR) phenotype in pigs. Using pigs pre-treated with heat-killed bacteria or bacterial components before allergic sensitization with the egg white protein ovomucoid (Ovm), differences were determined in IR phenotype of pigs in the categories treated-allergic, treated-tolerant, control-allergic (CA) and control-tolerant. Phenotype was established by measuring immunoglobulin (Ig)-associated antibody activity (AbA), cytokine profiles and the proportion of blood T-regulatory cells (T-regs) and observing late-phase allergen-specific skin tests (ST). Although 100% of pigs became sensitized to Ovm, only 33% of pigs had clinical signs of allergy after oral challenge with egg white. Pigs without clinical signs were classified as clinically tolerant. Sixty-seven percent of allergic pigs had a positive, late-phase ST classified as very strong or strong, while 84% of clinically tolerant pigs did not have late-phase ST. Treated-allergic pigs and CA pigs had greater total antibody IgG (H+L), IgE and IgG1 AbA than clinically tolerant pigs. Cytokine profiles of allergic pigs and the proportion of circulating T-regs, did not differ significantly between allergic and clinically tolerant pigs. Therefore, measurement of allergen-specific IgG, IgG1 and/or IgE activity and evaluation of late-phase ID ST may be useful in identifying allergic IR phenotypes in swine models of food allergy, which may be extended toward human use. Copyright © 2013 Elsevier B.V. All rights reserved.

Classifying the Quantum Phases of Matter

DTIC Science & Technology

2015-01-01

Kim related entanglement entropy to topological storage of quantum information [8]. Michalakis et al. showed that a particle-like excitation spectrum...Perturbative analysis of topological entanglement entropy from conditional independence, Phys. Rev. B 86, 254116 (2012), arXiv:1210.2360. [3] I. Kim...symmetries or long-range entanglement ), (2) elucidating the properties of three-dimensional quantum codes (in particular those which admit no string-like

Kinematic Features of Jaw and Lips Distinguish Symptomatic from Presymptomatic Stages of Bulbar Decline in Amyotrophic Lateral Sclerosis

ERIC Educational Resources Information Center

Bandini, Andrea; Green, Jordan R.; Wang, Jun; Campbell, Thomas F.; Zinman, Lorne; Yunusova, Yana

2018-01-01

Purpose: The goals of this study were to (a) classify speech movements of patients with amyotrophic lateral sclerosis (ALS) in presymptomatic and symptomatic phases of bulbar function decline relying solely on kinematic features of lips and jaw and (b) identify the most important measures that detect the transition between early and late bulbar…

Computational Analysis and Experimental Validation of the Friction-Stir Welding Behavior of Ti-6Al-4V

DTIC Science & Technology

2011-01-01

tempera- ture and high-strength workpiece materials like tita - nium. Specifically, it was shown that due to high attendant temperatures these tools...relative amounts of the two phases and are typically classified as a-type, aþb-type, and b-type alloys. Among tita - nium alloys, aþb-type are of

Application of Snyder-Dolan classification scheme to the selection of "orthogonal" columns for fast screening of illicit drugs and impurity profiling of pharmaceuticals--I. Isocratic elution.

PubMed

Fan, Wenzhe; Zhang, Yu; Carr, Peter W; Rutan, Sarah C; Dumarey, Melanie; Schellinger, Adam P; Pritts, Wayne

2009-09-18

Fourteen judiciously selected reversed phase columns were tested with 18 cationic drug solutes under the isocratic elution conditions advised in the Snyder-Dolan (S-D) hydrophobic subtraction method of column classification. The standard errors (S.E.) of the least squares regressions of logk' vs. logk'(REF) were obtained for a given column against a reference column and used to compare and classify columns based on their selectivity. The results are consistent with those obtained with a study of the 16 test solutes recommended by Snyder and Dolan. To the extent these drugs are representative, these results show that the S-D classification scheme is also generally applicable to pharmaceuticals under isocratic conditions. That is, those columns judged to be similar based on the 16 S-D solutes were similar based on the 18 drugs; furthermore those columns judged to have significantly different selectivities based on the 16 S-D probes appeared to be quite different for the drugs as well. Given that the S-D method has been used to classify more than 400 different types of reversed phases the extension to cationic drugs is a significant finding.

Automatic Gleason grading of prostate cancer using quantitative phase imaging and machine learning

NASA Astrophysics Data System (ADS)

Nguyen, Tan H.; Sridharan, Shamira; Macias, Virgilia; Kajdacsy-Balla, Andre; Melamed, Jonathan; Do, Minh N.; Popescu, Gabriel

2017-03-01

We present an approach for automatic diagnosis of tissue biopsies. Our methodology consists of a quantitative phase imaging tissue scanner and machine learning algorithms to process these data. We illustrate the performance by automatic Gleason grading of prostate specimens. The imaging system operates on the principle of interferometry and, as a result, reports on the nanoscale architecture of the unlabeled specimen. We use these data to train a random forest classifier to learn textural behaviors of prostate samples and classify each pixel in the image into different classes. Automatic diagnosis results were computed from the segmented regions. By combining morphological features with quantitative information from the glands and stroma, logistic regression was used to discriminate regions with Gleason grade 3 versus grade 4 cancer in prostatectomy tissue. The overall accuracy of this classification derived from a receiver operating curve was 82%, which is in the range of human error when interobserver variability is considered. We anticipate that our approach will provide a clinically objective and quantitative metric for Gleason grading, allowing us to corroborate results across instruments and laboratories and feed the computer algorithms for improved accuracy.

QA/QC requirements for physical properties sampling and analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Innis, B.E.

1993-07-21

This report presents results of an assessment of the available information concerning US Environmental Protection Agency (EPA) quality assurance/quality control (QA/QC) requirements and guidance applicable to sampling, handling, and analyzing physical parameter samples at Comprehensive Environmental Restoration, Compensation, and Liability Act (CERCLA) investigation sites. Geotechnical testing laboratories measure the following physical properties of soil and sediment samples collected during CERCLA remedial investigations (RI) at the Hanford Site: moisture content, grain size by sieve, grain size by hydrometer, specific gravity, bulk density/porosity, saturated hydraulic conductivity, moisture retention, unsaturated hydraulic conductivity, and permeability of rocks by flowing air. Geotechnical testing laboratories alsomore » measure the following chemical parameters of soil and sediment samples collected during Hanford Site CERCLA RI: calcium carbonate and saturated column leach testing. Physical parameter data are used for (1) characterization of vadose and saturated zone geology and hydrogeology, (2) selection of monitoring well screen sizes, (3) to support modeling and analysis of the vadose and saturated zones, and (4) for engineering design. The objectives of this report are to determine the QA/QC levels accepted in the EPA Region 10 for the sampling, handling, and analysis of soil samples for physical parameters during CERCLA RI.« less

Numerical sedimentation particle-size analysis using the Discrete Element Method

NASA Astrophysics Data System (ADS)

Bravo, R.; Pérez-Aparicio, J. L.; Gómez-Hernández, J. J.

2015-12-01

Sedimentation tests are widely used to determine the particle size distribution of a granular sample. In this work, the Discrete Element Method interacts with the simulation of flow using the well known one-way-coupling method, a computationally affordable approach for the time-consuming numerical simulation of the hydrometer, buoyancy and pipette sedimentation tests. These tests are used in the laboratory to determine the particle-size distribution of fine-grained aggregates. Five samples with different particle-size distributions are modeled by about six million rigid spheres projected on two-dimensions, with diameters ranging from 2.5 ×10-6 m to 70 ×10-6 m, forming a water suspension in a sedimentation cylinder. DEM simulates the particle's movement considering laminar flow interactions of buoyant, drag and lubrication forces. The simulation provides the temporal/spatial distributions of densities and concentrations of the suspension. The numerical simulations cannot replace the laboratory tests since they need the final granulometry as initial data, but, as the results show, these simulations can identify the strong and weak points of each method and eventually recommend useful variations and draw conclusions on their validity, aspects very difficult to achieve in the laboratory.

Effect on physical properties of laterite soil with difference percentage of sodium bentonite

NASA Astrophysics Data System (ADS)

Kasim, Nur Aisyah; Azmi, Nor Azizah Che; Mukri, Mazidah; Noor, Siti Nur Aishah Mohd

2017-08-01

This research was carried out in an attempt to know the physical properties of laterite soil with the appearance of difference percentage of sodium bentonite. Lateritic soils usually develop in tropical and other regions with similar hot and humid climate, where heavy rainfall, warm temperature and well drainage lead to the formation of thick horizons of reddish lateritic soil profiles rich in iron and aluminium. When sodium predominates, a large amount of water can be absorbed in the interlayer, resulting in the remarkable swelling properties observed with hydrating sodium bentonite. There are some basic physical properties test conducted in this research which are Specific Gravity Test, pH Test, Sieve Analysis, Hydrometer Test, Shrinkage Limit and Atterberg Limit. The test will be conducted with 0%, 5%, 10%, 15% and 20% of sodium bentonite. Each test will be repeated three times for the accuracy of the result. From the physical properties test the soil properties characteristic react with the sodium bentonite can be determine. Therefore the best percentage of sodium bentonite admixture can be determined for laterite soil. The outcomes of this study give positive results due to the potential of sodium bentonite to improve the laterite soil particle.

Basic and Morphological Properties of Bukit Goh Bauxite

NASA Astrophysics Data System (ADS)

Hasan, Muzamir; Nor Azmi, Ahmad Amirul Faez Ahmad; Tam, Weng Long; Phang, Biao Yu; Azizul Moqsud, M.

2018-03-01

Investigation conducted by International Maritime Organization (IMO) concluded that the loss of the Bulk Jupiter that carrying bauxite from Kuantan has uncovered evidence to suggest liquefaction led to loss of stability. This research analysed Bukit Goh bauxite and comparison was made with International Maritime Solid Bulk Cargoes (IMSBC Code) standard. To analyse these characteristics of the bauxite, four samples were selected at Bukit Goh, Kuantan ; two of the samples from the Bukit Goh mine and two samples from the stock piles were tested to identify the bauxite basic and morphological properties by referring to GEOSPEC 3 : Model Specification for Soil Testing ; particle size distribution, moisture content and specific gravity and its morphological properties. Laboratory tests involved including Hydrometer test, Small Pycnometer test, Dry Sieve test and Field Emission Scanning Electron Microscop (FESEM) test. The results show that the average moisture content of raw Bukit Goh bauxite is 20.64% which exceeded the recomended value of maximum 10%. Average fine material for raw bauxite is 37.75% which should not be greater than 30% per IMSBC standard. By that, the bauxite from Bukit Goh mine do not achieved the minimum requirements and standards of the IMSBC standard and need to undergo beneficiation process for better quality and safety.

Role of mixed precipitating cloud systems on the typhoon rainfall

NASA Astrophysics Data System (ADS)

Pan, C. J.; Krishna Reddy, K.; Lai, H. C.; Yang, S. S.

2010-01-01

L-band wind profiler data are utilized to diagnose the vertical structure of the typhoon precipitating cloud systems in Taiwan. For several typhoons, a pronounced bright band (BB) around 5 km is commonly observed from the observation. Since strong convection within typhoon circulation may disturb and/or disrupt the melting layer, the BB shall not appear persistently. Hence, an understanding of the vertical structure of the BB region is important because it holds extensive hydrometeors information on the type of precipitation and its variability. Wind profiler observational results suggest that the mixture of convective and stratiform (embedded type) clouds are mostly associated with typhoons. In the case of one typhoon, BB is appeared around 5.5 km with embedded precipitation and also BB height of 1 km higher than ordinary showery precipitation. This is evident from the long-term observations of wind profiler and Tropical Rainfall Measuring Mission. The Doppler velocity profiles show hydrometers (ice/snow) at 6 km but liquid below 5 km for typhoons and 4 km for showery precipitation. In the BB region the melting particles accelerations of 5.8 ms-1 km-1 and 3.2 ms-1 km-1 are observed for typhoon and showery precipitation, respectively.

W-band spaceborne radar observations of atmospheric river events

NASA Astrophysics Data System (ADS)

Matrosov, S. Y.

2010-12-01

While the main objective of the world first W-band radar aboard the CloudSat satellite is to provide vertically resolved information on clouds, it proved to be a valuable tool for observing precipitation. The CloudSat radar is generally able to resolve precipitating cloud systems in their vertical entirety. Although measurements from the liquid hydrometer layer containing rainfall are strongly attenuated, special retrieval approaches can be used to estimate rainfall parameters. These approaches are based on vertical gradients of observed radar reflectivity factor rather than on absolute estimates of reflectivity. Concurrent independent estimations of ice cloud parameters in the same vertical column allow characterization of precipitating systems and provide information on coupling between clouds and rainfall they produce. The potential of CloudSat for observations atmospheric river events affecting the West Coast of North America is evaluated. It is shown that spaceborne radar measurements can provide high resolution information on the height of the freezing level thus separating areas of rainfall and snowfall. CloudSat precipitation rate estimates complement information from the surface-based radars. Observations of atmospheric rivers at different locations above the ocean and during landfall help to understand evolutions of atmospheric rivers and their structures.

Investigation of a Hydrostatic Weighing Method for a 1 kg Mass Comparator

NASA Astrophysics Data System (ADS)

Probst, R.; Kochsiek, M.

1984-01-01

A mass comparator for the comparison of 1 kg weights was built according to a hydrostatic weighing principle, where the buoyancy in a liquid serves to compensate the force due to gravity. In accordance with the method known for hydrometers or areometers, the immersion depth of a float is measured as a function of the force due to gravity, using a laser interferometer. The substitution principle can thus be quite simply realized at constant load. An essential advantage of this weighing method compared with the mechanical beam balance results from the frictionless and vibration-resistant bearing of the float in the liquid. For achieving a high accuracy with this technique, two prerequisites were important: the reduction of the influence of temperature by adapting the coefficients of expansion of buoyant body and liquid to each other, and the improvement of the wetting property of the liquid by adding a surfactant. The accuracy was further improved by the use of an electromagnetic feedback control to keep the immersion depth constant. By this method, a relative standard deviation of the weighings of better than 5 × 10-9 could be achieved.

Patterns in shrinking gels

NASA Astrophysics Data System (ADS)

Matsuo, Eriko Sato; Tanaka, Toyoichi

1992-08-01

POLYMER gels can undergo a volume phase transition (either continuous or discontinuous) when an external condition, such as temperature or solvent composition, is altered1-3. During this transition, the volume may change by a factor of several thousand, and various patterns develop in the gel. The patterns arising from swelling and shrinking differ in both their appearance and their physical mechanisms. The mechanism for the formation and evolution of patterns on swelling gels has been established as being due to a single kind of mechanical instability4-7 in contrast, the shrinking patterns seem to be sensitive to both the initial and final states of the transition. Here we classify the various shrinking patterns in the form of a phase diagram, and explain the poly-morphism in terms of macroscopic phase separation.

Investigation of gastric cancers in nude mice using X-ray in-line phase contrast imaging

PubMed Central

2014-01-01

Background This paper is to report the new imaging of gastric cancers without the use of imaging agents. Both gastric normal regions and gastric cancer regions can be distinguished by using the principal component analysis (PCA) based on the gray level co-occurrence matrix (GLCM). Methods Human gastric cancer BGC823 cells were implanted into the stomachs of nude mice. Then, 3, 5, 7, 9 or 11 days after cancer cells implantation, the nude mice were sacrificed and their stomachs were removed. X-ray in-line phase contrast imaging (XILPCI), an X-ray phase contrast imaging method, has greater soft tissue contrast than traditional absorption radiography and generates higher-resolution images. The gastric specimens were imaged by an XILPCIs’ charge coupled device (CCD) of 9 μm image resolution. The PCA of the projective images’ region of interests (ROIs) based on GLCM were extracted to discriminate gastric normal regions and gastric cancer regions. Different stages of gastric cancers were classified by using support vector machines (SVMs). Results The X-ray in-line phase contrast images of nude mice gastric specimens clearly show the gastric architectures and the details of the early gastric cancers. The phase contrast computed tomography (CT) images of nude mice gastric cancer specimens are better than the traditional absorption CT images without the use of imaging agents. The results of the PCA of the texture parameters based on GLCM of normal regions is (F1 + F2) > 8.5, but those of cancer regions is (F1 + F2) < 8.5. The classification accuracy is 83.3% that classifying gastric specimens into different stages using SVMs. Conclusions This is a very preliminary feasibility study. With further researches, XILPCI could become a noninvasive method for future the early detection of gastric cancers or medical researches. PMID:25060352

A semi-Markov model for mitosis segmentation in time-lapse phase contrast microscopy image sequences of stem cell populations.

PubMed

Liu, An-An; Li, Kang; Kanade, Takeo

2012-02-01

We propose a semi-Markov model trained in a max-margin learning framework for mitosis event segmentation in large-scale time-lapse phase contrast microscopy image sequences of stem cell populations. Our method consists of three steps. First, we apply a constrained optimization based microscopy image segmentation method that exploits phase contrast optics to extract candidate subsequences in the input image sequence that contains mitosis events. Then, we apply a max-margin hidden conditional random field (MM-HCRF) classifier learned from human-annotated mitotic and nonmitotic sequences to classify each candidate subsequence as a mitosis or not. Finally, a max-margin semi-Markov model (MM-SMM) trained on manually-segmented mitotic sequences is utilized to reinforce the mitosis classification results, and to further segment each mitosis into four predefined temporal stages. The proposed method outperforms the event-detection CRF model recently reported by Huh as well as several other competing methods in very challenging image sequences of multipolar-shaped C3H10T1/2 mesenchymal stem cells. For mitosis detection, an overall precision of 95.8% and a recall of 88.1% were achieved. For mitosis segmentation, the mean and standard deviation for the localization errors of the start and end points of all mitosis stages were well below 1 and 2 frames, respectively. In particular, an overall temporal location error of 0.73 ± 1.29 frames was achieved for locating daughter cell birth events.

Generating virtual training samples for sparse representation of face images and face recognition

NASA Astrophysics Data System (ADS)

Du, Yong; Wang, Yu

2016-03-01

There are many challenges in face recognition. In real-world scenes, images of the same face vary with changing illuminations, different expressions and poses, multiform ornaments, or even altered mental status. Limited available training samples cannot convey these possible changes in the training phase sufficiently, and this has become one of the restrictions to improve the face recognition accuracy. In this article, we view the multiplication of two images of the face as a virtual face image to expand the training set and devise a representation-based method to perform face recognition. The generated virtual samples really reflect some possible appearance and pose variations of the face. By multiplying a training sample with another sample from the same subject, we can strengthen the facial contour feature and greatly suppress the noise. Thus, more human essential information is retained. Also, uncertainty of the training data is simultaneously reduced with the increase of the training samples, which is beneficial for the training phase. The devised representation-based classifier uses both the original and new generated samples to perform the classification. In the classification phase, we first determine K nearest training samples for the current test sample by calculating the Euclidean distances between the test sample and training samples. Then, a linear combination of these selected training samples is used to represent the test sample, and the representation result is used to classify the test sample. The experimental results show that the proposed method outperforms some state-of-the-art face recognition methods.

Hybrid carbon nanoparticles modified core-shell silica: a high efficiency carbon-based phase for hydrophilic interaction liquid chromatography.

PubMed

Ibrahim, Mohammed E A; Wahab, M Farooq; Lucy, Charles A

2014-04-11

Hydrophilic interaction liquid chromatography (HILIC) is a fast growing separation technique for hydrophilic and polar analytes. In this work, we combine the unique selectivity of carbon surfaces with the high efficiency of core-shell silica. First, 5 μm core-shell silica is electrostatically coated with 105 nm cationic latex bearing quaternary ammonium groups. Then 50 nm anionic carbon nanoparticles are anchored onto the surface of the latex coated core-shell silica particles to produce a hybrid carbon-silica phase. The hybrid phase shows different selectivity than ten previously classified HILIC column chemistries and 36 stationary phases. The hybrid HILIC phase has shape selectivity for positional isomeric pairs (phthalic/isophthalic and 1-naphthoic/2-naphthoic acids). Fast and high efficiency HILIC separations of biologically important carboxylates, phenols and pharmaceuticals are reported with efficiencies up to 85,000 plates m(-1). Reduced plate height of 1.9 (95,000 plates m(-1)) can be achieved. The hybrid phase is stable for at least 3 months of usage and storage under typical HILIC eluents. Copyright © 2014 Elsevier B.V. All rights reserved.

Automatic classification of canine PRG neuronal discharge patterns using K-means clustering.

PubMed

Zuperku, Edward J; Prkic, Ivana; Stucke, Astrid G; Miller, Justin R; Hopp, Francis A; Stuth, Eckehard A

2015-02-01

Respiratory-related neurons in the parabrachial-Kölliker-Fuse (PB-KF) region of the pons play a key role in the control of breathing. The neuronal activities of these pontine respiratory group (PRG) neurons exhibit a variety of inspiratory (I), expiratory (E), phase spanning and non-respiratory related (NRM) discharge patterns. Due to the variety of patterns, it can be difficult to classify them into distinct subgroups according to their discharge contours. This report presents a method that automatically classifies neurons according to their discharge patterns and derives an average subgroup contour of each class. It is based on the K-means clustering technique and it is implemented via SigmaPlot User-Defined transform scripts. The discharge patterns of 135 canine PRG neurons were classified into seven distinct subgroups. Additional methods for choosing the optimal number of clusters are described. Analysis of the results suggests that the K-means clustering method offers a robust objective means of both automatically categorizing neuron patterns and establishing the underlying archetypical contours of subtypes based on the discharge patterns of group of neurons. Published by Elsevier B.V.

Neural-network classifiers for automatic real-world aerial image recognition

NASA Astrophysics Data System (ADS)

Greenberg, Shlomo; Guterman, Hugo

1996-08-01

We describe the application of the multilayer perceptron (MLP) network and a version of the adaptive resonance theory version 2-A (ART 2-A) network to the problem of automatic aerial image recognition (AAIR). The classification of aerial images, independent of their positions and orientations, is required for automatic tracking and target recognition. Invariance is achieved by the use of different invariant feature spaces in combination with supervised and unsupervised neural networks. The performance of neural-network-based classifiers in conjunction with several types of invariant AAIR global features, such as the Fourier-transform space, Zernike moments, central moments, and polar transforms, are examined. The advantages of this approach are discussed. The performance of the MLP network is compared with that of a classical correlator. The MLP neural-network correlator outperformed the binary phase-only filter (BPOF) correlator. It was found that the ART 2-A distinguished itself with its speed and its low number of required training vectors. However, only the MLP classifier was able to deal with a combination of shift and rotation geometric distortions.

Neural-network classifiers for automatic real-world aerial image recognition.

PubMed

Greenberg, S; Guterman, H

1996-08-10

We describe the application of the multilayer perceptron (MLP) network and a version of the adaptive resonance theory version 2-A (ART 2-A) network to the problem of automatic aerial image recognition (AAIR). The classification of aerial images, independent of their positions and orientations, is required for automatic tracking and target recognition. Invariance is achieved by the use of different invariant feature spaces in combination with supervised and unsupervised neural networks. The performance of neural-network-based classifiers in conjunction with several types of invariant AAIR global features, such as the Fourier-transform space, Zernike moments, central moments, and polar transforms, are examined. The advantages of this approach are discussed. The performance of the MLP network is compared with that of a classical correlator. The MLP neural-network correlator outperformed the binary phase-only filter (BPOF) correlator. It was found that the ART 2-A distinguished itself with its speed and its low number of required training vectors. However, only the MLP classifier was able to deal with a combination of shift and rotation geometric distortions.

An approach for automatic classification of grouper vocalizations with passive acoustic monitoring.

PubMed

Ibrahim, Ali K; Chérubin, Laurent M; Zhuang, Hanqi; Schärer Umpierre, Michelle T; Dalgleish, Fraser; Erdol, Nurgun; Ouyang, B; Dalgleish, A

2018-02-01

Grouper, a family of marine fishes, produce distinct vocalizations associated with their reproductive behavior during spawning aggregation. These low frequencies sounds (50-350 Hz) consist of a series of pulses repeated at a variable rate. In this paper, an approach is presented for automatic classification of grouper vocalizations from ambient sounds recorded in situ with fixed hydrophones based on weighted features and sparse classifier. Group sounds were labeled initially by humans for training and testing various feature extraction and classification methods. In the feature extraction phase, four types of features were used to extract features of sounds produced by groupers. Once the sound features were extracted, three types of representative classifiers were applied to categorize the species that produced these sounds. Experimental results showed that the overall percentage of identification using the best combination of the selected feature extractor weighted mel frequency cepstral coefficients and sparse classifier achieved 82.7% accuracy. The proposed algorithm has been implemented in an autonomous platform (wave glider) for real-time detection and classification of group vocalizations.

A Dual-Wavelength Radar Technique to Detect Hydrometeor Phases

NASA Technical Reports Server (NTRS)

Liao, Liang; Meneghini, Robert

2016-01-01

This study is aimed at investigating the feasibility of a Ku- and Ka-band space/air-borne dual wavelength radar algorithm to discriminate various phase states of precipitating hydrometeors. A phase-state classification algorithm has been developed from the radar measurements of snow, mixed-phase and rain obtained from stratiform storms. The algorithm, presented in the form of the look-up table that links the Ku-band radar reflectivities and dual-frequency ratio (DFR) to the phase states of hydrometeors, is checked by applying it to the measurements of the Jet Propulsion Laboratory, California Institute of Technology, Airborne Precipitation Radar Second Generation (APR-2). In creating the statistically-based phase look-up table, the attenuation corrected (or true) radar reflectivity factors are employed, leading to better accuracy in determining the hydrometeor phase. In practice, however, the true radar reflectivities are not always available before the phase states of the hydrometeors are determined. Therefore, it is desirable to make use of the measured radar reflectivities in classifying the phase states. To do this, a phase-identification procedure is proposed that uses only measured radar reflectivities. The procedure is then tested using APR-2 airborne radar data. Analysis of the classification results in stratiform rain indicates that the regions of snow, mixed-phase and rain derived from the phase-identification algorithm coincide reasonably well with those determined from the measured radar reflectivities and linear depolarization ratio (LDR).

Final safety analysis report for the Ground Test Accelerator (GTA), Phase 2

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

1994-10-01

This document is the third volume of a 3 volume safety analysis report on the Ground Test Accelerator (GTA). The GTA program at the Los Alamos National Laboratory (LANL) is the major element of the national Neutral Particle Beam (NPB) program, which is supported by the Strategic Defense Initiative Office (SDIO). A principal goal of the national NPB program is to assess the feasibility of using hydrogen and deuterium neutral particle beams outside the Earth`s atmosphere. The main effort of the NPB program at Los Alamos concentrates on developing the GTA. The GTA is classified as a low-hazard facility, exceptmore » for the cryogenic-cooling system, which is classified as a moderate-hazard facility. This volume consists of appendices C through U of the report« less

Classifying Different Emotional States by Means of EEG-Based Functional Connectivity Patterns

PubMed Central

Lee, You-Yun; Hsieh, Shulan

2014-01-01

This study aimed to classify different emotional states by means of EEG-based functional connectivity patterns. Forty young participants viewed film clips that evoked the following emotional states: neutral, positive, or negative. Three connectivity indices, including correlation, coherence, and phase synchronization, were used to estimate brain functional connectivity in EEG signals. Following each film clip, participants were asked to report on their subjective affect. The results indicated that the EEG-based functional connectivity change was significantly different among emotional states. Furthermore, the connectivity pattern was detected by pattern classification analysis using Quadratic Discriminant Analysis. The results indicated that the classification rate was better than chance. We conclude that estimating EEG-based functional connectivity provides a useful tool for studying the relationship between brain activity and emotional states. PMID:24743695

In Situ Chemical Characterization of Mineral Phases in Lunar Granulite Meteorite Northwest Africa 5744

NASA Technical Reports Server (NTRS)

Kent, J. J.; Brandon, A. D.; Lapen, T. J.; Peslier, A. H.; Irving, A. J.; Coleff, D. M.

2012-01-01

Northwest Africa (NWA) 5744 meteorite is a granulitic and troctolitic lunar breccia which may represent nearly pristine lunar crust (Fig. 1). NWA 5744 is unusually magnesian compared to other lunar breccias, with bulk [Mg/(Mg+Fe)] 0.79 [1, 2]. Inspection shows impactor content is likely to be very minor, with low Ni content and a lack of metal grains. Some terrestrial contamination is present, evidenced by calcite within cracks. NWA 5744 has notably low concentrations of incompatible trace elements (ITEs) [2]. The goal of this study is to attempt to classify this lunar granulite through analyses of in situ phases.

The chronology of third molar eruption in the Croatian population.

PubMed

Brkić, Hrvoje; Vodanović, Marin; Dumancić, Jelena; Lovrić, Zeljka; Cuković-Bagić, Ivana; Petrovecki, Mladen

2011-06-01

Dental age estimation is common in orthodontics, paedodontics, paleodontology and forensic dentistry. The aim of this study was to assess chronological course of eruptive developmental phases of third molar and to establish parameters for the Croatian population. Sample of this study consisted of 1249 orthopantomograms of 530 (42.4%) male and 719 (57.6%) female subjects, aged 10 to 25 years. Eruptive phases were classified in 4 stages. No significant sex difference was found. Established chronology of the third molar eruption can be used as a standard for the assessment of dental age in clinical and forensic research on samples of Croatian population.

What’s in a drop? Correlating observations and outcomes to guide macromolecular crystallization experiments

PubMed Central

Luft, Joseph R.; Wolfley, Jennifer R.; Snell, Edward H.

2011-01-01

Observations of crystallization experiments are classified as specific outcomes and integrated through a phase diagram to visualize solubility and thereby direct subsequent experiments. Specific examples are taken from our high-throughput crystallization laboratory which provided a broad scope of data from 20 million crystallization experiments on 12,500 different biological macromolecules. The methods and rationale are broadly and generally applicable in any crystallization laboratory. Through a combination of incomplete factorial sampling of crystallization cocktails, standard outcome classifications, visualization of outcomes as they relate chemically and application of a simple phase diagram approach we demonstrate how to logically design subsequent crystallization experiments. PMID:21643490

Origami: Delineating Cosmic Structures with Phase-Space Folds

NASA Astrophysics Data System (ADS)

Neyrinck, Mark C.; Falck, Bridget L.; Szalay, Alex S.

2015-01-01

Structures like galaxies and filaments of galaxies in the Universe come about from the origami-like folding of an initially flat three-dimensional manifold in 6D phase space. The ORIGAMI method identifies these structures in a cosmological simulation, delineating the structures according to their outer folds. Structure identification is a crucial step in comparing cosmological simulations to observed maps of the Universe. The ORIGAMI definition is objective, dynamical and geometric: filament, wall and void particles are classified according to the number of orthogonal axes along which dark-matter streams have crossed. Here, we briefly review these ideas, and speculate on how ORIGAMI might be useful to find cosmic voids.

A comparison study between MLP and convolutional neural network models for character recognition

NASA Astrophysics Data System (ADS)

Ben Driss, S.; Soua, M.; Kachouri, R.; Akil, M.

2017-05-01

Optical Character Recognition (OCR) systems have been designed to operate on text contained in scanned documents and images. They include text detection and character recognition in which characters are described then classified. In the classification step, characters are identified according to their features or template descriptions. Then, a given classifier is employed to identify characters. In this context, we have proposed the unified character descriptor (UCD) to represent characters based on their features. Then, matching was employed to ensure the classification. This recognition scheme performs a good OCR Accuracy on homogeneous scanned documents, however it cannot discriminate characters with high font variation and distortion.3 To improve recognition, classifiers based on neural networks can be used. The multilayer perceptron (MLP) ensures high recognition accuracy when performing a robust training. Moreover, the convolutional neural network (CNN), is gaining nowadays a lot of popularity for its high performance. Furthermore, both CNN and MLP may suffer from the large amount of computation in the training phase. In this paper, we establish a comparison between MLP and CNN. We provide MLP with the UCD descriptor and the appropriate network configuration. For CNN, we employ the convolutional network designed for handwritten and machine-printed character recognition (Lenet-5) and we adapt it to support 62 classes, including both digits and characters. In addition, GPU parallelization is studied to speed up both of MLP and CNN classifiers. Based on our experimentations, we demonstrate that the used real-time CNN is 2x more relevant than MLP when classifying characters.

The Fifth ISM Phase as Revealed by Faraday Rotation

NASA Astrophysics Data System (ADS)

Heiles, Carl E.

2011-01-01

In the diffuse ISM, phases are classically categorized as largely ionized or neutral. The neutral phases come in two flavors, the Cold and Warm Neutral Media (the CNM and WNM), which have typical temperatures 50 and 5000 K. The ionized phases also come in two flavors, again classified by temperature: the Warm and Hot Ionized Media (the WIM and the HIM), which have typical temperatures 8000 and 106 K. There lurks a fifth phase, the Warm Partially Ionized Medium (WPIM). This is not widely recognized, mainly because it's presence is hard to establish observationally. It is well represented by the Local Interstellar Cloud (LIC), whose properties are very well specified in a series of papers by Redfield and Linsky. This fifth phase has a relatively high electron column but low emission measure, so it is not easily seen in H alpha. However, if the region is permeated by a typical magnetic field ( 6 microGauss), then it can produce a recognizable signature in Faraday rotation. We show a few examples and discuss the potential for large-scale mapping of this fifth ISM phase. Support for this work was provided in part by NSF grant AST-0908572.

Bug Smash, Bug Splash: A Case Report of an Unusual Transmission of American Trypanosomiasis with a Brief Review of the Literature

PubMed Central

Navarrete-Sandoval, Rafael Hernán; Servín-Rojas, Maximiliano

2016-01-01

Patient: Male, 44 Final Diagnosis: Acute phase Chagas disease Symptoms: Fever • headache • periorbital oedema Medication: — Clinical Procedure: — Specialty: Infectious Diseases Objective: Rare disease Background: Chagas disease is a chronic parasitosis transmitted by the inoculation of infected triatomine feces into wounds or conjunctival sac, transfusion, congenitally, organ transplantation, and ingestion of contaminated food. The disease is classified into an acute and chronic phase; the latter is a life-long infection that can be asymptomatic or progress to cardiac or digestive complications. Case Report: We report a case of acute-phase Chagas disease, transmitted by the splash of gut content from an infected triatomine into the conjunctival mucosa. Conclusions: The diagnosis of Chagas disease is made by the direct visualization of the parasite in blood smears during the acute phase of the disease; during the chronic phase of the disease the diagnosis is made by the detection of IgG antibodies. Parasitological cure can be achieved in up to 80% of the cases in acute phase of the disease, in contrast with less than 30% during the chronic phase. PMID:28031550

Systematic interrogation of diverse Omic data reveals interpretable, robust, and generalizable transcriptomic features of clinically successful therapeutic targets.

PubMed

Rouillard, Andrew D; Hurle, Mark R; Agarwal, Pankaj

2018-05-01

Target selection is the first and pivotal step in drug discovery. An incorrect choice may not manifest itself for many years after hundreds of millions of research dollars have been spent. We collected a set of 332 targets that succeeded or failed in phase III clinical trials, and explored whether Omic features describing the target genes could predict clinical success. We obtained features from the recently published comprehensive resource: Harmonizome. Nineteen features appeared to be significantly correlated with phase III clinical trial outcomes, but only 4 passed validation schemes that used bootstrapping or modified permutation tests to assess feature robustness and generalizability while accounting for target class selection bias. We also used classifiers to perform multivariate feature selection and found that classifiers with a single feature performed as well in cross-validation as classifiers with more features (AUROC = 0.57 and AUPR = 0.81). The two predominantly selected features were mean mRNA expression across tissues and standard deviation of expression across tissues, where successful targets tended to have lower mean expression and higher expression variance than failed targets. This finding supports the conventional wisdom that it is favorable for a target to be present in the tissue(s) affected by a disease and absent from other tissues. Overall, our results suggest that it is feasible to construct a model integrating interpretable target features to inform target selection. We anticipate deeper insights and better models in the future, as researchers can reuse the data we have provided to improve methods for handling sample biases and learn more informative features. Code, documentation, and data for this study have been deposited on GitHub at https://github.com/arouillard/omic-features-successful-targets.

Novel Strategies to Enhance Vaccine Immunity against Coccidioidomycosis

DTIC Science & Technology

2013-12-19

Mexico and Central and South America [1]. Coccidioides is a dimorphic ascomycetous fungus with distinct saprobic and parasitic phases and is classified in...lethal spore inoculum. However, sterile immunity was not achieved and pulmonary tissue damage associated with a persistent host inflammatory response...observation will translate to humans. A recent vector-based vaccine against tuberculosis intended to protect by eliciting strong CMI failed in humans despite

Strain Gage Signal Interpretation.

DTIC Science & Technology

1986-02-01

blades and vanes in many engines have been collected, played back and examined. The engine types encompass GE’s stable of turbine engines from the small...aeromechanical engineer . 1.3 SUMMARY OF RESULTS Strain gage signals from vibrating rotor blades and vanes were collected, examined, classified, and generalized...turboprops, to turbojets and to the large high bypass turbofan engines . Test conditions include all the phases that are investigated

Computational Analysis and Experimental Validation of the Friction-Stir Welding Behaviour of Ti-6Al-4V

DTIC Science & Technology

2013-05-04

tita - nium. Specifically, it was shown that due to high attendant temperatures these tools have to be made of high-temperature hard materials such as...the two phases and are typically classified as a-type, aþb-type, and b-type alloys. Among tita - nium alloys, aþb-type are of particular interest since

Optical Readout System for Bi-Material Terahertz Sensors

DTIC Science & Technology

2011-09-01

CCD Charged-Coupled Device DFG Difference-Frequency Generation FOV Field of View FPA Focal Plane Array fps Frames Per Second FTIR Fourier ...techniques in the THz range may be classified as either coherent or incoherent. Basically, coherent detection measures the amplitude and phase of the field...using a lock-in amplifier. In a piezoresistive detector, two electrodes are connected to two deformable temperature–sensitive legs. Monitoring the

Portable Language-Independent Adaptive Translation from OCR. Phase 1

DTIC Science & Technology

2009-04-01

including brute-force k-Nearest Neighbors ( kNN ), fast approximate kNN using hashed k-d trees, classification and regression trees, and locality...achieved by refinements in ground-truthing protocols. Recent algorithmic improvements to our approximate kNN classifier using hashed k-D trees allows...recent years discriminative training has been shown to outperform phonetic HMMs estimated using ML for speech recognition. Standard ML estimation

Characterization of Adrenal Lesions on Unenhanced MRI Using Texture Analysis: A Machine-Learning Approach.

PubMed

Romeo, Valeria; Maurea, Simone; Cuocolo, Renato; Petretta, Mario; Mainenti, Pier Paolo; Verde, Francesco; Coppola, Milena; Dell'Aversana, Serena; Brunetti, Arturo

2018-01-17

Adrenal adenomas (AA) are the most common benign adrenal lesions, often characterized based on intralesional fat content as either lipid-rich (LRA) or lipid-poor (LPA). The differentiation of AA, particularly LPA, from nonadenoma adrenal lesions (NAL) may be challenging. Texture analysis (TA) can extract quantitative parameters from MR images. Machine learning is a technique for recognizing patterns that can be applied to medical images by identifying the best combination of TA features to create a predictive model for the diagnosis of interest. To assess the diagnostic efficacy of TA-derived parameters extracted from MR images in characterizing LRA, LPA, and NAL using a machine-learning approach. Retrospective, observational study. Sixty MR examinations, including 20 LRA, 20 LPA, and 20 NAL. Unenhanced T 1 -weighted in-phase (IP) and out-of-phase (OP) as well as T 2 -weighted (T 2 -w) MR images acquired at 3T. Adrenal lesions were manually segmented, placing a spherical volume of interest on IP, OP, and T 2 -w images. Different selection methods were trained and tested using the J48 machine-learning classifiers. The feature selection method that obtained the highest diagnostic performance using the J48 classifier was identified; the diagnostic performance was also compared with that of a senior radiologist by means of McNemar's test. A total of 138 TA-derived features were extracted; among these, four features were selected, extracted from the IP (Short_Run_High_Gray_Level_Emphasis), OP (Mean_Intensity and Maximum_3D_Diameter), and T 2 -w (Standard_Deviation) images; the J48 classifier obtained a diagnostic accuracy of 80%. The expert radiologist obtained a diagnostic accuracy of 73%. McNemar's test did not show significant differences in terms of diagnostic performance between the J48 classifier and the expert radiologist. Machine learning conducted on MR TA-derived features is a potential tool to characterize adrenal lesions. 4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018. © 2018 International Society for Magnetic Resonance in Medicine.

An Ambulatory System for Gait Monitoring Based on Wireless Sensorized Insoles.

PubMed

González, Iván; Fontecha, Jesús; Hervás, Ramón; Bravo, José

2015-07-09

A new gait phase detection system for continuous monitoring based on wireless sensorized insoles is presented. The system can be used in gait analysis mobile applications, and it is designed for real-time demarcation of gait phases. The system employs pressure sensors to assess the force exerted by each foot during walking. A fuzzy rule-based inference algorithm is implemented on a smartphone and used to detect each of the gait phases based on the sensor signals. Additionally, to provide a solution that is insensitive to perturbations caused by non-walking activities, a probabilistic classifier is employed to discriminate walking forward from other low-level activities, such as turning, walking backwards, lateral walking, etc. The combination of these two algorithms constitutes the first approach towards a continuous gait assessment system, by means of the avoidance of non-walking influences.

Machine learning phases of matter

NASA Astrophysics Data System (ADS)

Carrasquilla, Juan; Melko, Roger G.

2017-02-01

Condensed-matter physics is the study of the collective behaviour of infinitely complex assemblies of electrons, nuclei, magnetic moments, atoms or qubits. This complexity is reflected in the size of the state space, which grows exponentially with the number of particles, reminiscent of the `curse of dimensionality' commonly encountered in machine learning. Despite this curse, the machine learning community has developed techniques with remarkable abilities to recognize, classify, and characterize complex sets of data. Here, we show that modern machine learning architectures, such as fully connected and convolutional neural networks, can identify phases and phase transitions in a variety of condensed-matter Hamiltonians. Readily programmable through modern software libraries, neural networks can be trained to detect multiple types of order parameter, as well as highly non-trivial states with no conventional order, directly from raw state configurations sampled with Monte Carlo.

THE ROLE OF METASTABLE STATES IN POLYMER PHASE TRANSITIONS: Concepts, Principles, and Experimental Observations

NASA Astrophysics Data System (ADS)

Cheng, Stephen Z. D.; Keller, Andrew

1998-08-01

Polymer phases can be described in the same way as phases in other condensed matter using a number density operator and its correlation functions. This description requires the understanding of symmetry operations and order at different atomic and molecular levels. Statistical mechanics provides a link between the microscopic description of the structure and motion and the macroscopic thermodynamic properties. Within the limits of the laws of thermodynamics, polymers exhibit a rich variety of phase transition behaviors. By definition, a first-order phase transition describes a transformation that involves a sudden change of thermodynamic properties at its transition temperature, whereas higher-order phase transitions are classified as critical phenomena. Of special interest is the role of metastability in phase and phase transition behaviors. Although a metastable state possesses a local free energy minimum, it is not at the global equilibrium. Furthermore, metastable states can also be associated with phase sizes. Metastable behavior is also observed in phase transformations that are impeded by kinetic limitations along the pathway to thermodynamic equilibrium. This is illustrated in structural and morphological investigations of crystallization and mesophase transitions, liquid-liquid phase separation, vitrification, and gel formation, as well as combinations of transformation processes. In these cases, the metastable state often becomes the dominant state for the entire system and is observed over a range of time and size scales. This review describes the general principles of metastability in polymer phases and phase transitions and provides illustrations from current experimental works in selected areas.

Context and explicit threat cue modulation of the startle reflex: Preliminary evidence of distinctions between adolescents with principal fear disorders versus distress disorders

PubMed Central

Waters, Allison M.; Nazarian, Maria; Mineka, Susan; Zinbarg, Richard E.; Griffith, James W.; Naliboff, Bruce; Ornitz, Edward M.; Craske, Michelle G.

2014-01-01

Anxiety and depression are prevalent, impairing disorders. High comorbidity has raised questions about how to define and classify them. Structural models emphasise distinctions between “fear” and “distress” disorders while other initiatives propose they be defined by neurobiological indicators that cut across disorders. This study examined startle reflex (SR) modulation in adolescents with principal fear disorders (specific phobia; social phobia) (n = 20), distress disorders (unipolar depressive disorders, dysthymia, generalized anxiety disorder; post-traumatic stress disorder) (n = 9), and controls (n = 29) during (a) baseline conditions, (b) threat context conditions (presence of contraction pads over the biceps muscle), and (c) an explicit threat cue paradigm involving phases that signalled safety from aversive stimuli (early and late stages of safe phases; early stages of danger phases) and phases that signalled immediate danger of an aversive stimulus (late stages of danger phases). Adolescents with principal fear disorders showed larger SRs than other groups throughout safe phases and early stages of danger phases. SRs did not differ between groups during late danger phases. Adolescents with principal distress disorders showed attenuated SRs during baseline and context conditions compared to other groups. Preliminary findings support initiatives to redefine emotional disorders based on neurobiological functioning. PMID:24679992

Symmetric Topological Phases and Tensor Network States

NASA Astrophysics Data System (ADS)

Jiang, Shenghan

Classification and simulation of quantum phases are one of main themes in condensed matter physics. Quantum phases can be distinguished by their symmetrical and topological properties. The interplay between symmetry and topology in condensed matter physics often leads to exotic quantum phases and rich phase diagrams. Famous examples include quantum Hall phases, spin liquids and topological insulators. In this thesis, I present our works toward a more systematically understanding of symmetric topological quantum phases in bosonic systems. In the absence of global symmetries, gapped quantum phases are characterized by topological orders. Topological orders in 2+1D are well studied, while a systematically understanding of topological orders in 3+1D is still lacking. By studying a family of exact solvable models, we find at least some topological orders in 3+1D can be distinguished by braiding phases of loop excitations. In the presence of both global symmetries and topological orders, the interplay between them leads to new phases termed as symmetry enriched topological (SET) phases. We develop a framework to classify a large class of SET phases using tensor networks. For each tensor class, we can write down generic variational wavefunctions. We apply our method to study gapped spin liquids on the kagome lattice, which can be viewed as SET phases of on-site symmetries as well as lattice symmetries. In the absence of topological order, symmetry could protect different topological phases, which are often referred to as symmetry protected topological (SPT) phases. We present systematic constructions of tensor network wavefunctions for bosonic symmetry protected topological (SPT) phases respecting both onsite and spatial symmetries.

Multi-phase classification by a least-squares support vector machine approach in tomography images of geological samples

NASA Astrophysics Data System (ADS)

Khan, Faisal; Enzmann, Frieder; Kersten, Michael

2016-03-01

Image processing of X-ray-computed polychromatic cone-beam micro-tomography (μXCT) data of geological samples mainly involves artefact reduction and phase segmentation. For the former, the main beam-hardening (BH) artefact is removed by applying a best-fit quadratic surface algorithm to a given image data set (reconstructed slice), which minimizes the BH offsets of the attenuation data points from that surface. A Matlab code for this approach is provided in the Appendix. The final BH-corrected image is extracted from the residual data or from the difference between the surface elevation values and the original grey-scale values. For the segmentation, we propose a novel least-squares support vector machine (LS-SVM, an algorithm for pixel-based multi-phase classification) approach. A receiver operating characteristic (ROC) analysis was performed on BH-corrected and uncorrected samples to show that BH correction is in fact an important prerequisite for accurate multi-phase classification. The combination of the two approaches was thus used to classify successfully three different more or less complex multi-phase rock core samples.

Conway's Game of Life is a near-critical metastable state in the multiverse of cellular automata.

PubMed

Reia, Sandro M; Kinouchi, Osame

2014-05-01

Conway's cellular automaton Game of Life has been conjectured to be a critical (or quasicritical) dynamical system. This criticality is generally seen as a continuous order-disorder transition in cellular automata (CA) rule space. Life's mean-field return map predicts an absorbing vacuum phase (ρ = 0) and an active phase density, with ρ = 0.37, which contrasts with Life's absorbing states in a square lattice, which have a stationary density of ρ(2D) ≈ 0.03. Here, we study and classify mean-field maps for 6144 outer-totalistic CA and compare them with the corresponding behavior found in the square lattice. We show that the single-site mean-field approach gives qualitative (and even quantitative) predictions for most of them. The transition region in rule space seems to correspond to a nonequilibrium discontinuous absorbing phase transition instead of a continuous order-disorder one. We claim that Life is a quasicritical nucleation process where vacuum phase domains invade the alive phase. Therefore, Life is not at the "border of chaos," but thrives on the "border of extinction."

DOE Office of Scientific and Technical Information (OSTI.GOV)

Robinson, Ian; Clark, Jesse; Harder, Ross

Materials are generally classified by a phase diagram which displays their properties as a function of external state variables, typically temperature and pressure. A new dimension that is relatively unexplored is time: a rich variety of new materials can become accessible in the transient period following laser excitation from the ground state. The timescale of nanoseconds to femtoseconds, is ripe for investigation using x-ray free-electron laser (XFEL) methods. There is no shortage of materials suitable for time-resolved materials-science exploration. Oxides alone represent most of the minerals making up the Earth's crust, catalysts, ferroelectrics, corrosion products and electronically ordered materials suchmore » as superconductors, to name a few. Some of the elements have metastable phase diagrams with predicted new phases. There are some examples known already: an oxide 'hidden phase' living only nanoseconds and an electronically ordered excited phase of fullerene C 60, lasting only femtoseconds. In a completely general way, optically excited states of materials can be probed with Bragg coherent diffraction imaging, both below the damage threshold and in the destructive regime. Lastly, prospective methods for carrying out such XFEL experiments are discussed.« less

Phase Evolution and Mechanical Properties of AlCoCrFeNiSi x High-Entropy Alloys Synthesized by Mechanical Alloying and Spark Plasma Sintering

NASA Astrophysics Data System (ADS)

Kumar, Anil; Swarnakar, Akhilesh Kumar; Chopkar, Manoj

2018-05-01

In the current investigation, AlCoCrFeNiSi x (x = 0, 0.3, 0.6 and 0.9 in atomic ratio) high-entropy alloy systems are prepared by mechanical alloying and subsequently consolidated by spark plasma sintering. The microstructural and mechanical properties were analyzed to understand the effect of Si addition in AlCoCrFeNi alloy. The x-ray diffraction analysis reveals the supersaturated solid solution of the body-centered cubic structure after 20 h of ball milling. However, the consolidation promotes the transformation of body-centered phases partially into the face-centered cubic structure and sigma phases. A recently proposed geometric model based on the atomic stress theory has been extended for the first time to classify single phase and multi-phases on the high-entropy alloys prepared by mechanical alloying and spark plasma sintering process. Improved microhardness and better wear resistance were achieved as the Si content increased from 0 to 0.9 in the present high-entropy alloy.

Conway's game of life is a near-critical metastable state in the multiverse of cellular automata

NASA Astrophysics Data System (ADS)

Reia, Sandro M.; Kinouchi, Osame

2014-05-01

Conway's cellular automaton Game of Life has been conjectured to be a critical (or quasicritical) dynamical system. This criticality is generally seen as a continuous order-disorder transition in cellular automata (CA) rule space. Life's mean-field return map predicts an absorbing vacuum phase (ρ =0) and an active phase density, with ρ =0.37, which contrasts with Life's absorbing states in a square lattice, which have a stationary density of ρ2D≈0.03. Here, we study and classify mean-field maps for 6144 outer-totalistic CA and compare them with the corresponding behavior found in the square lattice. We show that the single-site mean-field approach gives qualitative (and even quantitative) predictions for most of them. The transition region in rule space seems to correspond to a nonequilibrium discontinuous absorbing phase transition instead of a continuous order-disorder one. We claim that Life is a quasicritical nucleation process where vacuum phase domains invade the alive phase. Therefore, Life is not at the "border of chaos," but thrives on the "border of extinction."

A case study of microphysical structures and hydrometeor phase in convection using radar Doppler spectra at Darwin, Australia

DOE Office of Scientific and Technical Information (OSTI.GOV)

Riihimaki, Laura D.; Comstock, Jennifer M.; Luke, Edward

To understand the microphysical processes that impact diabatic heating and cloud lifetimes in convection, we need to characterize the spatial distribution of supercooled liquid water. To address this observational challenge, vertically pointing active sensors at the Darwin Atmospheric Radiation Measurement (ARM) site are used to classify cloud phase within a deep convective cloud in a shallow to deep convection transitional case. The cloud cannot be fully observed by a lidar due to signal attenuation. Thus we develop an objective method for identifying hydrometeor classes, including mixed-phase conditions, using k-means clustering on parameters that describe the shape of the Doppler spectramore » from vertically pointing Ka band cloud radar. This approach shows that multiple, overlapping mixed-phase layers exist within the cloud, rather than a single region of supercooled liquid, indicating complexity to how ice growth and diabatic heating occurs in the vertical structure of the cloud.« less

Automated Identification of the Heart Wall Throughout the Entire Cardiac Cycle Using Optimal Cardiac Phase for Extracted Features

NASA Astrophysics Data System (ADS)

Takahashi, Hiroki; Hasegawa, Hideyuki; Kanai, Hiroshi

2011-07-01

In most methods for evaluation of cardiac function based on echocardiography, the heart wall is currently identified manually by an operator. However, this task is very time-consuming and suffers from inter- and intraobserver variability. The present paper proposes a method that uses multiple features of ultrasonic echo signals for automated identification of the heart wall region throughout an entire cardiac cycle. In addition, the optimal cardiac phase to select a frame of interest, i.e., the frame for the initiation of tracking, was determined. The heart wall region at the frame of interest in this cardiac phase was identified by the expectation-maximization (EM) algorithm, and heart wall regions in the following frames were identified by tracking each point classified in the initial frame as the heart wall region using the phased tracking method. The results for two subjects indicate the feasibility of the proposed method in the longitudinal axis view of the heart.

Gait Partitioning Methods: A Systematic Review

PubMed Central

Taborri, Juri; Palermo, Eduardo; Rossi, Stefano; Cappa, Paolo

2016-01-01

In the last years, gait phase partitioning has come to be a challenging research topic due to its impact on several applications related to gait technologies. A variety of sensors can be used to feed algorithms for gait phase partitioning, mainly classifiable as wearable or non-wearable. Among wearable sensors, footswitches or foot pressure insoles are generally considered as the gold standard; however, to overcome some inherent limitations of the former, inertial measurement units have become popular in recent decades. Valuable results have been achieved also though electromyography, electroneurography, and ultrasonic sensors. Non-wearable sensors, such as opto-electronic systems along with force platforms, remain the most accurate system to perform gait analysis in an indoor environment. In the present paper we identify, select, and categorize the available methodologies for gait phase detection, analyzing advantages and disadvantages of each solution. Finally, we comparatively examine the obtainable gait phase granularities, the usable computational methodologies and the optimal sensor placements on the targeted body segments. PMID:26751449

Gait Partitioning Methods: A Systematic Review.

PubMed

Taborri, Juri; Palermo, Eduardo; Rossi, Stefano; Cappa, Paolo

2016-01-06

In the last years, gait phase partitioning has come to be a challenging research topic due to its impact on several applications related to gait technologies. A variety of sensors can be used to feed algorithms for gait phase partitioning, mainly classifiable as wearable or non-wearable. Among wearable sensors, footswitches or foot pressure insoles are generally considered as the gold standard; however, to overcome some inherent limitations of the former, inertial measurement units have become popular in recent decades. Valuable results have been achieved also though electromyography, electroneurography, and ultrasonic sensors. Non-wearable sensors, such as opto-electronic systems along with force platforms, remain the most accurate system to perform gait analysis in an indoor environment. In the present paper we identify, select, and categorize the available methodologies for gait phase detection, analyzing advantages and disadvantages of each solution. Finally, we comparatively examine the obtainable gait phase granularities, the usable computational methodologies and the optimal sensor placements on the targeted body segments.

Detection of Cardiac Abnormalities from Multilead ECG using Multiscale Phase Alternation Features.

PubMed

Tripathy, R K; Dandapat, S

2016-06-01

The cardiac activities such as the depolarization and the relaxation of atria and ventricles are observed in electrocardiogram (ECG). The changes in the morphological features of ECG are the symptoms of particular heart pathology. It is a cumbersome task for medical experts to visually identify any subtle changes in the morphological features during 24 hours of ECG recording. Therefore, the automated analysis of ECG signal is a need for accurate detection of cardiac abnormalities. In this paper, a novel method for automated detection of cardiac abnormalities from multilead ECG is proposed. The method uses multiscale phase alternation (PA) features of multilead ECG and two classifiers, k-nearest neighbor (KNN) and fuzzy KNN for classification of bundle branch block (BBB), myocardial infarction (MI), heart muscle defect (HMD) and healthy control (HC). The dual tree complex wavelet transform (DTCWT) is used to decompose the ECG signal of each lead into complex wavelet coefficients at different scales. The phase of the complex wavelet coefficients is computed and the PA values at each wavelet scale are used as features for detection and classification of cardiac abnormalities. A publicly available multilead ECG database (PTB database) is used for testing of the proposed method. The experimental results show that, the proposed multiscale PA features and the fuzzy KNN classifier have better performance for detection of cardiac abnormalities with sensitivity values of 78.12 %, 80.90 % and 94.31 % for BBB, HMD and MI classes. The sensitivity value of proposed method for MI class is compared with the state-of-art techniques from multilead ECG.

Gene masking - a technique to improve accuracy for cancer classification with high dimensionality in microarray data.

PubMed

Saini, Harsh; Lal, Sunil Pranit; Naidu, Vimal Vikash; Pickering, Vincel Wince; Singh, Gurmeet; Tsunoda, Tatsuhiko; Sharma, Alok

2016-12-05

High dimensional feature space generally degrades classification in several applications. In this paper, we propose a strategy called gene masking, in which non-contributing dimensions are heuristically removed from the data to improve classification accuracy. Gene masking is implemented via a binary encoded genetic algorithm that can be integrated seamlessly with classifiers during the training phase of classification to perform feature selection. It can also be used to discriminate between features that contribute most to the classification, thereby, allowing researchers to isolate features that may have special significance. This technique was applied on publicly available datasets whereby it substantially reduced the number of features used for classification while maintaining high accuracies. The proposed technique can be extremely useful in feature selection as it heuristically removes non-contributing features to improve the performance of classifiers.

Final safety analysis report for the Ground Test Accelerator (GTA), Phase 2

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

1994-10-01

This document is the first volume of a 3 volume safety analysis report on the Ground Test Accelerator (GTA). The GTA program at the Los Alamos National Laboratory (LANL) is the major element of the national Neutral Particle Beam (NPB) program, which is supported by the Strategic Defense Initiative Office (SDIO). A principal goal of the national NPB program is to assess the feasibility of using hydrogen and deuterium neutral particle beams outside the Earth`s atmosphere. The main effort of the NPB program at Los Alamos concentrates on developing the GTA. The GTA is classified as a low-hazard facility, exceptmore » for the cryogenic-cooling system, which is classified as a moderate-hazard facility. This volume consists of an introduction, summary/conclusion, site description and assessment, description of facility, and description of operation.« less

Accuracy assessments and areal estimates using two-phase stratified random sampling, cluster plots, and the multivariate composite estimator

Treesearch

Raymond L. Czaplewski

2000-01-01

Consider the following example of an accuracy assessment. Landsat data are used to build a thematic map of land cover for a multicounty region. The map classifier (e.g., a supervised classification algorithm) assigns each pixel into one category of land cover. The classification system includes 12 different types of forest and land cover: black spruce, balsam fir,...

Modulation Classification of Satellite Communication Signals Using Cumulants and Neural Networks

NASA Technical Reports Server (NTRS)

Smith, Aaron; Evans, Michael; Downey, Joseph

2017-01-01

National Aeronautics and Space Administration (NASA)'s future communication architecture is evaluating cognitive technologies and increased system intelligence. These technologies are expected to reduce the operational complexity of the network, increase science data return, and reduce interference to self and others. In order to increase situational awareness, signal classification algorithms could be applied to identify users and distinguish sources of interference. A significant amount of previous work has been done in the area of automatic signal classification for military and commercial applications. As a preliminary step, we seek to develop a system with the ability to discern signals typically encountered in satellite communication. Proposed is an automatic modulation classifier which utilizes higher order statistics (cumulants) and an estimate of the signal-to-noise ratio. These features are extracted from baseband symbols and then processed by a neural network for classification. The modulation types considered are phase-shift keying (PSK), amplitude and phase-shift keying (APSK),and quadrature amplitude modulation (QAM). Physical layer properties specific to the Digital Video Broadcasting - Satellite- Second Generation (DVB-S2) standard, such as pilots and variable ring ratios, are also considered. This paper will provide simulation results of a candidate modulation classifier, and performance will be evaluated over a range of signal-to-noise ratios, frequency offsets, and nonlinear amplifier distortions.

Foot placement control and gait instability among people with stroke

PubMed Central

Dean, Jesse C.; Kautz, Steven A.

2016-01-01

Gait instability is a common problem following stroke, as evidenced by increases in fall risk and fear of falling. However, the mechanism underlying gait instability is currently unclear. We recently found that young, healthy humans use a consistent gait stabilization strategy of actively controlling their mediolateral foot placement based on the concurrent mechanical state of the stance limb. In the present work, we tested whether people with stroke (n = 16) and age-matched controls (n = 19) used this neuromechanical strategy. Specifically, we used multiple linear regressions to test whether (1) swing phase gluteus medius (GM) activity was influenced by the simultaneous state of the stance limb and (2) mediolateral foot placement location was influenced by swing phase GM activity and the mechanical state of the swing limb at the start of the step. We found that both age-matched controls and people with stroke classified as having a low fall risk (Dynamic Gait Index [DGI] score >19) essentially used the stabilization strategy previously described in young controls. In contrast, this strategy was disrupted for people with stroke classified as higher fall risk (DGI

Application of Snyder-Dolan Classification Scheme to the Selection of “Orthogonal” Columns for Fast Screening for Illicit Drugs and Impurity Profiling of Pharmaceuticals - I. Isocratic Elution

PubMed Central

Fan, Wenzhe; Zhang, Yu; Carr, Peter W.; Rutan, Sarah C.; Dumarey, Melanie; Schellinger, Adam P.; Pritts, Wayne

2011-01-01

Fourteen judiciously selected reversed-phase columns were tested with 18 cationic drug solutes under the isocratic elution conditions advised in the Snyder-Dolan (S-D) hydrophobic subtraction method of column classification. The standard errors (S.E.) of the least squares regressions of log k′ vs. log k′REF were obtained for a given column against a reference column and used to compare and classify columns based on their selectivity. The results are consistent with those obtained with a study of the 16 test solutes recommended by Snyder and Dolan. To the extent that these drugs are representative these results show that the S-D classification scheme is also generally applicable to pharmaceuticals under isocratic conditions. That is, those columns judged to be similar based on the S-D 16 solutes were similar based on the 18 drugs; furthermore those columns judged to have significantly different selectivities based on the 16 S-D probes appeared to be quite different for the drugs as well. Given that the S-D method has been used to classify more than 400 different types of reversed phases the extension to cationic drugs is a significant finding. PMID:19698948

Cost-Sensitive Radial Basis Function Neural Network Classifier for Software Defect Prediction

PubMed Central

Venkatesan, R.

2016-01-01

Effective prediction of software modules, those that are prone to defects, will enable software developers to achieve efficient allocation of resources and to concentrate on quality assurance activities. The process of software development life cycle basically includes design, analysis, implementation, testing, and release phases. Generally, software testing is a critical task in the software development process wherein it is to save time and budget by detecting defects at the earliest and deliver a product without defects to the customers. This testing phase should be carefully operated in an effective manner to release a defect-free (bug-free) software product to the customers. In order to improve the software testing process, fault prediction methods identify the software parts that are more noted to be defect-prone. This paper proposes a prediction approach based on conventional radial basis function neural network (RBFNN) and the novel adaptive dimensional biogeography based optimization (ADBBO) model. The developed ADBBO based RBFNN model is tested with five publicly available datasets from the NASA data program repository. The computed results prove the effectiveness of the proposed ADBBO-RBFNN classifier approach with respect to the considered metrics in comparison with that of the early predictors available in the literature for the same datasets. PMID:27738649

Cost-Sensitive Radial Basis Function Neural Network Classifier for Software Defect Prediction.

PubMed

Kumudha, P; Venkatesan, R

Effective prediction of software modules, those that are prone to defects, will enable software developers to achieve efficient allocation of resources and to concentrate on quality assurance activities. The process of software development life cycle basically includes design, analysis, implementation, testing, and release phases. Generally, software testing is a critical task in the software development process wherein it is to save time and budget by detecting defects at the earliest and deliver a product without defects to the customers. This testing phase should be carefully operated in an effective manner to release a defect-free (bug-free) software product to the customers. In order to improve the software testing process, fault prediction methods identify the software parts that are more noted to be defect-prone. This paper proposes a prediction approach based on conventional radial basis function neural network (RBFNN) and the novel adaptive dimensional biogeography based optimization (ADBBO) model. The developed ADBBO based RBFNN model is tested with five publicly available datasets from the NASA data program repository. The computed results prove the effectiveness of the proposed ADBBO-RBFNN classifier approach with respect to the considered metrics in comparison with that of the early predictors available in the literature for the same datasets.

Automatic blood vessel based-liver segmentation using the portal phase abdominal CT

NASA Astrophysics Data System (ADS)

Maklad, Ahmed S.; Matsuhiro, Mikio; Suzuki, Hidenobu; Kawata, Yoshiki; Niki, Noboru; Shimada, Mitsuo; Iinuma, Gen

2018-02-01

Liver segmentation is the basis for computer-based planning of hepatic surgical interventions. In diagnosis and analysis of hepatic diseases and surgery planning, automatic segmentation of liver has high importance. Blood vessel (BV) has showed high performance at liver segmentation. In our previous work, we developed a semi-automatic method that segments the liver through the portal phase abdominal CT images in two stages. First stage was interactive segmentation of abdominal blood vessels (ABVs) and subsequent classification into hepatic (HBVs) and non-hepatic (non-HBVs). This stage had 5 interactions that include selective threshold for bone segmentation, selecting two seed points for kidneys segmentation, selection of inferior vena cava (IVC) entrance for starting ABVs segmentation, identification of the portal vein (PV) entrance to the liver and the IVC-exit for classifying HBVs from other ABVs (non-HBVs). Second stage is automatic segmentation of the liver based on segmented ABVs as described in [4]. For full automation of our method we developed a method [5] that segments ABVs automatically tackling the first three interactions. In this paper, we propose full automation of classifying ABVs into HBVs and non- HBVs and consequently full automation of liver segmentation that we proposed in [4]. Results illustrate that the method is effective at segmentation of the liver through the portal abdominal CT images.

Study of seismic activity during the ascending and descending phases of solar activity

NASA Astrophysics Data System (ADS)

Sukma, Indriani; Abidin, Zamri Zainal

2017-06-01

The study of the solar cycle and geomagnetic index associated with the seismic activity from the year 1901 to the end of 2015 has been done for an area that covers the majority of China and its bordering countries. Data of sunspot number, solar wind speed, daily storm time index and earthquake number are collected from NOAA, NASA, WDC, OMNI and USGS databases and websites. The earthquakes are classified into small (M < 5) and large (M ≥ 5) magnitudes (in Richter scale). We investigated the variation of earthquake activities with the geomagnetic storm index due to the solar wind. We focused on their variation in the ascending and descending phases of solar cycle. From our study, we conclude that there is a correlation between the phases' geomagnetic index and solar wind speed. We have also suggested that there is a certain degree of correlation between solar activity and seismicity in these phases. For every solar cycle, we find that there is a trend for earthquakes to occur in greater numbers during the descending phase. This can be explained by the increment in the solar wind speed and geomagnetic storm index during this phase.

Cyclic vomiting syndrome: diagnostic approach and current management strategies.

PubMed

Hayes, William J; VanGilder, Deidra; Berendse, Joseph; Lemon, Michael D; Kappes, John A

2018-01-01

Cyclic vomiting syndrome (CVS) is a disorder characterized by episodes of nausea and vomiting lasting for 1-5 days followed by asymptomatic periods. The etiology of CVS is unknown, but it shares similar characteristics to migraine headaches. CVS is generally classified as having four phases: prodromal, acute/vomiting/hyperemesis, recovery, and remission/interepisodic. Current management strategies include trigger avoidance, abortive and prophylactic medication therapies, and supportive care. The goal of therapy for the remission phase is prophylaxis of further episodes. Antidepressant, antiepileptic, and antimigraine medications show an overall reduction or remission of CVS symptoms in more than 70% of patients. This article provides a summary of diagnostic strategies and reviews current management strategies for CVS.

Cyclic vomiting syndrome: diagnostic approach and current management strategies

PubMed Central

Hayes, William J; VanGilder, Deidra; Berendse, Joseph; Lemon, Michael D; Kappes, John A

2018-01-01

Cyclic vomiting syndrome (CVS) is a disorder characterized by episodes of nausea and vomiting lasting for 1–5 days followed by asymptomatic periods. The etiology of CVS is unknown, but it shares similar characteristics to migraine headaches. CVS is generally classified as having four phases: prodromal, acute/vomiting/hyperemesis, recovery, and remission/interepisodic. Current management strategies include trigger avoidance, abortive and prophylactic medication therapies, and supportive care. The goal of therapy for the remission phase is prophylaxis of further episodes. Antidepressant, antiepileptic, and antimigraine medications show an overall reduction or remission of CVS symptoms in more than 70% of patients. This article provides a summary of diagnostic strategies and reviews current management strategies for CVS. PMID:29520160

Second-order topological insulators and superconductors with an order-two crystalline symmetry

NASA Astrophysics Data System (ADS)

Geier, Max; Trifunovic, Luka; Hoskam, Max; Brouwer, Piet W.

2018-05-01

Second-order topological insulators and superconductors have a gapped excitation spectrum in bulk and along boundaries, but protected zero modes at corners of a two-dimensional crystal or protected gapless modes at hinges of a three-dimensional crystal. A second-order topological phase can be induced by the presence of a bulk crystalline symmetry. Building on Shiozaki and Sato's complete classification of bulk crystalline phases with an order-two crystalline symmetry [Phys. Rev. B 90, 165114 (2014), 10.1103/PhysRevB.90.165114], such as mirror reflection, twofold rotation, or inversion symmetry, we classify all corresponding second-order topological insulators and superconductors. The classification also includes antiunitary symmetries and antisymmetries.

WannierTools: An open-source software package for novel topological materials

NASA Astrophysics Data System (ADS)

Wu, QuanSheng; Zhang, ShengNan; Song, Hai-Feng; Troyer, Matthias; Soluyanov, Alexey A.

2018-03-01

We present an open-source software package WannierTools, a tool for investigation of novel topological materials. This code works in the tight-binding framework, which can be generated by another software package Wannier90 (Mostofi et al., 2008). It can help to classify the topological phase of a given material by calculating the Wilson loop, and can get the surface state spectrum, which is detected by angle resolved photoemission (ARPES) and in scanning tunneling microscopy (STM) experiments. It also identifies positions of Weyl/Dirac points and nodal line structures, calculates the Berry phase around a closed momentum loop and Berry curvature in a part of the Brillouin zone (BZ).

Diagnosis of the three-phase induction motor using thermal imaging

NASA Astrophysics Data System (ADS)

Glowacz, Adam; Glowacz, Zygfryd

2017-03-01

Three-phase induction motors are used in the industry commonly for example woodworking machines, blowers, pumps, conveyors, elevators, compressors, mining industry, automotive industry, chemical industry and railway applications. Diagnosis of faults is essential for proper maintenance. Faults may damage a motor and damaged motors generate economic losses caused by breakdowns in production lines. In this paper the authors develop fault diagnostic techniques of the three-phase induction motor. The described techniques are based on the analysis of thermal images of three-phase induction motor. The authors analyse thermal images of 3 states of the three-phase induction motor: healthy three-phase induction motor, three-phase induction motor with 2 broken bars, three-phase induction motor with faulty ring of squirrel-cage. In this paper the authors develop an original method of the feature extraction of thermal images MoASoID (Method of Areas Selection of Image Differences). This method compares many training sets together and it selects the areas with the biggest changes for the recognition process. Feature vectors are obtained with the use of mentioned MoASoID and image histogram. Next 3 methods of classification are used: NN (the Nearest Neighbour classifier), K-means, BNN (the back-propagation neural network). The described fault diagnostic techniques are useful for protection of three-phase induction motor and other types of rotating electrical motors such as: DC motors, generators, synchronous motors.

Gait Phase Recognition for Lower-Limb Exoskeleton with Only Joint Angular Sensors

PubMed Central

Liu, Du-Xin; Wu, Xinyu; Du, Wenbin; Wang, Can; Xu, Tiantian

2016-01-01

Gait phase is widely used for gait trajectory generation, gait control and gait evaluation on lower-limb exoskeletons. So far, a variety of methods have been developed to identify the gait phase for lower-limb exoskeletons. Angular sensors on lower-limb exoskeletons are essential for joint closed-loop controlling; however, other types of sensors, such as plantar pressure, attitude or inertial measurement unit, are not indispensable.Therefore, to make full use of existing sensors, we propose a novel gait phase recognition method for lower-limb exoskeletons using only joint angular sensors. The method consists of two procedures. Firstly, the gait deviation distances during walking are calculated and classified by Fisher’s linear discriminant method, and one gait cycle is divided into eight gait phases. The validity of the classification results is also verified based on large gait samples. Secondly, we build a gait phase recognition model based on multilayer perceptron and train it with the phase-labeled gait data. The experimental result of cross-validation shows that the model has a 94.45% average correct rate of set (CRS) and an 87.22% average correct rate of phase (CRP) on the testing set, and it can predict the gait phase accurately. The novel method avoids installing additional sensors on the exoskeleton or human body and simplifies the sensory system of the lower-limb exoskeleton. PMID:27690023

The Characteristics and Generating Mechanism of Large Precipitates in Ti-Containing H13 Tool Steel

NASA Astrophysics Data System (ADS)

Xie, You; Cheng, Guoguang; Chen, Lie; Zhang, Yandong; Yan, Qingzhong

2017-02-01

The characteristics of large precipitates in H13 tool steel with 0.015wt% Ti were studied. The result shows that three types of phases larger than 1 μm exist in the as-cast ingot, that is, (Ti, V) (C, N) type phase, (V, Mo, Cr)C type phase and sulfide. (Ti, V) (C, N) type phase could be further classified as the homogeneous Ti-rich one and the Ti-V-rich one in which Ti/V ratio gradually changes. (V, Mo, Cr)C type phase contains the V-rich one and the Mo-Cr-rich one. The compositional characteristics in all of them have little relation with the cutting position or cooling rate. The precipitating process could be well described through calculation by Thermo-Calc software. During solidification, the primary phase (Ti, V)(C, N) first starts to precipitate in the form of Ti-rich carbonitride. With the development of solidification, the ratio of Ti decreases and that of V increases. Then the primary phase Ti-V-rich (Ti, V)(C, N) and V-rich (V, Mo, Cr)C appears successively. Mo-Cr-rich (V, Mo, Cr)C phase does not precipitate until the solidification process reaches to the end. Sulfide precipitates before (V, Mo, Cr)C type phase and it could act as the nucleus of (V, Mo, Cr)C.

Region grouping in natural foliage scenes: image statistics and human performance.

PubMed

Ing, Almon D; Wilson, J Anthony; Geisler, Wilson S

2010-04-27

This study investigated the mechanisms of grouping and segregation in natural scenes of close-up foliage, an important class of scenes for human and non-human primates. Close-up foliage images were collected with a digital camera calibrated to match the responses of human L, M, and S cones at each pixel. The images were used to construct a database of hand-segmented leaves and branches that correctly localizes the image region subtended by each object. We considered a task where a visual system is presented with two image patches and is asked to assign a category label (either same or different) depending on whether the patches appear to lie on the same surface or different surfaces. We estimated several approximately ideal classifiers for the task, each of which used a unique set of image properties. Of the image properties considered, we found that ideal classifiers rely primarily on the difference in average intensity and color between patches, and secondarily on the differences in the contrasts between patches. In psychophysical experiments, human performance mirrored the trends predicted by the ideal classifiers. In an initial phase without corrective feedback, human accuracy was slightly below ideal. After practice with feedback, human accuracy was approximately ideal.

MSEBAG: a dynamic classifier ensemble generation based on `minimum-sufficient ensemble' and bagging

NASA Astrophysics Data System (ADS)

Chen, Lei; Kamel, Mohamed S.

2016-01-01

In this paper, we propose a dynamic classifier system, MSEBAG, which is characterised by searching for the 'minimum-sufficient ensemble' and bagging at the ensemble level. It adopts an 'over-generation and selection' strategy and aims to achieve a good bias-variance trade-off. In the training phase, MSEBAG first searches for the 'minimum-sufficient ensemble', which maximises the in-sample fitness with the minimal number of base classifiers. Then, starting from the 'minimum-sufficient ensemble', a backward stepwise algorithm is employed to generate a collection of ensembles. The objective is to create a collection of ensembles with a descending fitness on the data, as well as a descending complexity in the structure. MSEBAG dynamically selects the ensembles from the collection for the decision aggregation. The extended adaptive aggregation (EAA) approach, a bagging-style algorithm performed at the ensemble level, is employed for this task. EAA searches for the competent ensembles using a score function, which takes into consideration both the in-sample fitness and the confidence of the statistical inference, and averages the decisions of the selected ensembles to label the test pattern. The experimental results show that the proposed MSEBAG outperforms the benchmarks on average.

Suppression of contrast-related artefacts in phase-measuring structured light techniques

NASA Astrophysics Data System (ADS)

Burke, Jan; Zhong, Liang

2017-06-01

Optical metrology using phase measurements has benefited significantly from the introduction of phase-shifting methods, first in interferometry, then also in fringe projection and fringe reflection. As opposed to interferometry, the latter two techniques generally use a spatiotemporal phase-shifting approach: A sequence of fringe patterns with varying spacing is used, and a phase map of each is generated by temporal phase shifting, to allow unique assignments of projector or screen pixels to camera pixels. One ubiquitous problem with phase-shifting structured-light techniques is that phase artefacts appear near regions of the image where the modulation amplitude of the projected or reflected fringes changes abruptly, e.g. near dirt/dust particles on the surface in deflectometry or bright-dark object colour transitions in fringe projection. Near the bright-dark boundaries, responses in the phase maps appear that are not plausible as actual surface features. The phenomenon has been known for a long time but is usually ignored because it does not compromise the overall reliability of results. In deflectometry, however, often the objective is to find and classify small defects, and of course it is then important to distinguish between bogus phase responses caused by fringe modulation changes, and actual surface defects. We present, for what we believe is the first time, an analytical derivation of the error terms, study the parameters influencing the phase artefacts (in particular the fringe period), and suggest some simple algorithms to minimise them.

Auditing the Physical Activity and Parkinson Disease Literature Using the Behavioral Epidemiologic Framework.

PubMed

Swank, Chad; Shearin, Staci; Cleveland, Samantha; Driver, Simon

2017-06-01

Motor and nonmotor symptoms associated with Parkinson disease place individuals at greater risk of sedentary behaviors and comorbidities. Physical activity is one modifiable means of improving health and reducing the risk of morbidity. We applied a behavioral framework to classify existing research on physical activity and Parkinson disease to describe the current evolution and inform knowledge gaps in this area. Research placed in phase 1 establishes links between physical activity and health-related outcomes; phase 2 develops approaches to quantify physical activity behavior; phase 3 identifies factors associated with implementation of physical activity behaviors; phase 4 assesses the effectiveness of interventions to promote activity; and phase 5 disseminates evidence-based recommendations. Peer-reviewed literature was identified by searching PubMed, Google Scholar, and EBSCO-host. We initially identified 287 potential articles. After further review, we excluded 109 articles, leaving 178 included articles. Of these, 75.84% were categorized into phase 1 (n = 135), 10.11% in phase 2 (n = 18), 9.55% into phase 3 (n = 17), 3.37% into phase 4 (n = 6), and 1.12% into phase 5 (n = 2). By applying the behavioral framework to the physical activity literature for people with Parkinson disease, we suggest this area of research is nascent with more than 75% of the literature in phase 1. III. Copyright © 2017 American Academy of Physical Medicine and Rehabilitation. Published by Elsevier Inc. All rights reserved.

Acute phase nutritional screening tool associated with functional outcomes of hip fracture patients: A longitudinal study to compare MNA-SF, MUST, NRS-2002 and GNRI.

PubMed

Inoue, Tatsuro; Misu, Shogo; Tanaka, Toshiaki; Kakehi, Tetsuya; Ono, Rei

2018-02-15

Several hip fracture patients are malnourished, but no study has attempted to determine the optimal nutritional screening tool for predicting functional outcomes. We investigated the association between each nutritional status assessed by four nutritional screening tools at admission and functional outcomes during the postoperative acute phase in hip fracture patients. The Mini Nutritional Assessment-Short Form (MNA-SF), the Malnutrition Universal Screening Tool (MUST), the Nutritional Risk Score 2002 (NRS-2002) and the Geriatric Nutritional Risk Index (GNRI) were assessed at admission before surgery. We evaluated the motor domain of the functional independence measure (motor-FIM) score at discharge, efficiency on the motor-FIM (change in the motor-FIM score after postoperative rehabilitation divided by postoperative length of hospital stay), and 10-m walking speed at postoperative 14 days as functional outcomes. Two hundred and five patients (mean patient age, 83.5 ± 7.0 years; range, 65-100 years; 82% female) were included. The MNA-SF evaluation classified 56 patients as well-nourished, 103 as at risk of malnutrition and 46 as malnourished. The MUST evaluation classified 97 patients as low risk, 42 as medium risk and 66 as high risk. The NRS-2002 evaluation classified 89 patients as well-nourished, 69 as medium risk and 47 as nutritionally at risk. The GNRI evaluation classified 44 patients as no risk, 74 as low risk and 87 as a major risk. Multiple linear regression analysis revealed that MNA-SF had a significant association with discharge motor-FIM (well-nourished vs. at risk of malnutrition, standardised β = -0.06, p = 0.04; vs. malnourished, standardised β = -0.32, p < 0.01), efficiency on the motor-FIM (well-nourished vs. malnourished, standardised β = -0.19, p = 0.02) and 10-m walking speed (well-nourished vs. malnourished, standardised β = -0.30, p < 0.01). The GNRI was significantly associated with 10-m walking speed (no risk vs. mild risk, standardised β = -0.23, p = 0.02; vs. major risk, standardised β = -0.37, p < 0.01), but not of motor-FIM and efficiency on the motor-FIM. No significant relationships were found among MUST and NRS-2002 and any functional outcomes. The MNA-SF was found to be an optimal nutritional screening tool to associate with functional outcomes during the postoperative acute phase of elderly hip fracture patients. Copyright © 2018 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

Gluon dynamics, center symmetry, and the deconfinement phase transition in SU(3) pure Yang-Mills theory

NASA Astrophysics Data System (ADS)

Silva, P. J.; Oliveira, O.

2016-06-01

The correlations between the modulus of the Polyakov loop, its phase θ , and the Landau gauge gluon propagator at finite temperature are investigated in connection with the center symmetry for pure Yang-Mills SU(3) theory. In the deconfined phase, where the center symmetry is spontaneously broken, the phase of the Polyakov loop per configuration is close to θ =0 , ±2 π /3 . We find that the gluon propagator form factors associated with θ ≈0 differ quantitatively and qualitatively from those associated to θ ≈±2 π /3 . This difference between the form factors is a property of the deconfined phase and a sign of the spontaneous breaking of the center symmetry. Furthermore, given that this difference vanishes in the confined phase, it can be used as an order parameter associated to the deconfinement transition. For simulations near the critical temperature Tc, the difference between the propagators associated to θ ≈0 and θ ≈±2 π /3 allows one to classify the configurations as belonging to the confined or deconfined phase. This establishes a selection procedure which has a measurable impact on the gluon form factors. Our results also show that the absence of the selection procedure can be erroneously interpreted as lattice artifacts.

Using phase for radar scatterer classification

NASA Astrophysics Data System (ADS)

Moore, Linda J.; Rigling, Brian D.; Penno, Robert P.; Zelnio, Edmund G.

2017-04-01

Traditional synthetic aperture radar (SAR) systems tend to discard phase information of formed complex radar imagery prior to automatic target recognition (ATR). This practice has historically been driven by available hardware storage, processing capabilities, and data link capacity. Recent advances in high performance computing (HPC) have enabled extremely dense storage and processing solutions. Therefore, previous motives for discarding radar phase information in ATR applications have been mitigated. First, we characterize the value of phase in one-dimensional (1-D) radar range profiles with respect to the ability to correctly estimate target features, which are currently employed in ATR algorithms for target discrimination. These features correspond to physical characteristics of targets through radio frequency (RF) scattering phenomenology. Physics-based electromagnetic scattering models developed from the geometrical theory of diffraction are utilized for the information analysis presented here. Information is quantified by the error of target parameter estimates from noisy radar signals when phase is either retained or discarded. Operating conditions (OCs) of signal-tonoise ratio (SNR) and bandwidth are considered. Second, we investigate the value of phase in 1-D radar returns with respect to the ability to correctly classify canonical targets. Classification performance is evaluated via logistic regression for three targets (sphere, plate, tophat). Phase information is demonstrated to improve radar target classification rates, particularly at low SNRs and low bandwidths.

Numerical analysis of natural convection in liquid droplets by phase change

NASA Astrophysics Data System (ADS)

Duh, J. C.; Yang, Wen-Jei

1989-09-01

A numerical analysis is performed on thermocapillary buoyancy convection induced by phase change in a liquid droplet. A finite-difference code is developed using an alternating-direction implicit (ADI) scheme. The intercoupling relation between thermocapillary force, buoyancy force, fluid property, heat transfer, and phase change, along with their effects on the induced flow patterns, are disclosed. The flow is classified into three types: thermocapillary, buoyancy, and combined convection. Among the three mechanisms, the combined convection simulates the experimental observations quite well, and the basic mechanism of the observed convection inside evaporating sessile drops is thus identified. It is disclosed that evaporation initiates unstable convection, while condensation always brings about a stable density distribution which eventually damps out all fluid disturbances. Another numerical model is presented to study the effect of boundary recession due to evaporation, and the 'peeling-off' effect (the removal of the surface layer of fluid by evaporation) is shown to be relevant.

Density profiles around A+B→C reaction-diffusion fronts in partially miscible systems: A general classification.

PubMed

Loodts, V; Trevelyan, P M J; Rongy, L; De Wit, A

2016-10-01

Various spatial density profiles can develop in partially miscible stratifications when a phase A dissolves with a finite solubility into a host phase containing a dissolved reactant B. We investigate theoretically the impact of an A+B→C reaction on such density profiles in the host phase and classify them in a parameter space spanned by the ratios of relative contributions to density and diffusion coefficients of the chemical species. While the density profile is either monotonically increasing or decreasing in the nonreactive case, reactions combined with differential diffusivity can create eight different types of density profiles featuring up to two extrema in density, at the reaction front or below it. We use this framework to predict various possible hydrodynamic instability scenarios inducing buoyancy-driven convection around such reaction fronts when they propagate parallel to the gravity field.

An Ambulatory System for Gait Monitoring Based on Wireless Sensorized Insoles

PubMed Central

González, Iván; Fontecha, Jesús; Hervás, Ramón; Bravo, José

2015-01-01

A new gait phase detection system for continuous monitoring based on wireless sensorized insoles is presented. The system can be used in gait analysis mobile applications, and it is designed for real-time demarcation of gait phases. The system employs pressure sensors to assess the force exerted by each foot during walking. A fuzzy rule-based inference algorithm is implemented on a smartphone and used to detect each of the gait phases based on the sensor signals. Additionally, to provide a solution that is insensitive to perturbations caused by non-walking activities, a probabilistic classifier is employed to discriminate walking forward from other low-level activities, such as turning, walking backwards, lateral walking, etc. The combination of these two algorithms constitutes the first approach towards a continuous gait assessment system, by means of the avoidance of non-walking influences. PMID:26184199

Numerical analysis of natural convection in liquid droplets by phase change

NASA Technical Reports Server (NTRS)

Duh, J. C.; Yang, Wen-Jei

1989-01-01

A numerical analysis is performed on thermocapillary buoyancy convection induced by phase change in a liquid droplet. A finite-difference code is developed using an alternating-direction implicit (ADI) scheme. The intercoupling relation between thermocapillary force, buoyancy force, fluid property, heat transfer, and phase change, along with their effects on the induced flow patterns, are disclosed. The flow is classified into three types: thermocapillary, buoyancy, and combined convection. Among the three mechanisms, the combined convection simulates the experimental observations quite well, and the basic mechanism of the observed convection inside evaporating sessile drops is thus identified. It is disclosed that evaporation initiates unstable convection, while condensation always brings about a stable density distribution which eventually damps out all fluid disturbances. Another numerical model is presented to study the effect of boundary recession due to evaporation, and the 'peeling-off' effect (the removal of the surface layer of fluid by evaporation) is shown to be relevant.

Manipulating Topological Edge Spins in One-Dimensional Optical Lattice

NASA Astrophysics Data System (ADS)

Liu, Xiong-Jun; Liu, Zheng-Xin; Cheng, Meng

2013-03-01

We propose to observe and manipulate topological edge spins in 1D optical lattice based on currently available experimental platforms. Coupling the atomic spin states to a laser-induced periodic Zeeman field, the lattice system can be driven into a symmetry protected topological (SPT) phase, which belongs to the chiral unitary (AIII) class protected by particle number conservation and chiral symmetries. In free-fermion case the SPT phase is classified by a Z invariant which reduces to Z4 with interactions. The zero edge modes of the SPT phase are spin-polarized, with left and right edge spins polarized to opposite directions and forming a topological spin-qubit (TSQ). We demonstrate a novel scheme to manipulate the zero modes and realize single spin control in optical lattice. The manipulation of TSQs has potential applications to quantum computation. We acknowledge the support from JQI-NSF-PFC, Microsoft-Q, and DARPA- QuEST.

Quantum Hall ferromagnets and transport properties of buckled Dirac materials

NASA Astrophysics Data System (ADS)

Luo, Wenchen; Chakraborty, Tapash

2015-10-01

We study the ground states and low-energy excitations of a generic Dirac material with spin-orbit coupling and a buckling structure in the presence of a magnetic field. The ground states can be classified into three types under different conditions: SU(2), easy-plane, and Ising quantum Hall ferromagnets. For the SU(2) and the easy-plane quantum Hall ferromagnets there are goldstone modes in the collective excitations, while all the modes are gapped in an Ising-type ground state. We compare the Ising quantum Hall ferromagnet with that of bilayer graphene and present the domain-wall solution at finite temperatures. We then specify the phase transitions and transport gaps in silicene in Landau levels 0 and 1. The phase diagram depends strongly on the magnetic field and the dielectric constant. We note that there exist triple points in the phase diagrams in Landau level N =1 that could be observed in experiments.

Schaeffler-Type Phase Diagram of Ti-Based Alloys

NASA Astrophysics Data System (ADS)

Ishida, K.

2017-10-01

The α(hcp)/β(bcc) phase equilibria of Ti-based multi-component alloys can be described by a Schaeffler-type diagram, where Al and Mo equivalents (Aleq and Moeq) are used. Aleq is thermodynamically defined by the ratio of partial molar free energy changes transfer of one mole of each α forming element and Al from a dilute solution of α to β phases, while Moeq is also deduced by similar thermodynamic quantities of β forming element and Mo. Aleq and Moeq for 40 alloying elements are estimated from the thermodynamic parameters assessed by Kaufman and Murray. It is shown that three types of Ti alloys, i.e., α and near α, α+β, and β alloys, can be exactly classified using Aleq and Moeq. The Ms and β transus temperatures can also be predicted by Aleq and Moeq. The proposed Aleq and Moeq are very useful for alloy design, heat treatment, and microstructural evolution of Ti-based alloys.

Tomographic phase microscopy and its biological applications

NASA Astrophysics Data System (ADS)

Choi, Wonshik

2012-12-01

Conventional interferometric microscopy techniques such as digital holographic microscopy and quantitative phase microscopy are often classified as 3D imaging techniques because a recorded complex field image can be numerically propagated to a different depth. In a strict sense, however, a single complex field image contains only 2D information on a specimen. The measured 2D image is only a subset of the 3D structure. For the 3D mapping of an object, multiple independent 2D images are to be taken, for example at multiple incident angles or wavelengths, and then combined by the so-called optical diffraction tomography (ODT). In this Letter, tomographic phase microscopy (TPM) is reviewed that experimentally realizes the concept of the ODT for the 3D mapping of biological cells in their native state, and some of its interesting biological and biomedical applications are introduced. [Figure not available: see fulltext.

Automated detection of age-related macular degeneration in OCT images using multiple instance learning

NASA Astrophysics Data System (ADS)

Sun, Weiwei; Liu, Xiaoming; Yang, Zhou

2017-07-01

Age-related Macular Degeneration (AMD) is a kind of macular disease which mostly occurs in old people，and it may cause decreased vision or even lead to permanent blindness. Drusen is an important clinical indicator for AMD which can help doctor diagnose disease and decide the strategy of treatment. Optical Coherence Tomography (OCT) is widely used in the diagnosis of ophthalmic diseases, include AMD. In this paper, we propose a classification method based on Multiple Instance Learning (MIL) to detect AMD. Drusen can exist in a few slices of OCT images, and MIL is utilized in our method. We divided the method into two phases: training phase and testing phase. We train the initial features and clustered to create a codebook, and employ the trained classifier in the test set. Experiment results show that our method achieved high accuracy and effectiveness.

Diagnosis of multiple sclerosis from EEG signals using nonlinear methods.

PubMed

Torabi, Ali; Daliri, Mohammad Reza; Sabzposhan, Seyyed Hojjat

2017-12-01

EEG signals have essential and important information about the brain and neural diseases. The main purpose of this study is classifying two groups of healthy volunteers and Multiple Sclerosis (MS) patients using nonlinear features of EEG signals while performing cognitive tasks. EEG signals were recorded when users were doing two different attentional tasks. One of the tasks was based on detecting a desired change in color luminance and the other task was based on detecting a desired change in direction of motion. EEG signals were analyzed in two ways: EEG signals analysis without rhythms decomposition and EEG sub-bands analysis. After recording and preprocessing, time delay embedding method was used for state space reconstruction; embedding parameters were determined for original signals and their sub-bands. Afterwards nonlinear methods were used in feature extraction phase. To reduce the feature dimension, scalar feature selections were done by using T-test and Bhattacharyya criteria. Then, the data were classified using linear support vector machines (SVM) and k-nearest neighbor (KNN) method. The best combination of the criteria and classifiers was determined for each task by comparing performances. For both tasks, the best results were achieved by using T-test criterion and SVM classifier. For the direction-based and the color-luminance-based tasks, maximum classification performances were 93.08 and 79.79% respectively which were reached by using optimal set of features. Our results show that the nonlinear dynamic features of EEG signals seem to be useful and effective in MS diseases diagnosis.

Ketosis-prone atypical diabetes in Cameroonian people with hyperglycaemic crisis: frequency, clinical and metabolic phenotypes.

PubMed

Lontchi-Yimagou, E; Nguewa, J L; Assah, F; Noubiap, J J; Boudou, P; Djahmeni, E; Balti, E V; Atogho-Tiedeu, B; Gautier, J F; Mbanya, J C; Sobngwi, E

2017-03-01

It is unclear whether ketosis-prone diabetes is a specific type or a subtype of Type 2 diabetes. We aimed to describe the clinical and metabolic features of ketosis-prone diabetes in a sub-Saharan population. We consecutively enrolled and characterized 173 people with non-autoimmune diabetes admitted for hyperglycaemic crisis at the Yaoundé Central Hospital, Cameroon. Blood samples were collected for fasting glucose, HbA 1c , lipid profile and C-peptide assays with insulin resistance and secretion estimation by homeostasis model assessment. People were classified as having Type 2 diabetes (n = 124) or ketosis-prone diabetes (n = 49). Ketosis-prone diabetes was sub-classified as new-onset ketotic phase (n = 34) or non-ketotic phase (n = 15). Ketosis-prone diabetes was found in 28.3% of the hyperglycaemic crises. Age at diabetes diagnosis was comparable in Type 2 and ketosis-prone diabetes [48 ± 14 vs 47 ± 11 years; P = 0.13] with a similar sex distribution. Overall BMI was 27.7 ± 13.4 kg/m 2 and was ≥ 25 kg/m 2 in 55.8% of those taking part, however, 73.5% of those with ketosis-prone diabetes reported weight loss of > 5% at diagnosis. Blood pressure and lipid profile were comparable in both types. Ketosis-prone diabetes in the ketotic phase was characterized by lower insulin secretion and higher serum triglycerides compared with non-ketotic ketosis prone and Type 2 diabetes. Type 2 and ketosis prone diabetes in the non-ketotic phase were comparable in terms of lipid profile, blood pressure, waist-to-hip ratio, BMI and fat mass, insulin secretion and insulin resistance indices. Ketosis-prone diabetes is likely to be a subtype of Type 2 diabetes with the potential to develop acute insulinopenic episodes. © 2016 Diabetes UK.

Country-wide distance training for delivery of screening and brief intervention for problematic substance use: A pilot evaluation of participant experiences and patient outcomes.

PubMed

Carneiro, Ana Paula Leal; Souza-Formigoni, Maria Lucia Oliveira

2018-01-02

In this study, the authors evaluated if the 120-hour distance learning (DL) course SUPERA (an acronym in Portuguese meaning "System for detection of excessive use or dependence on psychoactive substances: brief Intervention, social reinsertion and follow-up") was an effective way to train health professionals and social workers to apply screening and brief intervention (SBI) for patients with substance use disorders. In the first phase, 2420 health professionals or social workers, who had completed the course, answered an online survey about their use of the SBI. In the second phase, 25 of those professionals applied the ASSIST (Alcohol, Smoking and Substance Involvement Screening Test) followed by a brief intervention (BI) to patients with substance use disorders. Three months after the SBI delivery, independent researchers followed up 79 patients who had received SBI, reapplying the ASSIST and a questionnaire to evaluate the patients'/clients' satisfaction with the intervention they received. In the first phase, it was found that most health professionals and social workers who completed the course applied the SBI in their work and felt very motivated to do it. In the second phase of the study, at a 3-month follow-up, most patients had significantly reduced their ASSIST scores in respect of alcohol and cocaine/crack in relation to their baseline levels. Those patients classified by their ASSIST score as "suggestive of dependence" presented a significant reduction in their scores regarding alcohol, tobacco, and cocaine/crack, whereas those classified as "at risk" presented a reduction in respect of alcohol problems only. Patients associated changes in their substance use with the SBI received. A reduction in substance use-related problems was associated with the SBI applied by the health professionals or social workers trained by the DL course SUPERA. Two significant limitations of this study were the small number of participants (professionals and patients in the follow-up) and the absence of a control group in the second phase of the study.

Predicting treatment response to cognitive behavioral therapy in panic disorder with agoraphobia by integrating local neural information.

PubMed

Hahn, Tim; Kircher, Tilo; Straube, Benjamin; Wittchen, Hans-Ulrich; Konrad, Carsten; Ströhle, Andreas; Wittmann, André; Pfleiderer, Bettina; Reif, Andreas; Arolt, Volker; Lueken, Ulrike

2015-01-01

Although neuroimaging research has made substantial progress in identifying the large-scale neural substrate of anxiety disorders, its value for clinical application lags behind expectations. Machine-learning approaches have predictive potential for individual-patient prognostic purposes and might thus aid translational efforts in psychiatric research. To predict treatment response to cognitive behavioral therapy (CBT) on an individual-patient level based on functional magnetic resonance imaging data in patients with panic disorder with agoraphobia (PD/AG). We included 49 patients free of medication for at least 4 weeks and with a primary diagnosis of PD/AG in a longitudinal study performed at 8 clinical research institutes and outpatient centers across Germany. The functional magnetic resonance imaging study was conducted between July 2007 and March 2010. Twelve CBT sessions conducted 2 times a week focusing on behavioral exposure. Treatment response was defined as exceeding a 50% reduction in Hamilton Anxiety Rating Scale scores. Blood oxygenation level-dependent signal was measured during a differential fear-conditioning task. Regional and whole-brain gaussian process classifiers using a nested leave-one-out cross-validation were used to predict the treatment response from data acquired before CBT. Although no single brain region was predictive of treatment response, integrating regional classifiers based on data from the acquisition and the extinction phases of the fear-conditioning task for the whole brain yielded good predictive performance (accuracy, 82%; sensitivity, 92%; specificity, 72%; P < .001). Data from the acquisition phase enabled 73% correct individual-patient classifications (sensitivity, 80%; specificity, 67%; P < .001), whereas data from the extinction phase led to an accuracy of 74% (sensitivity, 64%; specificity, 83%; P < .001). Conservative reanalyses under consideration of potential confounders yielded nominally lower but comparable accuracy rates (acquisition phase, 70%; extinction phase, 71%; combined, 79%). Predicting treatment response to CBT based on functional neuroimaging data in PD/AG is possible with high accuracy on an individual-patient level. This novel machine-learning approach brings personalized medicine within reach, directly supporting clinical decisions for the selection of treatment options, thus helping to improve response rates.

Drop size distribution comparisons between Parsivel and 2-D video disdrometers

NASA Astrophysics Data System (ADS)

Thurai, M.; Petersen, W. A.; Tokay, A.; Schultz, C.; Gatlin, P.

2011-05-01

Measurements from a 2-D video disdrometer (2DVD) have been used for drop size distribution (DSD) comparisons with co-located Parsivel measurements in Huntsville, Alabama. The comparisons were made in terms of the mass-weighted mean diameter, Dm, the standard deviation of the mass-spectrum, σm, and the rainfall rate, R, all based on 1-min DSD from the two instruments. Time series comparisons show close agreement in all three parameters for cases where R was less than 20 mm h-1. In four cases, discrepancies in all three parameters were seen for "heavy" events, with the Parsivel showing higher Dm, σm and R, when R reached high values (particularly above 30 mm h-1). Possible causes for the discrepancies include the presence of a small percentage of non-fully melted hydrometers, with higher than expected fall velocity and with very different axis ratios as compared with rain, indicating small hail or ice pellets or graupel. We also present here Parsivel-to-Parsivel comparisons as well as comparisons between two 2DVD instruments, namely a low-profile unit and the latest generation, "compact unit" which was installed at the same site in November 2009. The comparisons are included to assess the variability between the same types of instrument. Correlation coefficients and the fractional standard errors are compared.

Probing aerosol indirect effect on deep convection using idealized cloud-resolving simulations with parameterized large-scale dynamics.

NASA Astrophysics Data System (ADS)

Anber, U.; Wang, S.; Gentine, P.; Jensen, M. P.

2017-12-01

A framework is introduced to investigate the indirect impact of aerosol loading on tropical deep convection using 3-dimentional idealized cloud-system resolving simulations with coupled large-scale circulation. The large scale dynamics is parameterized using a spectral weak temperature gradient approximation that utilizes the dominant balance in the tropics between adiabatic cooling and diabatic heating. Aerosol loading effect is examined by varying the number concentration of nuclei (CCN) to form cloud droplets in the bulk microphysics scheme over a wide range from 30 to 5000 without including any radiative effect as the radiative cooling is prescribed at a constant rate, to isolate the microphysical effect. Increasing aerosol number concentration causes mean precipitation to decrease monotonically, despite the increase in cloud condensates. Such reduction in precipitation efficiency is attributed to reduction in the surface enthalpy fluxes, and not to the divergent circulation, as the gross moist stability remains unchanged. We drive a simple scaling argument based on the moist static energy budget, that enables a direct estimation of changes in precipitation given known changes in surfaces enthalpy fluxes and the constant gross moist stability. The impact on cloud hydrometers and microphysical properties is also examined and is consistent with the macro-physical picture.

Evaluating Cloud Initialization in a Convection-permit NWP Model

NASA Astrophysics Data System (ADS)

Li, Jia; Chen, Baode

2015-04-01

In general, to avoid "double counting precipitation" problem, in convection permit NWP models, it was a common practice to turn off convective parameterization. However, if there were not any cloud information in the initial conditions, the occurrence of precipitation could be delayed due to spin-up of cloud field or microphysical variables. In this study, we utilized the complex cloud analysis package from the Advanced Regional Prediction System (ARPS) to adjust the initial states of the model on water substance, such as cloud water, cloud ice, rain water, et al., that is, to initialize the microphysical variables (i.e., hydrometers), mainly based on radar reflectivity observations. Using the Advanced Research WRF (ARW) model, numerical experiments with/without cloud initialization and convective parameterization were carried out at grey-zone resolutions (i.e. 1, 3, and 9 km). The results from the experiments without convective parameterization indicate that model ignition with radar reflectivity can significantly reduce spin-up time and accurately simulate precipitation at the initial time. In addition, it helps to improve location and intensity of predicted precipitation. With grey-zone resolutions (i.e. 1, 3, and 9 km), using the cumulus convective parameterization scheme (without radar data) cannot produce realistic precipitation at the early time. The issues related to microphysical parametrization associated with cloud initialization were also discussed.

All-Elastomer-Based Triboelectric Nanogenerator as a Keyboard Cover To Harvest Typing Energy.

PubMed

Li, Shengming; Peng, Wenbo; Wang, Jie; Lin, Long; Zi, Yunlong; Zhang, Gong; Wang, Zhong Lin

2016-08-23

The drastic expansion of consumer electronics (like personal computers, touch pads, smart phones, etc.) creates many human-machine interfaces and multiple types of interactions between human and electronics. Considering the high frequency of such operations in our daily life, an extraordinary amount of biomechanical energy from typing or pressing buttons is available. In this study, we have demonstrated a highly flexible triboelectric nanogenerator (TENG) solely made from elastomeric materials as a cover on a conventional keyboard to harvest biomechanical energy from typing. A dual-mode working mechanism is established with a high transferred charge density of ∼140 μC/m(2) due to both structural and material innovations. We have also carried out fundamental investigations of its performance dependence on various structural factors for optimizing the electric output in practice. The fully packaged keyboard-shaped TENG is further integrated with a horn-like polypyrrole-based supercapacitor as a self-powered system. Typing in normal speed for 1 h, ∼8 × 10(-4) J electricity could be stored, which is capable of driving an electronic thermometer/hydrometer. Our keyboard cover also performs outstanding long-term stability, water resistance, as well as insensitivity to surface conditions, and the last feature makes it useful to research the typing behaviors of different people.

Improving medium-range ensemble streamflow forecasts through statistical post-processing

NASA Astrophysics Data System (ADS)

Mendoza, Pablo; Wood, Andy; Clark, Elizabeth; Nijssen, Bart; Clark, Martyn; Ramos, Maria-Helena; Nowak, Kenneth; Arnold, Jeffrey

2017-04-01

Probabilistic hydrologic forecasts are a powerful source of information for decision-making in water resources operations. A common approach is the hydrologic model-based generation of streamflow forecast ensembles, which can be implemented to account for different sources of uncertainties - e.g., from initial hydrologic conditions (IHCs), weather forecasts, and hydrologic model structure and parameters. In practice, hydrologic ensemble forecasts typically have biases and spread errors stemming from errors in the aforementioned elements, resulting in a degradation of probabilistic properties. In this work, we compare several statistical post-processing techniques applied to medium-range ensemble streamflow forecasts obtained with the System for Hydromet Applications, Research and Prediction (SHARP). SHARP is a fully automated prediction system for the assessment and demonstration of short-term to seasonal streamflow forecasting applications, developed by the National Center for Atmospheric Research, University of Washington, U.S. Army Corps of Engineers, and U.S. Bureau of Reclamation. The suite of post-processing techniques includes linear blending, quantile mapping, extended logistic regression, quantile regression, ensemble analogs, and the generalized linear model post-processor (GLMPP). We assess and compare these techniques using multi-year hindcasts in several river basins in the western US. This presentation discusses preliminary findings about the effectiveness of the techniques for improving probabilistic skill, reliability, discrimination, sharpness and resolution.

Pattern recognition of the targets with help of polarization properties of the signal

NASA Astrophysics Data System (ADS)

Ponomaryov, Volodymyr I.; de Rivera, Luis N.; Castellanos, Aldo B.; Popov, Anatoly V.

1999-10-01

We proposed to use the possibility of recognition of the targets on background of the scattering from the surface, weather objects with the help of polarimetric 3-cm radar. It has been investigated such polarization characteristics: the amplitudes of the polarization matrix elements; an anisotropy coefficient; depolarization coefficient; asymmetry coefficient; the energy section was less than 1 dB at ranges up to 15 km and less than 1.5 dB at ranges up to 100 km. During the experiments urban objects and 6 various ships of small displacement having the closest values of the backscattering cross-section were used. The analysis has shown: the factor of the polarization selection for anisotropy objects and weather objects had the values about 0.02-0.08 Isotropy had the values of polarimetric correlation factor for hydrometers about 0.7-0.8, for earth surface about 0.8-0.9, for sea surface - from 0.33 to 0.7. The results of the work of recognition algorithm of a class 'concrete objects', and 'metal objects' are submitted as example in the paper. The result of experiments have shown that the probability of correct recognition of the identified objects was in the limits from 0.93 to 0.97.

Video Analytics Evaluation: Survey of Datasets, Performance Metrics and Approaches

DTIC Science & Technology

2014-09-01

training phase and a fusion of the detector outputs. 6.3.1 Training Techniques 1. Bagging: The basic idea of Bagging is to train multiple classifiers...can reduce more noise interesting points. Person detection and background subtraction methods were used to create hot regions. The hot regions were...detection algorithms are incorporated with MHT to construct one integrated detector /tracker. 6.8 IRDS-CASIA team IRDS-CASIA proposed a method to solve a

A Scientific Understanding of Keystroke Dynamics

DTIC Science & Technology

2012-01-01

keystroke- dynamics classifiers. Obaidat and Sadoun (1997) had 16 subjects type their own and each others’ user IDs. They constructed neural networks and a...puts are assigned high anomaly scores. In the training phase, the neural network is constructed with p input nodes and p out- put nodes (where p is...Berlin. S. Cho, C. Han, D. H. Han, and H.-I. Kim. Web- based keystroke dynamics identity ver- ification using neural network . Journal of Organizational

Loop Braiding Statistics and Interacting Fermionic Symmetry-Protected Topological Phases in Three Dimensions

NASA Astrophysics Data System (ADS)

Cheng, Meng; Tantivasadakarn, Nathanan; Wang, Chenjie

2018-01-01

We study Abelian braiding statistics of loop excitations in three-dimensional gauge theories with fermionic particles and the closely related problem of classifying 3D fermionic symmetry-protected topological (FSPT) phases with unitary symmetries. It is known that the two problems are related by turning FSPT phases into gauge theories through gauging the global symmetry of the former. We show that there exist certain types of Abelian loop braiding statistics that are allowed only in the presence of fermionic particles, which correspond to 3D "intrinsic" FSPT phases, i.e., those that do not stem from bosonic SPT phases. While such intrinsic FSPT phases are ubiquitous in 2D systems and in 3D systems with antiunitary symmetries, their existence in 3D systems with unitary symmetries was not confirmed previously due to the fact that strong interaction is necessary to realize them. We show that the simplest unitary symmetry to support 3D intrinsic FSPT phases is Z2×Z4. To establish the results, we first derive a complete set of physical constraints on Abelian loop braiding statistics. Solving the constraints, we obtain all possible Abelian loop braiding statistics in 3D gauge theories, including those that correspond to intrinsic FSPT phases. Then, we construct exactly soluble state-sum models to realize the loop braiding statistics. These state-sum models generalize the well-known Crane-Yetter and Dijkgraaf-Witten models.

Developing medical device software in compliance with regulations.

PubMed

Zema, M; Rosati, S; Gioia, V; Knaflitz, M; Balestra, G

2015-08-01

In the last decade, the use of information technology (IT) in healthcare has taken a growing role. In fact, the adoption of an increasing number of computer tools has led to several benefits related to the process of patient care and allowed easier access to social and health care resources. At the same time this trend gave rise to new challenges related to the implementation of these new technologies. Software used in healthcare can be classified as medical devices depending on the way they are used and on their functional characteristics. If they are classified as medical devices they must satisfy specific regulations. The aim of this work is to present a software development framework that can allow the production of safe and high quality medical device software and to highlight the correspondence between each software development phase and the appropriate standard and/or regulation.

A Machine Learns to Predict the Stability of Tightly Packed Planetary Systems

NASA Astrophysics Data System (ADS)

Tamayo, Daniel; Silburt, Ari; Valencia, Diana; Menou, Kristen; Ali-Dib, Mohamad; Petrovich, Cristobal; Huang, Chelsea X.; Rein, Hanno; van Laerhoven, Christa; Paradise, Adiv; Obertas, Alysa; Murray, Norman

2016-12-01

The requirement that planetary systems be dynamically stable is often used to vet new discoveries or set limits on unconstrained masses or orbital elements. This is typically carried out via computationally expensive N-body simulations. We show that characterizing the complicated and multi-dimensional stability boundary of tightly packed systems is amenable to machine-learning methods. We find that training an XGBoost machine-learning algorithm on physically motivated features yields an accurate classifier of stability in packed systems. On the stability timescale investigated (107 orbits), it is three orders of magnitude faster than direct N-body simulations. Optimized machine-learning classifiers for dynamical stability may thus prove useful across the discipline, e.g., to characterize the exoplanet sample discovered by the upcoming Transiting Exoplanet Survey Satellite. This proof of concept motivates investing computational resources to train algorithms capable of predicting stability over longer timescales and over broader regions of phase space.

Quaternion-Based Signal Analysis for Motor Imagery Classification from Electroencephalographic Signals.

PubMed

Batres-Mendoza, Patricia; Montoro-Sanjose, Carlos R; Guerra-Hernandez, Erick I; Almanza-Ojeda, Dora L; Rostro-Gonzalez, Horacio; Romero-Troncoso, Rene J; Ibarra-Manzano, Mario A

2016-03-05

Quaternions can be used as an alternative to model the fundamental patterns of electroencephalographic (EEG) signals in the time domain. Thus, this article presents a new quaternion-based technique known as quaternion-based signal analysis (QSA) to represent EEG signals obtained using a brain-computer interface (BCI) device to detect and interpret cognitive activity. This quaternion-based signal analysis technique can extract features to represent brain activity related to motor imagery accurately in various mental states. Experimental tests in which users where shown visual graphical cues related to left and right movements were used to collect BCI-recorded signals. These signals were then classified using decision trees (DT), support vector machine (SVM) and k-nearest neighbor (KNN) techniques. The quantitative analysis of the classifiers demonstrates that this technique can be used as an alternative in the EEG-signal modeling phase to identify mental states.

Quaternion-Based Signal Analysis for Motor Imagery Classification from Electroencephalographic Signals

PubMed Central

Batres-Mendoza, Patricia; Montoro-Sanjose, Carlos R.; Guerra-Hernandez, Erick I.; Almanza-Ojeda, Dora L.; Rostro-Gonzalez, Horacio; Romero-Troncoso, Rene J.; Ibarra-Manzano, Mario A.

2016-01-01

Quaternions can be used as an alternative to model the fundamental patterns of electroencephalographic (EEG) signals in the time domain. Thus, this article presents a new quaternion-based technique known as quaternion-based signal analysis (QSA) to represent EEG signals obtained using a brain-computer interface (BCI) device to detect and interpret cognitive activity. This quaternion-based signal analysis technique can extract features to represent brain activity related to motor imagery accurately in various mental states. Experimental tests in which users where shown visual graphical cues related to left and right movements were used to collect BCI-recorded signals. These signals were then classified using decision trees (DT), support vector machine (SVM) and k-nearest neighbor (KNN) techniques. The quantitative analysis of the classifiers demonstrates that this technique can be used as an alternative in the EEG-signal modeling phase to identify mental states. PMID:26959029

Classifying Degraded Modern Polymeric Museum Artefacts by Their Smell.

PubMed

Curran, Katherine; Underhill, Mark; Grau-Bové, Josep; Fearn, Tom; Gibson, Lorraine T; Strlič, Matija

2018-02-05

The use of VOC analysis to diagnose degradation in modern polymeric museum artefacts is reported. Volatile organic compound (VOC) analysis is a successful method for diagnosing medical conditions but to date has found little application in museums. Modern polymers are increasingly found in museum collections but pose serious conservation difficulties owing to unstable and widely varying formulations. Solid-phase microextraction gas chromatography/mass spectrometry and linear discriminant analysis were used to classify samples according to the length of time they had been artificially degraded. Accuracies in classification of 50-83 % were obtained after validation with separate test sets. The method was applied to three artefacts from collections at Tate to detect evidence of degradation. This approach could be used for any material in heritage collections and more widely in the field of polymer degradation. © 2018 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.

Improving atrial fibrillation detection in patients with implantable cardiac devices by means of a remote monitoring and management application.

PubMed

Zoppo, Franco; Facchin, Domenico; Molon, Giulio; Zanotto, Gabriele; Catanzariti, Domenico; Rossillo, Antonio; Baccillieri, Maria Stella; Menard, Cecile; Comisso, Jennifer; Gentili, Alessandra; Grammatico, Andrea; Bertaglia, Emanuele; Proclemer, Alessandro

2014-12-01

Atrial fibrillation (AF) is common in patients with cardiac implantable electronic devices (CIED) and has been associated with an increased stroke risk. The aim of our project was to assess the clinical value of a web-based application, Discovery Link AFinder, in improving AF detection in CIED patients. Seven Italian hospitals performed an observational study consisting of four phases. During phase 1, expert nurses and cardiologists prospectively followed-up CIED patients via in-hospital examinations and remote monitoring, and classified clinically relevant events, particularly AF occurrence. During phase 2, Discovery Link AFinder was exploited to identify patients who had suffered AF in the previous 12 months through the systematic scanning of device data remote transmissions. Phases 3 and 4 were repetitions of phases 1 and 2, respectively, and were implemented 6 months after the previous phases. A total of 472 consecutive patients were included in phase 1; AF occurred in 170 patients, 61 of whom were identified as new AF patients. Evidence of AF during this phase prompted prescription of oral anticoagulation (OAC) therapy in 30 patients. In phase 2, AFinder uncovered new AF, unidentified in phase 1, in 54 patients and prompted implementation of OAC therapy in 11 patients. During phase 3, 30 new AF patients were identified by means of remote monitoring, while during phase 4, a further three AF patients were identified by AFinder only. The AFinder web-based software, applied on top of standard in-hospital and remote monitoring, improved AF detection and enabled OAC treatment to be undertaken. ©2014 Wiley Periodicals, Inc.

Robust electroencephalogram phase estimation with applications in brain-computer interface systems.

PubMed

Seraj, Esmaeil; Sameni, Reza

2017-03-01

In this study, a robust method is developed for frequency-specific electroencephalogram (EEG) phase extraction using the analytic representation of the EEG. Based on recent theoretical findings in this area, it is shown that some of the phase variations-previously associated to the brain response-are systematic side-effects of the methods used for EEG phase calculation, especially during low analytical amplitude segments of the EEG. With this insight, the proposed method generates randomized ensembles of the EEG phase using minor perturbations in the zero-pole loci of narrow-band filters, followed by phase estimation using the signal's analytical form and ensemble averaging over the randomized ensembles to obtain a robust EEG phase and frequency. This Monte Carlo estimation method is shown to be very robust to noise and minor changes of the filter parameters and reduces the effect of fake EEG phase jumps, which do not have a cerebral origin. As proof of concept, the proposed method is used for extracting EEG phase features for a brain computer interface (BCI) application. The results show significant improvement in classification rates using rather simple phase-related features and a standard K-nearest neighbors and random forest classifiers, over a standard BCI dataset. The average performance was improved between 4-7% (in absence of additive noise) and 8-12% (in presence of additive noise). The significance of these improvements was statistically confirmed by a paired sample t-test, with 0.01 and 0.03 p-values, respectively. The proposed method for EEG phase calculation is very generic and may be applied to other EEG phase-based studies.

Simultaneous quantification of six alkaloid components from commercial stemonae radix by solid phase extraction-high-performance liquid chromatography coupled with evaporative light scattering detector

PubMed Central

Zhang, Rong-Rong; Lu, Dan-Yi; Yang, Zhen-Ya; Zhao, Wen; But, Paul Pui-Hay; Shaw, Pang-Chui; Jiang, Ren-Wang; Ma, Zhi-Guo

2015-01-01

Background: Stemonae radix has been applied in traditional Chinese medicine for centuries. Alkaloids are the main active ingredient in stemonae radix, so their composition and concentration levels are directly linked to clinic effects. Objective: The objective was to develop an analytical method with multiple markers for quality survey of commercial stemonae radix. Materials and Methods: A method for simultaneous determination of six compounds in commercial stemonae radix was performed using solid-phase extraction and high-performance liquid chromatography coupled with evaporative light scattering detector. The separation was carried out on an Agilent TC-C18 column with 0.1% acetonitrile solution of triethylamine aqueous solution and acetonitrile as the mobile phase under gradient elution within 70 min. The hierarchical clustering analysis (HCA) was successfully used to classify the samples in accordance with their chemical constituents. Results: Linearity (R2 > 0.9990), intra- and inter-day precision (relative standard deviations <4%), limit of detection (0.011–0.086 μg/mL), limit of quantification (0.033–0.259 μg/mL) of the six alkaloids were determined, and the recoveries were between 96.6% and 103.7%. The method was successfully applied to analysis 36 batches of commercial stemonae radix. All the samples could be classified into five clusters by HCA. Conclusion: This article provides an accurate and simple analytical method for quality survey of commercial stemonae radix. Because of the significant chemical variations, careful selection of Stemona sources with obvious antitussive value but devoid of croomine followed by good agricultural practice and good manufacturing practice process is suggested. PMID:25829776

A GIS based method for soil mapping in Sardinia, Italy: a geomatic approach.

PubMed

Vacca, A; Loddo, S; Melis, M T; Funedda, A; Puddu, R; Verona, M; Fanni, S; Fantola, F; Madrau, S; Marrone, V A; Serra, G; Tore, C; Manca, D; Pasci, S; Puddu, M R; Schirru, P

2014-06-01

A new project was recently initiated for the realization of the "Land Unit and Soil Capability Map of Sardinia" at a scale of 1:50,000 to support land use planning. In this study, we outline the general structure of the project and the methods used in the activities that have been thus far conducted. A GIS approach was used. We used the soil-landscape paradigm for the prediction of soil classes and their spatial distribution or the prediction of soil properties based on landscape features. The work is divided into two main phases. In the first phase, the available digital data on land cover, geology and topography were processed and classified according to their influence on weathering processes and soil properties. The methods used in the interpretation are based on consolidated and generalized knowledge about the influence of geology, topography and land cover on soil properties. The existing soil data (areal and point data) were collected, reviewed, validated and standardized according to international and national guidelines. Point data considered to be usable were input into a specific database created for the project. Using expert interpretation, all digital data were merged to produce a first draft of the Land Unit Map. During the second phase, this map will be implemented with the existing soil data and verified in the field if also needed with new soil data collection, and the final Land Unit Map will be produced. The Land Unit and Soil Capability Map will be produced by classifying the land units using a reference matching table of land capability classes created for this project. Copyright © 2013 Elsevier Ltd. All rights reserved.

Analysis of lipophilic marine biotoxins by liquid chromatography coupled with high-resolution mass spectrometry in seawater from the Catalan Coast.

PubMed

Bosch-Orea, Cristina; Sanchís, Josep; Farré, Marinella; Barceló, Damià

2017-09-01

Marine biotoxins regularly occur along the coast, with several consequences for the environment as well as the food industry. Monitoring of these compounds in seawater is required to assure the safety of marine resources for human consumption, providing a means for forecasting shellfish contamination events. In this study, an analytical method was developed for the detection of ten lipophilic marine biotoxins in seawater: azaspiracids 1, 2, 3, 4 and 5, classified as azaspiracid shellfish poisoning toxins, and pectenotoxin 2, okadaic acid and the related dinophysistoxin 1, yessotoxin and homoyessotoxin, classified as diarrheic shellfish poisoning toxins. The method is based on the application of solid-liquid ultrasound-assisted extraction and solid-phase extraction, followed by high-performance liquid chromatography coupled with high-resolution mass spectrometry. The limits of detection of this method are in the range of nanograms per litre and picograms per litre for most of the compounds, and recoveries range from 20.5% to 97.2%. To validate the effectiveness of this method, 36 samples of surface water from open coastal areas and marinas located along the Catalan coast on the Mediterranean Sea were collected and analysed. Eighty-eight per cent of these samples exhibited okadaic acid in particulate and aqueous phases in concentrations ranging from 0.11 to 560 μg/g and from 2.1 to 1780 ng/L respectively. Samples from open coastal areas exhibited higher concentrations of okadaic acid in particulate material, whereas in samples collected in sportive ports, the particulate material exhibited lower levels than the aqueous phase. Graphical Abstract Biotoxins investigated in seawater of the Catalan coast.

Churg-Strauss syndrome.

PubMed

Greco, Antonio; Rizzo, Maria Ida; De Virgilio, Armando; Gallo, Andrea; Fusconi, Massimo; Ruoppolo, Giovanni; Altissimi, Giancarlo; De Vincentiis, Marco

2015-04-01

Churg-Strauss syndrome (CSS), alternatively known as eosinophilic granulomatosis with polyangiitis (EGPA), was first described in 1951 by Churg and Strauss as a rare disease characterized by disseminated necrotizing vasculitis with extravascular granulomas occurring exclusively among patients with asthma and tissue eosinophilia. EGPA is classified as a small-vessel vasculitis associated with antineutrophil cytoplasmic antibodies (ANCAs) and the hypereosinophilic syndromes (HESs) in which vessel inflammation and eosinophilic proliferation are thought to contribute to organ damage. Although still considered an idiopathic condition, EGPA is classically considered a Th2-mediated disease. Emerging clinical observations provide compelling evidence that ANCAs are primarily and directly involved in the pathogenesis of AASVs, although recent evidence implicates B cells and the humoral response as further contributors to EGPA pathogenesis. EGPA has traditionally been described as evolving through a prodromic phase characterized by asthma and rhino-sinusitis, an eosinophilic phase marked by peripheral eosinophilia and organ involvement, and a vasculitic phase with clinical manifestations due to small-vessel vasculitis. The American College of Rheumatology defined the classification criteria to distinguish the different types of vasculitides and identified six criteria for EGPA. When four or more of these criteria are met, vasculitis can be classified as EGPA. The French Vasculitis Study Group has identified five prognostic factors that make up the so-called five-factor score (FFS). Patients without poor prognosis factors (FFS=0) have better survival rates than patients with poor prognosis factors (FFS≥1). The treatment of patients with CSS must be tailored to individual patients according to the presence of poor prognostic factors. A combination of high-dose corticosteroids and cyclophosphamide is still the gold standard for the treatment of severe cases, but the use of biological agents such as rituximab or mepolizumab seems to be a promising therapeutic alternative. Copyright © 2015 Elsevier B.V. All rights reserved.

Spontaneous Symmetry-Breaking in a Network Model for Quadruped Locomotion

NASA Astrophysics Data System (ADS)

Stewart, Ian

2017-12-01

Spontaneous symmetry-breaking proves a mechanism for pattern generation in legged locomotion of animals. The basic timing patterns of animal gaits are produced by a network of spinal neurons known as a Central Pattern Generator (CPG). Animal gaits are primarily characterized by phase differences between leg movements in a periodic gait cycle. Many different gaits occur, often having spatial or spatiotemporal symmetries. A natural way to explain gait patterns is to assume that the CPG is symmetric, and to classify the possible symmetry-breaking periodic motions. Pinto and Golubitsky have discussed a four-node model CPG network for biped gaits with ℤ2 × ℤ2 symmetry, classifying the possible periodic states that can arise. A more specific rate model with this structure has been analyzed in detail by Stewart. Here we extend these methods to quadruped gaits, using an eight-node network with ℤ4 × ℤ2 symmetry proposed by Golubitsky and coworkers. We formulate a rate model and calculate how the first steady or Hopf bifurcation depends on its parameters, which represent four connection strengths. The calculations involve a distinction between “real” gaits with one or two phase shifts (pronk, bound, pace, trot) and “complex” gaits with four phase shifts (forward and reverse walk, forward and reverse buck). The former correspond to real eigenvalues of the connection matrix, the latter to complex conjugate pairs. The partition of parameter space according to the first bifurcation, ignoring complex gaits, is described explicitly. The complex gaits introduce further complications, not yet fully understood. All eight gaits can occur as the first bifurcation from a fully synchronous equilibrium, for suitable parameters, and numerical simulations indicate that they can be asymptotically stable.

Pressure-induced switching in ferroelectrics: Phase-field modeling, electrochemistry, flexoelectric effect, and bulk vacancy dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cao, Ye; Morozovska, Anna; Kalinin, Sergei V.

Pressure-induced polarization switching in ferroelectric thin films has emerged as a powerful method for domain patterning, allowing us to create predefined domain patterns on free surfaces and under thin conductive top electrodes. However, the mechanisms for pressure-induced polarization switching in ferroelectrics remain highly controversial, with flexoelectricity, polarization rotation and suppression, and bulk and surface electrochemical processes all being potentially relevant. Here we classify possible pressure-induced switching mechanisms, perform elementary estimates, and study in depth using phase-field modeling. Finally, we show that magnitudes of these effects are remarkably close and give rise to complex switching diagrams as a function of pressuremore » and film thickness with nontrivial topology or switchable and nonswitchable regions.« less

Pressure-induced switching in ferroelectrics: Phase-field modeling, electrochemistry, flexoelectric effect, and bulk vacancy dynamics

DOE PAGES

Cao, Ye; Morozovska, Anna; Kalinin, Sergei V.

2017-11-01

Pressure-induced polarization switching in ferroelectric thin films has emerged as a powerful method for domain patterning, allowing us to create predefined domain patterns on free surfaces and under thin conductive top electrodes. However, the mechanisms for pressure-induced polarization switching in ferroelectrics remain highly controversial, with flexoelectricity, polarization rotation and suppression, and bulk and surface electrochemical processes all being potentially relevant. Here we classify possible pressure-induced switching mechanisms, perform elementary estimates, and study in depth using phase-field modeling. Finally, we show that magnitudes of these effects are remarkably close and give rise to complex switching diagrams as a function of pressuremore » and film thickness with nontrivial topology or switchable and nonswitchable regions.« less

Symmetry of Carrier-Envelope Phase Difference Effects in Strong-Field, Few-Cycle Ionization of Atoms and Molecules

DOE Office of Scientific and Technical Information (OSTI.GOV)

Martiny, Christian Per Juul; Madsen, Lars Bojer

2006-09-01

In few-cycle pulses, the exact value of the carrier-envelope phase difference (CEPD) has a pronounced influence on the ionization dynamics of atoms and molecules. We show that, for atoms in circularly polarized light, a change in the CEPD is mapped uniquely to an overall rotation of the system, and results for arbitrary CEPD are obtained by rotation of the results from a single calculation with fixed CEPD. For molecules, this is true only for linear molecules aligned parallel with the propagation direction of the field. The effects of CEPD are classified as geometric or nongeometric. The observations are exemplified bymore » strong-field calculations on hydrogen.« less

Optical properties of anthocyanins in the gas phase

NASA Astrophysics Data System (ADS)

Ge, Xiaochuan; Calzolari, Arrigo; Baroni, Stefano

2015-01-01

The gas-phase optical properties of the six most common anthocyanins are studied using time-dependent density-functional theory. Different anthocyanins are classified into three groups, according to the number of low-frequency peaks displayed in the UV-vis spectrum. This behavior is analyzed in terms of one-electron transitions and interaction effects, the latter being rationalized using a suitable double-pole model. Moving from PBE to hybrid exchange-correlation functionals results in a hypsochromic shift of the optical gap. While the colors thus predicted do not quite match those observed in solution, thus highlighting the importance of solvation effects, adoption of hybrid functionals remarkably determines a greater chromatic uniformity of different molecules, in qualitative agreement with experimental evidence in acidic solutions.

Variability of extreme climate events in the territory and water area of Russia

NASA Astrophysics Data System (ADS)

Serykh, Ilya; Kostianoy, Andrey

2016-04-01

The Fourth (2007) and Fifth (2014) Assessment Reports on Climate Change of the Intergovernmental Panel on Climate Change (IPCC) state that in the XXI century, climate change will be accompanied by an increase in the frequency, intensity and duration of extreme nature events such as: extreme precipitation and extreme high and low air temperatures. All these will lead to floods, droughts, fires, shallowing of rivers, lakes and water reservoirs, desertification, dust storms, melting of glaciers and permafrost, algal bloom events in the seas, lakes and water reservoirs. In its turn, these events will lead to chemical and biological contamination of water, land and air. These events will result in a deterioration of quality of life, significant financial loss due to damage to the houses, businesses, roads, agriculture, forestry, tourism, and in many cases they end in loss of life. These predictions are confirmed by the results of the studies presented in the RosHydromet First (2008) and Second (2014) Assessment Reports on Climate Change and its Consequences in Russian Federation. Scientists predictions have been repeatedly confirmed in the last 15 years - floods in Novorossiysk (2002), Krymsk and Gelendzhik (2012), the Far East (2013), heat waves in 2010, unusually cold winter (February) of 2012 and unusually warm winter of 2013/2014 in the European territory of Russia. In this regard, analysis and forecasting of extreme climate events associated with climate change in the territory of Russia are an extremely important task. This task is complicated by the fact that modern atmospheric models used by IPCC and RosHydromet badly reproduce and predict the intensity of precipitation. We are analyzing meteorological reanalysis data (NCEP/NCAR, 20th Century Reanalysis, ERA-20C, JRA-55) and satellite data (NASA and AVISO) on air, water and land temperature, rainfall, wind speed and cloud cover, water levels in seas and lakes, index of vegetation over the past 30-60 years (depending on the parameters) in the territory and water area of Russia for determining and mapping of the observed characteristics and trends in the extreme climate events and statistical forecast of these events for the next decades. Determination of a frequency, intensity and duration of extreme climate events in the territory and water area of Russia was done for the first time. It was found that the interannual-scale dynamics of ENSO is actually reflected in the climate features of different regions of the Earth, including the Russian Arctic. In particular, when the boreal winter season coincides with an El Niño event it is indicative by a negative anomaly of near-surface temperature (about -1°C) and a positive anomaly of sea level pressure over the Russian Western Arctic Basin. In contrary, significant (about +1°C) positive anomaly of near-surface temperature along with reduced sea level pressure over the regions of the Barents, White and Kara Seas is typical for any La Niña event (up to 95% significance of Student's t-test). The study was carried out with a support of the Russian Science Foundation Grant (Project N 14-50-00095).

Statistical prediction of seasonal discharge in Central Asia for water resources management: development of a generic (pre-)operational modeling tool

NASA Astrophysics Data System (ADS)

Apel, Heiko; Baimaganbetov, Azamat; Kalashnikova, Olga; Gavrilenko, Nadejda; Abdykerimova, Zharkinay; Agalhanova, Marina; Gerlitz, Lars; Unger-Shayesteh, Katy; Vorogushyn, Sergiy; Gafurov, Abror

2017-04-01

The semi-arid regions of Central Asia crucially depend on the water resources supplied by the mountainous areas of the Tien-Shan and Pamirs. During the summer months the snow and glacier melt dominated river discharge originating in the mountains provides the main water resource available for agricultural production, but also for storage in reservoirs for energy generation during the winter months. Thus a reliable seasonal forecast of the water resources is crucial for a sustainable management and planning of water resources. In fact, seasonal forecasts are mandatory tasks of all national hydro-meteorological services in the region. In order to support the operational seasonal forecast procedures of hydromet services, this study aims at the development of a generic tool for deriving statistical forecast models of seasonal river discharge. The generic model is kept as simple as possible in order to be driven by available hydrological and meteorological data, and be applicable for all catchments with their often limited data availability in the region. As snowmelt dominates summer runoff, the main meteorological predictors for the forecast models are monthly values of winter precipitation and temperature as recorded by climatological stations in the catchments. These data sets are accompanied by snow cover predictors derived from the operational ModSnow tool, which provides cloud free snow cover data for the selected catchments based on MODIS satellite images. In addition to the meteorological data antecedent streamflow is used as a predictor variable. This basic predictor set was further extended by multi-monthly means of the individual predictors, as well as composites of the predictors. Forecast models are derived based on these predictors as linear combinations of up to 3 or 4 predictors. A user selectable number of best models according to pre-defined performance criteria is extracted automatically by the developed model fitting algorithm, which includes a test for robustness by a leave-one-out cross validation. Based on the cross validation the predictive uncertainty was quantified for every prediction model. According to the official procedures of the hydromet services forecasts of the mean seasonal discharge of the period April to September are derived every month starting from January until June. The application of the model for several catchments in Central Asia - ranging from small to the largest rivers - for the period 2000-2015 provided skillful forecasts for most catchments already in January. The skill of the prediction increased every month, with R2 values often in the range 0.8 - 0.9 in April just before the prediction period. The forecasts further improve in the following months, most likely due to the integration of spring precipitation, which is not included in the predictors before May, or spring discharge, which contains indicative information for the overall seasonal discharge. In summary, the proposed generic automatic forecast model development tool provides robust predictions for seasonal water availability in Central Asia, which will be tested against the official forecasts in the upcoming years, with the vision of eventual operational implementation.

Automated classification of cell morphology by coherence-controlled holographic microscopy

NASA Astrophysics Data System (ADS)

Strbkova, Lenka; Zicha, Daniel; Vesely, Pavel; Chmelik, Radim

2017-08-01

In the last few years, classification of cells by machine learning has become frequently used in biology. However, most of the approaches are based on morphometric (MO) features, which are not quantitative in terms of cell mass. This may result in poor classification accuracy. Here, we study the potential contribution of coherence-controlled holographic microscopy enabling quantitative phase imaging for the classification of cell morphologies. We compare our approach with the commonly used method based on MO features. We tested both classification approaches in an experiment with nutritionally deprived cancer tissue cells, while employing several supervised machine learning algorithms. Most of the classifiers provided higher performance when quantitative phase features were employed. Based on the results, it can be concluded that the quantitative phase features played an important role in improving the performance of the classification. The methodology could be valuable help in refining the monitoring of live cells in an automated fashion. We believe that coherence-controlled holographic microscopy, as a tool for quantitative phase imaging, offers all preconditions for the accurate automated analysis of live cell behavior while enabling noninvasive label-free imaging with sufficient contrast and high-spatiotemporal phase sensitivity.