Testing for the Presence of Correlation Changes in a Multivariate Time Series: A Permutation Based Approach.

PubMed

Cabrieto, Jedelyn; Tuerlinckx, Francis; Kuppens, Peter; Hunyadi, Borbála; Ceulemans, Eva

2018-01-15

Detecting abrupt correlation changes in multivariate time series is crucial in many application fields such as signal processing, functional neuroimaging, climate studies, and financial analysis. To detect such changes, several promising correlation change tests exist, but they may suffer from severe loss of power when there is actually more than one change point underlying the data. To deal with this drawback, we propose a permutation based significance test for Kernel Change Point (KCP) detection on the running correlations. Given a requested number of change points K, KCP divides the time series into K + 1 phases by minimizing the within-phase variance. The new permutation test looks at how the average within-phase variance decreases when K increases and compares this to the results for permuted data. The results of an extensive simulation study and applications to several real data sets show that, depending on the setting, the new test performs either at par or better than the state-of-the art significance tests for detecting the presence of correlation changes, implying that its use can be generally recommended.

A travel time forecasting model based on change-point detection method

NASA Astrophysics Data System (ADS)

LI, Shupeng; GUANG, Xiaoping; QIAN, Yongsheng; ZENG, Junwei

2017-06-01

Travel time parameters obtained from road traffic sensors data play an important role in traffic management practice. A travel time forecasting model is proposed for urban road traffic sensors data based on the method of change-point detection in this paper. The first-order differential operation is used for preprocessing over the actual loop data; a change-point detection algorithm is designed to classify the sequence of large number of travel time data items into several patterns; then a travel time forecasting model is established based on autoregressive integrated moving average (ARIMA) model. By computer simulation, different control parameters are chosen for adaptive change point search for travel time series, which is divided into several sections of similar state.Then linear weight function is used to fit travel time sequence and to forecast travel time. The results show that the model has high accuracy in travel time forecasting.

Building Change Detection from Bi-Temporal Dense-Matching Point Clouds and Aerial Images.

PubMed

Pang, Shiyan; Hu, Xiangyun; Cai, Zhongliang; Gong, Jinqi; Zhang, Mi

2018-03-24

In this work, a novel building change detection method from bi-temporal dense-matching point clouds and aerial images is proposed to address two major problems, namely, the robust acquisition of the changed objects above ground and the automatic classification of changed objects into buildings or non-buildings. For the acquisition of changed objects above ground, the change detection problem is converted into a binary classification, in which the changed area above ground is regarded as the foreground and the other area as the background. For the gridded points of each period, the graph cuts algorithm is adopted to classify the points into foreground and background, followed by the region-growing algorithm to form candidate changed building objects. A novel structural feature that was extracted from aerial images is constructed to classify the candidate changed building objects into buildings and non-buildings. The changed building objects are further classified as "newly built", "taller", "demolished", and "lower" by combining the classification and the digital surface models of two periods. Finally, three typical areas from a large dataset are used to validate the proposed method. Numerous experiments demonstrate the effectiveness of the proposed algorithm.

Detecting P and S-wave of Mt. Rinjani seismic based on a locally stationary autoregressive (LSAR) model

NASA Astrophysics Data System (ADS)

Nurhaida, Subanar, Abdurakhman, Abadi, Agus Maman

2017-08-01

Seismic data is usually modelled using autoregressive processes. The aim of this paper is to find the arrival times of the seismic waves of Mt. Rinjani in Indonesia. Kitagawa algorithm's is used to detect the seismic P and S-wave. Householder transformation used in the algorithm made it effectively finding the number of change points and parameters of the autoregressive models. The results show that the use of Box-Cox transformation on the variable selection level makes the algorithm works well in detecting the change points. Furthermore, when the basic span of the subinterval is set 200 seconds and the maximum AR order is 20, there are 8 change points which occur at 1601, 2001, 7401, 7601,7801, 8001, 8201 and 9601. Finally, The P and S-wave arrival times are detected at time 1671 and 2045 respectively using a precise detection algorithm.

Distributed Sensing for Quickest Change Detection of Point Radiation Sources

DTIC Science & Technology

2017-02-01

point occurs simultaneously at all sensor nodes, thus neglecting signal propagation delays. For nuclear radiation , the observation period, which is on... nuclear radiation using a sensor network,” in Homeland Security (HST), 2012 IEEE Conference on Technologies for. IEEE, 2012, pp. 648–653. [8] G. Lorden...Distributed Sensing for Quickest Change Detection of Point Radiation Sources Gene T. Whipps⋆† Emre Ertin† Randolph L. Moses† †The Ohio State

Change-point detection of induced and natural seismicity

NASA Astrophysics Data System (ADS)

Fiedler, B.; Holschneider, M.; Zoeller, G.; Hainzl, S.

2016-12-01

Earthquake rates are influenced by tectonic stress buildup, earthquake-induced stress changes, and transient aseismic sources. While the first two sources can be well modeled due to the fact that the source is known, transient aseismic processes are more difficult to detect. However, the detection of the associated changes of the earthquake activity is of great interest, because it might help to identify natural aseismic deformation patterns (such as slow slip events) and the occurrence of induced seismicity related to human activities. We develop a Bayesian approach to detect change-points in seismicity data which are modeled by Poisson processes. By means of a Likelihood-Ratio-Test, we proof the significance of the change of the intensity. The model is also extended to spatiotemporal data to detect the area of the transient changes. The method is firstly tested for synthetic data and then applied to observational data from central US and the Bardarbunga volcano in Iceland.

Integrated Change Detection and Classification in Urban Areas Based on Airborne Laser Scanning Point Clouds.

PubMed

Tran, Thi Huong Giang; Ressl, Camillo; Pfeifer, Norbert

2018-02-03

This paper suggests a new approach for change detection (CD) in 3D point clouds. It combines classification and CD in one step using machine learning. The point cloud data of both epochs are merged for computing features of four types: features describing the point distribution, a feature relating to relative terrain elevation, features specific for the multi-target capability of laser scanning, and features combining the point clouds of both epochs to identify the change. All these features are merged in the points and then training samples are acquired to create the model for supervised classification, which is then applied to the whole study area. The final results reach an overall accuracy of over 90% for both epochs of eight classes: lost tree, new tree, lost building, new building, changed ground, unchanged building, unchanged tree, and unchanged ground.

Method of noncontacting ultrasonic process monitoring

DOEpatents

Garcia, Gabriel V.; Walter, John B.; Telschow, Kenneth L.

1992-01-01

A method of monitoring a material during processing comprising the steps of (a) shining a detection light on the surface of a material; (b) generating ultrasonic waves at the surface of the material to cause a change in frequency of the detection light; (c) detecting a change in the frequency of the detection light at the surface of the material; (d) detecting said ultrasonic waves at the surface point of detection of the material; (e) measuring a change in the time elapsed from generating the ultrasonic waves at the surface of the material and return to the surface point of detection of the material, to determine the transit time; and (f) comparing the transit time to predetermined values to determine properties such as, density and the elastic quality of the material.

The change points of HbA(1C) for detection of retinopathy in Chinese type 2 diabetic patients.

PubMed

Hou, Jia-Ning; Bi, Yu-Fang; Xu, Min; Huang, Yun; Li, Xiao-Ying; Wang, Wei-Qing; Chen, Yu-Hong; Ning, Guang

2011-03-01

To investigate the change points of HbA(1C) for detection of retinopathy in Chinese type 2 diabetic patients. This cross-sectional investigation included 992 diagnosed type 2 diabetic patients, who received non-mydriatic digital fundus photography examination. Joinpoint regression software was adopted to identify the change points of HbA(1C) in association with retinopathy prevalence. The mean age of all patients was 59.1 ± 8.4 years and the duration of diabetes was 5.5 (95% CI: 5.2-5.9) years. The prevalence of retinopathy was 10.3% in total, and 4.1%, 7.4% and 19.6% in patients with different diabetes duration of ≤ 5 years, 5-10 years and >10 years, respectively. The change point of HbA(1C) was 6.5% (95%CI 5.8-7.5%), at which retinopathy prevalence began to rise sharply. Furthermore, in subjects with diabetes duration ≤ 5 years, 5-10 years and >10 years, the change points of HbA(1C) were 8.1% (95%CI 7.9-8.3%), 6.1% (95%CI 5.7-6.8%), 5.6% (95%CI 5.1-8.1%) for detection of retinopathy, respectively. The steepest increase in retinopathy prevalence occurred when HbA(1C) reached 6.5%. However, the duration of diabetes should be taken into concern, when using the change points of HbA(1C) for detection of retinopathy in diabetic patients. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Landscape Change Detected Over A 60 Year Period In The Arctic National Wildlife Refuge, Alaska, Using High Resolution Aerial Photographs And Satellite Images

NASA Astrophysics Data System (ADS)

Jorgenson, J. C.; Jorgenson, M. T.; Boldenow, M.; Orndahl, K. M.

2016-12-01

We documented landscape change over a 60 year period in the Arctic National Wildlife Refuge in northeastern Alaska using aerial photographs and satellite images. We used a stratified random sample to allow inference to the whole refuge (78,050 km2), with five random sites in each of seven ecoregions. Each site (2 km2) had a systematic grid of 100 points for a total of 3500 points. We chose study sites in the overlap area covered by acceptable imagery in three time periods: aerial photographs from 1947 - 1955 and 1978 - 1988, Quick Bird and IKONOS satellite images from 2000 - 2007.At each point a 10 meter radius circle was visually evaluated in ARC-MAP for each time period for vegetation type, disturbance, presence of ice wedge polygon microtopography and surface water. A landscape change category was assigned to each point based on differences detected between the three periods. Change types were assigned for time interval 1, interval 2 and overall. Additional explanatory variables included elevation, slope, aspect, geology, physiography and temperature. Overall, 23% of points changed over the study period. Fire was the most common change agent, affecting 28% of the Boreal Forest points. The next most common change was degradation of soil ice wedges (thermokarst), detected at 12% of the points on the North Slope Tundra. The other most common changes included increase in cover of trees or shrubs (7% of Boreal Forest and Brooks Range points) and erosion or deposition on river floodplains and at the Beaufort Sea coast. Changes on the North Slope Tundra tended to be related to landscape wetting, mainly thermokarst. Changes in the Boreal Forest tended to involve landscape drying, including fire, reduced area of lakes and tree increase on wet sites. The second time interval coincided with a shift towards a warmer climate and had greater change in several categories including thermokarst, lake changes and tree and shrub increase.

Trend analysis and change point detection of annual and seasonal temperature series in Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Suhaila, Jamaludin; Yusop, Zulkifli

2017-06-01

Most of the trend analysis that has been conducted has not considered the existence of a change point in the time series analysis. If these occurred, then the trend analysis will not be able to detect an obvious increasing or decreasing trend over certain parts of the time series. Furthermore, the lack of discussion on the possible factors that influenced either the decreasing or the increasing trend in the series needs to be addressed in any trend analysis. Hence, this study proposes to investigate the trends, and change point detection of mean, maximum and minimum temperature series, both annually and seasonally in Peninsular Malaysia and determine the possible factors that could contribute to the significance trends. In this study, Pettitt and sequential Mann-Kendall (SQ-MK) tests were used to examine the occurrence of any abrupt climate changes in the independent series. The analyses of the abrupt changes in temperature series suggested that most of the change points in Peninsular Malaysia were detected during the years 1996, 1997 and 1998. These detection points captured by Pettitt and SQ-MK tests are possibly related to climatic factors, such as El Niño and La Niña events. The findings also showed that the majority of the significant change points that exist in the series are related to the significant trend of the stations. Significant increasing trends of annual and seasonal mean, maximum and minimum temperatures in Peninsular Malaysia were found with a range of 2-5 °C/100 years during the last 32 years. It was observed that the magnitudes of the increasing trend in minimum temperatures were larger than the maximum temperatures for most of the studied stations, particularly at the urban stations. These increases are suspected to be linked with the effect of urban heat island other than El Niño event.

Detecting correlation changes in multivariate time series: A comparison of four non-parametric change point detection methods.

PubMed

Cabrieto, Jedelyn; Tuerlinckx, Francis; Kuppens, Peter; Grassmann, Mariel; Ceulemans, Eva

2017-06-01

Change point detection in multivariate time series is a complex task since next to the mean, the correlation structure of the monitored variables may also alter when change occurs. DeCon was recently developed to detect such changes in mean and\\or correlation by combining a moving windows approach and robust PCA. However, in the literature, several other methods have been proposed that employ other non-parametric tools: E-divisive, Multirank, and KCP. Since these methods use different statistical approaches, two issues need to be tackled. First, applied researchers may find it hard to appraise the differences between the methods. Second, a direct comparison of the relative performance of all these methods for capturing change points signaling correlation changes is still lacking. Therefore, we present the basic principles behind DeCon, E-divisive, Multirank, and KCP and the corresponding algorithms, to make them more accessible to readers. We further compared their performance through extensive simulations using the settings of Bulteel et al. (Biological Psychology, 98 (1), 29-42, 2014) implying changes in mean and in correlation structure and those of Matteson and James (Journal of the American Statistical Association, 109 (505), 334-345, 2014) implying different numbers of (noise) variables. KCP emerged as the best method in almost all settings. However, in case of more than two noise variables, only DeCon performed adequately in detecting correlation changes.

Damage diagnosis algorithm using a sequential change point detection method with an unknown distribution for damage

NASA Astrophysics Data System (ADS)

Noh, Hae Young; Rajagopal, Ram; Kiremidjian, Anne S.

2012-04-01

This paper introduces a damage diagnosis algorithm for civil structures that uses a sequential change point detection method for the cases where the post-damage feature distribution is unknown a priori. This algorithm extracts features from structural vibration data using time-series analysis and then declares damage using the change point detection method. The change point detection method asymptotically minimizes detection delay for a given false alarm rate. The conventional method uses the known pre- and post-damage feature distributions to perform a sequential hypothesis test. In practice, however, the post-damage distribution is unlikely to be known a priori. Therefore, our algorithm estimates and updates this distribution as data are collected using the maximum likelihood and the Bayesian methods. We also applied an approximate method to reduce the computation load and memory requirement associated with the estimation. The algorithm is validated using multiple sets of simulated data and a set of experimental data collected from a four-story steel special moment-resisting frame. Our algorithm was able to estimate the post-damage distribution consistently and resulted in detection delays only a few seconds longer than the delays from the conventional method that assumes we know the post-damage feature distribution. We confirmed that the Bayesian method is particularly efficient in declaring damage with minimal memory requirement, but the maximum likelihood method provides an insightful heuristic approach.

Point pattern match-based change detection in a constellation of previously detected objects

DOEpatents

Paglieroni, David W.

2016-06-07

A method and system is provided that applies attribute- and topology-based change detection to objects that were detected on previous scans of a medium. The attributes capture properties or characteristics of the previously detected objects, such as location, time of detection, detection strength, size, elongation, orientation, etc. The locations define a three-dimensional network topology forming a constellation of previously detected objects. The change detection system stores attributes of the previously detected objects in a constellation database. The change detection system detects changes by comparing the attributes and topological consistency of newly detected objects encountered during a new scan of the medium to previously detected objects in the constellation database. The change detection system may receive the attributes of the newly detected objects as the objects are detected by an object detection system in real time.

Quantum Change Point

NASA Astrophysics Data System (ADS)

Sentís, Gael; Bagan, Emilio; Calsamiglia, John; Chiribella, Giulio; Muñoz-Tapia, Ramon

2016-10-01

Sudden changes are ubiquitous in nature. Identifying them is crucial for a number of applications in biology, medicine, and social sciences. Here we take the problem of detecting sudden changes to the quantum domain. We consider a source that emits quantum particles in a default state, until a point where a mutation occurs that causes the source to switch to another state. The problem is then to find out where the change occurred. We determine the maximum probability of correctly identifying the change point, allowing for collective measurements on the whole sequence of particles emitted by the source. Then, we devise online strategies where the particles are measured individually and an answer is provided as soon as a new particle is received. We show that these online strategies substantially underperform the optimal quantum measurement, indicating that quantum sudden changes, although happening locally, are better detected globally.

Fetal heart rate deceleration detection using a discrete cosine transform implementation of singular spectrum analysis.

PubMed

Warrick, P A; Precup, D; Hamilton, E F; Kearney, R E

2007-01-01

To develop a singular-spectrum analysis (SSA) based change-point detection algorithm applicable to fetal heart rate (FHR) monitoring to improve the detection of deceleration events. We present a method for decomposing a signal into near-orthogonal components via the discrete cosine transform (DCT) and apply this in a novel online manner to change-point detection based on SSA. The SSA technique forms models of the underlying signal that can be compared over time; models that are sufficiently different indicate signal change points. To adapt the algorithm to deceleration detection where many successive similar change events can occur, we modify the standard SSA algorithm to hold the reference model constant under such conditions, an approach that we term "base-hold SSA". The algorithm is applied to a database of 15 FHR tracings that have been preprocessed to locate candidate decelerations and is compared to the markings of an expert obstetrician. Of the 528 true and 1285 false decelerations presented to the algorithm, the base-hold approach improved on standard SSA, reducing the number of missed decelerations from 64 to 49 (21.9%) while maintaining the same reduction in false-positives (278). The standard SSA assumption that changes are infrequent does not apply to FHR analysis where decelerations can occur successively and in close proximity; our base-hold SSA modification improves detection of these types of event series.

Drivers' and non-drivers' performance in a change detection task with static driving scenes: is there a benefit of experience?

PubMed

Zhao, Nan; Chen, Wenfeng; Xuan, Yuming; Mehler, Bruce; Reimer, Bryan; Fu, Xiaolan

2014-01-01

The 'looked-but-failed-to-see' phenomenon is crucial to driving safety. Previous research utilising change detection tasks related to driving has reported inconsistent effects of driver experience on the ability to detect changes in static driving scenes. Reviewing these conflicting results, we suggest that drivers' increased ability to detect changes will only appear when the task requires a pattern of visual attention distribution typical of actual driving. By adding a distant fixation point on the road image, we developed a modified change blindness paradigm and measured detection performance of drivers and non-drivers. Drivers performed better than non-drivers only in scenes with a fixation point. Furthermore, experience effect interacted with the location of the change and the relevance of the change to driving. These results suggest that learning associated with driving experience reflects increased skill in the efficient distribution of visual attention across both the central focus area and peripheral objects. This article provides an explanation for the previously conflicting reports of driving experience effects in change detection tasks. We observed a measurable benefit of experience in static driving scenes, using a modified change blindness paradigm. These results have translational opportunities for picture-based training and testing tools to improve driver skill.

A guide for recording esthetic and biologic changes with photographs

Treesearch

Arthur W. Magill; R.H. Twiss

1965-01-01

Photography has long been a useful tool for recording and analyzing environmental conditions. Permanent camera points can be established to help detect ,and analyze changes in the esthetics and ecology of wildland resources. This note describes the usefulness of permanent camera points and outlines procedures for establishing points and recording data.

Sample size and power calculations for detecting changes in malaria transmission using antibody seroconversion rate.

PubMed

Sepúlveda, Nuno; Paulino, Carlos Daniel; Drakeley, Chris

2015-12-30

Several studies have highlighted the use of serological data in detecting a reduction in malaria transmission intensity. These studies have typically used serology as an adjunct measure and no formal examination of sample size calculations for this approach has been conducted. A sample size calculator is proposed for cross-sectional surveys using data simulation from a reverse catalytic model assuming a reduction in seroconversion rate (SCR) at a given change point before sampling. This calculator is based on logistic approximations for the underlying power curves to detect a reduction in SCR in relation to the hypothesis of a stable SCR for the same data. Sample sizes are illustrated for a hypothetical cross-sectional survey from an African population assuming a known or unknown change point. Overall, data simulation demonstrates that power is strongly affected by assuming a known or unknown change point. Small sample sizes are sufficient to detect strong reductions in SCR, but invariantly lead to poor precision of estimates for current SCR. In this situation, sample size is better determined by controlling the precision of SCR estimates. Conversely larger sample sizes are required for detecting more subtle reductions in malaria transmission but those invariantly increase precision whilst reducing putative estimation bias. The proposed sample size calculator, although based on data simulation, shows promise of being easily applicable to a range of populations and survey types. Since the change point is a major source of uncertainty, obtaining or assuming prior information about this parameter might reduce both the sample size and the chance of generating biased SCR estimates.

a Voxel-Based Metadata Structure for Change Detection in Point Clouds of Large-Scale Urban Areas

NASA Astrophysics Data System (ADS)

Gehrung, J.; Hebel, M.; Arens, M.; Stilla, U.

2018-05-01

Mobile laser scanning has not only the potential to create detailed representations of urban environments, but also to determine changes up to a very detailed level. An environment representation for change detection in large scale urban environments based on point clouds has drawbacks in terms of memory scalability. Volumes, however, are a promising building block for memory efficient change detection methods. The challenge of working with 3D occupancy grids is that the usual raycasting-based methods applied for their generation lead to artifacts caused by the traversal of unfavorable discretized space. These artifacts have the potential to distort the state of voxels in close proximity to planar structures. In this work we propose a raycasting approach that utilizes knowledge about planar surfaces to completely prevent this kind of artifacts. To demonstrate the capabilities of our approach, a method for the iterative volumetric approximation of point clouds that allows to speed up the raycasting by 36 percent is proposed.

Building Change Detection from LIDAR Point Cloud Data Based on Connected Component Analysis

NASA Astrophysics Data System (ADS)

Awrangjeb, M.; Fraser, C. S.; Lu, G.

2015-08-01

Building data are one of the important data types in a topographic database. Building change detection after a period of time is necessary for many applications, such as identification of informal settlements. Based on the detected changes, the database has to be updated to ensure its usefulness. This paper proposes an improved building detection technique, which is a prerequisite for many building change detection techniques. The improved technique examines the gap between neighbouring buildings in the building mask in order to avoid under segmentation errors. Then, a new building change detection technique from LIDAR point cloud data is proposed. Buildings which are totally new or demolished are directly added to the change detection output. However, for demolished or extended building parts, a connected component analysis algorithm is applied and for each connected component its area, width and height are estimated in order to ascertain if it can be considered as a demolished or new building part. Finally, a graphical user interface (GUI) has been developed to update detected changes to the existing building map. Experimental results show that the improved building detection technique can offer not only higher performance in terms of completeness and correctness, but also a lower number of undersegmentation errors as compared to its original counterpart. The proposed change detection technique produces no omission errors and thus it can be exploited for enhanced automated building information updating within a topographic database. Using the developed GUI, the user can quickly examine each suggested change and indicate his/her decision with a minimum number of mouse clicks.

Consistent and powerful non-Euclidean graph-based change-point test with applications to segmenting random interfered video data.

PubMed

Shi, Xiaoping; Wu, Yuehua; Rao, Calyampudi Radhakrishna

2018-06-05

The change-point detection has been carried out in terms of the Euclidean minimum spanning tree (MST) and shortest Hamiltonian path (SHP), with successful applications in the determination of authorship of a classic novel, the detection of change in a network over time, the detection of cell divisions, etc. However, these Euclidean graph-based tests may fail if a dataset contains random interferences. To solve this problem, we present a powerful non-Euclidean SHP-based test, which is consistent and distribution-free. The simulation shows that the test is more powerful than both Euclidean MST- and SHP-based tests and the non-Euclidean MST-based test. Its applicability in detecting both landing and departure times in video data of bees' flower visits is illustrated.

Point count length and detection of forest neotropical migrant birds

USGS Publications Warehouse

Dawson, D.K.; Smith, D.R.; Robbins, C.S.; Ralph, C. John; Sauer, John R.; Droege, Sam

1995-01-01

Comparisons of bird abundances among years or among habitats assume that the rates at which birds are detected and counted are constant within species. We use point count data collected in forests of the Mid-Atlantic states to estimate detection probabilities for Neotropical migrant bird species as a function of count length. For some species, significant differences existed among years or observers in both the probability of detecting the species and in the rate at which individuals are counted. We demonstrate the consequence that variability in species' detection probabilities can have on estimates of population change, and discuss ways for reducing this source of bias in point count studies.

An Online 3D Database System for Endangered Architectural and Archaeological Heritage in the South-Eastern Mediterranean

NASA Astrophysics Data System (ADS)

Abate, D.; Avgousti, A.; Faka, M.; Hermon, S.; Bakirtzis, N.; Christofi, P.

2017-10-01

This study compares performance of aerial image based point clouds (IPCs) and light detection and ranging (LiDAR) based point clouds in detection of thinnings and clear cuts in forests. IPCs are an appealing method to update forest resource data, because of their accuracy in forest height estimation and cost-efficiency of aerial image acquisition. We predicted forest changes over a period of three years by creating difference layers that displayed the difference in height or volume between the initial and subsequent time points. Both IPCs and LiDAR data were used in this process. The IPCs were constructed with the Semi-Global Matching (SGM) algorithm. Difference layers were constructed by calculating differences in fitted height or volume models or in canopy height models (CHMs) from both time points. The LiDAR-derived digital terrain model (DTM) was used to scale heights to above ground level. The study area was classified in logistic regression into the categories ClearCut, Thinning or NoChange with the values from the difference layers. We compared the predicted changes with the true changes verified in the field, and obtained at best a classification accuracy for clear cuts 93.1 % with IPCs and 91.7 % with LiDAR data. However, a classification accuracy for thinnings was only 8.0 % with IPCs. With LiDAR data 41.4 % of thinnings were detected. In conclusion, the LiDAR data proved to be more accurate method to predict the minor changes in forests than IPCs, but both methods are useful in detection of major changes.

Series length used during trend analysis affects sensitivity to changes in progression rate in the ocular hypertension treatment study.

PubMed

Gardiner, Stuart K; Demirel, Shaban; De Moraes, Carlos Gustavo; Liebmann, Jeffrey M; Cioffi, George A; Ritch, Robert; Gordon, Mae O; Kass, Michael A

2013-02-15

Trend analysis techniques to detect glaucomatous progression typically assume a constant rate of change. This study uses data from the Ocular Hypertension Treatment Study to assess whether this assumption decreases sensitivity to changes in progression rate, by including earlier periods of stability. Series of visual fields (mean 24 per eye) completed at 6-month intervals from participants randomized initially to observation were split into subseries before and after the initiation of treatment (the "split-point"). The mean deviation rate of change (MDR) was derived using these entire subseries, and using only the window length (W) tests nearest the split-point, for different window lengths of W tests. A generalized estimating equation model was used to detect changes in MDR occurring at the split-point. Using shortened subseries with W = 7 tests, the MDR slowed by 0.142 dB/y upon initiation of treatment (P < 0.001), and the proportion of eyes showing "rapid deterioration" (MDR <-0.5 dB/y with P < 5%) decreased from 11.8% to 6.5% (P < 0.001). Using the entire sequence, no significant change in MDR was detected (P = 0.796), and there was no change in the proportion of eyes progressing (P = 0.084). Window lengths 6 ≤ W ≤ 9 produced similar benefits. Event analysis revealed a beneficial treatment effect in this dataset. This effect was not detected by linear trend analysis applied to entire series, but was detected when using shorter subseries of length between six and nine fields. Using linear trend analysis on the entire field sequence may not be optimal for detecting and monitoring progression. Nonlinear analyses may be needed for long series of fields. (ClinicalTrials.gov number, NCT00000125.).

Zinc finger point mutations within the WT1 gene in Wilms tumor patients.

PubMed Central

Little, M H; Prosser, J; Condie, A; Smith, P J; Van Heyningen, V; Hastie, N D

1992-01-01

A proposed Wilms tumor gene, WT1, which encodes a zinc finger protein, has previously been isolated from human chromosome 11p13. Chemical mismatch cleavage analysis was used to identify point mutations in the zinc finger region of this gene in a series of 32 Wilms tumors. Two exonic single base changes were detected. In zinc finger 3 of a bilateral Wilms tumor patient, a constitutional de novo C----T base change was found changing an arginine to a stop codon. One tumor from this patient showed allele loss leading to 11p hemizygosity of the abnormal allele. In zinc finger 2 of a sporadic Wilms tumor patient, a C----T base change resulted in an arginine to cysteine amino acid change. To our knowledge, a WT1 gene missense mutation has not been detected previously in a Wilms tumor. By comparison with a recent NMR and x-ray crystallographic analysis of an analogous zinc finger gene, early growth response gene 1 (EGR1), this amino acid change in WT1 occurs at a residue predicted to be critical for DNA binding capacity and site specificity. The detection of one nonsense point mutation and one missense WT1 gene point mutation adds to the accumulating evidence implicating this gene in a proportion of Wilms tumor patients. Images PMID:1317572

Method to detect the end-point for PCR DNA amplification using an ionically labeled probe and measuring impedance change

DOEpatents

Miles, Robin R [Danville, CA; Belgrader, Phillip [Severna Park, MD; Fuller, Christopher D [Oakland, CA

2007-01-02

Impedance measurements are used to detect the end-point for PCR DNA amplification. A pair of spaced electrodes are located on a surface of a microfluidic channel and an AC or DC voltage is applied across the electrodes to produce an electric field. An ionically labeled probe will attach to a complementary DNA segment, and a polymerase enzyme will release the ionic label. This causes the conductivity of the solution in the area of the electrode to change. This change in conductivity is measured as a change in the impedance been the two electrodes.

Change in the Embedding Dimension as an Indicator of an Approaching Transition

PubMed Central

Neuman, Yair; Marwan, Norbert; Cohen, Yohai

2014-01-01

Predicting a transition point in behavioral data should take into account the complexity of the signal being influenced by contextual factors. In this paper, we propose to analyze changes in the embedding dimension as contextual information indicating a proceeding transitive point, called OPtimal Embedding tRANsition Detection (OPERAND). Three texts were processed and translated to time-series of emotional polarity. It was found that changes in the embedding dimension proceeded transition points in the data. These preliminary results encourage further research into changes in the embedding dimension as generic markers of an approaching transition point. PMID:24979691

Statistical methods for change-point detection in surface temperature records

NASA Astrophysics Data System (ADS)

Pintar, A. L.; Possolo, A.; Zhang, N. F.

2013-09-01

We describe several statistical methods to detect possible change-points in a time series of values of surface temperature measured at a meteorological station, and to assess the statistical significance of such changes, taking into account the natural variability of the measured values, and the autocorrelations between them. These methods serve to determine whether the record may suffer from biases unrelated to the climate signal, hence whether there may be a need for adjustments as considered by M. J. Menne and C. N. Williams (2009) "Homogenization of Temperature Series via Pairwise Comparisons", Journal of Climate 22 (7), 1700-1717. We also review methods to characterize patterns of seasonality (seasonal decomposition using monthly medians or robust local regression), and explain the role they play in the imputation of missing values, and in enabling robust decompositions of the measured values into a seasonal component, a possible climate signal, and a station-specific remainder. The methods for change-point detection that we describe include statistical process control, wavelet multi-resolution analysis, adaptive weights smoothing, and a Bayesian procedure, all of which are applicable to single station records.

On analyzing colour constancy approach for improving SURF detector performance

NASA Astrophysics Data System (ADS)

Zulkiey, Mohd Asyraf; Zaki, Wan Mimi Diyana Wan; Hussain, Aini; Mustafa, Mohd. Marzuki

2012-04-01

Robust key point detector plays a crucial role in obtaining a good tracking feature. The main challenge in outdoor tracking is the illumination change due to various reasons such as weather fluctuation and occlusion. This paper approaches the illumination change problem by transforming the input image through colour constancy algorithm before applying the SURF detector. Masked grey world approach is chosen because of its ability to perform well under local as well as global illumination change. Every image is transformed to imitate the canonical illuminant and Gaussian distribution is used to model the global change. The simulation results show that the average number of detected key points have increased by 69.92%. Moreover, the average of improved performance cases far out weight the degradation case where the former is improved by 215.23%. The approach is suitable for tracking implementation where sudden illumination occurs frequently and robust key point detection is needed.

Variance change point detection for fractional Brownian motion based on the likelihood ratio test

NASA Astrophysics Data System (ADS)

Kucharczyk, Daniel; Wyłomańska, Agnieszka; Sikora, Grzegorz

2018-01-01

Fractional Brownian motion is one of the main stochastic processes used for describing the long-range dependence phenomenon for self-similar processes. It appears that for many real time series, characteristics of the data change significantly over time. Such behaviour one can observe in many applications, including physical and biological experiments. In this paper, we present a new technique for the critical change point detection for cases where the data under consideration are driven by fractional Brownian motion with a time-changed diffusion coefficient. The proposed methodology is based on the likelihood ratio approach and represents an extension of a similar methodology used for Brownian motion, the process with independent increments. Here, we also propose a statistical test for testing the significance of the estimated critical point. In addition to that, an extensive simulation study is provided to test the performance of the proposed method.

Fast and Robust Segmentation and Classification for Change Detection in Urban Point Clouds

NASA Astrophysics Data System (ADS)

Roynard, X.; Deschaud, J.-E.; Goulette, F.

2016-06-01

Change detection is an important issue in city monitoring to analyse street furniture, road works, car parking, etc. For example, parking surveys are needed but are currently a laborious task involving sending operators in the streets to identify the changes in car locations. In this paper, we propose a method that performs a fast and robust segmentation and classification of urban point clouds, that can be used for change detection. We apply this method to detect the cars, as a particular object class, in order to perform parking surveys automatically. A recently proposed method already addresses the need for fast segmentation and classification of urban point clouds, using elevation images. The interest to work on images is that processing is much faster, proven and robust. However there may be a loss of information in complex 3D cases: for example when objects are one above the other, typically a car under a tree or a pedestrian under a balcony. In this paper we propose a method that retain the three-dimensional information while preserving fast computation times and improving segmentation and classification accuracy. It is based on fast region-growing using an octree, for the segmentation, and specific descriptors with Random-Forest for the classification. Experiments have been performed on large urban point clouds acquired by Mobile Laser Scanning. They show that the method is as fast as the state of the art, and that it gives more robust results in the complex 3D cases.

Vehicle Localization by LIDAR Point Correlation Improved by Change Detection

NASA Astrophysics Data System (ADS)

Schlichting, A.; Brenner, C.

2016-06-01

LiDAR sensors are proven sensors for accurate vehicle localization. Instead of detecting and matching features in the LiDAR data, we want to use the entire information provided by the scanners. As dynamic objects, like cars, pedestrians or even construction sites could lead to wrong localization results, we use a change detection algorithm to detect these objects in the reference data. If an object occurs in a certain number of measurements at the same position, we mark it and every containing point as static. In the next step, we merge the data of the single measurement epochs to one reference dataset, whereby we only use static points. Further, we also use a classification algorithm to detect trees. For the online localization of the vehicle, we use simulated data of a vertical aligned automotive LiDAR sensor. As we only want to use static objects in this case as well, we use a random forest classifier to detect dynamic scan points online. Since the automotive data is derived from the LiDAR Mobile Mapping System, we are able to use the labelled objects from the reference data generation step to create the training data and further to detect dynamic objects online. The localization then can be done by a point to image correlation method using only static objects. We achieved a localization standard deviation of about 5 cm (position) and 0.06° (heading), and were able to successfully localize the vehicle in about 93 % of the cases along a trajectory of 13 km in Hannover, Germany.

a Method of Time-Series Change Detection Using Full Polsar Images from Different Sensors

NASA Astrophysics Data System (ADS)

Liu, W.; Yang, J.; Zhao, J.; Shi, H.; Yang, L.

2018-04-01

Most of the existing change detection methods using full polarimetric synthetic aperture radar (PolSAR) are limited to detecting change between two points in time. In this paper, a novel method was proposed to detect the change based on time-series data from different sensors. Firstly, the overall difference image of a time-series PolSAR was calculated by ominous statistic test. Secondly, difference images between any two images in different times ware acquired by Rj statistic test. Generalized Gaussian mixture model (GGMM) was used to obtain time-series change detection maps in the last step for the proposed method. To verify the effectiveness of the proposed method, we carried out the experiment of change detection by using the time-series PolSAR images acquired by Radarsat-2 and Gaofen-3 over the city of Wuhan, in China. Results show that the proposed method can detect the time-series change from different sensors.

Exact Identification of a Quantum Change Point

NASA Astrophysics Data System (ADS)

Sentís, Gael; Calsamiglia, John; Muñoz-Tapia, Ramon

2017-10-01

The detection of change points is a pivotal task in statistical analysis. In the quantum realm, it is a new primitive where one aims at identifying the point where a source that supposedly prepares a sequence of particles in identical quantum states starts preparing a mutated one. We obtain the optimal procedure to identify the change point with certainty—naturally at the price of having a certain probability of getting an inconclusive answer. We obtain the analytical form of the optimal probability of successful identification for any length of the particle sequence. We show that the conditional success probabilities of identifying each possible change point show an unexpected oscillatory behavior. We also discuss local (online) protocols and compare them with the optimal procedure.

Exact Identification of a Quantum Change Point.

PubMed

Sentís, Gael; Calsamiglia, John; Muñoz-Tapia, Ramon

2017-10-06

The detection of change points is a pivotal task in statistical analysis. In the quantum realm, it is a new primitive where one aims at identifying the point where a source that supposedly prepares a sequence of particles in identical quantum states starts preparing a mutated one. We obtain the optimal procedure to identify the change point with certainty-naturally at the price of having a certain probability of getting an inconclusive answer. We obtain the analytical form of the optimal probability of successful identification for any length of the particle sequence. We show that the conditional success probabilities of identifying each possible change point show an unexpected oscillatory behavior. We also discuss local (online) protocols and compare them with the optimal procedure.

Vision System for Coarsely Estimating Motion Parameters for Unknown Fast Moving Objects in Space

PubMed Central

Chen, Min; Hashimoto, Koichi

2017-01-01

Motivated by biological interests in analyzing navigation behaviors of flying animals, we attempt to build a system measuring their motion states. To do this, in this paper, we build a vision system to detect unknown fast moving objects within a given space, calculating their motion parameters represented by positions and poses. We proposed a novel method to detect reliable interest points from images of moving objects, which can be hardly detected by general purpose interest point detectors. 3D points reconstructed using these interest points are then grouped and maintained for detected objects, according to a careful schedule, considering appearance and perspective changes. In the estimation step, a method is introduced to adapt the robust estimation procedure used for dense point set to the case for sparse set, reducing the potential risk of greatly biased estimation. Experiments are conducted against real scenes, showing the capability of the system of detecting multiple unknown moving objects and estimating their positions and poses. PMID:29206189

Time Series UAV Image-Based Point Clouds for Landslide Progression Evaluation Applications

PubMed Central

Moussa, Adel; El-Sheimy, Naser; Habib, Ayman

2017-01-01

Landslides are major and constantly changing threats to urban landscapes and infrastructure. It is essential to detect and capture landslide changes regularly. Traditional methods for monitoring landslides are time-consuming, costly, dangerous, and the quality and quantity of the data is sometimes unable to meet the necessary requirements of geotechnical projects. This motivates the development of more automatic and efficient remote sensing approaches for landslide progression evaluation. Automatic change detection involving low-altitude unmanned aerial vehicle image-based point clouds, although proven, is relatively unexplored, and little research has been done in terms of accounting for volumetric changes. In this study, a methodology for automatically deriving change displacement rates, in a horizontal direction based on comparisons between extracted landslide scarps from multiple time periods, has been developed. Compared with the iterative closest projected point (ICPP) registration method, the developed method takes full advantage of automated geometric measuring, leading to fast processing. The proposed approach easily processes a large number of images from different epochs and enables the creation of registered image-based point clouds without the use of extensive ground control point information or further processing such as interpretation and image correlation. The produced results are promising for use in the field of landslide research. PMID:29057847

Time Series UAV Image-Based Point Clouds for Landslide Progression Evaluation Applications.

PubMed

Al-Rawabdeh, Abdulla; Moussa, Adel; Foroutan, Marzieh; El-Sheimy, Naser; Habib, Ayman

2017-10-18

Landslides are major and constantly changing threats to urban landscapes and infrastructure. It is essential to detect and capture landslide changes regularly. Traditional methods for monitoring landslides are time-consuming, costly, dangerous, and the quality and quantity of the data is sometimes unable to meet the necessary requirements of geotechnical projects. This motivates the development of more automatic and efficient remote sensing approaches for landslide progression evaluation. Automatic change detection involving low-altitude unmanned aerial vehicle image-based point clouds, although proven, is relatively unexplored, and little research has been done in terms of accounting for volumetric changes. In this study, a methodology for automatically deriving change displacement rates, in a horizontal direction based on comparisons between extracted landslide scarps from multiple time periods, has been developed. Compared with the iterative closest projected point (ICPP) registration method, the developed method takes full advantage of automated geometric measuring, leading to fast processing. The proposed approach easily processes a large number of images from different epochs and enables the creation of registered image-based point clouds without the use of extensive ground control point information or further processing such as interpretation and image correlation. The produced results are promising for use in the field of landslide research.

Method for detecting point mutations in DNA utilizing fluorescence energy transfer

DOEpatents

Parkhurst, Lawrence J.; Parkhurst, Kay M.; Middendorf, Lyle

2001-01-01

A method for detecting point mutations in DNA using a fluorescently labeled oligomeric probe and Forster resonance energy transfer (FRET) is disclosed. The selected probe is initially labeled at each end with a fluorescence dye, which act together as a donor/acceptor pair for FRET. The fluorescence emission from the dyes changes dramatically from the duplex stage, wherein the probe is hybridized to the complementary strand of DNA, to the single strand stage, when the probe is melted to become detached from the DNA. The change in fluorescence is caused by the dyes coming into closer proximity after melting occurs and the probe becomes detached from the DNA strand. The change in fluorescence emission as a function of temperature is used to calculate the melting temperature of the complex or T.sub.m. In the case where there is a base mismatch between the probe and the DNA strand, indicating a point mutation, the T.sub.m has been found to be significantly lower than the T.sub.m for a perfectly match probelstand duplex. The present invention allows for the detection of the existence and magnitude of T.sub.m, which allows for the quick and accurate detection of a point mutation in the DNA strand and, in some applications, the determination of the approximate location of the mutation within the sequence.

The future point-of-care detection of disease and its data capture and handling.

PubMed

Lopez-Barbosa, Natalia; Gamarra, Jorge D; Osma, Johann F

2016-04-01

Point-of-care detection is a widely studied area that attracts effort and interest from a large number of fields and companies. However, there is also increased interest from the general public in this type of device, which has driven enormous changes in the design and conception of these developments and the way data is handled. Therefore, future point-of-care detection has to include communication with front-end technology, such as smartphones and networks, automation of manufacture, and the incorporation of concepts like the Internet of Things (IoT) and cloud computing. Three key examples, based on different sensing technology, are analyzed in detail on the basis of these items to highlight a route for the future design and development of point-of-care detection devices and their data capture and handling.

Landsat change detection can aid in water quality monitoring

NASA Technical Reports Server (NTRS)

Macdonald, H. C.; Steele, K. F.; Waite, W. P.; Shinn, M. R.

1977-01-01

Comparison between Landsat-1 and -2 imagery of Arkansas provided evidence of significant land use changes during the 1972-75 time period. Analysis of Arkansas historical water quality information has shown conclusively that whereas point source pollution generally can be detected by use of water quality data collected by state and federal agencies, sampling methodologies for nonpoint source contamination attributable to surface runoff are totally inadequate. The expensive undertaking of monitoring all nonpoint sources for numerous watersheds can be lessened by implementing Landsat change detection analyses.

Evaluating Google, Twitter, and Wikipedia as Tools for Influenza Surveillance Using Bayesian Change Point Analysis: A Comparative Analysis.

PubMed

Sharpe, J Danielle; Hopkins, Richard S; Cook, Robert L; Striley, Catherine W

2016-10-20

Traditional influenza surveillance relies on influenza-like illness (ILI) syndrome that is reported by health care providers. It primarily captures individuals who seek medical care and misses those who do not. Recently, Web-based data sources have been studied for application to public health surveillance, as there is a growing number of people who search, post, and tweet about their illnesses before seeking medical care. Existing research has shown some promise of using data from Google, Twitter, and Wikipedia to complement traditional surveillance for ILI. However, past studies have evaluated these Web-based sources individually or dually without comparing all 3 of them, and it would be beneficial to know which of the Web-based sources performs best in order to be considered to complement traditional methods. The objective of this study is to comparatively analyze Google, Twitter, and Wikipedia by examining which best corresponds with Centers for Disease Control and Prevention (CDC) ILI data. It was hypothesized that Wikipedia will best correspond with CDC ILI data as previous research found it to be least influenced by high media coverage in comparison with Google and Twitter. Publicly available, deidentified data were collected from the CDC, Google Flu Trends, HealthTweets, and Wikipedia for the 2012-2015 influenza seasons. Bayesian change point analysis was used to detect seasonal changes, or change points, in each of the data sources. Change points in Google, Twitter, and Wikipedia that occurred during the exact week, 1 preceding week, or 1 week after the CDC's change points were compared with the CDC data as the gold standard. All analyses were conducted using the R package "bcp" version 4.0.0 in RStudio version 0.99.484 (RStudio Inc). In addition, sensitivity and positive predictive values (PPV) were calculated for Google, Twitter, and Wikipedia. During the 2012-2015 influenza seasons, a high sensitivity of 92% was found for Google, whereas the PPV for Google was 85%. A low sensitivity of 50% was calculated for Twitter; a low PPV of 43% was found for Twitter also. Wikipedia had the lowest sensitivity of 33% and lowest PPV of 40%. Of the 3 Web-based sources, Google had the best combination of sensitivity and PPV in detecting Bayesian change points in influenza-related data streams. Findings demonstrated that change points in Google, Twitter, and Wikipedia data occasionally aligned well with change points captured in CDC ILI data, yet these sources did not detect all changes in CDC data and should be further studied and developed.

Investigation of Raman chemical imaging for detection of Lycopene changes in tomatoes during postharvest ripening

USDA-ARS?s Scientific Manuscript database

Lycopene is a major carotenoid in tomatoes and detecting changes in lycopene content can be used to monitor the ripening of tomatoes. Raman chemical imaging is a new technique that shows promise for mapping constituents of interest in complex food matrices. In this study, a benchtop point-scanning...

Assessing the response of runoff to climate change and human activities for a typical basin in the Northern Taihang Mountain, China

NASA Astrophysics Data System (ADS)

Wang, Jinfeng; Gao, Yanchuan; Wang, Sheng

2018-04-01

Climate change and human activities are the two main factors on runoff change. Quantifying the contribution of climate change and human activities on runoff change is important for water resources planning and management. In this study, the variation trend and abrupt change point of hydro-meteorological factors during 1960-2012 were detected by using the Mann-Kendall test and Pettitt change-point statistics. Then the runoff was simulated by SWAT model. The contribution of climate change and human activities on runoff change was calculated based on the SWAT model and the elasticity coefficient method. The results showed that in contrast to the increasing trend for annual temperature, the significant decreasing trends were detected for annual runoff and precipitation, with an abrupt change point in 1982. The simulated results of SWAT had good consistency with observed ones, and the values of R2 and E_{NS} all exceeded 0.75. The two methods used for assessing the contribution of climate change and human activities on runoff reduction yielded consistent results. The contribution of climate change (precipitation reduction and temperature rise) was {˜ }37.5%, while the contribution of human activities (the increase of economic forest and built-up land, hydrologic projects) was {˜ }62.5%.

Quantification of Forecasting and Change-Point Detection Methods for Predictive Maintenance

DTIC Science & Technology

2015-08-19

industries to manage the service life of equipment, and also to detect precursors to the failure of components found in nuclear power plants, wind turbines ...detection methods for predictive maintenance 5a. CONTRACT NUMBER FA2386-14-1-4096 5b. GRANT NUMBER Grant 14IOA015 AOARD-144096 5c. PROGRAM ELEMENT...sensitive to changes related to abnormality. 15. SUBJECT TERMS predictive maintenance , predictive maintenance , forecasting 16

Analysis of ICESat Data Using Kalman Filter and Kriging to Study Height Changes in East Antarctica

NASA Technical Reports Server (NTRS)

Herring, Thomas A.

2005-01-01

We analyze ICESat derived heights collected between Feb. 03-Nov. 04 using a kriging/Kalman filtering approach to investigate height changes in East Antarctica. The model's parameters are height change to an a priori static digital height model, seasonal signal expressed as an amplitude Beta and phase Theta, and height-change rate dh/dt for each (100 km)(exp 2) block. From the Kalman filter results, dh/dt has a mean of -0.06 m/yr in the flat interior of East Antarctica. Spatially correlated pointing errors in the current data releases give uncertainties in the range 0.06 m/yr, making height change detection unreliable at this time. Our test shows that when using all available data with pointing knowledge equivalent to that of Laser 2a, height change detection with an accuracy level 0.02 m/yr can be achieved over flat terrains in East Antarctica.

Jump point detection for real estate investment success

NASA Astrophysics Data System (ADS)

Hui, Eddie C. M.; Yu, Carisa K. W.; Ip, Wai-Cheung

2010-03-01

In the literature, studies on real estate market were mainly concentrating on the relation between property price and some key factors. The trend of the real estate market is a major concern. It is believed that changes in trend are signified by some jump points in the property price series. Identifying such jump points reveals important findings that enable policy-makers to look forward. However, not all jump points are observable from the plot of the series. This paper looks into the trend and introduces a new approach to the framework for real estate investment success. The main purpose of this paper is to detect jump points in the time series of some housing price indices and stock price index in Hong Kong by applying the wavelet analysis. The detected jump points reflect to some significant political issues and economic collapse. Moreover, the relations among properties of different classes and between stocks and properties are examined. It can be shown from the empirical result that a lead-lag effect happened between the prices of large-size property and those of small/medium-size property. However, there is no apparent relation or consistent lead in terms of change point measure between property price and stock price. This may be due to the fact that globalization effect has more impact on the stock price than the property price.

Assessing the accuracy and repeatability of automated photogrammetrically generated digital surface models from unmanned aerial system imagery

NASA Astrophysics Data System (ADS)

Chavis, Christopher

Using commercial digital cameras in conjunction with Unmanned Aerial Systems (UAS) to generate 3-D Digital Surface Models (DSMs) and orthomosaics is emerging as a cost-effective alternative to Light Detection and Ranging (LiDAR). Powerful software applications such as Pix4D and APS can automate the generation of DSM and orthomosaic products from a handful of inputs. However, the accuracy of these models is relatively untested. The objectives of this study were to generate multiple DSM and orthomosaic pairs of the same area using Pix4D and APS from flights of imagery collected with a lightweight UAS. The accuracy of each individual DSM was assessed in addition to the consistency of the method to model one location over a period of time. Finally, this study determined if the DSMs automatically generated using lightweight UAS and commercial digital cameras could be used for detecting changes in elevation and at what scale. Accuracy was determined by comparing DSMs to a series of reference points collected with survey grade GPS. Other GPS points were also used as control points to georeference the products within Pix4D and APS. The effectiveness of the products for change detection was assessed through image differencing and observance of artificially induced, known elevation changes. The vertical accuracy with the optimal data and model is ≈ 25 cm and the highest consistency over repeat flights is a standard deviation of ≈ 5 cm. Elevation change detection based on such UAS imagery and DSM models should be viable for detecting infrastructure change in urban or suburban environments with little dense canopy vegetation.

Comparative responsiveness and minimal clinically important differences for idiopathic ulnar impaction syndrome.

PubMed

Kim, Jae Kwang; Park, Eun Soo

2013-05-01

Patient-reported questionnaires have been widely used to predict symptom severity and functional disability in musculoskeletal disease. Importantly, questionnaires can detect clinical changes in patients; however, this impact has not been determined for ulnar impaction syndrome. We asked (1) which of Patient-Rated Wrist Evaluation (PRWE), DASH, and other physical measures was more responsive to clinical improvements, and (2) what was the minimal clinically important difference for the PRWE and DASH after ulnar shortening osteotomy for idiopathic ulnar impaction syndrome. All patients who underwent ulnar shortening osteotomy between March 2008 and February 2011 for idiopathic ulnar impaction syndrome were enrolled in this study. All patients completed the PRWE and DASH questionnaires, and all were evaluated for grip strength and wrist ROM, preoperatively and 12 months postoperatively. We compared the effect sizes observed by each of these instruments. Effect size is calculated by dividing the mean change in a score of each instrument during a specified interval by the standard deviation of the baseline score. In addition, patient-perceived overall improvement was used as the anchor to determine the minimal clinically important differences on the PRWE and DASH 12 months after surgery. The average score of each item except for wrist flexion and supination improved after surgery. The PRWE was more sensitive than the DASH or than physical measurements in detecting clinical changes. The effect sizes and standardized response means of the outcome measures were as follows: PRWE (1.51, 1.64), DASH (1.12, 1.24), grip strength (0.59, 0.68), wrist pronation (0.33, 0.41), and wrist extension (0.28, 0.36). Patient-perceived overall improvement and score changes of the PRWE and DASH correlated significantly. Minimal clinically important differences were 17 points (of a possible 100) for the PRWE and 13.5 for the DASH (also of 100), and minimal detectable changes were 7.7 points for the PRWE and 9.3 points for the DASH. Although the PRWE and DASH were highly sensitive to clinical changes, the PRWE was more sensitive in terms of detecting clinical changes after ulnar shortening osteotomy for idiopathic ulnar impaction syndrome. A minimal change of 17 PRWE points or 13.5 DASH points was necessary to achieve a benefit that patients perceived as clinically important. The minimal clinically important differences using these instruments were higher than the values produced by measurement errors.

Feature-based registration of historical aerial images by Area Minimization

NASA Astrophysics Data System (ADS)

Nagarajan, Sudhagar; Schenk, Toni

2016-06-01

The registration of historical images plays a significant role in assessing changes in land topography over time. By comparing historical aerial images with recent data, geometric changes that have taken place over the years can be quantified. However, the lack of ground control information and precise camera parameters has limited scientists' ability to reliably incorporate historical images into change detection studies. Other limitations include the methods of determining identical points between recent and historical images, which has proven to be a cumbersome task due to continuous land cover changes. Our research demonstrates a method of registering historical images using Time Invariant Line (TIL) features. TIL features are different representations of the same line features in multi-temporal data without explicit point-to-point or straight line-to-straight line correspondence. We successfully determined the exterior orientation of historical images by minimizing the area formed between corresponding TIL features in recent and historical images. We then tested the feasibility of the approach with synthetic and real data and analyzed the results. Based on our analysis, this method shows promise for long-term 3D change detection studies.

Person Fit Analysis in Computerized Adaptive Testing Using Tests for a Change Point

ERIC Educational Resources Information Center

Sinharay, Sandip

2016-01-01

Meijer and van Krimpen-Stoop noted that the number of person-fit statistics (PFSs) that have been designed for computerized adaptive tests (CATs) is relatively modest. This article partially addresses that concern by suggesting three new PFSs for CATs. The statistics are based on tests for a change point and can be used to detect an abrupt change…

Measurement error in the Liebowitz Social Anxiety Scale: results from a general adult population in Japan.

PubMed

Takada, Koki; Takahashi, Kana; Hirao, Kazuki

2018-01-17

Although the self-report version of Liebowitz Social Anxiety Scale (LSAS) is frequently used to measure social anxiety, data is lacking on the smallest detectable change (SDC), an important index of measurement error. We therefore aimed to determine the SDC of LSAS. Japanese adults aged 20-69 years were invited from a panel managed by a nationwide internet research agency. We then conducted a test-retest internet survey with a two-week interval to estimate the SDC at the individual (SDC ind ) and group (SDC group ) levels. The analysis included 1300 participants. The SDC ind and SDC group for the total fear subscale (scoring range: 0-72) were 23.52 points (32.7%) and 0.65 points (0.9%), respectively. The SDC ind and SDC group for the total avoidance subscale (scoring range: 0-72) were 32.43 points (45.0%) and 0.90 points (1.2%), respectively. The SDC ind and SDC group for the overall total score (scoring range: 0-144) were 45.90 points (31.9%) and 1.27 points (0.9%), respectively. Measurement error is large and indicate the potential for major problems when attempting to use the LSAS to detect changes at the individual level. These results should be considered when using the LSAS as measures of treatment change.

Hypothesis testing of a change point during cognitive decline among Alzheimer's disease patients.

PubMed

Ji, Ming; Xiong, Chengjie; Grundman, Michael

2003-10-01

In this paper, we present a statistical hypothesis test for detecting a change point over the course of cognitive decline among Alzheimer's disease patients. The model under the null hypothesis assumes a constant rate of cognitive decline over time and the model under the alternative hypothesis is a general bilinear model with an unknown change point. When the change point is unknown, however, the null distribution of the test statistics is not analytically tractable and has to be simulated by parametric bootstrap. When the alternative hypothesis that a change point exists is accepted, we propose an estimate of its location based on the Akaike's Information Criterion. We applied our method to a data set from the Neuropsychological Database Initiative by implementing our hypothesis testing method to analyze Mini Mental Status Exam scores based on a random-slope and random-intercept model with a bilinear fixed effect. Our result shows that despite large amount of missing data, accelerated decline did occur for MMSE among AD patients. Our finding supports the clinical belief of the existence of a change point during cognitive decline among AD patients and suggests the use of change point models for the longitudinal modeling of cognitive decline in AD research.

Applications of multiscale change point detections to monthly stream flow and rainfall in Xijiang River in southern China, part I: correlation and variance

NASA Astrophysics Data System (ADS)

Zhu, Yuxiang; Jiang, Jianmin; Huang, Changxing; Chen, Yongqin David; Zhang, Qiang

2018-04-01

This article, as part I, introduces three algorithms and applies them to both series of the monthly stream flow and rainfall in Xijiang River, southern China. The three algorithms include (1) normalization of probability distribution, (2) scanning U test for change points in correlation between two time series, and (3) scanning F-test for change points in variances. The normalization algorithm adopts the quantile method to normalize data from a non-normal into the normal probability distribution. The scanning U test and F-test have three common features: grafting the classical statistics onto the wavelet algorithm, adding corrections for independence into each statistic criteria at given confidence respectively, and being almost objective and automatic detection on multiscale time scales. In addition, the coherency analyses between two series are also carried out for changes in variance. The application results show that the changes of the monthly discharge are still controlled by natural precipitation variations in Xijiang's fluvial system. Human activities disturbed the ecological balance perhaps in certain content and in shorter spells but did not violate the natural relationships of correlation and variance changes so far.

Ratio-based estimators for a change point in persistence.

PubMed

Halunga, Andreea G; Osborn, Denise R

2012-11-01

We study estimation of the date of change in persistence, from [Formula: see text] to [Formula: see text] or vice versa. Contrary to statements in the original papers, our analytical results establish that the ratio-based break point estimators of Kim [Kim, J.Y., 2000. Detection of change in persistence of a linear time series. Journal of Econometrics 95, 97-116], Kim et al. [Kim, J.Y., Belaire-Franch, J., Badillo Amador, R., 2002. Corringendum to "Detection of change in persistence of a linear time series". Journal of Econometrics 109, 389-392] and Busetti and Taylor [Busetti, F., Taylor, A.M.R., 2004. Tests of stationarity against a change in persistence. Journal of Econometrics 123, 33-66] are inconsistent when a mean (or other deterministic component) is estimated for the process. In such cases, the estimators converge to random variables with upper bound given by the true break date when persistence changes from [Formula: see text] to [Formula: see text]. A Monte Carlo study confirms the large sample downward bias and also finds substantial biases in moderate sized samples, partly due to properties at the end points of the search interval.

Defining the minimal detectable change in scores on the eight-item Morisky Medication Adherence Scale.

PubMed

Muntner, Paul; Joyce, Cara; Holt, Elizabeth; He, Jiang; Morisky, Donald; Webber, Larry S; Krousel-Wood, Marie

2011-05-01

Self-report scales are used to assess medication adherence. Data on how to discriminate change in self-reported adherence over time from random variability are limited. To determine the minimal detectable change for scores on the 8-item Morisky Medication Adherence Scale (MMAS-8). The MMAS-8 was administered twice, using a standard telephone script, with administration separated by 14-22 days, to 210 participants taking antihypertensive medication in the CoSMO (Cohort Study of Medication Adherence among Older Adults). MMAS-8 scores were calculated and participants were grouped into previously defined categories (<6, 6 to <8, and 8 for low, medium, and high adherence). The mean (SD) age of participants was 78.1 (5.8) years, 43.8% were black, and 68.1% were women. Overall, 8.1% (17/210), 16.2% (34/210), and 51.0% (107/210) of participants had low, medium, and high MMAS-8 scores, respectively, at both survey administrations (overall agreement 75.2%; 158/210). The weighted κ statistic was 0.63 (95% CI 0.53 to 0.72). The intraclass correlation coefficient was 0.78. The within-person standard error of the mean for change in MMAS-8 scores was 0.81, which equated to a minimal detectable change of 1.98 points. Only 4.3% (9/210) of the participants had a change in MMAS-8 of 2 or more points between survey administrations. Within-person changes in MMAS-8 scores of 2 or more points over time may represent a real change in antihypertensive medication adherence.

Can Probability Maps of Swept-Source Optical Coherence Tomography Predict Visual Field Changes in Preperimetric Glaucoma?

PubMed

Lee, Won June; Kim, Young Kook; Jeoung, Jin Wook; Park, Ki Ho

2017-12-01

To determine the usefulness of swept-source optical coherence tomography (SS-OCT) probability maps in detecting locations with significant reduction in visual field (VF) sensitivity or predicting future VF changes, in patients with classically defined preperimetric glaucoma (PPG). Of 43 PPG patients, 43 eyes were followed-up on every 6 months for at least 2 years were analyzed in this longitudinal study. The patients underwent wide-field SS-OCT scanning and standard automated perimetry (SAP) at the time of enrollment. With this wide-scan protocol, probability maps originating from the corresponding thickness map and overlapped with SAP VF test points could be generated. We evaluated the vulnerable VF points with SS-OCT probability maps as well as the prevalence of locations with significant VF reduction or subsequent VF changes observed in the corresponding damaged areas of the probability maps. The vulnerable VF points were shown in superior and inferior arcuate patterns near the central fixation. In 19 of 43 PPG eyes (44.2%), significant reduction in baseline VF was detected within the areas of structural change on the SS-OCT probability maps. In 16 of 43 PPG eyes (37.2%), subsequent VF changes within the areas of SS-OCT probability map change were observed over the course of the follow-up. Structural changes on SS-OCT probability maps could detect or predict VF changes using SAP, in a considerable number of PPG eyes. Careful comparison of probability maps with SAP results could be useful in diagnosing and monitoring PPG patients in the clinical setting.

Ten Years of Land Cover Change on the California Coast Detected using Landsat Satellite Image Analysis

NASA Technical Reports Server (NTRS)

Potter, Christopher S.

2013-01-01

Landsat satellite imagery was analyzed to generate a detailed record of 10 years of vegetation disturbance and regrowth for Pacific coastal areas of Marin and San Francisco Counties. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) methodology, a transformation of Tasseled-Cap data space, was applied to detected changes in perennial coastal shrubland, woodland, and forest cover from 1999 to 2009. Results showed several principal points of interest, within which extensive contiguous areas of similar LEDAPS vegetation change (either disturbed or restored) were detected. Regrowth areas were delineated as burned forest areas in the Point Reyes National Seashore (PRNS) from the 1995 Vision Fire. LEDAPS-detected disturbance patterns on Inverness Ridge, PRNS in areas observed with dieback of tanoak and bay laurel trees was consistent with defoliation by sudden oak death (Phytophthora ramorum). LEDAPS regrowth pixels were detected over much of the predominantly grassland/herbaceous cover of the Olema Valley ranchland near PRNS. Extensive restoration of perennial vegetation cover on Crissy Field, Baker Beach and Lobos Creek dunes in San Francisco was identified. Based on these examples, the LEDAPS methodology will be capable of fulfilling much of the need for continual, low-cost monitoring of emerging changes to coastal ecosystems.

Evaluating Google, Twitter, and Wikipedia as Tools for Influenza Surveillance Using Bayesian Change Point Analysis: A Comparative Analysis

PubMed Central

Hopkins, Richard S; Cook, Robert L; Striley, Catherine W

2016-01-01

Background Traditional influenza surveillance relies on influenza-like illness (ILI) syndrome that is reported by health care providers. It primarily captures individuals who seek medical care and misses those who do not. Recently, Web-based data sources have been studied for application to public health surveillance, as there is a growing number of people who search, post, and tweet about their illnesses before seeking medical care. Existing research has shown some promise of using data from Google, Twitter, and Wikipedia to complement traditional surveillance for ILI. However, past studies have evaluated these Web-based sources individually or dually without comparing all 3 of them, and it would be beneficial to know which of the Web-based sources performs best in order to be considered to complement traditional methods. Objective The objective of this study is to comparatively analyze Google, Twitter, and Wikipedia by examining which best corresponds with Centers for Disease Control and Prevention (CDC) ILI data. It was hypothesized that Wikipedia will best correspond with CDC ILI data as previous research found it to be least influenced by high media coverage in comparison with Google and Twitter. Methods Publicly available, deidentified data were collected from the CDC, Google Flu Trends, HealthTweets, and Wikipedia for the 2012-2015 influenza seasons. Bayesian change point analysis was used to detect seasonal changes, or change points, in each of the data sources. Change points in Google, Twitter, and Wikipedia that occurred during the exact week, 1 preceding week, or 1 week after the CDC’s change points were compared with the CDC data as the gold standard. All analyses were conducted using the R package “bcp” version 4.0.0 in RStudio version 0.99.484 (RStudio Inc). In addition, sensitivity and positive predictive values (PPV) were calculated for Google, Twitter, and Wikipedia. Results During the 2012-2015 influenza seasons, a high sensitivity of 92% was found for Google, whereas the PPV for Google was 85%. A low sensitivity of 50% was calculated for Twitter; a low PPV of 43% was found for Twitter also. Wikipedia had the lowest sensitivity of 33% and lowest PPV of 40%. Conclusions Of the 3 Web-based sources, Google had the best combination of sensitivity and PPV in detecting Bayesian change points in influenza-related data streams. Findings demonstrated that change points in Google, Twitter, and Wikipedia data occasionally aligned well with change points captured in CDC ILI data, yet these sources did not detect all changes in CDC data and should be further studied and developed. PMID:27765731

Presenting a model for dynamic facial expression changes in detecting drivers' drowsiness.

PubMed

Karchani, Mohsen; Mazloumi, Adel; Saraji, Gebraeil Nasl; Gharagozlou, Faramarz; Nahvi, Ali; Haghighi, Khosro Sadeghniiat; Abadi, Bahador Makki; Foroshani, Abbas Rahimi

2015-01-01

Drowsiness while driving is a major cause of accidents. A driver fatigue detection system that is designed to sound an alarm, when appropriate, can prevent many accidents that sometime leads to the loss of life and property. In this paper, we classify drowsiness detection sensors and their strong and weak points. A compound model is proposed that uses image processing techniques to study the dynamic changes of the face to recognize drowsiness during driving.

Revealing turning points in ecosystem functioning over the Northern Eurasian agricultural frontier.

PubMed

Horion, Stéphanie; Prishchepov, Alexander V; Verbesselt, Jan; de Beurs, Kirsten; Tagesson, Torbern; Fensholt, Rasmus

2016-08-01

The collapse of the Soviet Union in 1991 has been a turning point in the World history that left a unique footprint on the Northern Eurasian ecosystems. Conducting large scale mapping of environmental change and separating between naturogenic and anthropogenic drivers is a difficult endeavor in such highly complex systems. In this research a piece-wise linear regression method was used for breakpoint detection in Rain-Use Efficiency (RUE) time series and a classification of ecosystem response types was produced. Supported by earth observation data, field data, and expert knowledge, this study provides empirical evidence regarding the occurrence of drastic changes in RUE (assessment of the timing, the direction and the significance of these changes) in Northern Eurasian ecosystems between 1982 and 2011. About 36% of the study area (3.4 million km(2) ) showed significant (P < 0.05) trends and/or turning points in RUE during the observation period. A large proportion of detected turning points in RUE occurred around the fall of the Soviet Union in 1991 and in the following years which were attributed to widespread agricultural land abandonment. Our study also showed that recurrent droughts deeply affected vegetation productivity throughout the observation period, with a general worsening of the drought conditions in recent years. Moreover, recent human-induced turning points in ecosystem functioning were detected and attributed to ongoing recultivation and change in irrigation practices in the Volgograd region, and to increased salinization and increased grazing intensity around Lake Balkhash. The ecosystem-state assessment method introduced here proved to be a valuable support that highlighted hotspots of potentially altered ecosystems and allowed for disentangling human from climatic disturbances. © 2016 John Wiley & Sons Ltd.

Self-Similar Spin Images for Point Cloud Matching

NASA Astrophysics Data System (ADS)

Pulido, Daniel

The rapid growth of Light Detection And Ranging (Lidar) technologies that collect, process, and disseminate 3D point clouds have allowed for increasingly accurate spatial modeling and analysis of the real world. Lidar sensors can generate massive 3D point clouds of a collection area that provide highly detailed spatial and radiometric information. However, a Lidar collection can be expensive and time consuming. Simultaneously, the growth of crowdsourced Web 2.0 data (e.g., Flickr, OpenStreetMap) have provided researchers with a wealth of freely available data sources that cover a variety of geographic areas. Crowdsourced data can be of varying quality and density. In addition, since it is typically not collected as part of a dedicated experiment but rather volunteered, when and where the data is collected is arbitrary. The integration of these two sources of geoinformation can provide researchers the ability to generate products and derive intelligence that mitigate their respective disadvantages and combine their advantages. Therefore, this research will address the problem of fusing two point clouds from potentially different sources. Specifically, we will consider two problems: scale matching and feature matching. Scale matching consists of computing feature metrics of each point cloud and analyzing their distributions to determine scale differences. Feature matching consists of defining local descriptors that are invariant to common dataset distortions (e.g., rotation and translation). Additionally, after matching the point clouds they can be registered and processed further (e.g., change detection). The objective of this research is to develop novel methods to fuse and enhance two point clouds from potentially disparate sources (e.g., Lidar and crowdsourced Web 2.0 datasets). The scope of this research is to investigate both scale and feature matching between two point clouds. The specific focus of this research will be in developing a novel local descriptor based on the concept of self-similarity to aid in the scale and feature matching steps. An open problem in fusion is how best to extract features from two point clouds and then perform feature-based matching. The proposed approach for this matching step is the use of local self-similarity as an invariant measure to match features. In particular, the proposed approach is to combine the concept of local self-similarity with a well-known feature descriptor, Spin Images, and thereby define "Self-Similar Spin Images". This approach is then extended to the case of matching two points clouds in very different coordinate systems (e.g., a geo-referenced Lidar point cloud and stereo-image derived point cloud without geo-referencing). The use of Self-Similar Spin Images is again applied to address this problem by introducing a "Self-Similar Keyscale" that matches the spatial scales of two point clouds. Another open problem is how best to detect changes in content between two point clouds. A method is proposed to find changes between two point clouds by analyzing the order statistics of the nearest neighbors between the two clouds, and thereby define the "Nearest Neighbor Order Statistic" method. Note that the well-known Hausdorff distance is a special case as being just the maximum order statistic. Therefore, by studying the entire histogram of these nearest neighbors it is expected to yield a more robust method to detect points that are present in one cloud but not the other. This approach is applied at multiple resolutions. Therefore, changes detected at the coarsest level will yield large missing targets and at finer levels will yield smaller targets.

Structure Line Detection from LIDAR Point Clouds Using Topological Elevation Analysis

NASA Astrophysics Data System (ADS)

Lo, C. Y.; Chen, L. C.

2012-07-01

Airborne LIDAR point clouds, which have considerable points on object surfaces, are essential to building modeling. In the last two decades, studies have developed different approaches to identify structure lines using two main approaches, data-driven and modeldriven. These studies have shown that automatic modeling processes depend on certain considerations, such as used thresholds, initial value, designed formulas, and predefined cues. Following the development of laser scanning systems, scanning rates have increased and can provide point clouds with higher point density. Therefore, this study proposes using topological elevation analysis (TEA) to detect structure lines instead of threshold-dependent concepts and predefined constraints. This analysis contains two parts: data pre-processing and structure line detection. To preserve the original elevation information, a pseudo-grid for generating digital surface models is produced during the first part. The highest point in each grid is set as the elevation value, and its original threedimensional position is preserved. In the second part, using TEA, the structure lines are identified based on the topology of local elevation changes in two directions. Because structure lines can contain certain geometric properties, their locations have small relieves in the radial direction and steep elevation changes in the circular direction. Following the proposed approach, TEA can be used to determine 3D line information without selecting thresholds. For validation, the TEA results are compared with those of the region growing approach. The results indicate that the proposed method can produce structure lines using dense point clouds.

Sequential structural damage diagnosis algorithm using a change point detection method

NASA Astrophysics Data System (ADS)

Noh, H.; Rajagopal, R.; Kiremidjian, A. S.

2013-11-01

This paper introduces a damage diagnosis algorithm for civil structures that uses a sequential change point detection method. The general change point detection method uses the known pre- and post-damage feature distributions to perform a sequential hypothesis test. In practice, however, the post-damage distribution is unlikely to be known a priori, unless we are looking for a known specific type of damage. Therefore, we introduce an additional algorithm that estimates and updates this distribution as data are collected using the maximum likelihood and the Bayesian methods. We also applied an approximate method to reduce the computation load and memory requirement associated with the estimation. The algorithm is validated using a set of experimental data collected from a four-story steel special moment-resisting frame and multiple sets of simulated data. Various features of different dimensions have been explored, and the algorithm was able to identify damage, particularly when it uses multidimensional damage sensitive features and lower false alarm rates, with a known post-damage feature distribution. For unknown feature distribution cases, the post-damage distribution was consistently estimated and the detection delays were only a few time steps longer than the delays from the general method that assumes we know the post-damage feature distribution. We confirmed that the Bayesian method is particularly efficient in declaring damage with minimal memory requirement, but the maximum likelihood method provides an insightful heuristic approach.

Meaningful change and responsiveness in common physical performance measures in older adults.

PubMed

Perera, Subashan; Mody, Samir H; Woodman, Richard C; Studenski, Stephanie A

2006-05-01

To estimate the magnitude of small meaningful and substantial individual change in physical performance measures and evaluate their responsiveness. Secondary data analyses using distribution- and anchor-based methods to determine meaningful change. Secondary analysis of data from an observational study and clinical trials of community-dwelling older people and subacute stroke survivors. Older adults with mobility disabilities in a strength training trial (n=100), subacute stroke survivors in an intervention trial (n=100), and a prospective cohort of community-dwelling older people (n=492). Gait speed, Short Physical Performance Battery (SPPB), 6-minute-walk distance (6MWD), and self-reported mobility. Most small meaningful change estimates ranged from 0.04 to 0.06 m/s for gait speed, 0.27 to 0.55 points for SPPB, and 19 to 22 m for 6MWD. Most substantial change estimates ranged from 0.08 to 0.14 m/s for gait speed, 0.99 to 1.34 points for SPPB, and 47 to 49 m for 6MWD. Based on responsiveness indices, per-group sample sizes for clinical trials ranged from 13 to 42 for substantial change and 71 to 161 for small meaningful change. Best initial estimates of small meaningful change are near 0.05 m/s for gait speed, 0.5 points for SPPB, and 20 m for 6MWD and of substantial change are near 0.10 m/s for gait speed, 1.0 point for SPPB, and 50 m for 6MWD. For clinical use, substantial change in these measures and small change in gait speed and 6MWD, but not SPPB, are detectable. For research use, these measures yield feasible sample sizes for detecting meaningful change.

Smallest detectable change and test-retest reliability of a self-reported outcome measure: Results of the Center for Epidemiologic Studies Depression Scale, General Self-Efficacy Scale, and 12-item General Health Questionnaire.

PubMed

Ohno, Shotaro; Takahashi, Kana; Inoue, Aimi; Takada, Koki; Ishihara, Yoshiaki; Tanigawa, Masaru; Hirao, Kazuki

2017-12-01

This study aims to examine the smallest detectable change (SDC) and test-retest reliability of the Center for Epidemiologic Studies Depression Scale (CES-D), General Self-Efficacy Scale (GSES), and 12-item General Health Questionnaire (GHQ-12). We tested 154 young adults at baseline and 2 weeks later. We calculated the intra-class correlation coefficients (ICCs) for test-retest reliability with a two-way random effects model for agreement. We then calculated the standard error of measurement (SEM) for agreement using the ICC formula. The SEM for agreement was used to calculate SDC values at the individual level (SDC ind ) and group level (SDC group ). The study participants included 137 young adults. The ICCs for all self-reported outcome measurement scales exceeded 0.70. The SEM of CES-D was 3.64, leading to an SDC ind of 10.10 points and SDC group of 0.86 points. The SEM of GSES was 1.56, leading to an SDC ind of 4.33 points and SDC group of 0.37 points. The SEM of GHQ-12 with bimodal scoring was 1.47, leading to an SDC ind of 4.06 points and SDC group of 0.35 points. The SEM of GHQ-12 with Likert scoring was 2.44, leading to an SDC ind of 6.76 points and SDC group of 0.58 points. To confirm that the change was not a result of measurement error, a score of self-reported outcome measurement scales would need to change by an amount greater than these SDC values. This has important implications for clinicians and epidemiologists when assessing outcomes. © 2017 John Wiley & Sons, Ltd.

Land use change detection with LANDSAT-2 data for monitoring and predicting regional water quality degradation. [Arkansas

NASA Technical Reports Server (NTRS)

Macdonald, H.; Steele, K. (Principal Investigator); Waite, W.; Rice, R.; Shinn, M.; Dillard, T.; Petersen, C.

1977-01-01

The author has identified the following significant results. Comparison between LANDSAT 1 and 2 imagery of Arkansas provided evidence of significant land use changes during the 1972-75 time period. Analysis of Arkansas historical water quality information has shown conclusively that whereas point source pollution generally can be detected by use of water quality data collected by state and federal agencies, sampling methodologies for nonpoint source contamination attributable to surface runoff are totally inadequate. The expensive undertaking of monitoring all nonpoint sources for numerous watersheds can be lessened by implementing LANDSAT change detection analyses.

Presenting a model for dynamic facial expression changes in detecting drivers’ drowsiness

PubMed Central

Karchani, Mohsen; Mazloumi, Adel; Saraji, Gebraeil Nasl; Gharagozlou, Faramarz; Nahvi, Ali; Haghighi, Khosro Sadeghniiat; Abadi, Bahador Makki; Foroshani, Abbas Rahimi

2015-01-01

Drowsiness while driving is a major cause of accidents. A driver fatigue detection system that is designed to sound an alarm, when appropriate, can prevent many accidents that sometime leads to the loss of life and property. In this paper, we classify drowsiness detection sensors and their strong and weak points. A compound model is proposed that uses image processing techniques to study the dynamic changes of the face to recognize drowsiness during driving. PMID:26120417

Interest point detection for hyperspectral imagery

NASA Astrophysics Data System (ADS)

Dorado-Muñoz, Leidy P.; Vélez-Reyes, Miguel; Roysam, Badrinath; Mukherjee, Amit

2009-05-01

This paper presents an algorithm for automated extraction of interest points (IPs)in multispectral and hyperspectral images. Interest points are features of the image that capture information from its neighbours and they are distinctive and stable under transformations such as translation and rotation. Interest-point operators for monochromatic images were proposed more than a decade ago and have since been studied extensively. IPs have been applied to diverse problems in computer vision, including image matching, recognition, registration, 3D reconstruction, change detection, and content-based image retrieval. Interest points are helpful in data reduction, and reduce the computational burden of various algorithms (like registration, object detection, 3D reconstruction etc) by replacing an exhaustive search over the entire image domain by a probe into a concise set of highly informative points. An interest operator seeks out points in an image that are structurally distinct, invariant to imaging conditions, stable under geometric transformation, and interpretable which are good candidates for interest points. Our approach extends ideas from Lowe's keypoint operator that uses local extrema of Difference of Gaussian (DoG) operator at multiple scales to detect interest point in gray level images. The proposed approach extends Lowe's method by direct conversion of scalar operations such as scale-space generation, and extreme point detection into operations that take the vector nature of the image into consideration. Experimental results with RGB and hyperspectral images which demonstrate the potential of the method for this application and the potential improvements of a fully vectorial approach over band-by-band approaches described in the literature.

Geomorphological activity at a rock glacier front detected with a 3D density-based clustering algorithm

NASA Astrophysics Data System (ADS)

Micheletti, Natan; Tonini, Marj; Lane, Stuart N.

2017-02-01

Acquisition of high density point clouds using terrestrial laser scanners (TLSs) has become commonplace in geomorphic science. The derived point clouds are often interpolated onto regular grids and the grids compared to detect change (i.e. erosion and deposition/advancement movements). This procedure is necessary for some applications (e.g. digital terrain analysis), but it inevitably leads to a certain loss of potentially valuable information contained within the point clouds. In the present study, an alternative methodology for geomorphological analysis and feature detection from point clouds is proposed. It rests on the use of the Density-Based Spatial Clustering of Applications with Noise (DBSCAN), applied to TLS data for a rock glacier front slope in the Swiss Alps. The proposed methods allowed the detection and isolation of movements directly from point clouds which yield to accuracies in the following computation of volumes that depend only on the actual registered distance between points. We demonstrated that these values are more conservative than volumes computed with the traditional DEM comparison. The results are illustrated for the summer of 2015, a season of enhanced geomorphic activity associated with exceptionally high temperatures.

Calculation of the ELISA's cut-off based on the change-point analysis method for detection of Trypanosoma cruzi infection in Bolivian dogs in the absence of controls.

PubMed

Lardeux, Frédéric; Torrico, Gino; Aliaga, Claudia

2016-07-04

In ELISAs, sera of individuals infected by Trypanosoma cruzi show absorbance values above a cut-off value. The cut-off is generally computed by means of formulas that need absorbance readings of negative (and sometimes positive) controls, which are included in the titer plates amongst the unknown samples. When no controls are available, other techniques should be employed such as change-point analysis. The method was applied to Bolivian dog sera processed by ELISA to diagnose T. cruzi infection. In each titer plate, the change-point analysis estimated a step point which correctly discriminated among known positive and known negative sera, unlike some of the six usual cut-off formulas tested. To analyse the ELISAs results, the change-point method was as good as the usual cut-off formula of the form "mean + 3 standard deviation of negative controls". Change-point analysis is therefore an efficient alternative method to analyse ELISA absorbance values when no controls are available.

Probabilistic change mapping from airborne LiDAR for post-disaster damage assessment

NASA Astrophysics Data System (ADS)

Jalobeanu, A.; Runyon, S. C.; Kruse, F. A.

2013-12-01

When both pre- and post-event LiDAR point clouds are available, change detection can be performed to identify areas that were most affected by a disaster event, and to obtain a map of quantitative changes in terms of height differences. In the case of earthquakes in built-up areas for instance, first responders can use a LiDAR change map to help prioritize search and recovery efforts. The main challenge consists of producing reliable change maps, robust to collection conditions, free of processing artifacts (due for instance to triangulation or gridding), and taking into account the various sources of uncertainty. Indeed, datasets acquired within a few years interval are often of different point density (sometimes an order of magnitude higher for recent data), different acquisition geometries, and very likely suffer from georeferencing errors and geometric discrepancies. All these differences might not be important for producing maps from each dataset separately, but they are crucial when performing change detection. We have developed a novel technique for the estimation of uncertainty maps from the LiDAR point clouds, using Bayesian inference, treating all variables as random. The main principle is to grid all points on a common grid before attempting any comparison, as working directly with point clouds is cumbersome and time consuming. A non-parametric approach based on local linear regression was implemented, assuming a locally linear model for the surface. This enabled us to derive error bars on gridded elevations, and then elevation differences. In this way, a map of statistically significant changes could be computed - whereas a deterministic approach would not allow testing of the significance of differences between the two datasets. This approach allowed us to take into account not only the observation noise (due to ranging, position and attitude errors) but also the intrinsic roughness of the observed surfaces occurring when scanning vegetation. As only elevation differences above a predefined noise level are accounted for (according to a specified confidence interval related to the allowable false alarm rate) the change detection is robust to all these sources of noise. To first validate the approach, we built small-scale models and scanned them using a terrestrial laser scanner to establish 'ground truth'. Changes were manually applied to the models then new scans were performed and analyzed. Additionally, two airborne datasets of the Monterey Peninsula, California, were processed and analyzed. The first one was acquired during 2010 (with relatively low point density, 1-3 pts/m2), and the second one was acquired during 2012 (with up to 30 pts/m2). To perform the comparison, a new point cloud registration technique was developed and the data were registered to a common 1 m grid. The goal was to correct systematic shifts due to GPS and INS errors, and focus on the actual height differences regardless of the absolute planimetric accuracy of the datasets. Though no major disaster event occurred between the two acquisition dates, sparse changes were detected and interpreted mostly as construction and natural landscape evolution.

Monitoring of Building Construction by 4D Change Detection Using Multi-temporal SAR Images

NASA Astrophysics Data System (ADS)

Yang, C. H.; Pang, Y.; Soergel, U.

2017-05-01

Monitoring urban changes is important for city management, urban planning, updating of cadastral map, etc. In contrast to conventional field surveys, which are usually expensive and slow, remote sensing techniques are fast and cost-effective alternatives. Spaceborne synthetic aperture radar (SAR) sensors provide radar images captured rapidly over vast areas at fine spatiotemporal resolution. In addition, the active microwave sensors are capable of day-and-night vision and independent of weather conditions. These advantages make multi-temporal SAR images suitable for scene monitoring. Persistent scatterer interferometry (PSI) detects and analyses PS points, which are characterized by strong, stable, and coherent radar signals throughout a SAR image sequence and can be regarded as substructures of buildings in built-up cities. Attributes of PS points, for example, deformation velocities, are derived and used for further analysis. Based on PSI, a 4D change detection technique has been developed to detect disappearance and emergence of PS points (3D) at specific times (1D). In this paper, we apply this 4D technique to the centre of Berlin, Germany, to investigate its feasibility and application for construction monitoring. The aims of the three case studies are to monitor construction progress, business districts, and single buildings, respectively. The disappearing and emerging substructures of the buildings are successfully recognized along with their occurrence times. The changed substructures are then clustered into single construction segments based on DBSCAN clustering and α-shape outlining for object-based analysis. Compared with the ground truth, these spatiotemporal results have proven able to provide more detailed information for construction monitoring.

Bronchial intubation could be detected by the visual stethoscope techniques in pediatric patients.

PubMed

Kimura, Tetsuro; Suzuki, Akira; Mimuro, Soichiro; Makino, Hiroshi; Sato, Shigehito

2012-12-01

We created a system that allows the visualization of breath sounds (visual stethoscope). We compared the visual stethoscope technique with auscultation for the detection of bronchial intubation in pediatric patients. In the auscultation group, an anesthesiologist advanced the tracheal tube, while another anesthesiologist auscultated bilateral breath sounds to detect the change and/or disappearance of unilateral breath sounds. In the visualization group, the stethoscope was used to detect changes in breath sounds and/or disappearance of unilateral breath sounds. The distance from the edge of the mouth to the carina was measured using a fiberoptic bronchoscope. Forty pediatric patients were enrolled in the study. At the point at which irregular breath sounds were auscultated, the tracheal tube was located at 0.5 ± 0.8 cm on the bronchial side from the carina. When a detectable change of shape of the visualized breath sound was observed, the tracheal tube was located 0.1 ± 1.2 cm on the bronchial side (not significant). At the point at which unilateral breath sounds were auscultated or a unilateral shape of the visualized breath sound was observed, the tracheal tube was 1.5 ± 0.8 or 1.2 ± 1.0 cm on the bronchial side, respectively (not significant). The visual stethoscope allowed to display the left and the right lung sound simultaneously and detected changes of breath sounds and unilateral breath sound as a tracheal tube was advanced. © 2012 Blackwell Publishing Ltd.

Towards a Framework for Change Detection in Data Sets

NASA Astrophysics Data System (ADS)

Böttcher, Mirko; Nauck, Detlef; Ruta, Dymitr; Spott, Martin

Since the world with its markets, innovations and customers is changing faster than ever before, the key to survival for businesses is the ability to detect, assess and respond to changing conditions rapidly and intelligently. Discovering changes and reacting to or acting upon them before others do has therefore become a strategical issue for many companies. However, existing data analysis techniques are insufflent for this task since they typically assume that the domain under consideration is stable over time. This paper presents a framework that detects changes within a data set at virtually any level of granularity. The underlying idea is to derive a rule-based description of the data set at different points in time and to subsequently analyse how these rules change. Nevertheless, further techniques are required to assist the data analyst in interpreting and assessing their changes. Therefore the framework also contains methods to discard rules that are non-drivers for change and to assess the interestingness of detected changes.

Application of change-point problem to the detection of plant patches.

PubMed

López, I; Gámez, M; Garay, J; Standovár, T; Varga, Z

2010-03-01

In ecology, if the considered area or space is large, the spatial distribution of individuals of a given plant species is never homogeneous; plants form different patches. The homogeneity change in space or in time (in particular, the related change-point problem) is an important research subject in mathematical statistics. In the paper, for a given data system along a straight line, two areas are considered, where the data of each area come from different discrete distributions, with unknown parameters. In the paper a method is presented for the estimation of the distribution change-point between both areas and an estimate is given for the distributions separated by the obtained change-point. The solution of this problem will be based on the maximum likelihood method. Furthermore, based on an adaptation of the well-known bootstrap resampling, a method for the estimation of the so-called change-interval is also given. The latter approach is very general, since it not only applies in the case of the maximum-likelihood estimation of the change-point, but it can be also used starting from any other change-point estimation known in the ecological literature. The proposed model is validated against typical ecological situations, providing at the same time a verification of the applied algorithms.

Application of terrestrial laser scanning for coastal geomorphologic research questions in western Greece

NASA Astrophysics Data System (ADS)

Hoffmeister, Dirk; Curdt, Constanze; Tilly, Nora; Ntageretzis, Konstantin; Aasen, Helge; Vött, Andreas; Bareth, Georg

2013-04-01

Coasts are areas of permanent change, influenced by gradual changes and sudden impacts. In particular, western Greece is a tectonically active region, due to the nearby plate boundary of the Hellenic Arc. The region has suffered from numerous earthquakes and tsunamis during prehistoric and historic times and is thus characterized by a high seismic and tsunami hazard risk. Additionally, strong winter storms may reach considerable dimensions. In this study, terrestrial laser scanning was applied for (i) annual change detection at seven coastal areas of western Greece for three years (2009-2011) and (ii) accurate parameter detection of large boulders, dislocated by high-energy wave impacts. The Riegl LMS-Z420i laser scanner was used in combination with a precise DGPS system (Topcon HiPer Pro) for all surveys. Each scan position and a further target were recorded for georeferencing and merging of the point clouds. (i) For the annual detection of changes, reference points for the base station of the DGPS system were marked. High-resolution digital elevation models (HRDEM) were generated from each dataset of the different years and are compared to each other, resulting in mass balances. (ii) 3D-models of dislocated boulders were reconstructed and parameters (e.g. volume in combination with density measurements, distance and height above present sea-level) were derived for the solution of wave transport equations, which estimate the minimum wave height or velocity that is necessary for boulder movement. (i) Our results show that annual changes are detectable by multi-temporal terrestrial laser scanning. In general, volumetric changes and affected areas are quantifiable and maps of changes can be established. On exposed beach areas, bigger changes were detectable, where seagrass and sand is eroded and gravel accumulated. In opposite, only minor changes for elevated areas are derived. Dislocated boulders on several sites showed no movement. At coastal areas with a high surface roughness and along recent beaches, post-processing of point clouds turned out to be more difficult, due to noise effects by water and shadowing effects. A point to point comparison was used in addition to check the results. (ii) Furthermore, it is possible to obtain highly accurate volumetric data of dislocated boulders by 3D reconstruction. Further parameters, such as inclination, elevation above sea level or the distance of the boulder to the sea can be extracted from the 3D model of the study site. Accurate maps of the geomorphological settings are established. All parameters were incorporated into selected wave transport equations, which regard the variable "mass" as a direct input parameter for the calculation of wave heights and velocities needed for boulder dislocation. Our results were compared to data based on manual measurement of boulder axes and roughly estimated rock density values, which show a combined, general overestimation of ~40%.

Modified screening and ranking algorithm for copy number variation detection.

PubMed

Xiao, Feifei; Min, Xiaoyi; Zhang, Heping

2015-05-01

Copy number variation (CNV) is a type of structural variation, usually defined as genomic segments that are 1 kb or larger, which present variable copy numbers when compared with a reference genome. The screening and ranking algorithm (SaRa) was recently proposed as an efficient approach for multiple change-points detection, which can be applied to CNV detection. However, some practical issues arise from application of SaRa to single nucleotide polymorphism data. In this study, we propose a modified SaRa on CNV detection to address these issues. First, we use the quantile normalization on the original intensities to guarantee that the normal mean model-based SaRa is a robust method. Second, a novel normal mixture model coupled with a modified Bayesian information criterion is proposed for candidate change-point selection and further clustering the potential CNV segments to copy number states. Simulations revealed that the modified SaRa became a robust method for identifying change-points and achieved better performance than the circular binary segmentation (CBS) method. By applying the modified SaRa to real data from the HapMap project, we illustrated its performance on detecting CNV segments. In conclusion, our modified SaRa method improves SaRa theoretically and numerically, for identifying CNVs with high-throughput genotyping data. The modSaRa package is implemented in R program and freely available at http://c2s2.yale.edu/software/modSaRa. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

The Detection of Transport Land-Use Data Using Crowdsourcing Taxi Trajectory

NASA Astrophysics Data System (ADS)

Ai, T.; Yang, W.

2016-06-01

This study tries to explore the question of transport land-use change detection by large volume of vehicle trajectory data, presenting a method based on Deluanay triangulation. The whole method includes three steps. The first one is to pre-process the vehicle trajectory data including the point anomaly removing and the conversion of trajectory point to track line. Secondly, construct Deluanay triangulation within the vehicle trajectory line to detect neighborhood relation. Considering the case that some of the trajectory segments are too long, we use a interpolation measure to add more points for the improved triangulation. Thirdly, extract the transport road by cutting short triangle edge and organizing the polygon topology. We have conducted the experiment of transport land-use change discovery using the data of taxi track in Beijing City. We extract not only the transport land-use area but also the semantic information such as the transformation speed, the traffic jam distribution, the main vehicle movement direction and others. Compared with the existed transport network data, such as OpenStreet Map, our method is proved to be quick and accurate.

Can fractal methods applied to video tracking detect the effects of deltamethrin pesticide or mercury on the locomotion behavior of shrimps?

PubMed

Tenorio, Bruno Mendes; da Silva Filho, Eurípedes Alves; Neiva, Gentileza Santos Martins; da Silva, Valdemiro Amaro; Tenorio, Fernanda das Chagas Angelo Mendes; da Silva, Themis de Jesus; Silva, Emerson Carlos Soares E; Nogueira, Romildo de Albuquerque

2017-08-01

Shrimps can accumulate environmental toxicants and suffer behavioral changes. However, methods to quantitatively detect changes in the behavior of these shrimps are still needed. The present study aims to verify whether mathematical and fractal methods applied to video tracking can adequately describe changes in the locomotion behavior of shrimps exposed to low concentrations of toxic chemicals, such as 0.15µgL -1 deltamethrin pesticide or 10µgL -1 mercuric chloride. Results showed no change after 1min, 4, 24, and 48h of treatment. However, after 72 and 96h of treatment, both the linear methods describing the track length, mean speed, mean distance from the current to the previous track point, as well as the non-linear methods of fractal dimension (box counting or information entropy) and multifractal analysis were able to detect changes in the locomotion behavior of shrimps exposed to deltamethrin. Analysis of angular parameters of the track points vectors and lacunarity were not sensitive to those changes. None of the methods showed adverse effects to mercury exposure. These mathematical and fractal methods applicable to software represent low cost useful tools in the toxicological analyses of shrimps for quality of food, water and biomonitoring of ecosystems. Copyright © 2017 Elsevier Inc. All rights reserved.

Sample size and classification error for Bayesian change-point models with unlabelled sub-groups and incomplete follow-up.

PubMed

White, Simon R; Muniz-Terrera, Graciela; Matthews, Fiona E

2018-05-01

Many medical (and ecological) processes involve the change of shape, whereby one trajectory changes into another trajectory at a specific time point. There has been little investigation into the study design needed to investigate these models. We consider the class of fixed effect change-point models with an underlying shape comprised two joined linear segments, also known as broken-stick models. We extend this model to include two sub-groups with different trajectories at the change-point, a change and no change class, and also include a missingness model to account for individuals with incomplete follow-up. Through a simulation study, we consider the relationship of sample size to the estimates of the underlying shape, the existence of a change-point, and the classification-error of sub-group labels. We use a Bayesian framework to account for the missing labels, and the analysis of each simulation is performed using standard Markov chain Monte Carlo techniques. Our simulation study is inspired by cognitive decline as measured by the Mini-Mental State Examination, where our extended model is appropriate due to the commonly observed mixture of individuals within studies who do or do not exhibit accelerated decline. We find that even for studies of modest size ( n = 500, with 50 individuals observed past the change-point) in the fixed effect setting, a change-point can be detected and reliably estimated across a range of observation-errors.

Understanding the impacts of climate change and human activities on streamflow: a case study of the Soan River basin, Pakistan

NASA Astrophysics Data System (ADS)

Shahid, Muhammad; Cong, Zhentao; Zhang, Danwu

2017-09-01

Climate change and land use change are the two main factors that can alter the catchment hydrological process. The objective of this study is to evaluate the relative contribution of climate change and land use change to runoff change of the Soan River basin. The Mann-Kendal and the Pettit tests are used to find out the trends and change point in hydroclimatic variables during the period 1983-2012. Two different approaches including the abcd hydrological model and the Budyko framework are then used to quantify the impact of climate change and land use change on streamflow. The results from both methods are consistent and show that annual runoff has significantly decreased with a change point around 1997. The decrease in precipitation and increases in potential evapotranspiration contribute 68% of the detected change while the rest of the detected change is due to land use change. The land use change acquired from Landsat shows that during post-change period, the agriculture has increased in the Soan basin, which is in line with the positive contribution of land use change to runoff decrease. This study concludes that aforementioned methods performed well in quantifying the relative contribution of land use change and climate change to runoff change.

Two-stage Keypoint Detection Scheme for Region Duplication Forgery Detection in Digital Images.

PubMed

Emam, Mahmoud; Han, Qi; Zhang, Hongli

2018-01-01

In digital image forensics, copy-move or region duplication forgery detection became a vital research topic recently. Most of the existing keypoint-based forgery detection methods fail to detect the forgery in the smooth regions, rather than its sensitivity to geometric changes. To solve these problems and detect points which cover all the regions, we proposed two steps for keypoint detection. First, we employed the scale-invariant feature operator to detect the spatially distributed keypoints from the textured regions. Second, the keypoints from the missing regions are detected using Harris corner detector with nonmaximal suppression to evenly distribute the detected keypoints. To improve the matching performance, local feature points are described using Multi-support Region Order-based Gradient Histogram descriptor. Based on precision-recall rates and commonly tested dataset, comprehensive performance evaluation is performed. The results demonstrated that the proposed scheme has better detection and robustness against some geometric transformation attacks compared with state-of-the-art methods. © 2017 American Academy of Forensic Sciences.

An information-based approach to change-point analysis with applications to biophysics and cell biology.

PubMed

Wiggins, Paul A

2015-07-21

This article describes the application of a change-point algorithm to the analysis of stochastic signals in biological systems whose underlying state dynamics consist of transitions between discrete states. Applications of this analysis include molecular-motor stepping, fluorophore bleaching, electrophysiology, particle and cell tracking, detection of copy number variation by sequencing, tethered-particle motion, etc. We present a unified approach to the analysis of processes whose noise can be modeled by Gaussian, Wiener, or Ornstein-Uhlenbeck processes. To fit the model, we exploit explicit, closed-form algebraic expressions for maximum-likelihood estimators of model parameters and estimated information loss of the generalized noise model, which can be computed extremely efficiently. We implement change-point detection using the frequentist information criterion (which, to our knowledge, is a new information criterion). The frequentist information criterion specifies a single, information-based statistical test that is free from ad hoc parameters and requires no prior probability distribution. We demonstrate this information-based approach in the analysis of simulated and experimental tethered-particle-motion data. Copyright © 2015 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Contrast Invariant Interest Point Detection by Zero-Norm LoG Filter.

PubMed

Zhenwei Miao; Xudong Jiang; Kim-Hui Yap

2016-01-01

The Laplacian of Gaussian (LoG) filter is widely used in interest point detection. However, low-contrast image structures, though stable and significant, are often submerged by the high-contrast ones in the response image of the LoG filter, and hence are difficult to be detected. To solve this problem, we derive a generalized LoG filter, and propose a zero-norm LoG filter. The response of the zero-norm LoG filter is proportional to the weighted number of bright/dark pixels in a local region, which makes this filter be invariant to the image contrast. Based on the zero-norm LoG filter, we develop an interest point detector to extract local structures from images. Compared with the contrast dependent detectors, such as the popular scale invariant feature transform detector, the proposed detector is robust to illumination changes and abrupt variations of images. Experiments on benchmark databases demonstrate the superior performance of the proposed zero-norm LoG detector in terms of the repeatability and matching score of the detected points as well as the image recognition rate under different conditions.

Laser Truss Sensor for Segmented Telescope Phasing

NASA Technical Reports Server (NTRS)

Liu, Duncan T.; Lay, Oliver P.; Azizi, Alireza; Erlig, Herman; Dorsky, Leonard I.; Asbury, Cheryl G.; Zhao, Feng

2011-01-01

A paper describes the laser truss sensor (LTS) for detecting piston motion between two adjacent telescope segment edges. LTS is formed by two point-to-point laser metrology gauges in a crossed geometry. A high-resolution (<30 nm) LTS can be implemented with existing laser metrology gauges. The distance change between the reference plane and the target plane is measured as a function of the phase change between the reference and target beams. To ease the bandwidth requirements for phase detection electronics (or phase meter), homodyne or heterodyne detection techniques have been used. The phase of the target beam also changes with the refractive index of air, which changes with the air pressure, temperature, and humidity. This error can be minimized by enclosing the metrology beams in baffles. For longer-term (weeks) tracking at the micron level accuracy, the same gauge can be operated in the absolute metrology mode with an accuracy of microns; to implement absolute metrology, two laser frequencies will be used on the same gauge. Absolute metrology using heterodyne laser gauges is a demonstrated technology. Complexity of laser source fiber distribution can be optimized using the range-gated metrology (RGM) approach.

The influence of transducer operating point on distortion generation in the cochlea

NASA Astrophysics Data System (ADS)

Sirjani, Davud B.; Salt, Alec N.; Gill, Ruth M.; Hale, Shane A.

2004-03-01

Distortion generated by the cochlea can provide a valuable indicator of its functional state. In the present study, the dependence of distortion on the operating point of the cochlear transducer and its relevance to endolymph volume disturbances has been investigated. Calculations have suggested that as the operating point moves away from zero, second harmonic distortion would increase. Cochlear microphonic waveforms were analyzed to derive the cochlear transducer operating point and to quantify harmonic distortions. Changes in operating point and distortion were measured during endolymph manipulations that included 200-Hz tone exposures at 115-dB SPL, injections of artificial endolymph into scala media at 80, 200, or 400 nl/min, and treatment with furosemide given intravenously or locally into the cochlea. Results were compared with other functional changes that included action potential thresholds at 2.8 or 8 kHz, summating potential, endocochlear potential, and the 2 f1-f2 and f2-f1 acoustic emissions. The results demonstrated that volume disturbances caused changes in the operating point that resulted in predictable changes in distortion. Understanding the factors influencing operating point is important in the interpretation of distortion measurements and may lead to tests that can detect abnormal endolymph volume states.

Terahertz time-domain spectroscopy of edible oils

PubMed Central

Valchev, Dimitar G.

2017-01-01

Chemical degradation of edible oils has been studied using conventional spectroscopic methods spanning the spectrum from ultraviolet to mid-IR. However, the possibility of morphological changes of oil molecules that can be detected at terahertz frequencies is beginning to receive some attention. Furthermore, the rapidly decreasing cost of this technology and its capability for convenient, in situ measurement of material properties, raises the possibility of monitoring oil during cooking and processing at production facilities, and more generally within the food industry. In this paper, we test the hypothesis that oil undergoes chemical and physical changes when heated above the smoke point, which can be detected in the 0.05–2 THz spectral range, measured using the conventional terahertz time-domain spectroscopy technique. The measurements demonstrate a null result in that there is no significant change in the spectra of terahertz optical parameters after heating above the smoke point for 5 min. PMID:28680681

Terahertz time-domain spectroscopy of edible oils

NASA Astrophysics Data System (ADS)

Dinovitser, Alex; Valchev, Dimitar G.; Abbott, Derek

2017-06-01

Chemical degradation of edible oils has been studied using conventional spectroscopic methods spanning the spectrum from ultraviolet to mid-IR. However, the possibility of morphological changes of oil molecules that can be detected at terahertz frequencies is beginning to receive some attention. Furthermore, the rapidly decreasing cost of this technology and its capability for convenient, in situ measurement of material properties, raises the possibility of monitoring oil during cooking and processing at production facilities, and more generally within the food industry. In this paper, we test the hypothesis that oil undergoes chemical and physical changes when heated above the smoke point, which can be detected in the 0.05-2 THz spectral range, measured using the conventional terahertz time-domain spectroscopy technique. The measurements demonstrate a null result in that there is no significant change in the spectra of terahertz optical parameters after heating above the smoke point for 5 min.

Detection of Local Temperature Change on HTS Cables via Time-Frequency Domain Reflectometry

NASA Astrophysics Data System (ADS)

Bang, Su Sik; Lee, Geon Seok; Kwon, Gu-Young; Lee, Yeong Ho; Ji, Gyeong Hwan; Sohn, Songho; Park, Kijun; Shin, Yong-June

2017-07-01

High temperature superconducting (HTS) cables are drawing attention as transmission and distribution cables in future grid, and related researches on HTS cables have been conducted actively. As HTS cables have come to the demonstration stage, failures of cooling systems inducing quench phenomenon of the HTS cables have become significant. Several diagnosis of the HTS cables have been developed but there are still some limitations of the experimental setup. In this paper, a non-destructive diagnostic technique for the detection of the local temperature change point is proposed. Also, a simulation model of HTS cables with a local temperature change point is suggested to verify the proposed diagnosis. The performance of the diagnosis is checked by comparative analysis between the proposed simulation results and experiment results of a real-world HTS cable. It is expected that the suggested simulation model and diagnosis will contribute to the commercialization of HTS cables in the power grid.

Terahertz time-domain spectroscopy of edible oils.

PubMed

Dinovitser, Alex; Valchev, Dimitar G; Abbott, Derek

2017-06-01

Chemical degradation of edible oils has been studied using conventional spectroscopic methods spanning the spectrum from ultraviolet to mid-IR. However, the possibility of morphological changes of oil molecules that can be detected at terahertz frequencies is beginning to receive some attention. Furthermore, the rapidly decreasing cost of this technology and its capability for convenient, in situ measurement of material properties, raises the possibility of monitoring oil during cooking and processing at production facilities, and more generally within the food industry. In this paper, we test the hypothesis that oil undergoes chemical and physical changes when heated above the smoke point, which can be detected in the 0.05-2 THz spectral range, measured using the conventional terahertz time-domain spectroscopy technique. The measurements demonstrate a null result in that there is no significant change in the spectra of terahertz optical parameters after heating above the smoke point for 5 min.

Obstacle Detection and Avoidance System Based on Monocular Camera and Size Expansion Algorithm for UAVs

PubMed Central

Al-Kaff, Abdulla; García, Fernando; Martín, David; De La Escalera, Arturo; Armingol, José María

2017-01-01

One of the most challenging problems in the domain of autonomous aerial vehicles is the designing of a robust real-time obstacle detection and avoidance system. This problem is complex, especially for the micro and small aerial vehicles, that is due to the Size, Weight and Power (SWaP) constraints. Therefore, using lightweight sensors (i.e., Digital camera) can be the best choice comparing with other sensors; such as laser or radar.For real-time applications, different works are based on stereo cameras in order to obtain a 3D model of the obstacles, or to estimate their depth. Instead, in this paper, a method that mimics the human behavior of detecting the collision state of the approaching obstacles using monocular camera is proposed. The key of the proposed algorithm is to analyze the size changes of the detected feature points, combined with the expansion ratios of the convex hull constructed around the detected feature points from consecutive frames. During the Aerial Vehicle (UAV) motion, the detection algorithm estimates the changes in the size of the area of the approaching obstacles. First, the method detects the feature points of the obstacles, then extracts the obstacles that have the probability of getting close toward the UAV. Secondly, by comparing the area ratio of the obstacle and the position of the UAV, the method decides if the detected obstacle may cause a collision. Finally, by estimating the obstacle 2D position in the image and combining with the tracked waypoints, the UAV performs the avoidance maneuver. The proposed algorithm was evaluated by performing real indoor and outdoor flights, and the obtained results show the accuracy of the proposed algorithm compared with other related works. PMID:28481277

Mapping the order and pattern of brain structural MRI changes using change-point analysis in premanifest Huntington's disease.

PubMed

Wu, Dan; Faria, Andreia V; Younes, Laurent; Mori, Susumu; Brown, Timothy; Johnson, Hans; Paulsen, Jane S; Ross, Christopher A; Miller, Michael I

2017-10-01

Huntington's disease (HD) is an autosomal dominant neurodegenerative disorder that progressively affects motor, cognitive, and emotional functions. Structural MRI studies have demonstrated brain atrophy beginning many years prior to clinical onset ("premanifest" period), but the order and pattern of brain structural changes have not been fully characterized. In this study, we investigated brain regional volumes and diffusion tensor imaging (DTI) measurements in premanifest HD, and we aim to determine (1) the extent of MRI changes in a large number of structures across the brain by atlas-based analysis, and (2) the initiation points of structural MRI changes in these brain regions. We adopted a novel multivariate linear regression model to detect the inflection points at which the MRI changes begin (namely, "change-points"), with respect to the CAG-age product (CAP, an indicator of extent of exposure to the effects of CAG repeat expansion). We used approximately 300 T1-weighted and DTI data from premanifest HD and control subjects in the PREDICT-HD study, with atlas-based whole brain segmentation and change-point analysis. The results indicated a distinct topology of structural MRI changes: the change-points of the volumetric measurements suggested a central-to-peripheral pattern of atrophy from the striatum to the deep white matter; and the change points of DTI measurements indicated the earliest changes in mean diffusivity in the deep white matter and posterior white matter. While interpretation needs to be cautious given the cross-sectional nature of the data, these findings suggest a spatial and temporal pattern of spread of structural changes within the HD brain. Hum Brain Mapp 38:5035-5050, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Measurement Error, Reliability, and Minimum Detectable Change in the Mini-Mental State Examination, Montreal Cognitive Assessment, and Color Trails Test among Community Living Middle-Aged and Older Adults.

PubMed

Feeney, Joanne; Savva, George M; O'Regan, Claire; King-Kallimanis, Bellinda; Cronin, Hilary; Kenny, Rose Anne

2016-05-31

Knowing the reliability of cognitive tests, particularly those commonly used in clinical practice, is important in order to interpret the clinical significance of a change in performance or a low score on a single test. To report the intra-class correlation (ICC), standard error of measurement (SEM) and minimum detectable change (MDC) for the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and Color Trails Test (CTT) among community dwelling older adults. 130 participants aged 55 and older without severe cognitive impairment underwent two cognitive assessments between two and four months apart. Half the group changed rater between assessments and half changed time of day. Mean (standard deviation) MMSE was 28.1 (2.1) at baseline and 28.4 (2.1) at repeat. Mean (SD) MoCA increased from 24.8 (3.6) to 25.2 (3.6). There was a rater effect on CTT, but not on the MMSE or MoCA. The SEM of the MMSE was 1.0, leading to an MDC (based on a 95% confidence interval) of 3 points. The SEM of the MoCA was 1.5, implying an MDC95 of 4 points. MoCA (ICC = 0.81) was more reliable than MMSE (ICC = 0.75), but all tests examined showed substantial within-patient variation. An individual's score would have to change by greater than or equal to 3 points on the MMSE and 4 points on the MoCA for the rater to be confident that the change was not due to measurement error. This has important implications for epidemiologists and clinicians in dementia screening and diagnosis.

HPLC-DAD-ESI/MS identification of light harvesting and light screening pigments in the lake sediments at Edmonson Point.

PubMed

Giovannetti, Rita; Alibabaei, Leila; Zannotti, Marco; Ferraro, Stefano; Petetta, Laura

2013-01-01

The composition of sedimentary pigments in the Antarctic lake at Edmonson Point has been investigated and compared with the aim to provide a useful analytical method for pigments separation and identification, providing reference data for future assessment of possible changes in environmental conditions. Reversed phase high performance liquid chromatography (HPLC) with electrospray-mass spectrometry (ESI-MS) detection and diode array detection (DAD) has been used to identify light screening and light harvesting pigments. The results are discussed in terms of local environmental conditions.

Monitoring of Progressive Damage in Buildings Using Laser Scan Data

NASA Astrophysics Data System (ADS)

Puente, I.; Lindenbergh, R.; Van Natijne, A.; Esposito, R.; Schipper, R.

2018-05-01

Vulnerability of buildings to natural and man-induced hazards has become a main concern for our society. Ensuring their serviceability, safety and sustainability is of vital importance and the main reason for setting up monitoring systems to detect damages at an early stage. In this work, a method is presented for detecting changes from laser scan data, where no registration between different epochs is needed. To show the potential of the method, a case study of a laboratory test carried out at the Stevin laboratory of Delft University of Technology was selected. The case study was a quasi-static cyclic pushover test on a two-story high unreinforced masonry structure designed to simulate damage evolution caused by cyclic loading. During the various phases, we analysed the behaviour of the masonry walls by monitoring the deformation of each masonry unit. First a plane is fitted to the selected wall point cloud, consisting of one single terrestrial laser scan, using Principal Component Analysis (PCA). Second, the segmentation of individual elements is performed. Then deformations with respect to this plane model, for each epoch and specific element, are determined by computing their corresponding rotation and cloud-to-plane distances. The validation of the changes detected within this approach is done by comparison with traditional deformation analysis based on co-registered TLS point clouds between two or more epochs of building measurements. Initial results show that the sketched methodology is indeed able to detect changes at the mm level while avoiding 3D point cloud registration, which is a main issue in computer vision and remote sensing.

Assessing natural and anthropogenic influences on water discharge and sediment load in the Yangtze River, China.

PubMed

Zhao, Yifei; Zou, Xinqing; Liu, Qing; Yao, Yulong; Li, Yali; Wu, Xiaowei; Wang, Chenglong; Yu, Wenwen; Wang, Teng

2017-12-31

The water discharge and sediment load of rivers are changing substantially under the impacts of climate change and human activities, becoming a hot issue in hydro-environmental research. In this study, the water discharge and sediment load in the mainstream and seven tributaries of the Yangtze River were investigated by using long-term hydro-meteorological data from 1953 to 2013. The non-parametric Mann-Kendall test and double mass curve (DMC) were used to detect trends and abrupt change-points in water discharge and sediment load and to quantify the effects of climate change and human activities on water discharge and sediment load. The results are as follows: (1) the water discharge showed a non-significant decreasing trend at most stations except Hukou station. Among these, water discharge at Dongting Lake and the Min River basin shows a significant decreasing trend with average rates of -13.93×10 8 m 3 /year and -1.8×10 8 m 3 /year (P<0.05), respectively. However, the sediment load exhibited a significant decreasing trend in all tributaries of the Yangtze River. (2) No significant abrupt change-points were detected in the time series of water discharge for all hydrological stations. In contrast, significant abrupt change-points were detected in sediment load, most of these changes appeared in the late 1980s. (3) The water discharge was mainly influenced by precipitation in the Yangtze River basin, whereas sediment load was mainly affected by climate change and human activities; the relative contribution ratios of human activities were above 70% for the Yangtze River. (4) The decrease of sediment load has directly impacted the lower Yangtze River and the delta region. These results will provide a reference for better resource management in the Yangtze River Basin. Copyright © 2017 Elsevier B.V. All rights reserved.

Integrated electrochemical microsystems for genetic detection of pathogens at the point of care.

PubMed

Hsieh, Kuangwen; Ferguson, B Scott; Eisenstein, Michael; Plaxco, Kevin W; Soh, H Tom

2015-04-21

The capacity to achieve rapid, sensitive, specific, quantitative, and multiplexed genetic detection of pathogens via a robust, portable, point-of-care platform could transform many diagnostic applications. And while contemporary technologies have yet to effectively achieve this goal, the advent of microfluidics provides a potentially viable approach to this end by enabling the integration of sophisticated multistep biochemical assays (e.g., sample preparation, genetic amplification, and quantitative detection) in a monolithic, portable device from relatively small biological samples. Integrated electrochemical sensors offer a particularly promising solution to genetic detection because they do not require optical instrumentation and are readily compatible with both integrated circuit and microfluidic technologies. Nevertheless, the development of generalizable microfluidic electrochemical platforms that integrate sample preparation and amplification as well as quantitative and multiplexed detection remains a challenging and unsolved technical problem. Recognizing this unmet need, we have developed a series of microfluidic electrochemical DNA sensors that have progressively evolved to encompass each of these critical functionalities. For DNA detection, our platforms employ label-free, single-step, and sequence-specific electrochemical DNA (E-DNA) sensors, in which an electrode-bound, redox-reporter-modified DNA "probe" generates a current change after undergoing a hybridization-induced conformational change. After successfully integrating E-DNA sensors into a microfluidic chip format, we subsequently incorporated on-chip genetic amplification techniques including polymerase chain reaction (PCR) and loop-mediated isothermal amplification (LAMP) to enable genetic detection at clinically relevant target concentrations. To maximize the potential point-of-care utility of our platforms, we have further integrated sample preparation via immunomagnetic separation, which allowed the detection of influenza virus directly from throat swabs and developed strategies for the multiplexed detection of related bacterial strains from the blood of septic mice. Finally, we developed an alternative electrochemical detection platform based on real-time LAMP, which not is only capable of detecting across a broad dynamic range of target concentrations, but also greatly simplifies quantitative measurement of nucleic acids. These efforts represent considerable progress toward the development of a true sample-in-answer-out platform for genetic detection of pathogens at the point of care. Given the many advantages of these systems, and the growing interest and innovative contributions from researchers in this field, we are optimistic that iterations of these systems will arrive in clinical settings in the foreseeable future.

Laser-based structural sensing and surface damage detection

NASA Astrophysics Data System (ADS)

Guldur, Burcu

Damage due to age or accumulated damage from hazards on existing structures poses a worldwide problem. In order to evaluate the current status of aging, deteriorating and damaged structures, it is vital to accurately assess the present conditions. It is possible to capture the in situ condition of structures by using laser scanners that create dense three-dimensional point clouds. This research investigates the use of high resolution three-dimensional terrestrial laser scanners with image capturing abilities as tools to capture geometric range data of complex scenes for structural engineering applications. Laser scanning technology is continuously improving, with commonly available scanners now capturing over 1,000,000 texture-mapped points per second with an accuracy of ~2 mm. However, automatically extracting meaningful information from point clouds remains a challenge, and the current state-of-the-art requires significant user interaction. The first objective of this research is to use widely accepted point cloud processing steps such as registration, feature extraction, segmentation, surface fitting and object detection to divide laser scanner data into meaningful object clusters and then apply several damage detection methods to these clusters. This required establishing a process for extracting important information from raw laser-scanned data sets such as the location, orientation and size of objects in a scanned region, and location of damaged regions on a structure. For this purpose, first a methodology for processing range data to identify objects in a scene is presented and then, once the objects from model library are correctly detected and fitted into the captured point cloud, these fitted objects are compared with the as-is point cloud of the investigated object to locate defects on the structure. The algorithms are demonstrated on synthetic scenes and validated on range data collected from test specimens and test-bed bridges. The second objective of this research is to combine useful information extracted from laser scanner data with color information, which provides information in the fourth dimension that enables detection of damage types such as cracks, corrosion, and related surface defects that are generally difficult to detect using only laser scanner data; moreover, the color information also helps to track volumetric changes on structures such as spalling. Although using images with varying resolution to detect cracks is an extensively researched topic, damage detection using laser scanners with and without color images is a new research area that holds many opportunities for enhancing the current practice of visual inspections. The aim is to combine the best features of laser scans and images to create an automatic and effective surface damage detection method, which will reduce the need for skilled labor during visual inspections and allow automatic documentation of related information. This work enables developing surface damage detection strategies that integrate existing condition rating criteria for a wide range damage types that are collected under three main categories: small deformations already existing on the structure (cracks); damage types that induce larger deformations, but where the initial topology of the structure has not changed appreciably (e.g., bent members); and large deformations where localized changes in the topology of the structure have occurred (e.g., rupture, discontinuities and spalling). The effectiveness of the developed damage detection algorithms are validated by comparing the detection results with the measurements taken from test specimens and test-bed bridges.

Expanding Cancer Detection Using Molecular Imprinting for a Novel Point-of-Care Diagnostic Device

NASA Astrophysics Data System (ADS)

Yu, Yingjie; Rafailovich, Miriam; Wang, Yantian; Ranjbaran, Alina; Wang, Tom; Nam, David

2012-02-01

We propose the use of a potentiometric biosensor that incorporates the efficient and specific molecular imprinting (MI) method with a self-assembled monolayer (SAM). We first tested the biosensor using carcinoembryonic antigen, CEA, a biomarker associated with pancreatic cancer. No change in detection efficiency was observed when detection was performed in the presence of 100% serum albumin, indicating that the sensor is able to discriminate for the template analyte even in concentrated solution of similar substances. Computer simulations of the protein structure were performed in order to estimate the changes in morphology and determine the sensitivity of the biosensor to conformational changes in the proteins. We found that even small changes in PH can generate rotation of the surface functional groups, without significant change in the morphology. Yet, the results show that only when the detection and imprinting conditions are similar, robust signals occurs. Hence we concluded that both morphology and surface chemistry play a role in the recognition.

a Landsat Time-Series Stacks Model for Detection of Cropland Change

NASA Astrophysics Data System (ADS)

Chen, J.; Chen, J.; Zhang, J.

2017-09-01

Global, timely, accurate and cost-effective cropland monitoring with a fine spatial resolution will dramatically improve our understanding of the effects of agriculture on greenhouse gases emissions, food safety, and human health. Time-series remote sensing imagery have been shown particularly potential to describe land cover dynamics. The traditional change detection techniques are often not capable of detecting land cover changes within time series that are severely influenced by seasonal difference, which are more likely to generate pseuso changes. Here,we introduced and tested LTSM ( Landsat time-series stacks model), an improved Continuous Change Detection and Classification (CCDC) proposed previously approach to extract spectral trajectories of land surface change using a dense Landsat time-series stacks (LTS). The method is expected to eliminate pseudo changes caused by phenology driven by seasonal patterns. The main idea of the method is that using all available Landsat 8 images within a year, LTSM consisting of two term harmonic function are estimated iteratively for each pixel in each spectral band .LTSM can defines change area by differencing the predicted and observed Landsat images. The LTSM approach was compared with change vector analysis (CVA) method. The results indicated that the LTSM method correctly detected the "true change" without overestimating the "false" one, while CVA pointed out "true change" pixels with a large number of "false changes". The detection of change areas achieved an overall accuracy of 92.37 %, with a kappa coefficient of 0.676.

Spectral pattern classification in lidar data for rock identification in outcrops.

PubMed

Campos Inocencio, Leonardo; Veronez, Mauricio Roberto; Wohnrath Tognoli, Francisco Manoel; de Souza, Marcelo Kehl; da Silva, Reginaldo Macedônio; Gonzaga, Luiz; Blum Silveira, César Leonardo

2014-01-01

The present study aimed to develop and implement a method for detection and classification of spectral signatures in point clouds obtained from terrestrial laser scanner in order to identify the presence of different rocks in outcrops and to generate a digital outcrop model. To achieve this objective, a software based on cluster analysis was created, named K-Clouds. This software was developed through a partnership between UNISINOS and the company V3D. This tool was designed to begin with an analysis and interpretation of a histogram from a point cloud of the outcrop and subsequently indication of a number of classes provided by the user, to process the intensity return values. This classified information can then be interpreted by geologists, to provide a better understanding and identification from the existing rocks in the outcrop. Beyond the detection of different rocks, this work was able to detect small changes in the physical-chemical characteristics of the rocks, as they were caused by weathering or compositional changes.

Segmentation of time series with long-range fractal correlations.

PubMed

Bernaola-Galván, P; Oliver, J L; Hackenberg, M; Coronado, A V; Ivanov, P Ch; Carpena, P

2012-06-01

Segmentation is a standard method of data analysis to identify change-points dividing a nonstationary time series into homogeneous segments. However, for long-range fractal correlated series, most of the segmentation techniques detect spurious change-points which are simply due to the heterogeneities induced by the correlations and not to real nonstationarities. To avoid this oversegmentation, we present a segmentation algorithm which takes as a reference for homogeneity, instead of a random i.i.d. series, a correlated series modeled by a fractional noise with the same degree of correlations as the series to be segmented. We apply our algorithm to artificial series with long-range correlations and show that it systematically detects only the change-points produced by real nonstationarities and not those created by the correlations of the signal. Further, we apply the method to the sequence of the long arm of human chromosome 21, which is known to have long-range fractal correlations. We obtain only three segments that clearly correspond to the three regions of different G + C composition revealed by means of a multi-scale wavelet plot. Similar results have been obtained when segmenting all human chromosome sequences, showing the existence of previously unknown huge compositional superstructures in the human genome.

Design and analysis of surface plasmon resonance (SPR) sensor to check the quality of food from adulteration

NASA Astrophysics Data System (ADS)

Kumar, Manish; Raghuwanshi, Sanjeev Kumar

2018-02-01

In recent years, food safety issues caused by contamination of chemical substances or microbial species have raised a major area of concern to mankind. The conventional chromatography-based methods for detection of chemical are based on human-observation and slow for real-time monitoring. The surface plasmon resonance (SPR) sensors offers the capability of detection of very low concentrations of adulterated chemical and biological agents for real-time by monitoring. Thus, adulterant agent in food gives change in refractive index of pure food result in corresponding phase change. These changes can be detected at the output and can be related to the concentration of the chemical species present at the point.

Increasing point-count duration increases standard error

USGS Publications Warehouse

Smith, W.P.; Twedt, D.J.; Hamel, P.B.; Ford, R.P.; Wiedenfeld, D.A.; Cooper, R.J.

1998-01-01

We examined data from point counts of varying duration in bottomland forests of west Tennessee and the Mississippi Alluvial Valley to determine if counting interval influenced sampling efficiency. Estimates of standard error increased as point count duration increased both for cumulative number of individuals and species in both locations. Although point counts appear to yield data with standard errors proportional to means, a square root transformation of the data may stabilize the variance. Using long (>10 min) point counts may reduce sample size and increase sampling error, both of which diminish statistical power and thereby the ability to detect meaningful changes in avian populations.

Measuring and modeling high-resolution topographic change at archaeological sites in Grand Canyon National Park, Arizona, U.S.A.

NASA Astrophysics Data System (ADS)

Collins, B. D.; Corbett, S. C.; Fairley, H. C.

2012-04-01

Erosion of archaeological sites within Grand Canyon National Park (GCNP) Arizona, located in the southwestern United States is a subject of continuing interest to land and resource managers. This is partly fueled by an ongoing debate about whether and to what degree controlled releases from Glen Canyon Dam, located immediately upstream of GCNP, are affecting the physical integrity of archaeological sites. Long-term topographic change due to natural sources is typical in the desert southwest region. However, continuing erosion, which may be related in-part to anthropogenic factors, threatens both the preservation of archaeological sites as well as our ability to study evidence of past human habitation in GCNP that dates back at least 8,000 years before present. To quantitatively identify changes to archaeological sites in this region, and with the broader intention of developing numerical models to predict how and under what circumstances dam-controlled flows influence archaeological sites, we undertook a detailed terrestrial-lidar based monitoring program at thirteen sites between 2006 and 2010. Our studies looked specifically at sites located along the Colorado River that are potentially subject to changes related to dam operations. This could occur, for example, by limited sediment supply to sand bars which in turn contribute aeolian sediment to archaeologic sites. Each site was several hundred to several thousand square meters in size and was surveyed multiple times during the 5-year period. Our monitoring program shows how various data registration and georeferencing techniques result in varying degrees of topographic surface model accuracy. For example, surveys performed between 2006 and 2007 used point cloud registration methods and resulted in estimated change detection thresholds of 8 cm between repeat surveys. In 2010, surveys at the same sites used control point registration methods and resulted in estimated change detection thresholds of 3 cm. Error thresholds were determined using two types of change detection error analyses. The first used the absolute errors inherent in each step of the lidar data collection process (i.e., directly combining laser, survey, and registration errors) and provides a conservative estimate of potential errors. The second used an empirical metric based on the closest point-to-point match between known fixed objects (e.g., large boulders) and results in a more realistic error bound. Our data indicate that some sites changed significantly during the monitored time period. These measurements provide much of the essential data required for developing an in-house, physically-based, numerical sediment transport model that can provide estimates on the likelihood for future archaeological site change in GCNP. Thus far, we are finding that the data provided by typical terrestrial lidar surveys is likely overly-dense for numerical model requirements with respect to computational efficiency. Despite this, we also find that high-resolution data is necessary to perform change detection at the accuracy required for model calibration and to document changes before they have progressed beyond the point when site integrity is compromised. The results of the study will provide land and resource managers with the pertinent information needed to oversee these archaeological resources in the best way possible.

Protocol for monitoring forest-nesting birds in National Park Service parks

USGS Publications Warehouse

Dawson, Deanna K.; Efford, Murray G.

2013-01-01

These documents detail the protocol for monitoring forest-nesting birds in National Park Service parks in the National Capital Region Network (NCRN). In the first year of sampling, counts of birds should be made at 384 points on the NCRN spatially randomized grid, developed to sample terrestrial resources. Sampling should begin on or about May 20 and continue into early July; on each day the sampling period begins at sunrise and ends five hours later. Each point should be counted twice, once in the first half of the field season and once in the second half, with visits made by different observers, balancing the within-season coverage of points and their spatial coverage by observers, and allowing observer differences to be tested. Three observers, skilled in identifying birds of the region by sight and sound and with previous experience in conducting timed counts of birds, will be needed for this effort. Observers should be randomly assigned to ‘routes’ consisting of eight points, in close proximity and, ideally, in similar habitat, that can be covered in one morning. Counts are 10 minutes in length, subdivided into four 2.5-min intervals. Within each time interval, new birds (i.e., those not already detected) are recorded as within or beyond 50 m of the point, based on where first detected. Binomial distance methods are used to calculate annual estimates of density for species. The data are also amenable to estimation of abundance and detection probability via the removal method. Generalized linear models can be used to assess between-year changes in density estimates or unadjusted count data. This level of sampling is expected to be sufficient to detect a 50% decline in 10 years for approximately 50 bird species, including 14 of 19 species that are priorities for conservation efforts, if analyses are based on unadjusted count data, and for 30 species (6 priority species) if analyses are based on density estimates. The estimates of required sample sizes are based on the mean number of individuals detected per 10 minutes in available data from surveys in three NCRN parks. Once network-wide data from the first year of sampling are available, this and other aspects of the protocol should be re-assessed, and changes made as desired or necessary before the start of the second field season. Thereafter, changes should not be made to the field methods, and sampling should be conducted annually for at least ten years. NCRN staff should keep apprised of new analytical methods developed for analysis of point-count data.

Applications of multiple change point detections to monthly streamflow and rainfall in Xijiang River in southern China, part II: trend and mean

NASA Astrophysics Data System (ADS)

Chen, Yongqin David; Jiang, Jianmin; Zhu, Yuxiang; Huang, Changxing; Zhang, Qiang

2018-05-01

This article, as part II, illustrates applications of other two algorithms, i.e., the scanning F test of change points in trend and the scanning t test of change points in mean, to both series of the normalized streamflow index (NSI) at Makou section in the Xijiang River and the normalized precipitation index (NPI) over the watershed of Xijiang River. The results from these two tests show mainly positive coherency of changes between the NSI and NPI. However, some minor negative coherency patches may expose somewhat impacts of human activities, but they were often associated with nearly normal climate periods. These suggest that the runoff still depends upon well the precipitation in the Xijiang catchment. The anthropogenic disturbances have not yet reached up to violating natural relationship on the whole in this river.

(Quickly) Testing the Tester via Path Coverage

NASA Technical Reports Server (NTRS)

Groce, Alex

2009-01-01

The configuration complexity and code size of an automated testing framework may grow to a point that the tester itself becomes a significant software artifact, prone to poor configuration and implementation errors. Unfortunately, testing the tester by using old versions of the software under test (SUT) may be impractical or impossible: test framework changes may have been motivated by interface changes in the tested system, or fault detection may become too expensive in terms of computing time to justify running until errors are detected on older versions of the software. We propose the use of path coverage measures as a "quick and dirty" method for detecting many faults in complex test frameworks. We also note the possibility of using techniques developed to diversify state-space searches in model checking to diversify test focus, and an associated classification of tester changes into focus-changing and non-focus-changing modifications.

Characterization of lipid films by an angle-interrogation surface plasmon resonance imaging device.

PubMed

Liu, Linlin; Wang, Qiong; Yang, Zhong; Wang, Wangang; Hu, Ning; Luo, Hongyan; Liao, Yanjian; Zheng, Xiaolin; Yang, Jun

2015-04-01

Surface topographies of lipid films have an important significance in the analysis of the preparation of giant unilamellar vesicles (GUVs). In order to achieve accurately high-throughput and rapidly analysis of surface topographies of lipid films, a homemade SPR imaging device is constructed based on the classical Kretschmann configuration and an angle interrogation manner. A mathematical model is developed to accurately describe the shift including the light path in different conditions and the change of the illumination point on the CCD camera, and thus a SPR curve for each sampling point can also be achieved, based on this calculation method. The experiment results show that the topographies of lipid films formed in distinct experimental conditions can be accurately characterized, and the measuring resolution of the thickness lipid film may reach 0.05 nm. Compared with existing SPRi devices, which realize detection by monitoring the change of the reflective-light intensity, this new SPRi system can achieve the change of the resonance angle on the entire sensing surface. Thus, it has higher detection accuracy as the traditional angle-interrogation SPR sensor, with much wider detectable range of refractive index. Copyright © 2015 Elsevier B.V. All rights reserved.

Psychometric survey of nursing competences illustrated with nursing students and apprentices

PubMed

Reichardt, Christoph; Wernecke, Frances; Giesler, Marianne; Petersen-Ewert, Corinna

2016-09-01

Background: The term competences is discussed differently in various disciplines of science. Furthermore there is no international or discipline comprehensive accepted definition of this term. Problem: So far, there are few practical, reliable and valid measuring instruments for a survey of general nursing skills. This article describes the adaptation process of a measuring instrument for medical skills into one for nursing competences. Method: The measurement quality of the questionnaire was audited using a sample of two different courses of studies and regular nursing apprentices. Another research question focused whether the adapted questionnaire is able to detect a change of nursing skills. For the validation of reliability and validity data from the first point of measurement was used (n = 240). The data from the second point of measurement, which was conducted two years later (n = 163), were used to validate, whether the questionnaire is able to detect a change of nursing competences. Results/Conclusions: The results indicate that the adapted version of the questionnaire is reliable and valid. Also the questionnaire was able to detect significant, partly even strong, effects of change in nursing skills (d = 0,17 – 1,04). It was possible to adapt the questionnaire for the measurement of nursing competences.

Unsupervised change detection of multispectral images based on spatial constraint chi-squared transform and Markov random field model

NASA Astrophysics Data System (ADS)

Shi, Aiye; Wang, Chao; Shen, Shaohong; Huang, Fengchen; Ma, Zhenli

2016-10-01

Chi-squared transform (CST), as a statistical method, can describe the difference degree between vectors. The CST-based methods operate directly on information stored in the difference image and are simple and effective methods for detecting changes in remotely sensed images that have been registered and aligned. However, the technique does not take spatial information into consideration, which leads to much noise in the result of change detection. An improved unsupervised change detection method is proposed based on spatial constraint CST (SCCST) in combination with a Markov random field (MRF) model. First, the mean and variance matrix of the difference image of bitemporal images are estimated by an iterative trimming method. In each iteration, spatial information is injected to reduce scattered changed points (also known as "salt and pepper" noise). To determine the key parameter confidence level in the SCCST method, a pseudotraining dataset is constructed to estimate the optimal value. Then, the result of SCCST, as an initial solution of change detection, is further improved by the MRF model. The experiments on simulated and real multitemporal and multispectral images indicate that the proposed method performs well in comprehensive indices compared with other methods.

Monitoring gully change: A comparison of airborne and terrestrial laser scanning using a case study from Aratula, Queensland

NASA Astrophysics Data System (ADS)

Goodwin, Nicholas R.; Armston, John D.; Muir, Jasmine; Stiller, Issac

2017-04-01

Airborne laser scanning (ALS) and terrestrial laser scanning (TLS) technologies capture spatially detailed estimates of surface topography and when collected multi-temporally can be used to assess geomorphic change. The sensitivity and repeatability of ALS measurements to characterise geomorphic change in topographically complex environments such as gullies; however, remains an area lacking quantitative research. In this study, we captured coincident ALS and TLS datasets to assess their ability and synergies to detect geomorphic change for a gully located in Aratula, southeast Queensland, Australia. We initially used the higher spatial density and ranging accuracy of TLS to provide an assessment of the Digital Elevation Models (DEM) derived from ALS within a gully environment. Results indicated mean residual errors of 0.13 and 0.09 m along with standard deviation (SD) of residual errors of 0.20 and 0.16 m using pixel sizes of 0.5 and 1.0 m, respectively. The positive mean residual errors confirm that TLS data consistently detected deeper sections of the gully than ALS. We also compared the repeatability of ALS and TLS for characterising gully morphology. This indicated that the sensitivity to detect change using ALS is substantially lower than TLS, as expected, and that the ALS survey characteristics influence the ability to detect change. Notably, we found that using one ALS transect (mean density of 5 points / m2) as opposed to three transects increased the SD of residual error by approximately 30%. The supplied classification of ALS ground points was also demonstrated to misclassify gully features as non-ground, with minimum elevation filtering found to provide a more accurate DEM of the gully. The number and placement of terrestrial laser scans were also found to influence the derived DEMs. Furthermore, we applied change detection using two ALS data captures over a four year period and four TLS field surveys over an eight month period. This demonstrated that ALS can detect large scale erosional changes with head cutting of gully branches migrating approximately 10 m upslope. In comparison, TLS captured smaller scale intra-annual erosional patterns largely undetectable by the ALS dataset with a large rainfall event coinciding with the highest volumetric change (net change > 46 m3). Overall, these findings reaffirm the importance of quantifying DEM errors and demonstrate that ALS is unlikely to detect subtle geomorphic changes (< 0.45 m) potentially missing significant sediment change. TLS was able to detect more subtle intra-annual changes but was limited in its spatial coverage. This suggests TLS and ALS surveys are complementary technologies and when used together can provide a more detailed understanding of gully processes at different temporal and spatial scales, provided the inherent errors are taken into account.

Experimental and environmental factors affect spurious detection of ecological thresholds

USGS Publications Warehouse

Daily, Jonathan P.; Hitt, Nathaniel P.; Smith, David; Snyder, Craig D.

2012-01-01

Threshold detection methods are increasingly popular for assessing nonlinear responses to environmental change, but their statistical performance remains poorly understood. We simulated linear change in stream benthic macroinvertebrate communities and evaluated the performance of commonly used threshold detection methods based on model fitting (piecewise quantile regression [PQR]), data partitioning (nonparametric change point analysis [NCPA]), and a hybrid approach (significant zero crossings [SiZer]). We demonstrated that false detection of ecological thresholds (type I errors) and inferences on threshold locations are influenced by sample size, rate of linear change, and frequency of observations across the environmental gradient (i.e., sample-environment distribution, SED). However, the relative importance of these factors varied among statistical methods and between inference types. False detection rates were influenced primarily by user-selected parameters for PQR (τ) and SiZer (bandwidth) and secondarily by sample size (for PQR) and SED (for SiZer). In contrast, the location of reported thresholds was influenced primarily by SED. Bootstrapped confidence intervals for NCPA threshold locations revealed strong correspondence to SED. We conclude that the choice of statistical methods for threshold detection should be matched to experimental and environmental constraints to minimize false detection rates and avoid spurious inferences regarding threshold location.

Terrestrial Laser Scanning for Coastal Geomorphologic Research in Western Greece

NASA Astrophysics Data System (ADS)

Hoffmeister, D.; Tilly, N.; Curdt, C.; Aasen, H.; Ntageretzis, K.; Hadler, H.; Willershäuser, T.; Vött, A.; Bareth, G.

2012-07-01

We used terrestrial laser scanning (TLS) for (i) accurate volume estimations of dislocated boulders moved by high-energy impacts and for (ii) monitoring of annual coastal changes. In this contribution, we present three selected sites in Western Greece that were surveyed during a time span of four years (2008-2011). The Riegl LMS-Z420i laser scanner was used in combination with a precise DGPS system (Topcon HiPer Pro). Each scan position and a further target were recorded for georeferencing and merging of the point clouds. For the annual detection of changes, reference points for the base station of the DGPS system were marked. Our studies show that TLS is capable to accurately estimate volumes of boulders, which were dislocated and deposited inland from the littoral zone. The mass of each boulder was calculated from this 3D-reconstructed volume and according density data. The masses turned out to be considerably smaller than common estimated masses based on tape-measurements and according density approximations. The accurate mass data was incorporated into wave transport equations, which estimate wave velocities of high-energy impacts. As expected, these show smaller wave velocities, due to the incorporated smaller mass. Furthermore, TLS is capable to monitor annual changes on coastal areas. The changes are detected by comparing high resolution digital elevation models from every year. On a beach site, larger areas of sea-weed and sandy sediments are eroded. In contrast, bigger gravel with 30-50 cm diameter was accumulated. At the other area with bigger boulders and a different coastal configuration only slightly differences were detectable. In low-lying coastal areas and along recent beaches, post-processing of point clouds turned out to be more difficult, due to noise effects by water and shadowing effects. However, our studies show that the application of TLS in different littoral settings is an appropriate and promising tool. The combination of both instruments worked well and the annual positioning procedure with own survey point is precose for this purpose.

Bayesian Model Averaging with Change Points to Assess the Impact of Vaccination and Public Health Interventions

PubMed Central

Warren, Joshua L.; Schuck-Paim, Cynthia; Lustig, Roger; Lewnard, Joseph A.; Fuentes, Rodrigo; Bruhn, Christian A. W.; Taylor, Robert J.; Simonsen, Lone; Weinberger, Daniel M.

2017-01-01

Background: Pneumococcal conjugate vaccines (PCVs) prevent invasive pneumococcal disease and pneumonia. However, some low-and middle-income countries have yet to introduce PCV into their immunization programs due, in part, to lack of certainty about the potential impact. Assessing PCV benefits is challenging because specific data on pneumococcal disease are often lacking, and it can be difficult to separate the effects of factors other than the vaccine that could also affect pneumococcal disease rates. Methods: We assess PCV impact by combining Bayesian model averaging with change-point models to estimate the timing and magnitude of vaccine-associated changes, while controlling for seasonality and other covariates. We applied our approach to monthly time series of age-stratified hospitalizations related to pneumococcal infection in children younger 5 years of age in the United States, Brazil, and Chile. Results: Our method accurately detected changes in data in which we knew true and noteworthy changes occurred, i.e., in simulated data and for invasive pneumococcal disease. Moreover, 24 months after the vaccine introduction, we detected reductions of 14%, 9%, and 9% in the United States, Brazil, and Chile, respectively, in all-cause pneumonia (ACP) hospitalizations for age group 0 to <1 years of age. Conclusions: Our approach provides a flexible and sensitive method to detect changes in disease incidence that occur after the introduction of a vaccine or other intervention, while avoiding biases that exist in current approaches to time-trend analyses. PMID:28767518

Thermocouple design for measuring temperatures of small insects

Treesearch

A.A. Hanson; R.C. Venette

2013-01-01

Contact thermocouples often are used to measure surface body temperature changes of insects during cold exposure. However, small temperature changes of minute insects can be difficult to detect, particularly during the measurement of supercooling points. We developed two thermocouple designs, which use 0.51 mm diameter or 0.127 mm diameter copper-constantan wires, to...

The motion of radio meteor reflection point of Geminids

NASA Astrophysics Data System (ADS)

Ohnishi, Kouji; Ishikawa, Toshiyuki; Hattori, Shinobu; Nishimura, Osamu; Miyazawa, Akiko; Yanagisawa, Masatoshi; Endo, Makoto; Kawamura, Masaki; Maruyama, Toshiyuki; Hosayama, Kai; Tokunaga, Mai; Maegawa, Kimio; Abe, Shinsuke

2001-11-01

Ham-band Radio Observation (HRO) is one of the observational techniques for the forward scatter observation of meteors. We observe the meteor echo with two-element loop antennas (F/B ratio is 10 dB) at the Nagano National College of Technology (Nagano, Japan) using the continuous transmission of beacon signals for meteor observations at 53.750 MHz, 50W from Fukui National College of Technology (Fukui, Japan). To prove that the radio echo is really the echo due to meteor, we have constructed the direction determination system using the paired antennas that can detect the direction roughly where the radio echo come from. The direction of one of this paired antennas was West toward Sabae and the other was East which has proved to be the most sensitive for this research. Using this system, we detected the change of the direction of reflection point of meteor radio signal of Geminids in 2000; from the westward to eastward before and after the culmination of the radiant which is consistent the formula of reflection point of meteors. At the same time, we detected the change of an intensity and a trend of the Doppler shift of meteor echoes. This result is consistent of the meteor wind data of MU Rader of Radio Science Center for Space & Atmosphere (RASC), Kyoto University.

Spatiotemporal attention operator using isotropic contrast and regional homogeneity

NASA Astrophysics Data System (ADS)

Palenichka, Roman; Lakhssassi, Ahmed; Zaremba, Marek

2011-04-01

A multiscale operator for spatiotemporal isotropic attention is proposed to reliably extract attention points during image sequence analysis. Its consecutive local maxima indicate attention points as the centers of image fragments of variable size with high intensity contrast, region homogeneity, regional shape saliency, and temporal change presence. The scale-adaptive estimation of temporal change (motion) and its aggregation with the regional shape saliency contribute to the accurate determination of attention points in image sequences. Multilocation descriptors of an image sequence are extracted at the attention points in the form of a set of multidimensional descriptor vectors. A fast recursive implementation is also proposed to make the operator's computational complexity independent from the spatial scale size, which is the window size in the spatial averaging filter. Experiments on the accuracy of attention-point detection have proved the operator consistency and its high potential for multiscale feature extraction from image sequences.

Animals as Mobile Biological Sensors for Forest Fire Detection

PubMed Central

2007-01-01

This paper proposes a mobile biological sensor system that can assist in early detection of forest fires one of the most dreaded natural disasters on the earth. The main idea presented in this paper is to utilize animals with sensors as Mobile Biological Sensors (MBS). The devices used in this system are animals which are native animals living in forests, sensors (thermo and radiation sensors with GPS features) that measure the temperature and transmit the location of the MBS, access points for wireless communication and a central computer system which classifies of animal actions. The system offers two different methods, firstly: access points continuously receive data about animals' location using GPS at certain time intervals and the gathered data is then classified and checked to see if there is a sudden movement (panic) of the animal groups: this method is called animal behavior classification (ABC). The second method can be defined as thermal detection (TD): the access points get the temperature values from the MBS devices and send the data to a central computer to check for instant changes in the temperatures. This system may be used for many purposes other than fire detection, namely animal tracking, poaching prevention and detecting instantaneous animal death. PMID:28903281

Slowing down as an early warning signal for abrupt climate change.

PubMed

Dakos, Vasilis; Scheffer, Marten; van Nes, Egbert H; Brovkin, Victor; Petoukhov, Vladimir; Held, Hermann

2008-09-23

In the Earth's history, periods of relatively stable climate have often been interrupted by sharp transitions to a contrasting state. One explanation for such events of abrupt change is that they happened when the earth system reached a critical tipping point. However, this remains hard to prove for events in the remote past, and it is even more difficult to predict if and when we might reach a tipping point for abrupt climate change in the future. Here, we analyze eight ancient abrupt climate shifts and show that they were all preceded by a characteristic slowing down of the fluctuations starting well before the actual shift. Such slowing down, measured as increased autocorrelation, can be mathematically shown to be a hallmark of tipping points. Therefore, our results imply independent empirical evidence for the idea that past abrupt shifts were associated with the passing of critical thresholds. Because the mechanism causing slowing down is fundamentally inherent to tipping points, it follows that our way to detect slowing down might be used as a universal early warning signal for upcoming catastrophic change. Because tipping points in ecosystems and other complex systems are notoriously hard to predict in other ways, this is a promising perspective.

Slowing down as an early warning signal for abrupt climate change

PubMed Central

Dakos, Vasilis; Scheffer, Marten; van Nes, Egbert H.; Brovkin, Victor; Petoukhov, Vladimir; Held, Hermann

2008-01-01

In the Earth's history, periods of relatively stable climate have often been interrupted by sharp transitions to a contrasting state. One explanation for such events of abrupt change is that they happened when the earth system reached a critical tipping point. However, this remains hard to prove for events in the remote past, and it is even more difficult to predict if and when we might reach a tipping point for abrupt climate change in the future. Here, we analyze eight ancient abrupt climate shifts and show that they were all preceded by a characteristic slowing down of the fluctuations starting well before the actual shift. Such slowing down, measured as increased autocorrelation, can be mathematically shown to be a hallmark of tipping points. Therefore, our results imply independent empirical evidence for the idea that past abrupt shifts were associated with the passing of critical thresholds. Because the mechanism causing slowing down is fundamentally inherent to tipping points, it follows that our way to detect slowing down might be used as a universal early warning signal for upcoming catastrophic change. Because tipping points in ecosystems and other complex systems are notoriously hard to predict in other ways, this is a promising perspective. PMID:18787119

Combining isothermal rolling circle amplification and electrochemiluminescence for highly sensitive point mutation detection

NASA Astrophysics Data System (ADS)

Su, Qiang; Zhou, Xiaoming

2008-12-01

Many pathogenic and genetic diseases are associated with changes in the sequence of particular genes. We describe here a rapid and highly efficient assay for the detection of point mutation. This method is a combination of isothermal rolling circle amplification (RCA) and high sensitive electrochemluminescence (ECL) detection. In the design, a circular template generated by ligation upon the recognition of a point mutation on DNA targets was amplified isothermally by the Phi29 polymerase using a biotinylated primer. The elongation products were hybridized with tris (bipyridine) ruthenium (TBR)-tagged probes and detected in a magnetic bead based ECL platform, indicating the mutation occurrence. P53 was chosen as a model for the identification of this method. The method allowed sensitive determination of the P53 mutation from wild-type and mutant samples. The main advantage of RCA-ECL is that it can be performed under isothermal conditions and avoids the generation of false-positive results. Furthermore, ECL provides a faster, more sensitive, and economical option to currently available electrophoresis-based methods.

Expanding Cancer Detection Using Molecular Imprinting for a Novel Point-of-Care Diagnostic Device

NASA Astrophysics Data System (ADS)

Yu, Yingjie; Rafailovich, Miriam; Wang, Yantian; Kang, Yeona; Zhang, Lingxi; Rigas, Basil; Division of Gastroenterology, School of Medicine Team

2013-03-01

We propose the use of a potentiometric biosensor that incorporates the efficient and specific molecular imprinting (MI) method with a self-assembled monolayer (SAM). We first tested the biosensor using carcinoembryonic antigen, CEA, a biomarker associated with pancreatic cancer. No change in detection efficiency was observed, indicating that the sensor is able to discriminate for the template analyte even in concentrated solution of similar substances. In addition, we use biosensor to discriminate normal fibrinogen and damaged fibrinogen, which is critical for the detection of bleeding disorder. Computer simulations of the protein structure were performed in order to estimate the changes in morphology and determine the sensitivity of the biosensor to conformational changes in the proteins. We found that even small changes in PH can generate rotation of the surface functional groups. Yet, the results show that only when the detection and imprinting conditions are similar, robust signals occurs. Hence we concluded that both morphology and surface chemistry play a role in the recognition.

An open-population hierarchical distance sampling model

USGS Publications Warehouse

Sollmann, Rachel; Beth Gardner,; Richard B Chandler,; Royle, J. Andrew; T Scott Sillett,

2015-01-01

Modeling population dynamics while accounting for imperfect detection is essential to monitoring programs. Distance sampling allows estimating population size while accounting for imperfect detection, but existing methods do not allow for direct estimation of demographic parameters. We develop a model that uses temporal correlation in abundance arising from underlying population dynamics to estimate demographic parameters from repeated distance sampling surveys. Using a simulation study motivated by designing a monitoring program for island scrub-jays (Aphelocoma insularis), we investigated the power of this model to detect population trends. We generated temporally autocorrelated abundance and distance sampling data over six surveys, using population rates of change of 0.95 and 0.90. We fit the data generating Markovian model and a mis-specified model with a log-linear time effect on abundance, and derived post hoc trend estimates from a model estimating abundance for each survey separately. We performed these analyses for varying number of survey points. Power to detect population changes was consistently greater under the Markov model than under the alternatives, particularly for reduced numbers of survey points. The model can readily be extended to more complex demographic processes than considered in our simulations. This novel framework can be widely adopted for wildlife population monitoring.

An open-population hierarchical distance sampling model.

PubMed

Sollmann, Rahel; Gardner, Beth; Chandler, Richard B; Royle, J Andrew; Sillett, T Scott

2015-02-01

Modeling population dynamics while accounting for imperfect detection is essential to monitoring programs. Distance sampling allows estimating population size while accounting for imperfect detection, but existing methods do not allow for estimation of demographic parameters. We develop a model that uses temporal correlation in abundance arising from underlying population dynamics to estimate demographic parameters from repeated distance sampling surveys. Using a simulation study motivated by designing a monitoring program for Island Scrub-Jays (Aphelocoma insularis), we investigated the power of this model to detect population trends. We generated temporally autocorrelated abundance and distance sampling data over six surveys, using population rates of change of 0.95 and 0.90. We fit the data generating Markovian model and a mis-specified model with a log-linear time effect on abundance, and derived post hoc trend estimates from a model estimating abundance for each survey separately. We performed these analyses for varying numbers of survey points. Power to detect population changes was consistently greater under the Markov model than under the alternatives, particularly for reduced numbers of survey points. The model can readily be extended to more complex demographic processes than considered in our simulations. This novel framework can be widely adopted for wildlife population monitoring.

Development of Matched (migratory Analytical Time Change Easy Detection) Method for Satellite-Tracked Migratory Birds

NASA Astrophysics Data System (ADS)

Doko, Tomoko; Chen, Wenbo; Higuchi, Hiroyoshi

2016-06-01

Satellite tracking technology has been used to reveal the migration patterns and flyways of migratory birds. In general, bird migration can be classified according to migration status. These statuses include the wintering period, spring migration, breeding period, and autumn migration. To determine the migration status, periods of these statuses should be individually determined, but there is no objective method to define 'a threshold date' for when an individual bird changes its status. The research objective is to develop an effective and objective method to determine threshold dates of migration status based on satellite-tracked data. The developed method was named the "MATCHED (Migratory Analytical Time Change Easy Detection) method". In order to demonstrate the method, data acquired from satellite-tracked Tundra Swans were used. MATCHED method is composed by six steps: 1) dataset preparation, 2) time frame creation, 3) automatic identification, 4) visualization of change points, 5) interpretation, and 6) manual correction. Accuracy was tested. In general, MATCHED method was proved powerful to identify the change points between migration status as well as stopovers. Nevertheless, identifying "exact" threshold dates is still challenging. Limitation and application of this method was discussed.

Empirical likelihood based detection procedure for change point in mean residual life functions under random censorship.

PubMed

Chen, Ying-Ju; Ning, Wei; Gupta, Arjun K

2016-05-01

The mean residual life (MRL) function is one of the basic parameters of interest in survival analysis that describes the expected remaining time of an individual after a certain age. The study of changes in the MRL function is practical and interesting because it may help us to identify some factors such as age and gender that may influence the remaining lifetimes of patients after receiving a certain surgery. In this paper, we propose a detection procedure based on the empirical likelihood for the changes in MRL functions with right censored data. Two real examples are also given: Veterans' administration lung cancer study and Stanford heart transplant to illustrate the detecting procedure. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Detection of a sudden change of the field time series based on the Lorenz system.

PubMed

Da, ChaoJiu; Li, Fang; Shen, BingLu; Yan, PengCheng; Song, Jian; Ma, DeShan

2017-01-01

We conducted an exploratory study of the detection of a sudden change of the field time series based on the numerical solution of the Lorenz system. First, the time when the Lorenz path jumped between the regions on the left and right of the equilibrium point of the Lorenz system was quantitatively marked and the sudden change time of the Lorenz system was obtained. Second, the numerical solution of the Lorenz system was regarded as a vector; thus, this solution could be considered as a vector time series. We transformed the vector time series into a time series using the vector inner product, considering the geometric and topological features of the Lorenz system path. Third, the sudden change of the resulting time series was detected using the sliding t-test method. Comparing the test results with the quantitatively marked time indicated that the method could detect every sudden change of the Lorenz path, thus the method is effective. Finally, we used the method to detect the sudden change of the pressure field time series and temperature field time series, and obtained good results for both series, which indicates that the method can apply to high-dimension vector time series. Mathematically, there is no essential difference between the field time series and vector time series; thus, we provide a new method for the detection of the sudden change of the field time series.

Urban area change detection procedures with remote sensing data

NASA Technical Reports Server (NTRS)

Maxwell, E. L. (Principal Investigator); Riordan, C. J.

1980-01-01

The underlying factors affecting the detection and identification of nonurban to urban land cover change using satellite data were studied. Computer programs were developed to create a digital scene and to simulate the effect of the sensor point spread function (PSF) on the transfer of modulation from the scene to an image of the scene. The theory behind the development of a digital filter representing the PSF is given as well as an example of its application. Atmospheric effects on modulation transfer are also discussed. A user's guide and program listings are given.

Urban Growth Detection Using Filtered Landsat Dense Time Trajectory in an Arid City

NASA Astrophysics Data System (ADS)

Ye, Z.; Schneider, A.

2014-12-01

Among all remote sensing environment monitoring techniques, time series analysis of biophysical index is drawing increasing attention. Although many of them studied forest disturbance and land cover change detection, few focused on urban growth mapping at medium spatial resolution. As Landsat archive becomes open accessible, methods using Landsat time-series imagery to detect urban growth is possible. It is found that a time trajectory from a newly developed urban area shows a dramatic drop of vegetation index. This enable the utilization of time trajectory analysis to distinguish impervious surface and crop land that has a different temporal biophysical pattern. Also, the time of change can be estimated, yet many challenges remain. Landsat data has lower temporal resolution, which may be worse when cloud-contaminated pixels and SLC-off effect exist. It is difficult to tease apart intra-annual, inter-annual, and land cover difference in a time series. Here, several methods of time trajectory analysis are utilized and compared to find a computationally efficient and accurate way on urban growth detection. A case study city, Ankara, Turkey is chosen for its arid climate and various landscape distributions. For preliminary research, Landsat TM and ETM+ scenes from 1998 to 2002 are chosen. NDVI, EVI, and SAVI are selected as research biophysical indices. The procedure starts with a seasonality filtering. Only areas with seasonality need to be filtered so as to decompose seasonality and extract overall trend. Harmonic transform, wavelet transform, and a pre-defined bell shape filter are used to estimate the overall trend in the time trajectory for each pixel. The point with significant drop in the trajectory is tagged as change point. After an urban change is detected, forward and backward checking is undertaken to make sure it is really new urban expansion other than short time crop fallow or forest disturbance. The method proposed here can capture most of the urban growth during research time period, although the accuracy of time point determination is a bit lower than this. Results from several biophysical indices and filtering methods are similar. Some fallows and bare lands in arid area are easily confused with urban impervious surface.

Detecting a Change in School Performance: A Bayesian Analysis for a Multilevel Join Point Problem. CSE Technical Report 542.

ERIC Educational Resources Information Center

Thum, Yeow Meng; Bhattacharya, Suman Kumar

To better describe individual behavior within a system, this paper uses a sample of longitudinal test scores from a large urban school system to consider hierarchical Bayes estimation of a multilevel linear regression model in which each individual regression slope of test score on time switches at some unknown point in time, "kj."…

Localized Surface Plasmon Resonance Biosensing: Current Challenges and Approaches

PubMed Central

Unser, Sarah; Bruzas, Ian; He, Jie; Sagle, Laura

2015-01-01

Localized surface plasmon resonance (LSPR) has emerged as a leader among label-free biosensing techniques in that it offers sensitive, robust, and facile detection. Traditional LSPR-based biosensing utilizes the sensitivity of the plasmon frequency to changes in local index of refraction at the nanoparticle surface. Although surface plasmon resonance technologies are now widely used to measure biomolecular interactions, several challenges remain. In this article, we have categorized these challenges into four categories: improving sensitivity and limit of detection, selectivity in complex biological solutions, sensitive detection of membrane-associated species, and the adaptation of sensing elements for point-of-care diagnostic devices. The first section of this article will involve a conceptual discussion of surface plasmon resonance and the factors affecting changes in optical signal detected. The following sections will discuss applications of LSPR biosensing with an emphasis on recent advances and approaches to overcome the four limitations mentioned above. First, improvements in limit of detection through various amplification strategies will be highlighted. The second section will involve advances to improve selectivity in complex media through self-assembled monolayers, “plasmon ruler” devices involving plasmonic coupling, and shape complementarity on the nanoparticle surface. The following section will describe various LSPR platforms designed for the sensitive detection of membrane-associated species. Finally, recent advances towards multiplexed and microfluidic LSPR-based devices for inexpensive, rapid, point-of-care diagnostics will be discussed. PMID:26147727

Comparison of point counts and territory mapping for detecting effects of forest management on songbirds

USGS Publications Warehouse

Newell, Felicity L.; Sheehan, James; Wood, Petra Bohall; Rodewald, Amanda D.; Buehler, David A.; Keyser, Patrick D.; Larkin, Jeffrey L.; Beachy, Tiffany A.; Bakermans, Marja H.; Boves, Than J.; Evans, Andrea; George, Gregory A.; McDermott, Molly E.; Perkins, Kelly A.; White, Matthew; Wigley, T. Bently

2013-01-01

Point counts are commonly used to assess changes in bird abundance, including analytical approaches such as distance sampling that estimate density. Point-count methods have come under increasing scrutiny because effects of detection probability and field error are difficult to quantify. For seven forest songbirds, we compared fixed-radii counts (50 m and 100 m) and density estimates obtained from distance sampling to known numbers of birds determined by territory mapping. We applied point-count analytic approaches to a typical forest management question and compared results to those obtained by territory mapping. We used a before–after control impact (BACI) analysis with a data set collected across seven study areas in the central Appalachians from 2006 to 2010. Using a 50-m fixed radius, variance in error was at least 1.5 times that of the other methods, whereas a 100-m fixed radius underestimated actual density by >3 territories per 10 ha for the most abundant species. Distance sampling improved accuracy and precision compared to fixed-radius counts, although estimates were affected by birds counted outside 10-ha units. In the BACI analysis, territory mapping detected an overall treatment effect for five of the seven species, and effects were generally consistent each year. In contrast, all point-count methods failed to detect two treatment effects due to variance and error in annual estimates. Overall, our results highlight the need for adequate sample sizes to reduce variance, and skilled observers to reduce the level of error in point-count data. Ultimately, the advantages and disadvantages of different survey methods should be considered in the context of overall study design and objectives, allowing for trade-offs among effort, accuracy, and power to detect treatment effects.

Homogenising time series: Beliefs, dogmas and facts

NASA Astrophysics Data System (ADS)

Domonkos, P.

2010-09-01

For obtaining reliable information about climate change and climate variability the use of high quality data series is essentially important, and one basic tool of quality improvements is the statistical homogenisation of observed time series. In the recent decades large number of homogenisation methods has been developed, but the real effects of their application on time series are still not known entirely. The ongoing COST HOME project (COST ES0601) is devoted to reveal the real impacts of homogenisation methods more detailed and with higher confidence than earlier. As part of the COST activity, a benchmark dataset was built whose characteristics approach well the characteristics of real networks of observed time series. This dataset offers much better opportunity than ever to test the wide variety of homogenisation methods, and analyse the real effects of selected theoretical recommendations. The author believes that several old theoretical rules have to be re-evaluated. Some examples of the hot questions, a) Statistically detected change-points can be accepted only with the confirmation of metadata information? b) Do semi-hierarchic algorithms for detecting multiple change-points in time series function effectively in practise? c) Is it good to limit the spatial comparison of candidate series with up to five other series in the neighbourhood? Empirical results - those from the COST benchmark, and other experiments too - show that real observed time series usually include several inhomogeneities of different sizes. Small inhomogeneities seem like part of the climatic variability, thus the pure application of classic theory that change-points of observed time series can be found and corrected one-by-one is impossible. However, after homogenisation the linear trends, seasonal changes and long-term fluctuations of time series are usually much closer to the reality, than in raw time series. The developers and users of homogenisation methods have to bear in mind that the eventual purpose of homogenisation is not to find change-points, but to have the observed time series with statistical properties those characterise well the climate change and climate variability.

Responsiveness, minimal detectable change, and minimal clinically important difference of the Nottingham Extended Activities of Daily Living Scale in patients with improved performance after stroke rehabilitation.

PubMed

Wu, Ching-yi; Chuang, Li-ling; Lin, Keh-chung; Lee, Shin-da; Hong, Wei-hsien

2011-08-01

To determine the responsiveness, minimal detectable change (MDC), and minimal clinically important differences (MCIDs) of the Nottingham Extended Activities of Daily Living (NEADL) scale and to assess percentages of patients' change scores exceeding the MDC and MCID after stroke rehabilitation. Secondary analyses of patients who received stroke rehabilitation therapy. Medical centers. Patients with stroke (N=78). Secondary analyses of patients who received 1 of 4 rehabilitation interventions. Responsiveness (standardized response mean [SRM]), 90% confidence that a change score at this threshold or higher is true and reliable rather than measurement error (MDC(90)), and MCID on the NEADL score and percentages of patients exceeding the MDC(90) and MCID. The SRM of the total NEADL scale was 1.3. The MDC(90) value for the total NEADL scale was 4.9, whereas minima and maxima of the MCID for total NEADL score were 2.4 and 6.1 points, respectively. Percentages of patients exceeding the MDC(90) and MCID of the total NEADL score were 50.0%, 73.1%, and 32.1%, respectively. The NEADL is a responsive instrument relevant for measuring change in instrumental activities of daily living after stroke rehabilitation. A patient's change score has to reach 4.9 points on the total to indicate a true change. The mean change score of a stroke group on the total NEADL scale should achieve 6.1 points to be regarded as clinically important. Our findings are based on patients with improved NEADL performance after they received specific interventions. Future research with larger sample sizes is warranted to validate these estimates. Copyright © 2011 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

The fate of object memory traces under change detection and change blindness.

PubMed

Busch, Niko A

2013-07-03

Observers often fail to detect substantial changes in a visual scene. This so-called change blindness is often taken as evidence that visual representations are sparse and volatile. This notion rests on the assumption that the failure to detect a change implies that representations of the changing objects are lost all together. However, recent evidence suggests that under change blindness, object memory representations may be formed and stored, but not retrieved. This study investigated the fate of object memory representations when changes go unnoticed. Participants were presented with scenes consisting of real world objects, one of which changed on each trial, while recording event-related potentials (ERPs). Participants were first asked to localize where the change had occurred. In an additional recognition task, participants then discriminated old objects, either from the pre-change or the post-change scene, from entirely new objects. Neural traces of object memories were studied by comparing ERPs for old and novel objects. Participants performed poorly in the detection task and often failed to recognize objects from the scene, especially pre-change objects. However, a robust old/novel effect was observed in the ERP, even when participants were change blind and did not recognize the old object. This implicit memory trace was found both for pre-change and post-change objects. These findings suggest that object memories are stored even under change blindness. Thus, visual representations may not be as sparse and volatile as previously thought. Rather, change blindness may point to a failure to retrieve and use these representations for change detection. Copyright © 2013 Elsevier B.V. All rights reserved.

Intrinsic low pass filtering improves signal-to-noise ratio in critical-point flexure biosensors

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

Jain, Ankit; Alam, Muhammad Ashraful, E-mail: alam@purdue.edu

2014-08-25

A flexure biosensor consists of a suspended beam and a fixed bottom electrode. The adsorption of the target biomolecules on the beam changes its stiffness and results in change of beam's deflection. It is now well established that the sensitivity of sensor is maximized close to the pull-in instability point, where effective stiffness of the beam vanishes. The question: “Do the signal-to-noise ratio (SNR) and the limit-of-detection (LOD) also improve close to the instability point?”, however remains unanswered. In this article, we systematically analyze the noise response to evaluate SNR and establish LOD of critical-point flexure sensors. We find thatmore » a flexure sensor acts like an effective low pass filter close to the instability point due to its relatively small resonance frequency, and rejects high frequency noise, leading to improved SNR and LOD. We believe that our conclusions should establish the uniqueness and the technological relevance of critical-point biosensors.« less

A 6.7 GHz Methanol Maser Survey at High Galactic Latitudes

NASA Astrophysics Data System (ADS)

Yang, Kai; Chen, Xi; Shen, Zhi-Qiang; Li, Xiao-Qiong; Wang, Jun-Zhi; Jiang, Dong-Rong; Li, Juan; Dong, Jian; Wu, Ya-Jun; Qiao, Hai-Hua; Ren, Zhiyuan

2017-09-01

We performed a systematic 6.7 GHz Class II methanol maser survey using the Shanghai Tianma Radio Telescope toward targets selected from the all-sky Wide-Field Infrared Survey Explorer (WISE) point catalog. In this paper, we report the results from the survey of those at high Galactic latitudes, I.e., | b| > 2°. Of 1473 selected WISE point sources at high latitude, 17 point positions that were actually associated with 12 sources were detected with maser emission, reflecting the rarity (1%-2%) of methanol masers in the region away from the Galactic plane. Out of the 12 sources, 3 are detected for the first time. The spectral energy distribution at infrared bands shows that these new detected masers occur in the massive star-forming regions. Compared to previous detections, the methanol maser changes significantly in both spectral profiles and flux densities. The infrared WISE images show that almost all of these masers are located in the positions of the bright WISE point sources. Compared to the methanol masers at the Galactic plane, these high-latitude methanol masers provide good tracers for investigating the physics and kinematics around massive young stellar objects, because they are believed to be less affected by the surrounding cluster environment.

Arterial endothelial function measurement method and apparatus

DOEpatents

Maltz, Jonathan S; Budinger, Thomas F

2014-03-04

A "relaxoscope" (100) detects the degree of arterial endothelial function. Impairment of arterial endothelial function is an early event in atherosclerosis and correlates with the major risk factors for cardiovascular disease. An artery (115), such as the brachial artery (BA) is measured for diameter before and after several minutes of either vasoconstriction or vasorelaxation. The change in arterial diameter is a measure of flow-mediated vasomodification (FMVM). The relaxoscope induces an artificial pulse (128) at a superficial radial artery (115) via a linear actuator (120). An ultrasonic Doppler stethoscope (130) detects this pulse 10-20 cm proximal to the point of pulse induction (125). The delay between pulse application and detection provides the pulse transit time (PTT). By measuring PTT before (160) and after arterial diameter change (170), FMVM may be measured based on the changes in PTT caused by changes in vessel caliber, smooth muscle tone and wall thickness.

Ecological change points: The strength of density dependence and the loss of history.

PubMed

Ponciano, José M; Taper, Mark L; Dennis, Brian

2018-05-01

Change points in the dynamics of animal abundances have extensively been recorded in historical time series records. Little attention has been paid to the theoretical dynamic consequences of such change-points. Here we propose a change-point model of stochastic population dynamics. This investigation embodies a shift of attention from the problem of detecting when a change will occur, to another non-trivial puzzle: using ecological theory to understand and predict the post-breakpoint behavior of the population dynamics. The proposed model and the explicit expressions derived here predict and quantify how density dependence modulates the influence of the pre-breakpoint parameters into the post-breakpoint dynamics. Time series transitioning from one stationary distribution to another contain information about where the process was before the change-point, where is it heading and how long it will take to transition, and here this information is explicitly stated. Importantly, our results provide a direct connection of the strength of density dependence with theoretical properties of dynamic systems, such as the concept of resilience. Finally, we illustrate how to harness such information through maximum likelihood estimation for state-space models, and test the model robustness to widely different forms of compensatory dynamics. The model can be used to estimate important quantities in the theory and practice of population recovery. Copyright © 2018 Elsevier Inc. All rights reserved.

Edge detection techniques for iris recognition system

NASA Astrophysics Data System (ADS)

Tania, U. T.; Motakabber, S. M. A.; Ibrahimy, M. I.

2013-12-01

Nowadays security and authentication are the major parts of our daily life. Iris is one of the most reliable organ or part of human body which can be used for identification and authentication purpose. To develop an iris authentication algorithm for personal identification, this paper examines two edge detection techniques for iris recognition system. Between the Sobel and the Canny edge detection techniques, the experimental result shows that the Canny's technique has better ability to detect points in a digital image where image gray level changes even at slow rate.

Detectability of change in winter precipitation within mountain landscapes: Spatial patterns and uncertainty

NASA Astrophysics Data System (ADS)

Silverman, N. L.; Maneta, M. P.

2016-06-01

Detecting long-term change in seasonal precipitation using ground observations is dependent on the representativity of the point measurement to the surrounding landscape. In mountainous regions, representativity can be poor and lead to large uncertainties in precipitation estimates at high elevations or in areas where observations are sparse. If the uncertainty in the estimate is large compared to the long-term shifts in precipitation, then the change will likely go undetected. In this analysis, we examine the minimum detectable change across mountainous terrain in western Montana, USA. We ask the question: What is the minimum amount of change that is necessary to be detected using our best estimates of precipitation in complex terrain? We evaluate the spatial uncertainty in the precipitation estimates by conditioning historic regional climate model simulations to ground observations using Bayesian inference. By using this uncertainty as a null hypothesis, we test for detectability across the study region. To provide context for the detectability calculations, we look at a range of future scenarios from the Coupled Model Intercomparison Project 5 (CMIP5) multimodel ensemble downscaled to 4 km resolution using the MACAv2-METDATA data set. When using the ensemble averages we find that approximately 65% of the significant increases in winter precipitation go undetected at midelevations. At high elevation, approximately 75% of significant increases in winter precipitation are undetectable. Areas where change can be detected are largely controlled by topographic features. Elevation and aspect are key characteristics that determine whether or not changes in winter precipitation can be detected. Furthermore, we find that undetected increases in winter precipitation at high elevation will likely remain as snow under climate change scenarios. Therefore, there is potential for these areas to offset snowpack loss at lower elevations and confound the effects of climate change on water resources.

Incorporating availability for detection in estimates of bird abundance

USGS Publications Warehouse

Diefenbach, D.R.; Marshall, M.R.; Mattice, J.A.; Brauning, D.W.

2007-01-01

Several bird-survey methods have been proposed that provide an estimated detection probability so that bird-count statistics can be used to estimate bird abundance. However, some of these estimators adjust counts of birds observed by the probability that a bird is detected and assume that all birds are available to be detected at the time of the survey. We marked male Henslow's Sparrows (Ammodramus henslowii) and Grasshopper Sparrows (A. savannarum) and monitored their behavior during May-July 2002 and 2003 to estimate the proportion of time they were available for detection. We found that the availability of Henslow's Sparrows declined in late June to <10% for 5- or 10-min point counts when a male had to sing and be visible to the observer; but during 20 May-19 June, males were available for detection 39.1% (SD = 27.3) of the time for 5-min point counts and 43.9% (SD = 28.9) of the time for 10-min point counts (n = 54). We detected no temporal changes in availability for Grasshopper Sparrows, but estimated availability to be much lower for 5-min point counts (10.3%, SD = 12.2) than for 10-min point counts (19.2%, SD = 22.3) when males had to be visible and sing during the sampling period (n = 80). For distance sampling, we estimated the availability of Henslow's Sparrows to be 44.2% (SD = 29.0) and the availability of Grasshopper Sparrows to be 20.6% (SD = 23.5). We show how our estimates of availability can be incorporated in the abundance and variance estimators for distance sampling and modify the abundance and variance estimators for the double-observer method. Methods that directly estimate availability from bird counts but also incorporate detection probabilities need further development and will be important for obtaining unbiased estimates of abundance for these species.

An evaluation of the effectiveness of low-cost UAVs and structure from motion for geomorphic change detection

NASA Astrophysics Data System (ADS)

Cook, Kristen L.

2017-02-01

The measurement of topography and of topographic change is essential for the study of many geomorphic processes. In recent years, structure from motion (SfM) techniques applied to photographs taken by camera-equipped unmanned aerial vehicles (UAVs) has become a powerful new tool for the generation of high resolution topography. The variety of available UAV systems continues to increase rapidly, but it is not clear whether increased UAV sophistication translates into improved quality of the calculated topography. To evaluate the lower end of the UAV spectrum, a simple low cost UAV was deployed to calculate high resolution topography in the Daan River gorge in western Taiwan, a site with a complicated 3D morphology and a wide range of surface types, making it a challenging site for topographic measurement. Terrestrial lidar surveys were conducted in parallel with UAV surveys in both June and November 2014, enabling an assessment of the reliability of the UAV survey to detect geomorphic changes in the range of 30 cm to several meters. A further UAV survey was conducted in June 2015 in order to quantify changes resulting from the 2015 spring monsoon. To evaluate the accuracy of the UAV derived topography, it was compared to terrestrial lidar data collected during the same survey period using the cloud-to-cloud comparison algorithm M3C2. The UAV-generated point clouds match the lidar point clouds well, with RMS errors of 30-40 cm; however, the accuracy of the SfM point clouds depends strongly on the characteristics of the surface being considered, with vegetation, water, and small scale texture causing inaccuracies. The lidar and SfM data yield similar maps of change from June to November 2014, with the same areas of geomorphic change detected by both methods. The SfM-generated change map for November 2014 to June 2015 indicates that the 2015 spring monsoon caused erosion throughout the gorge and highlights the importance of event-driven erosion in the Daan River. The results suggest that even very basic UAVs can yield data suitable for measuring geomorphic change on the scale of a channel reach.

Segmentation of time series with long-range fractal correlations

PubMed Central

Bernaola-Galván, P.; Oliver, J.L.; Hackenberg, M.; Coronado, A.V.; Ivanov, P.Ch.; Carpena, P.

2012-01-01

Segmentation is a standard method of data analysis to identify change-points dividing a nonstationary time series into homogeneous segments. However, for long-range fractal correlated series, most of the segmentation techniques detect spurious change-points which are simply due to the heterogeneities induced by the correlations and not to real nonstationarities. To avoid this oversegmentation, we present a segmentation algorithm which takes as a reference for homogeneity, instead of a random i.i.d. series, a correlated series modeled by a fractional noise with the same degree of correlations as the series to be segmented. We apply our algorithm to artificial series with long-range correlations and show that it systematically detects only the change-points produced by real nonstationarities and not those created by the correlations of the signal. Further, we apply the method to the sequence of the long arm of human chromosome 21, which is known to have long-range fractal correlations. We obtain only three segments that clearly correspond to the three regions of different G + C composition revealed by means of a multi-scale wavelet plot. Similar results have been obtained when segmenting all human chromosome sequences, showing the existence of previously unknown huge compositional superstructures in the human genome. PMID:23645997

Micro spectrometer for parallel light and method of use

NASA Technical Reports Server (NTRS)

Park, Yeonjoon (Inventor); Choi, Sang H. (Inventor); King, Glen C. (Inventor); Elliott, James R. (Inventor)

2011-01-01

A spectrometer system includes an optical assembly for collimating light, a micro-ring grating assembly having a plurality of coaxially-aligned ring gratings, an aperture device defining an aperture circumscribing a target focal point, and a photon detector. An electro-optical layer of the grating assembly may be electrically connected to an energy supply to change the refractive index of the electro-optical layer. Alternately, the gratings may be electrically connected to the energy supply and energized, e.g., with alternating voltages, to change the refractive index. A data recorder may record the predetermined spectral characteristic. A method of detecting a spectral characteristic of a predetermined wavelength of source light includes generating collimated light using an optical assembly, directing the collimated light onto the micro-ring grating assembly, and selectively energizing the micro-ring grating assembly to diffract the predetermined wavelength onto the target focal point, and detecting the spectral characteristic using a photon detector.

Acromegaly determination using discriminant analysis of the three-dimensional facial classification in Taiwanese.

PubMed

Wang, Ming-Hsu; Lin, Jen-Der; Chang, Chen-Nen; Chiou, Wen-Ko

2017-08-01

The aim of this study was to assess the size, angles and positional characteristics of facial anthropometry between "acromegalic" patients and control subjects. We also identify possible facial soft tissue measurements for generating discriminant functions toward acromegaly determination in males and females for acromegaly early self-awareness. This is a cross-sectional study. Subjects participating in this study included 70 patients diagnosed with acromegaly (35 females and 35 males) and 140 gender-matched control individuals. Three-dimensional facial images were collected via a camera system. Thirteen landmarks were selected. Eleven measurements from the three categories were selected and applied, including five frontal widths, three lateral depths and three lateral angular measurements. Descriptive analyses were conducted using means and standard deviations for each measurement. Univariate and multivariate discriminant function analyses were applied in order to calculate the accuracy of acromegaly detection. Patients with acromegaly exhibit soft-tissue facial enlargement and hypertrophy. Frontal widths as well as lateral depth and angle of facial changes were evident. The average accuracies of all functions for female patient detection ranged from 80.0-91.40%. The average accuracies of all functions for male patient detection were from 81.0-94.30%. The greatest anomaly observed was evidenced in the lateral angles, with greater enlargement of "nasofrontal" angles for females and greater "mentolabial" angles for males. Additionally, shapes of the lateral angles showed changes. The majority of the facial measurements proved dynamic for acromegaly patients; however, it is problematic to detect the disease with progressive body anthropometric changes. The discriminant functions of detection developed in this study could help patients, their families, medical practitioners and others to identify and track progressive facial change patterns before the possible patients go to the hospital, especially the lateral "angles" which can be calculated by relative point-to-point changes derived from 2D lateral imagery without the 3D anthropometric measurements. This study tries to provide a novel and easy method to detect acromegaly when the patients start to have awareness of abnormal appearance because of facial measurement changes, and it also suggests that undiagnosed patients be urged to go to the hospital as soon as possible for acromegaly early diagnosis.

Organic-matter loading determines regime shifts and alternative states in an aquatic ecosystem

PubMed Central

Sirota, Jennie; Baiser, Benjamin; Gotelli, Nicholas J.; Ellison, Aaron M.

2013-01-01

Slow changes in underlying state variables can lead to “tipping points,” rapid transitions between alternative states (“regime shifts”) in a wide range of complex systems. Tipping points and regime shifts routinely are documented retrospectively in long time series of observational data. Experimental induction of tipping points and regime shifts is rare, but could lead to new methods for detecting impending tipping points and forestalling regime shifts. By using controlled additions of detrital organic matter (dried, ground arthropod prey), we experimentally induced a shift from aerobic to anaerobic states in a miniature aquatic ecosystem: the self-contained pools that form in leaves of the carnivorous northern pitcher plant, Sarracenia purpurea. In unfed controls, the concentration of dissolved oxygen ([O2]) in all replicates exhibited regular diurnal cycles associated with daytime photosynthesis and nocturnal plant respiration. In low prey-addition treatments, the regular diurnal cycles of [O2] were disrupted, but a regime shift was not detected. In high prey-addition treatments, the variance of the [O2] time series increased until the system tipped from an aerobic to an anaerobic state. In these treatments, replicate [O2] time series predictably crossed a tipping point at ∼45 h as [O2] was decoupled from diurnal cycles of photosynthesis and respiration. Increasing organic-matter loading led to predictable changes in [O2] dynamics, with high loading consistently driving the system past a well-defined tipping point. The Sarracenia microecosystem functions as a tractable experimental system in which to explore the forecasting and management of tipping points and alternative regimes. PMID:23613583

Organic-matter loading determines regime shifts and alternative states in an aquatic ecosystem.

PubMed

Sirota, Jennie; Baiser, Benjamin; Gotelli, Nicholas J; Ellison, Aaron M

2013-05-07

Slow changes in underlying state variables can lead to "tipping points," rapid transitions between alternative states ("regime shifts") in a wide range of complex systems. Tipping points and regime shifts routinely are documented retrospectively in long time series of observational data. Experimental induction of tipping points and regime shifts is rare, but could lead to new methods for detecting impending tipping points and forestalling regime shifts. By using controlled additions of detrital organic matter (dried, ground arthropod prey), we experimentally induced a shift from aerobic to anaerobic states in a miniature aquatic ecosystem: the self-contained pools that form in leaves of the carnivorous northern pitcher plant, Sarracenia purpurea. In unfed controls, the concentration of dissolved oxygen ([O2]) in all replicates exhibited regular diurnal cycles associated with daytime photosynthesis and nocturnal plant respiration. In low prey-addition treatments, the regular diurnal cycles of [O2] were disrupted, but a regime shift was not detected. In high prey-addition treatments, the variance of the [O2] time series increased until the system tipped from an aerobic to an anaerobic state. In these treatments, replicate [O2] time series predictably crossed a tipping point at ~45 h as [O2] was decoupled from diurnal cycles of photosynthesis and respiration. Increasing organic-matter loading led to predictable changes in [O2] dynamics, with high loading consistently driving the system past a well-defined tipping point. The Sarracenia microecosystem functions as a tractable experimental system in which to explore the forecasting and management of tipping points and alternative regimes.

Detection of Rooftop Cooling Unit Faults Based on Electrical Measurements

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

Armstrong, Peter R.; Laughman, C R.; Leeb, S B.

Non-intrusive load monitoring (NILM) is accomplished by sampling voltage and current at high rates and reducing the resulting start transients or harmonic contents to concise ''signatures''. Changes in these signatures can be used to detect, and in many cases directly diagnose, equipment and component faults associated with roof-top cooling units. Use of the NILM for fault detection and diagnosis (FDD) is important because (1) it complements other FDD schemes that are based on thermo-fluid sensors and analyses and (2) it is minimally intrusive (one measuring point in the relatively protected confines of the control panel) and therefore inherently reliable. Thismore » paper describes changes in the power signatures of fans and compressors that were found, experimentally and theoretically, to be useful for fault detection.« less

Islanding detection technique using wavelet energy in grid-connected PV system

NASA Astrophysics Data System (ADS)

Kim, Il Song

2016-08-01

This paper proposes a new islanding detection method using wavelet energy in a grid-connected photovoltaic system. The method detects spectral changes in the higher-frequency components of the point of common coupling voltage and obtains wavelet coefficients by multilevel wavelet analysis. The autocorrelation of the wavelet coefficients can clearly identify islanding detection, even in the variations of the grid voltage harmonics during normal operating conditions. The advantage of the proposed method is that it can detect islanding condition the conventional under voltage/over voltage/under frequency/over frequency methods fail to detect. The theoretical method to obtain wavelet energies is evolved and verified by the experimental result.

The sequentially discounting autoregressive (SDAR) method for on-line automatic seismic event detecting on long term observation

NASA Astrophysics Data System (ADS)

Wang, L.; Toshioka, T.; Nakajima, T.; Narita, A.; Xue, Z.

2017-12-01

In recent years, more and more Carbon Capture and Storage (CCS) studies focus on seismicity monitoring. For the safety management of geological CO2 storage at Tomakomai, Hokkaido, Japan, an Advanced Traffic Light System (ATLS) combined different seismic messages (magnitudes, phases, distributions et al.) is proposed for injection controlling. The primary task for ATLS is the seismic events detection in a long-term sustained time series record. Considering the time-varying characteristics of Signal to Noise Ratio (SNR) of a long-term record and the uneven energy distributions of seismic event waveforms will increase the difficulty in automatic seismic detecting, in this work, an improved probability autoregressive (AR) method for automatic seismic event detecting is applied. This algorithm, called sequentially discounting AR learning (SDAR), can identify the effective seismic event in the time series through the Change Point detection (CPD) of the seismic record. In this method, an anomaly signal (seismic event) can be designed as a change point on the time series (seismic record). The statistical model of the signal in the neighborhood of event point will change, because of the seismic event occurrence. This means the SDAR aims to find the statistical irregularities of the record thought CPD. There are 3 advantages of SDAR. 1. Anti-noise ability. The SDAR does not use waveform messages (such as amplitude, energy, polarization) for signal detecting. Therefore, it is an appropriate technique for low SNR data. 2. Real-time estimation. When new data appears in the record, the probability distribution models can be automatic updated by SDAR for on-line processing. 3. Discounting property. the SDAR introduces a discounting parameter to decrease the influence of present statistic value on future data. It makes SDAR as a robust algorithm for non-stationary signal processing. Within these 3 advantages, the SDAR method can handle the non-stationary time-varying long-term series and achieve real-time monitoring. Finally, we employ the SDAR on a synthetic model and Tomakomai Ocean Bottom Cable (OBC) baseline data to prove the feasibility and advantage of our method.

The Minimum Clinically Important Difference of the Patient-rated Wrist Evaluation Score for Patients With Distal Radius Fractures.

PubMed

Walenkamp, Monique M J; de Muinck Keizer, Robert-Jan; Goslings, J Carel; Vos, Lara M; Rosenwasser, Melvin P; Schep, Niels W L

2015-10-01

The Patient-rated Wrist Evaluation (PRWE) is a commonly used instrument in upper extremity surgery and in research. However, to recognize a treatment effect expressed as a change in PRWE, it is important to be aware of the minimum clinically important difference (MCID) and the minimum detectable change (MDC). The MCID of an outcome tool like the PRWE is defined as the smallest change in a score that is likely to be appreciated by a patient as an important change, while the MDC is defined as the smallest amount of change that can be detected by an outcome measure. A numerical change in score that is less than the MCID, even when statistically significant, does not represent a true clinically relevant change. To our knowledge, the MCID and MDC of the PRWE have not been determined in patients with distal radius fractures. We asked: (1) What is the MCID of the PRWE score for patients with distal radius fractures? (2) What is the MDC of the PRWE? Our prospective cohort study included 102 patients with a distal radius fracture and a median age of 59 years (interquartile range [IQR], 48-66 years). All patients completed the PRWE questionnaire during each of two separate visits. At the second visit, patients were asked to indicate the degree of clinical change they appreciated since the previous visit. Accordingly, patients were categorized in two groups: (1) minimally improved or (2) no change. The groups were used to anchor the changes observed in the PRWE score to patients' perspectives of what was clinically important. We determined the MCID using an anchor-based receiver operator characteristic method. In this context, the change in the PRWE score was considered a diagnostic test, and the anchor (minimally improved or no change as noted by the patients from visit to visit) was the gold standard. The optimal receiver operator characteristic cutoff point calculated with the Youden index reflected the value of the MCID. In our study, the MCID of the PRWE was 11.5 points. The area under the curve was 0.54 (95% CI, 0.37-0.70) for the pain subscale and 0.71 (95% CI, 0.57-0.85) for the function subscale. We determined the MDC to be 11.0 points. We determined the MCID of the PRWE score for patients with distal radius fractures using the anchor-based approach and verified that the MDC of the PRWE was sufficiently small to detect our MCID. We recommend using an improvement on the PRWE of more than 11.5 points as the smallest clinically relevant difference when evaluating the effects of treatments and when performing sample-size calculations on studies of distal radius fractures.

Dose-escalation using intensity-modulated radiotherapy for prostate cancer - evaluation of quality of life with and without (18)F-choline PET-CT detected simultaneous integrated boost.

PubMed

Pinkawa, Michael; Piroth, Marc D; Holy, Richard; Klotz, Jens; Djukic, Victoria; Corral, Nuria Escobar; Caffaro, Mariana; Winz, Oliver H; Krohn, Thomas; Mottaghy, Felix M; Eble, Michael J

2012-01-30

In comparison to the conventional whole-prostate dose escalation, an integrated boost to the macroscopic malignant lesion might potentially improve tumor control rates without increasing toxicity. Quality of life after radiotherapy (RT) with vs. without (18)F-choline PET-CT detected simultaneous integrated boost (SIB) was prospectively evaluated in this study. Whole body image acquisition in supine patient position followed 1 h after injection of 178-355MBq (18)F-choline. SIB was defined by a tumor-to-background uptake value ratio > 2 (GTV(PET)). A dose of 76Gy was prescribed to the prostate (PTV(prostate)) in 2Gy fractions, with or without SIB up to 80Gy. Patients treated with (n = 46) vs. without (n = 21) SIB were surveyed prospectively before (A), at the last day of RT (B) and a median time of two (C) and 19 month (D) after RT to compare QoL changes applying a validated questionnaire (EPIC - expanded prostate cancer index composite). With a median cut-off standard uptake value (SUV) of 3, a median GTV(PET) of 4.0 cm(3) and PTV(boost) (GTV(PET) with margins) of 17.3 cm(3) was defined. No significant differences were found for patients treated with vs. without SIB regarding urinary and bowel QoL changes at times B, C and D (mean differences ≤3 points for all comparisons). Significantly decreasing acute urinary and bowel score changes (mean changes > 5 points in comparison to baseline level at time A) were found for patients with and without SIB. However, long-term urinary and bowel QoL (time D) did not differ relative to baseline levels - with mean urinary and bowel function score changes < 3 points in both groups (median changes = 0 points). Only sexual function scores decreased significantly (> 5 points) at time D. Treatment planning with (18)F-choline PET-CT allows a dose escalation to a macroscopic intraprostatic lesion without significantly increasing toxicity.

Shifts in river-floodplain relationship reveal the impacts of river regulation: A case study of Dongting Lake in China

NASA Astrophysics Data System (ADS)

Lu, Cai; Jia, Yifei; Jing, Lei; Zeng, Qing; Lei, Jialin; Zhang, Shuanghu; Lei, Guangchun; Wen, Li

2018-04-01

Better understanding of the dynamics of hydrological connectivity between river and floodplain is essential for the ecological integrity of river systems. In this study, we proposed a regime-switch modelling (RSM) framework, which integrates change point analysis with dynamic linear regression, to detect and date change points in linear regression, and to quantify the relative importance of natural variations and anthropogenic disturbances. The approach was applied to the long-term hydrological time series to investigate the evolution of river-floodplain relation in Dongting Lake in the last five decades, during which the Yangtze River system experienced unprecedented anthropogenic manipulations. Our results suggested that 1) there were five distinct regimes during which the influence of inflows and local climate on lake water level changed significantly. The detected change points were well corresponding to the major events occurred upon the Yangtze; 2) although the importance of inflows from the Yangtze was greater than that of the tributaries flows over the five regimes, the relative contribution gradually decreased from regime 1 to regime 5. The weakening of hydrological forcing from the Yangtze was mainly attributed to the reduction in channel capacity resulting from sedimentation in the outfalls and water level dropping caused by river bed scour in the mainstream; 3) the effects of local climate was much smaller than these of inflows; and 4) since the operation of The Three Gorges Dam in 2006, the river-floodplain relationship entered a new equilibrium in that all investigated variables changed synchronously in terms of direction and magnitude. The results from this study reveal the mechanisms underlying the alternated inundation regime in Dongting Lake. The identified change points, some of which have not been previously reported, will allow a reappraisal of the current dam and reservoir operation strategies not only for flood/drought risk management but also for the maintenance and restoration of the regional ecological integrity.

Statistics is not enough: revisiting Ronald A. Fisher's critique (1936) of Mendel's experimental results (1866).

PubMed

Pilpel, Avital

2007-09-01

This paper is concerned with the role of rational belief change theory in the philosophical understanding of experimental error. Today, philosophers seek insight about error in the investigation of specific experiments, rather than in general theories. Nevertheless, rational belief change theory adds to our understanding of just such cases: R. A. Fisher's criticism of Mendel's experiments being a case in point. After an historical introduction, the main part of this paper investigates Fisher's paper from the point of view of rational belief change theory: what changes of belief about Mendel's experiment does Fisher go through and with what justification. It leads to surprising insights about what Fisher had done right and wrong, and, more generally, about the limits of statistical methods in detecting error.

The plasma interleukin-6 response to acute psychosocial stress in humans is detected by a magnetic multiplex assay: comparison to high-sensitivity ELISA.

PubMed

Quinn, Andrea M; Williams, Allison R; Sivilli, Teresa I; Raison, Charles L; Pace, Thaddeus W W

2018-03-13

Circulating concentrations of interleukin (IL)-6, an inflammatory biomarker widely assessed in humans to study the inflammatory response to acute psychological stress, have for decades been quantified using enzyme-linked immunosorbent assay (ELISA). However, biobehavioral researchers are increasingly using cytokine multiplex assays instead of ELISA to measure IL-6 and other cytokines. Despite this trend, multiplex assays have not been directly compared to ELISA for their ability to detect subtle stress-induced changes of IL-6. Here, we tested the prediction that a high-sensitivity multiplex assay (human Magnetic Luminex Performance Assay, R&D Systems, Minneapolis, MN) would detect changes in IL-6 as a result of acute stress challenge in a manner comparable to high-sensitivity ELISA. Blood was collected from 12 healthy adults immediately before and then 90 and 210 min after the start of the Trier Social Stress Test (TSST), an acute laboratory psychosocial stress challenge. In addition to quantifying IL-6 concentrations in plasma with both multiplex and ELISA, we also assessed concentrations of tumor necrosis factor-alpha, IL-8, IL-10, IL-5, and IL-2 with multiplex. The multiplex detected IL-6 in all samples. Concentrations strongly correlated with values determined by ELISA across all samples (r = 0.941, p < .001) as well as among samples collected at individual TSST time points. IL-6 responses to the TSST (i.e. area under the curve) captured by multiplex and ELISA were also strongly correlated (r s   = 0.937, p < .001). While other cytokines were detected by multiplex, none changed as a result of TSST challenge at time points examined. These results suggest high-sensitivity magnetic multiplex assay is able to detect changes in plasma concentrations of IL-6 as a result of acute stress in humans.

Development of new structural health monitoring techniques

NASA Astrophysics Data System (ADS)

Fekrmandi, Hadi

During the past two decades, many researchers have developed methods for the detection of structural defects at the early stages to operate the aerospace vehicles safely and to reduce the operating costs. The Surface Response to Excitation (SuRE) method is one of these approaches developed at FIU to reduce the cost and size of the equipment. The SuRE method excites the surface at a series of frequencies and monitors the propagation characteristics of the generated waves. The amplitude of the waves reaching to any point on the surface varies with frequency; however, it remains consistent as long as the integrity and strain distribution on the part is consistent. These spectral characteristics change when cracks develop or the strain distribution changes. The SHM methods may be used for many applications, from the detection of loose screws to the monitoring of manufacturing operations. A scanning laser vibrometer was used in this study to investigate the characteristics of the spectral changes at different points on the parts. The study started with detecting a load on a plate and estimating its location. The modifications on the part with manufacturing operations were detected and the Part-Based Manufacturing Process Performance Monitoring (PbPPM) method was developed. Hardware was prepared to demonstrate the feasibility of the proposed methods in real time. Using low-cost piezoelectric elements and the non-contact scanning laser vibrometer successfully, the data was collected for the SuRE and PbPPM methods. Locational force, loose bolts and material loss could be easily detected by comparing the spectral characteristics of the arriving waves. On-line methods used fast computational methods for estimating the spectrum and detecting the changing operational conditions from sum of the squares of the variations. Neural networks classified the spectrums when the desktop -- DSP combination was used. The results demonstrated the feasibility of the SuRE and PbPPM methods.

Fusional vergence detected by prism bar and synoptophore in chinese childhood intermittent exotropia.

PubMed

Fu, Tao; Wang, Jing; Levin, Moran; Su, Qing; Li, Dongguo; Li, Junfa

2015-01-01

Purpose. To measure the changes in fusional vergence in Chinese children with intermittent exotropia (IXT) and the association with the control of IXT. Methods. Ninety-two patients with IXT (8-15 years old) were compared with 86 controls. Exodeviation control was evaluated using the Revised Newcastle Control Score. Angle of deviation was measured using prism and alternate cover testing at distance and near. Fusional vergence was measured using prism bar and synoptophore. This study was registered with ChiCTR-RCC-13003920. Results. Using prism bar, convergence break points were lower whereas divergence break points were higher in children with IXT at distance (P < 0.001) and near (P < 0.001) compared with controls. There was no significant difference in mean divergence amplitudes between the two groups when testing using a synoptophore (P = 0.53). In children with IXT, the distance between recovery point and break point in both convergence (distance: P = 0.02; near: P = 0.02) and divergence (distance: P < 0.001; near: P < 0.001) was larger than controls when detected by prism bar and synoptophore (convergence: P = 0.005; divergence: P = 0.006). Conclusions. Children with IXT have reduced convergence amplitudes as detected by both prism bar and synoptophore.

Change of point mutations in Helicobacter pylori rRNA associated with clarithromycin resistance in Italy.

PubMed

De Francesco, Vincenzo; Zullo, Angelo; Giorgio, Floriana; Saracino, Ilaria; Zaccaro, Cristina; Hassan, Cesare; Ierardi, Enzo; Di Leo, Alfredo; Fiorini, Giulia; Castelli, Valentina; Lo Re, Giovanna; Vaira, Dino

2014-03-01

Primary clarithromycin resistance is the main factor affecting the efficacy of Helicobacter pylori therapy. This study aimed: (i) to assess the concordance between phenotypic (culture) and genotypic (real-time PCR) tests in resistant strains; (ii) to search, in the case of disagreement between the methods, for point mutations other than those reported as the most frequent in Europe; and (iii) to compare the MICs associated with the single point mutations. In order to perform real-time PCR, we retrieved biopsies from patients in whom H. pylori infection was successful diagnosed by bacterial culture and clarithromycin resistance was assessed using the Etest. Only patients who had never been previously treated, and with H. pylori strains that were either resistant exclusively to clarithromycin or without any resistance, were included. Biopsies from 82 infected patients were analysed, including 42 strains that were clarithromycin resistant and 40 that were clarithromycin susceptible on culture. On genotypic analysis, at least one of the three most frequently reported point mutations (A2142C, A2142G and A2143G) was detected in only 23 cases (54.8%), with a concordance between the two methods of 0.67. Novel point mutations (A2115G, G2141A and A2144T) were detected in a further 14 out of 19 discordant cases, increasing the resistance detection rate of PCR to 88% (P<0.001; odds ratio 6.1, 95% confidence interval 2-18.6) and the concordance to 0.81. No significant differences in MIC values among different point mutations were observed. This study suggests that: (i) the prevalence of the usually reported point mutations may be decreasing, with a concomitant emergence of new mutations; (ii) PCR-based methods should search for at least six point mutations to achieve good accuracy in detecting clarithromycin resistance; and (iii) none of the tested point mutations is associated with significantly higher MIC values than the others.

Detection of a sudden change of the field time series based on the Lorenz system

PubMed Central

Li, Fang; Shen, BingLu; Yan, PengCheng; Song, Jian; Ma, DeShan

2017-01-01

We conducted an exploratory study of the detection of a sudden change of the field time series based on the numerical solution of the Lorenz system. First, the time when the Lorenz path jumped between the regions on the left and right of the equilibrium point of the Lorenz system was quantitatively marked and the sudden change time of the Lorenz system was obtained. Second, the numerical solution of the Lorenz system was regarded as a vector; thus, this solution could be considered as a vector time series. We transformed the vector time series into a time series using the vector inner product, considering the geometric and topological features of the Lorenz system path. Third, the sudden change of the resulting time series was detected using the sliding t-test method. Comparing the test results with the quantitatively marked time indicated that the method could detect every sudden change of the Lorenz path, thus the method is effective. Finally, we used the method to detect the sudden change of the pressure field time series and temperature field time series, and obtained good results for both series, which indicates that the method can apply to high-dimension vector time series. Mathematically, there is no essential difference between the field time series and vector time series; thus, we provide a new method for the detection of the sudden change of the field time series. PMID:28141832

On the sensitivity of TG-119 and IROC credentialing to TPS commissioning errors.

PubMed

McVicker, Drew; Yin, Fang-Fang; Adamson, Justus D

2016-01-08

We investigate the sensitivity of IMRT commissioning using the TG-119 C-shape phantom and credentialing with the IROC head and neck phantom to treatment planning system commissioning errors. We introduced errors into the various aspects of the commissioning process for a 6X photon energy modeled using the analytical anisotropic algorithm within a commercial treatment planning system. Errors were implemented into the various components of the dose calculation algorithm including primary photons, secondary photons, electron contamination, and MLC parameters. For each error we evaluated the probability that it could be committed unknowingly during the dose algorithm commissioning stage, and the probability of it being identified during the verification stage. The clinical impact of each commissioning error was evaluated using representative IMRT plans including low and intermediate risk prostate, head and neck, mesothelioma, and scalp; the sensitivity of the TG-119 and IROC phantoms was evaluated by comparing dosimetric changes to the dose planes where film measurements occur and change in point doses where dosimeter measurements occur. No commissioning errors were found to have both a low probability of detection and high clinical severity. When errors do occur, the IROC credentialing and TG 119 commissioning criteria are generally effective at detecting them; however, for the IROC phantom, OAR point-dose measurements are the most sensitive despite being currently excluded from IROC analysis. Point-dose measurements with an absolute dose constraint were the most effective at detecting errors, while film analysis using a gamma comparison and the IROC film distance to agreement criteria were less effective at detecting the specific commissioning errors implemented here.

Animals as Mobile Biological Sensors for Forest Fire Detection.

PubMed

Sahin, Yasar Guneri

2007-12-04

This paper proposes a mobile biological sensor system that can assist in earlydetection of forest fires one of the most dreaded natural disasters on the earth. The main ideapresented in this paper is to utilize animals with sensors as Mobile Biological Sensors(MBS). The devices used in this system are animals which are native animals living inforests, sensors (thermo and radiation sensors with GPS features) that measure thetemperature and transmit the location of the MBS, access points for wireless communicationand a central computer system which classifies of animal actions. The system offers twodifferent methods, firstly: access points continuously receive data about animals' locationusing GPS at certain time intervals and the gathered data is then classified and checked tosee if there is a sudden movement (panic) of the animal groups: this method is called animalbehavior classification (ABC). The second method can be defined as thermal detection(TD): the access points get the temperature values from the MBS devices and send the datato a central computer to check for instant changes in the temperatures. This system may beused for many purposes other than fire detection, namely animal tracking, poachingprevention and detecting instantaneous animal death.

Detection of single-nucleotide polymorphisms using gold nanoparticles and single-strand-specific nucleases.

PubMed

Chen, Yen-Ting; Hsu, Chiao-Ling; Hou, Shao-Yi

2008-04-15

The current study reports an assay approach that can detect single-nucleotide polymorphisms (SNPs) and identify the position of the point mutation through a single-strand-specific nuclease reaction and a gold nanoparticle assembly. The assay can be implemented via three steps: a single-strand-specific nuclease reaction that allows the enzyme to truncate the mutant DNA; a purification step that uses capture probe-gold nanoparticles and centrifugation; and a hybridization reaction that induces detector probe-gold nanoparticles, capture probe-gold nanoparticles, and the target DNA to form large DNA-linked three-dimensional aggregates of gold nanoparticles. At high temperature (63 degrees C in the current case), the purple color of the perfect match solution would not change to red, whereas a mismatched solution becomes red as the assembled gold nanoparticles separate. Using melting analysis, the position of the point mutation could be identified. This assay provides a convenient colorimetric detection that enables point mutation identification without the need for expensive mass spectrometry. To our knowledge, this is the first report concerning SNP detection based on a single-strand-specific nuclease reaction and a gold nanoparticle assembly.

Relationships between Participants' International Prostate Symptom Score and BPH Impact Index Changes and Global Ratings of Change in a Trial of Phytotherapy for Men with Lower Urinary Tract Symptoms

PubMed Central

Barry, Michael J.; Cantor, Alan; Roehrborn, Claus G.

2014-01-01

Purpose To relate changes in AUA Symptom Index (AUASI) scores with bother measures and global ratings of change among men with lower urinary tract symptoms enrolled in a trial of saw palmetto. Materials and Methods To be eligible, men were ≥45 years old, had ajpeak uroflow ≥4 ml/sec, and an AUASI score ≥ 8 and ≤ 24. Participants self-administered the AUASI, IPSS quality of life item (IPSS QoL), BPH Impact Index (BII) and two global change questions at baseline and 24, 48, and 72 weeks. Results Among 357 participants, global ratings of “a little better” were associated with mean decreases in AUASI scores from 2.8 to 4.1 points, across three time points. The analogous range for mean decreases in BII scores was 1.0 to 1.7 points, and for the IPSS QoL item 0.5 to 0.8 points. At 72 weeks, for the first global change question, each change measure could discriminate between participants rating themselves at least a little better versus unchanged or worse 70-72% of the time. A multivariable model increased discrimination to 77%. For the second global change question, each change measure correctly discriminated ratings of at least a little better versus unchanged or worse 69-74% of the time, and a multivariable model increased discrimination to 79%. Conclusions Changes in AUASI scores could discriminate between participants rating themselves at least a little better versus unchanged or worse. Our findings support the practice of powering studies to detect group mean differences in AUASI scores of at least 3 points. PMID:23017510

An Unconditional Test for Change Point Detection in Binary Sequences with Applications to Clinical Registries.

PubMed

Ellenberger, David; Friede, Tim

2016-08-05

Methods for change point (also sometimes referred to as threshold or breakpoint) detection in binary sequences are not new and were introduced as early as 1955. Much of the research in this area has focussed on asymptotic and exact conditional methods. Here we develop an exact unconditional test. An unconditional exact test is developed which assumes the total number of events as random instead of conditioning on the number of observed events. The new test is shown to be uniformly more powerful than Worsley's exact conditional test and means for its efficient numerical calculations are given. Adaptions of methods by Berger and Boos are made to deal with the issue that the unknown event probability imposes a nuisance parameter. The methods are compared in a Monte Carlo simulation study and applied to a cohort of patients undergoing traumatic orthopaedic surgery involving external fixators where a change in pin site infections is investigated. The unconditional test controls the type I error rate at the nominal level and is uniformly more powerful than (or to be more precise uniformly at least as powerful as) Worsley's exact conditional test which is very conservative for small sample sizes. In the application a beneficial effect associated with the introduction of a new treatment procedure for pin site care could be revealed. We consider the new test an effective and easy to use exact test which is recommended in small sample size change point problems in binary sequences.

Graphical methods for the sensitivity analysis in discriminant analysis

DOE PAGES

Kim, Youngil; Anderson-Cook, Christine M.; Dae-Heung, Jang

2015-09-30

Similar to regression, many measures to detect influential data points in discriminant analysis have been developed. Many follow similar principles as the diagnostic measures used in linear regression in the context of discriminant analysis. Here we focus on the impact on the predicted classification posterior probability when a data point is omitted. The new method is intuitive and easily interpretative compared to existing methods. We also propose a graphical display to show the individual movement of the posterior probability of other data points when a specific data point is omitted. This enables the summaries to capture the overall pattern ofmore » the change.« less

Algorithms and data structures for automated change detection and classification of sidescan sonar imagery

NASA Astrophysics Data System (ADS)

Gendron, Marlin Lee

During Mine Warfare (MIW) operations, MIW analysts perform change detection by visually comparing historical sidescan sonar imagery (SSI) collected by a sidescan sonar with recently collected SSI in an attempt to identify objects (which might be explosive mines) placed at sea since the last time the area was surveyed. This dissertation presents a data structure and three algorithms, developed by the author, that are part of an automated change detection and classification (ACDC) system. MIW analysts at the Naval Oceanographic Office, to reduce the amount of time to perform change detection, are currently using ACDC. The dissertation introductory chapter gives background information on change detection, ACDC, and describes how SSI is produced from raw sonar data. Chapter 2 presents the author's Geospatial Bitmap (GB) data structure, which is capable of storing information geographically and is utilized by the three algorithms. This chapter shows that a GB data structure used in a polygon-smoothing algorithm ran between 1.3--48.4x faster than a sparse matrix data structure. Chapter 3 describes the GB clustering algorithm, which is the author's repeatable, order-independent method for clustering. Results from tests performed in this chapter show that the time to cluster a set of points is not affected by the distribution or the order of the points. In Chapter 4, the author presents his real-time computer-aided detection (CAD) algorithm that automatically detects mine-like objects on the seafloor in SSI. The author ran his GB-based CAD algorithm on real SSI data, and results of these tests indicate that his real-time CAD algorithm performs comparably to or better than other non-real-time CAD algorithms. The author presents his computer-aided search (CAS) algorithm in Chapter 5. CAS helps MIW analysts locate mine-like features that are geospatially close to previously detected features. A comparison between the CAS and a great circle distance algorithm shows that the CAS performs geospatial searching 1.75x faster on large data sets. Finally, the concluding chapter of this dissertation gives important details on how the completed ACDC system will function, and discusses the author's future research to develop additional algorithms and data structures for ACDC.

Detection of brown-rot antigens in southern pine

Treesearch

Carol A. Clausen

1996-01-01

Brown-rot fungal antigens were detected by particle capture immunoassay(PCI) in southern pine 2 X 4’s beyond visible or culturable hyphal growth. Further analysis of test samples revealed changes along the 2 X 4’s that could be grouped into zones. Zone 1, the point of inoculation through 6 cm, showed low pH, measurable oxalic acid, high moisture, and high protein. Zone...

Hockey Concussion Education Project, Part 1: Susceptibility-weighted imaging study in male and female ice hockey players over a single season

PubMed Central

Helmer, Karl G.; Pasternak, Ofer; Fredman, Eli; Preciado, Ronny I.; Koerte, Inga K.; Sasaki, Takeshi; Mayinger, Michael; Johnson, Andrew M.; Holmes, Jeffrey D.; Forwell, Lorie; Skopelja, Elaine N.; Shenton, Martha E.; Echlin, Paul S.

2015-01-01

Object Concussion, or mild traumatic brain injury (mTBI), is a commonly occurring sports-related injury, especially in contact sports such as hockey. Cerebral microbleeds (CMBs), which are small, hypointense lesions on T2*-weighted images, can result from TBI. The authors use susceptibility-weighted imaging (SWI) to automatically detect small hypointensities that may be subtle signs of chronic and acute damage due to both subconcussive and concussive injury. The goal was to investigate how the burden of these hypointensities change over time, over a playing season, and postconcussion, compared with subjects who did not suffer a medically observed and diagnosed concussion. Methods Images were obtained in 45 university-level adult male and female ice hockey players before and after a single Canadian Interuniversity Sports season. In addition, 11 subjects (5 men and 6 women) underwent imaging at 72 hours, 2 weeks, and 2 months after concussion. To identify subtle changes in brain tissue and potential CMBs, nonvessel clusters of hypointensities on SWI were automatically identified and a hypointensity burden index was calculated for all subjects at the beginning of the season (BOS) and the end of the season (EOS), in addition to postconcussion time points (where applicable). Results A statistically significant increase in the hypointensity burden, relative to the BOS, was observed for male subjects at the 2-week postconcussion time point. A smaller, nonsignificant rise in the burden for all female subjects was also observed within the same time period. The difference in hypointensity burden was also statistically significant for men with concussions between the 2-week time point and the BOS. There were no significant changes in burden for nonconcussed subjects of either sex between the BOS and EOS time points. However, there was a statistically significant difference in the burden between male and female subjects in the nonconcussed group at both the BOS and EOS time points, with males having a higher burden. Conclusions This method extends the utility of SWI from the enhancement and detection of larger (> 5 mm) CMBs that are often observed in more severe TBI, to concussion in which visual detection of injury is difficult. The hypointensity burden metric proposed here shows statistically significant changes over time in the male subjects. A smaller, nonsignificant increase in the burden metric was observed in the female subjects. PMID:24490839

In vivo detection of hemoglobin oxygen saturation and carboxyhemoglobin saturation with multiwavelength photoacoustic microscopy.

PubMed

Chen, Zhongjiang; Yang, Sihua; Xing, Da

2012-08-15

A method for noninvasively detecting hemoglobin oxygen saturation (SO2) and carboxyhemoglobin saturation (SCO) in subcutaneous microvasculature with multiwavelength photoacoustic microscopy is presented. Blood samples mixed with different concentrations of carboxyhemoglobin were used to test the feasibility and accuracy of photoacoustic microscopy compared with the blood-gas analyzer. Moreover, fixed-point detection of SO2 and SCO in mouse ear was obtained, and the changes from normoxia to carbon monoxide hypoxia were dynamically monitored in vivo. Experimental results demonstrate that multiwavelength photoacoustic microscopy can detect SO2 and SCO, which has future potential clinical applications.

Image Mosaic Method Based on SIFT Features of Line Segment

PubMed Central

Zhu, Jun; Ren, Mingwu

2014-01-01

This paper proposes a novel image mosaic method based on SIFT (Scale Invariant Feature Transform) feature of line segment, aiming to resolve incident scaling, rotation, changes in lighting condition, and so on between two images in the panoramic image mosaic process. This method firstly uses Harris corner detection operator to detect key points. Secondly, it constructs directed line segments, describes them with SIFT feature, and matches those directed segments to acquire rough point matching. Finally, Ransac method is used to eliminate wrong pairs in order to accomplish image mosaic. The results from experiment based on four pairs of images show that our method has strong robustness for resolution, lighting, rotation, and scaling. PMID:24511326

Threshold-adaptive canny operator based on cross-zero points

NASA Astrophysics Data System (ADS)

Liu, Boqi; Zhang, Xiuhua; Hong, Hanyu

2018-03-01

Canny edge detection[1] is a technique to extract useful structural information from different vision objects and dramatically reduce the amount of data to be processed. It has been widely applied in various computer vision systems. There are two thresholds have to be settled before the edge is segregated from background. Usually, by the experience of developers, two static values are set as the thresholds[2]. In this paper, a novel automatic thresholding method is proposed. The relation between the thresholds and Cross-zero Points is analyzed, and an interpolation function is deduced to determine the thresholds. Comprehensive experimental results demonstrate the effectiveness of proposed method and advantageous for stable edge detection at changing illumination.

Pole Photogrammetry with AN Action Camera for Fast and Accurate Surface Mapping

NASA Astrophysics Data System (ADS)

Gonçalves, J. A.; Moutinho, O. F.; Rodrigues, A. C.

2016-06-01

High resolution and high accuracy terrain mapping can provide height change detection for studies of erosion, subsidence or land slip. A UAV flying at a low altitude above the ground, with a compact camera, acquires images with resolution appropriate for these change detections. However, there may be situations where different approaches may be needed, either because higher resolution is required or the operation of a drone is not possible. Pole photogrammetry, where a camera is mounted on a pole, pointing to the ground, is an alternative. This paper describes a very simple system of this kind, created for topographic change detection, based on an action camera. These cameras have high quality and very flexible image capture. Although radial distortion is normally high, it can be treated in an auto-calibration process. The system is composed by a light aluminium pole, 4 meters long, with a 12 megapixel GoPro camera. Average ground sampling distance at the image centre is 2.3 mm. The user moves along a path, taking successive photos, with a time lapse of 0.5 or 1 second, and adjusting the speed in order to have an appropriate overlap, with enough redundancy for 3D coordinate extraction. Marked ground control points are surveyed with GNSS for precise georeferencing of the DSM and orthoimage that are created by structure from motion processing software. An average vertical accuracy of 1 cm could be achieved, which is enough for many applications, for example for soil erosion. The GNSS survey in RTK mode with permanent stations is now very fast (5 seconds per point), which results, together with the image collection, in a very fast field work. If an improved accuracy is needed, since image resolution is 1/4 cm, it can be achieved using a total station for the control point survey, although the field work time increases.

Human location estimation using thermopile array sensor

NASA Astrophysics Data System (ADS)

Parnin, S.; Rahman, M. M.

2017-11-01

Utilization of Thermopile sensor at an early stage of human detection is challenging as there are many things that produce thermal heat other than human such as electrical appliances and animals. Therefrom, an algorithm for early presence detection has been developed through the study of human body temperature behaviour with respect to the room temperature. The change in non-contact detected temperature of human varied according to body parts. In an indoor room, upper parts of human body change up to 3°C whereas lower part ranging from 0.58°C to 1.71°C. The average changes in temperature of human is used as a conditional set-point value in the program algorithm to detect human presence. The current position of human and its respective angle is gained when human is presence at certain pixels of Thermopile’s sensor array. Human position is estimated successfully as the developed sensory system is tested to the actuator of a stand fan.

Deformation analysis of a sinkhole in Thuringia using multi-temporal multi-view stereo 3D reconstruction data

NASA Astrophysics Data System (ADS)

Petschko, Helene; Goetz, Jason; Schmidt, Sven

2017-04-01

Sinkholes are a serious threat on life, personal property and infrastructure in large parts of Thuringia. Over 9000 sinkholes have been documented by the Geological Survey of Thuringia, which are caused by collapsing hollows which formed due to solution processes within the local bedrock material. However, little is known about surface processes and their dynamics at the flanks of the sinkhole once the sinkhole has shaped. These processes are of high interest as they might lead to dangerous situations at or within the vicinity of the sinkhole. Our objective was the analysis of these deformations over time in 3D by applying terrestrial photogrammetry with a simple DSLR camera. Within this study, we performed an analysis of deformations within a sinkhole close to Bad Frankenhausen (Thuringia) using terrestrial photogrammetry and multi-view stereo 3D reconstruction to obtain a 3D point cloud describing the morphology of the sinkhole. This was performed for multiple data collection campaigns over a 6-month period. The photos of the sinkhole were taken with a Nikon D3000 SLR Camera. For the comparison of the point clouds the Multiscale Model to Model Comparison (M3C2) plugin of the software CloudCompare was used. It allows to apply advanced methods of point cloud difference calculation which considers the co-registration error between two point clouds for assessing the significance of the calculated difference (given in meters). Three Styrofoam cuboids of known dimensions (16 cm wide/29 cm high/11.5 cm deep) were placed within the sinkhole to test the accuracy of the point cloud difference calculation. The multi-view stereo 3D reconstruction was performed with Agisoft Photoscan. Preliminary analysis indicates that about 26% of the sinkhole showed changes exceeding the co-registration error of the point clouds. The areas of change can mainly be detected on the flanks of the sinkhole and on an earth pillar that formed in the center of the sinkhole. These changes describe toppling (positive change of a few centimeters at the earth pillar) and a few erosion processes along the flanks (negative change of a few centimeters) compared to the first date of data acquisition. Additionally, the Styrofoam cuboids have successfully been detected with an observed depth change of 10 cm. However, the limitations of this approach related to the co-registration of the point clouds and data acquisition (windy conditions) have to be analyzed in more detail.

Detection of degenerative change in lateral projection cervical spine x-ray images

NASA Astrophysics Data System (ADS)

Jebri, Beyrem; Phillips, Michael; Knapp, Karen; Appelboam, Andy; Reuben, Adam; Slabaugh, Greg

2015-03-01

Degenerative changes to the cervical spine can be accompanied by neck pain, which can result from narrowing of the intervertebral disc space and growth of osteophytes. In a lateral x-ray image of the cervical spine, degenerative changes are characterized by vertebral bodies that have indistinct boundaries and limited spacing between vertebrae. In this paper, we present a machine learning approach to detect and localize degenerative changes in lateral x-ray images of the cervical spine. Starting from a user-supplied set of points in the center of each vertebral body, we fit a central spline, from which a region of interest is extracted and image features are computed. A Random Forest classifier labels regions as degenerative change or normal. Leave-one-out cross-validation studies performed on a dataset of 103 patients demonstrates performance of above 95% accuracy.

A Fast Framework for Abrupt Change Detection Based on Binary Search Trees and Kolmogorov Statistic

PubMed Central

Qi, Jin-Peng; Qi, Jie; Zhang, Qing

2016-01-01

Change-Point (CP) detection has attracted considerable attention in the fields of data mining and statistics; it is very meaningful to discuss how to quickly and efficiently detect abrupt change from large-scale bioelectric signals. Currently, most of the existing methods, like Kolmogorov-Smirnov (KS) statistic and so forth, are time-consuming, especially for large-scale datasets. In this paper, we propose a fast framework for abrupt change detection based on binary search trees (BSTs) and a modified KS statistic, named BSTKS (binary search trees and Kolmogorov statistic). In this method, first, two binary search trees, termed as BSTcA and BSTcD, are constructed by multilevel Haar Wavelet Transform (HWT); second, three search criteria are introduced in terms of the statistic and variance fluctuations in the diagnosed time series; last, an optimal search path is detected from the root to leaf nodes of two BSTs. The studies on both the synthetic time series samples and the real electroencephalograph (EEG) recordings indicate that the proposed BSTKS can detect abrupt change more quickly and efficiently than KS, t-statistic (t), and Singular-Spectrum Analyses (SSA) methods, with the shortest computation time, the highest hit rate, the smallest error, and the highest accuracy out of four methods. This study suggests that the proposed BSTKS is very helpful for useful information inspection on all kinds of bioelectric time series signals. PMID:27413364

A Fast Framework for Abrupt Change Detection Based on Binary Search Trees and Kolmogorov Statistic.

PubMed

Qi, Jin-Peng; Qi, Jie; Zhang, Qing

2016-01-01

Change-Point (CP) detection has attracted considerable attention in the fields of data mining and statistics; it is very meaningful to discuss how to quickly and efficiently detect abrupt change from large-scale bioelectric signals. Currently, most of the existing methods, like Kolmogorov-Smirnov (KS) statistic and so forth, are time-consuming, especially for large-scale datasets. In this paper, we propose a fast framework for abrupt change detection based on binary search trees (BSTs) and a modified KS statistic, named BSTKS (binary search trees and Kolmogorov statistic). In this method, first, two binary search trees, termed as BSTcA and BSTcD, are constructed by multilevel Haar Wavelet Transform (HWT); second, three search criteria are introduced in terms of the statistic and variance fluctuations in the diagnosed time series; last, an optimal search path is detected from the root to leaf nodes of two BSTs. The studies on both the synthetic time series samples and the real electroencephalograph (EEG) recordings indicate that the proposed BSTKS can detect abrupt change more quickly and efficiently than KS, t-statistic (t), and Singular-Spectrum Analyses (SSA) methods, with the shortest computation time, the highest hit rate, the smallest error, and the highest accuracy out of four methods. This study suggests that the proposed BSTKS is very helpful for useful information inspection on all kinds of bioelectric time series signals.

Gold Nanoparticle-Based Facile Detection of Human Serum Albumin and Its Application as an INHIBIT Logic Gate.

PubMed

Huang, Zhenzhen; Wang, Haonan; Yang, Wensheng

2015-05-06

In this work, a facile colorimetric method is developed for quantitative detection of human serum albumin (HSA) based on the antiaggregation effect of gold nanoparticles (Au NPs) in the presence of HSA. The citrate-capped Au NPs undergo a color change from red to blue when melamine is added as a cross-linker to induce the aggregation of the NPs. Such an aggregation is efficiently suppressed upon the adsorption of HSA on the particle surface. This method provides the advantages of simplicity and cost-efficiency for quantitative detection of HSA with a detection limit of ∼1.4 nM by monitoring the colorimetric changes of the Au NPs with UV-vis spectroscopy. In addition, this approach shows good selectivity for HSA over various amino acids, peptides, and proteins and is qualified for detection of HSA in a biological sample. Such an antiaggregation effect can be further extended to fabricate an INHIBIT logic gate by using HSA and melamine as inputs and the color changes of Au NPs as outputs, which may have application potentials in point-of-care medical diagnosis.

Pattern-histogram-based temporal change detection using personal chest radiographs

NASA Astrophysics Data System (ADS)

Ugurlu, Yucel; Obi, Takashi; Hasegawa, Akira; Yamaguchi, Masahiro; Ohyama, Nagaaki

1999-05-01

An accurate and reliable detection of temporal changes from a pair of images has considerable interest in the medical science. Traditional registration and subtraction techniques can be applied to extract temporal differences when,the object is rigid or corresponding points are obvious. However, in radiological imaging, loss of the depth information, the elasticity of object, the absence of clearly defined landmarks and three-dimensional positioning differences constraint the performance of conventional registration techniques. In this paper, we propose a new method in order to detect interval changes accurately without using an image registration technique. The method is based on construction of so-called pattern histogram and comparison procedure. The pattern histogram is a graphic representation of the frequency counts of all allowable patterns in the multi-dimensional pattern vector space. K-means algorithm is employed to partition pattern vector space successively. Any differences in the pattern histograms imply that different patterns are involved in the scenes. In our experiment, a pair of chest radiographs of pneumoconiosis is employed and the changing histogram bins are visualized on both of the images. We found that the method can be used as an alternative way of temporal change detection, particularly when the precise image registration is not available.

Detection of retinal changes from illumination normalized fundus images using convolutional neural networks

NASA Astrophysics Data System (ADS)

Adal, Kedir M.; van Etten, Peter G.; Martinez, Jose P.; Rouwen, Kenneth; Vermeer, Koenraad A.; van Vliet, Lucas J.

2017-03-01

Automated detection and quantification of spatio-temporal retinal changes is an important step to objectively assess disease progression and treatment effects for dynamic retinal diseases such as diabetic retinopathy (DR). However, detecting retinal changes caused by early DR lesions such as microaneurysms and dot hemorrhages from longitudinal pairs of fundus images is challenging due to intra and inter-image illumination variation between fundus images. This paper explores a method for automated detection of retinal changes from illumination normalized fundus images using a deep convolutional neural network (CNN), and compares its performance with two other CNNs trained separately on color and green channel fundus images. Illumination variation was addressed by correcting for the variability in the luminosity and contrast estimated from a large scale retinal regions. The CNN models were trained and evaluated on image patches extracted from a registered fundus image set collected from 51 diabetic eyes that were screened at two different time-points. The results show that using normalized images yield better performance than color and green channel images, suggesting that illumination normalization greatly facilitates CNNs to quickly and correctly learn distinctive local image features of DR related retinal changes.

Is the Oswestry Disability Index a valid measure of response to sacroiliac joint treatment?

PubMed

Copay, Anne G; Cher, Daniel J

2016-02-01

Disease-specific measures of the impact of sacroiliac (SI) joint pain on back/pelvis function are not available. The Oswestry Disability Index (ODI) is a validated functional measure for lower back pain, but its responsiveness to SI joint treatment has yet to be established. We sought to assess the validity of ODI to capture disability caused by SI joint pain and the minimum clinically important difference (MCID) after SI joint treatment. Patients (n = 155) participating in a prospective clinical trial of minimally invasive SI joint fusion underwent baseline and follow-up assessments using ODI, visual analog scale (VAS) pain assessment, Short Form 36 (SF-36), EuroQoL-5D, and questions (at follow-up only) regarding satisfaction with the SI joint fusion and whether the patient would have the fusion surgery again. All outcomes were compared from baseline to 12 months postsurgery. The health transition item of the SF-36 and the satisfaction scale were used as external anchors to calculate MCID. MCID was estimated for ODI using four calculation methods: (1) minimum detectable change, (2) average ODI change of patients' subsets, (3) change difference between patients' subsets, and (4) receiver operating characteristic (ROC) curve. After SI fusion, patients improved significantly (p < .0001) on all measures: SI joint pain (48.8 points), ODI (23.8 points), EQ-5D (0.29 points), EQ-5D VAS (11.7 points), PCS (8.9 points), and MCS (9.2 points). The improvement in ODI was significantly correlated (p < .0001) with SI joint pain improvement (r = .48) and with the two external anchors: SF-36 health transition item (r = .49) and satisfaction level (r = .34). The MCID values calculated for ODI using the various methods ranged from 3.5 to 19.5 points. The ODI minimum detectable change was 15.5 with the health transition item as the anchor and 13.5 with the satisfaction scale as the anchor. ODI is a valid measure of change in SI joint health. Hence, researchers and clinicians may rely on ODI scores to measure disability caused by SI pain. We estimated the MCID for ODI to be 13-15 points, which falls within the range of that previously reported for lumbar back pain and indicates that an improvement in disability should be at least 15 % to be beyond random variation.

Automatic detection of slight parameter changes associated to complex biomedical signals using multiresolution q-entropy1.

PubMed

Torres, M E; Añino, M M; Schlotthauer, G

2003-12-01

It is well known that, from a dynamical point of view, sudden variations in physiological parameters which govern certain diseases can cause qualitative changes in the dynamics of the corresponding physiological process. The purpose of this paper is to introduce a technique that allows the automated temporal localization of slight changes in a parameter of the law that governs the nonlinear dynamics of a given signal. This tool takes, from the multiresolution entropies, the ability to show these changes as statistical variations at each scale. These variations are held in the corresponding principal component. Appropriately combining these techniques with a statistical changes detector, a complexity change detection algorithm is obtained. The relevance of the approach, together with its robustness in the presence of moderate noise, is discussed in numerical simulations and the automatic detector is applied to real and simulated biological signals.

Detection of Subtle Cognitive Changes after mTBI Using a Novel Tablet-Based Task.

PubMed

Fischer, Tara D; Red, Stuart D; Chuang, Alice Z; Jones, Elizabeth B; McCarthy, James J; Patel, Saumil S; Sereno, Anne B

2016-07-01

This study examined the potential for novel tablet-based tasks, modeled after eye tracking techniques, to detect subtle sensorimotor and cognitive deficits after mild traumatic brain injury (mTBI). Specifically, we examined whether performance on these tablet-based tasks (Pro-point and Anti-point) was able to correctly categorize concussed versus non-concussed participants, compared with performance on other standardized tests for concussion. Patients admitted to the emergency department with mTBI were tested on the Pro-point and Anti-point tasks, a current standard cognitive screening test (i.e., the Standard Assessment of Concussion [SAC]), and another eye movement-based tablet test, the King-Devick(®) (KD). Within hours after injury, mTBI patients showed significant slowing in response times, compared with both orthopedic and age-matched control groups, in the Pro-point task, demonstrating deficits in sensorimotor function. Mild TBI patients also showed significant slowing, compared with both control groups, on the Anti-point task, even when controlling for sensorimotor slowing, indicating deficits in cognitive function. Performance on the SAC test revealed similar deficits of cognitive function in the mTBI group, compared with the age-matched control group; however, the KD test showed no evidence of cognitive slowing in mTBI patients, compared with either control group. Further, measuring the sensitivity and specificity of these tasks to accurately predict mTBI with receiver operating characteristic analysis indicated that the Anti-point and Pro-point tasks reached excellent levels of accuracy and fared better than current standardized tools for assessment of concussion. Our findings suggest that these rapid tablet-based tasks are able to reliably detect and measure functional impairment in cognitive and sensorimotor control within hours after mTBI. These tasks may provide a more sensitive diagnostic measure for functional deficits that could prove key to earlier detection of concussion, evaluation of interventions, or even prediction of persistent symptoms.

Detection of Subtle Cognitive Changes after mTBI Using a Novel Tablet-Based Task

PubMed Central

Red, Stuart D.; Chuang, Alice Z.; Jones, Elizabeth B.; McCarthy, James J.; Patel, Saumil S.; Sereno, Anne B.

2016-01-01

Abstract This study examined the potential for novel tablet-based tasks, modeled after eye tracking techniques, to detect subtle sensorimotor and cognitive deficits after mild traumatic brain injury (mTBI). Specifically, we examined whether performance on these tablet-based tasks (Pro-point and Anti-point) was able to correctly categorize concussed versus non-concussed participants, compared with performance on other standardized tests for concussion. Patients admitted to the emergency department with mTBI were tested on the Pro-point and Anti-point tasks, a current standard cognitive screening test (i.e., the Standard Assessment of Concussion [SAC]), and another eye movement–based tablet test, the King-Devick® (KD). Within hours after injury, mTBI patients showed significant slowing in response times, compared with both orthopedic and age-matched control groups, in the Pro-point task, demonstrating deficits in sensorimotor function. Mild TBI patients also showed significant slowing, compared with both control groups, on the Anti-point task, even when controlling for sensorimotor slowing, indicating deficits in cognitive function. Performance on the SAC test revealed similar deficits of cognitive function in the mTBI group, compared with the age-matched control group; however, the KD test showed no evidence of cognitive slowing in mTBI patients, compared with either control group. Further, measuring the sensitivity and specificity of these tasks to accurately predict mTBI with receiver operating characteristic analysis indicated that the Anti-point and Pro-point tasks reached excellent levels of accuracy and fared better than current standardized tools for assessment of concussion. Our findings suggest that these rapid tablet-based tasks are able to reliably detect and measure functional impairment in cognitive and sensorimotor control within hours after mTBI. These tasks may provide a more sensitive diagnostic measure for functional deficits that could prove key to earlier detection of concussion, evaluation of interventions, or even prediction of persistent symptoms. PMID:26398492

Dynamic connectivity regression: Determining state-related changes in brain connectivity

PubMed Central

Cribben, Ivor; Haraldsdottir, Ragnheidur; Atlas, Lauren Y.; Wager, Tor D.; Lindquist, Martin A.

2014-01-01

Most statistical analyses of fMRI data assume that the nature, timing and duration of the psychological processes being studied are known. However, often it is hard to specify this information a priori. In this work we introduce a data-driven technique for partitioning the experimental time course into distinct temporal intervals with different multivariate functional connectivity patterns between a set of regions of interest (ROIs). The technique, called Dynamic Connectivity Regression (DCR), detects temporal change points in functional connectivity and estimates a graph, or set of relationships between ROIs, for data in the temporal partition that falls between pairs of change points. Hence, DCR allows for estimation of both the time of change in connectivity and the connectivity graph for each partition, without requiring prior knowledge of the nature of the experimental design. Permutation and bootstrapping methods are used to perform inference on the change points. The method is applied to various simulated data sets as well as to an fMRI data set from a study (N=26) of a state anxiety induction using a socially evaluative threat challenge. The results illustrate the method’s ability to observe how the networks between different brain regions changed with subjects’ emotional state. PMID:22484408

Validity, responsiveness, minimal detectable change, and minimal clinically important change of the Pediatric Motor Activity Log in children with cerebral palsy.

PubMed

Lin, Keh-chung; Chen, Hui-fang; Chen, Chia-ling; Wang, Tien-ni; Wu, Ching-yi; Hsieh, Yu-wei; Wu, Li-ling

2012-01-01

This study examined criterion-related validity and clinimetric properties of the Pediatric Motor Activity Log (PMAL) in children with cerebral palsy. Study participants were 41 children (age range: 28-113 months) and their parents. Criterion-related validity was evaluated by the associations between the PMAL and criterion measures at baseline and posttreatment, including the self-care, mobility, and cognition subscale, the total performance of the Functional Independence Measure in children (WeeFIM), and the grasping and visual-motor integration of the Peabody Developmental Motor Scales. Pearson correlation coefficients were calculated. Responsiveness was examined using the paired t test and the standardized response mean, the minimal detectable change was captured at the 90% confidence level, and the minimal clinically important change was estimated using anchor-based and distribution-based approaches. The PMAL-QOM showed fair concurrent validity at pretreatment and posttreatment and predictive validity, whereas the PMAL-AOU had fair concurrent validity at posttreatment only. The PMAL-AOU and PMAL-QOM were both markedly responsive to change after treatment. Improvement of at least 0.67 points on the PMAL-AOU and 0.66 points on the PMAL-QOM can be considered as a true change, not measurement error. A mean change has to exceed the range of 0.39-0.94 on the PMAL-AOU and the range of 0.38-0.74 on the PMAL-QOM to be regarded as clinically important change. Copyright © 2011 Elsevier Ltd. All rights reserved.

Application of flat panel OLED display technology for the point-of-care detection of circulating cancer biomarkers

PubMed Central

Katchman, Benjamin A.; Smith, Joseph T.; Obahiagbon, Uwadiae; Kesiraju, Sailaja; Lee, Yong-Kyun; O’Brien, Barry; Kaftanoglu, Korhan; Blain Christen, Jennifer; Anderson, Karen S.

2016-01-01

Point-of-care molecular diagnostics can provide efficient and cost-effective medical care, and they have the potential to fundamentally change our approach to global health. However, most existing approaches are not scalable to include multiple biomarkers. As a solution, we have combined commercial flat panel OLED display technology with protein microarray technology to enable high-density fluorescent, programmable, multiplexed biorecognition in a compact and disposable configuration with clinical-level sensitivity. Our approach leverages advances in commercial display technology to reduce pre-functionalized biosensor substrate costs to pennies per cm2. Here, we demonstrate quantitative detection of IgG antibodies to multiple viral antigens in patient serum samples with detection limits for human IgG in the 10 pg/mL range. We also demonstrate multiplexed detection of antibodies to the HPV16 proteins E2, E6, and E7, which are circulating biomarkers for cervical as well as head and neck cancers. PMID:27374875

Application of flat panel OLED display technology for the point-of-care detection of circulating cancer biomarkers.

PubMed

Katchman, Benjamin A; Smith, Joseph T; Obahiagbon, Uwadiae; Kesiraju, Sailaja; Lee, Yong-Kyun; O'Brien, Barry; Kaftanoglu, Korhan; Blain Christen, Jennifer; Anderson, Karen S

2016-07-04

Point-of-care molecular diagnostics can provide efficient and cost-effective medical care, and they have the potential to fundamentally change our approach to global health. However, most existing approaches are not scalable to include multiple biomarkers. As a solution, we have combined commercial flat panel OLED display technology with protein microarray technology to enable high-density fluorescent, programmable, multiplexed biorecognition in a compact and disposable configuration with clinical-level sensitivity. Our approach leverages advances in commercial display technology to reduce pre-functionalized biosensor substrate costs to pennies per cm(2). Here, we demonstrate quantitative detection of IgG antibodies to multiple viral antigens in patient serum samples with detection limits for human IgG in the 10 pg/mL range. We also demonstrate multiplexed detection of antibodies to the HPV16 proteins E2, E6, and E7, which are circulating biomarkers for cervical as well as head and neck cancers.

An energy- and depth-dependent model for x-ray imaging

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

Gallas, Brandon D.; Boswell, Jonathan S.; Badano, Aldo

In this paper, we model an x-ray imaging system, paying special attention to the energy- and depth-dependent characteristics of the inputs and interactions: x rays are polychromatic, interaction depth and conversion to optical photons is energy-dependent, optical scattering and the collection efficiency depend on the depth of interaction. The model we construct is a random function of the point process that begins with the distribution of x rays incident on the phosphor and ends with optical photons being detected by the active area of detector pixels to form an image. We show how the point-process representation can be used tomore » calculate the characteristic statistics of the model. We then simulate a Gd{sub 2}O{sub 2}S:Tb phosphor, estimate its characteristic statistics, and proceed with a signal-detection experiment to investigate the impact of the pixel fill factor on detecting spherical calcifications (the signal). The two extremes possible from this experiment are that SNR{sup 2} does not change with fill factor or changes in proportion to fill factor. In our results, the impact of fill factor is between these extremes, and depends on the diameter of the signal.« less

Modeling spatially-varying landscape change points in species occurrence thresholds

USGS Publications Warehouse

Wagner, Tyler; Midway, Stephen R.

2014-01-01

Predicting species distributions at scales of regions to continents is often necessary, as large-scale phenomena influence the distributions of spatially structured populations. Land use and land cover are important large-scale drivers of species distributions, and landscapes are known to create species occurrence thresholds, where small changes in a landscape characteristic results in abrupt changes in occurrence. The value of the landscape characteristic at which this change occurs is referred to as a change point. We present a hierarchical Bayesian threshold model (HBTM) that allows for estimating spatially varying parameters, including change points. Our model also allows for modeling estimated parameters in an effort to understand large-scale drivers of variability in land use and land cover on species occurrence thresholds. We use range-wide detection/nondetection data for the eastern brook trout (Salvelinus fontinalis), a stream-dwelling salmonid, to illustrate our HBTM for estimating and modeling spatially varying threshold parameters in species occurrence. We parameterized the model for investigating thresholds in landscape predictor variables that are measured as proportions, and which are therefore restricted to values between 0 and 1. Our HBTM estimated spatially varying thresholds in brook trout occurrence for both the proportion agricultural and urban land uses. There was relatively little spatial variation in change point estimates, although there was spatial variability in the overall shape of the threshold response and associated uncertainty. In addition, regional mean stream water temperature was correlated to the change point parameters for the proportion of urban land use, with the change point value increasing with increasing mean stream water temperature. We present a framework for quantify macrosystem variability in spatially varying threshold model parameters in relation to important large-scale drivers such as land use and land cover. Although the model presented is a logistic HBTM, it can easily be extended to accommodate other statistical distributions for modeling species richness or abundance.

Characterizing Sorghum Panicles using 3D Point Clouds

NASA Astrophysics Data System (ADS)

Lonesome, M.; Popescu, S. C.; Horne, D. W.; Pugh, N. A.; Rooney, W.

2017-12-01

To address demands of population growth and impacts of global climate change, plant breeders must increase crop yield through genetic improvement. However, plant phenotyping, the characterization of a plant's physical attributes, remains a primary bottleneck in modern crop improvement programs. 3D point clouds generated from terrestrial laser scanning (TLS) and unmanned aerial systems (UAS) based structure from motion (SfM) are a promising data source to increase the efficiency of screening plant material in breeding programs. This study develops and evaluates methods for characterizing sorghum (Sorghum bicolor) panicles (heads) in field plots from both TLS and UAS-based SfM point clouds. The TLS point cloud over experimental sorghum field at Texas A&M farm in Burleston County TX were collected using a FARO Focus X330 3D laser scanner. SfM point cloud was generated from UAS imagery captured using a Phantom 3 Professional UAS at 10m altitude and 85% image overlap. The panicle detection method applies point cloud reflectance, height and point density attributes characteristic of sorghum panicles to detect them and estimate their dimensions (panicle length and width) through image classification and clustering procedures. We compare the derived panicle counts and panicle sizes with field-based and manually digitized measurements in selected plots and study the strengths and limitations of each data source for sorghum panicle characterization.

Video change detection for fixed wing UAVs

NASA Astrophysics Data System (ADS)

Bartelsen, Jan; Müller, Thomas; Ring, Jochen; Mück, Klaus; Brüstle, Stefan; Erdnüß, Bastian; Lutz, Bastian; Herbst, Theresa

2017-10-01

In this paper we proceed the work of Bartelsen et al.1 We present the draft of a process chain for an image based change detection which is designed for videos acquired by fixed wing unmanned aerial vehicles (UAVs). From our point of view, automatic video change detection for aerial images can be useful to recognize functional activities which are typically caused by the deployment of improvised explosive devices (IEDs), e.g. excavations, skid marks, footprints, left-behind tooling equipment, and marker stones. Furthermore, in case of natural disasters, like flooding, imminent danger can be recognized quickly. Due to the necessary flight range, we concentrate on fixed wing UAVs. Automatic change detection can be reduced to a comparatively simple photogrammetric problem when the perspective change between the "before" and "after" image sets is kept as small as possible. Therefore, the aerial image acquisition demands a mission planning with a clear purpose including flight path and sensor configuration. While the latter can be enabled simply by a fixed and meaningful adjustment of the camera, ensuring a small perspective change for "before" and "after" videos acquired by fixed wing UAVs is a challenging problem. Concerning this matter, we have performed tests with an advanced commercial off the shelf (COTS) system which comprises a differential GPS and autopilot system estimating the repetition accuracy of its trajectory. Although several similar approaches have been presented,23 as far as we are able to judge, the limits for this important issue are not estimated so far. Furthermore, we design a process chain to enable the practical utilization of video change detection. It consists of a front-end of a database to handle large amounts of video data, an image processing and change detection implementation, and the visualization of the results. We apply our process chain on the real video data acquired by the advanced COTS fixed wing UAV and synthetic data. For the image processing and change detection, we use the approach of Muller.4 Although it was developed for unmanned ground vehicles (UGVs), it enables a near real time video change detection for aerial videos. Concluding, we discuss the demands on sensor systems in the matter of change detection.

Image enhancement and color constancy for a vehicle-mounted change detection system

NASA Astrophysics Data System (ADS)

Tektonidis, Marco; Monnin, David

2016-10-01

Vehicle-mounted change detection systems allow to improve situational awareness on outdoor itineraries of inter- est. Since the visibility of acquired images is often affected by illumination effects (e.g., shadows) it is important to enhance local contrast. For the analysis and comparison of color images depicting the same scene at different time points it is required to compensate color and lightness inconsistencies caused by the different illumination conditions. We have developed an approach for image enhancement and color constancy based on the center/surround Retinex model and the Gray World hypothesis. The combination of the two methods using a color processing function improves color rendition, compared to both methods. The use of stacked integral images (SII) allows to efficiently perform local image processing. Our combined Retinex/Gray World approach has been successfully applied to image sequences acquired on outdoor itineraries at different time points and a comparison with previous Retinex-based approaches has been carried out.

Mapping the Critical Gestational Age at Birth that Alters Brain Development in Preterm-born Infants using Multi-Modal MRI

PubMed Central

Wu, Dan; Chang, Linda; Akazawa, Kentaro; Oishi, Kumiko; Skranes, Jon; Ernst, Thomas; Oishi, Kenichi

2017-01-01

Preterm birth adversely affects postnatal brain development. In order to investigate the critical gestational age at birth (GAB) that alters the developmental trajectory of gray and white matter structures in the brain, we investigated diffusion tensor and quantitative T2 mapping data in 43 term-born and 43 preterm-born infants. A novel multivariate linear model—the change point model, was applied to detect change points in fractional anisotropy, mean diffusivity, and T2 relaxation time. Change points captured the “critical” GAB value associated with a change in the linear relation between GAB and MRI measures. The analysis was performed in 126 regions across the whole brain using an atlas-based image quantification approach to investigate the spatial pattern of the critical GAB. Our results demonstrate that the critical GABs are region- and modality-specific, generally following a central-to-peripheral and bottom-to-top order of structural development. This study may offer unique insights into the postnatal neurological development associated with differential degrees of preterm birth. PMID:28111189

Mapping the critical gestational age at birth that alters brain development in preterm-born infants using multi-modal MRI.

PubMed

Wu, Dan; Chang, Linda; Akazawa, Kentaro; Oishi, Kumiko; Skranes, Jon; Ernst, Thomas; Oishi, Kenichi

2017-04-01

Preterm birth adversely affects postnatal brain development. In order to investigate the critical gestational age at birth (GAB) that alters the developmental trajectory of gray and white matter structures in the brain, we investigated diffusion tensor and quantitative T2 mapping data in 43 term-born and 43 preterm-born infants. A novel multivariate linear model-the change point model, was applied to detect change points in fractional anisotropy, mean diffusivity, and T2 relaxation time. Change points captured the "critical" GAB value associated with a change in the linear relation between GAB and MRI measures. The analysis was performed in 126 regions across the whole brain using an atlas-based image quantification approach to investigate the spatial pattern of the critical GAB. Our results demonstrate that the critical GABs are region- and modality-specific, generally following a central-to-peripheral and bottom-to-top order of structural development. This study may offer unique insights into the postnatal neurological development associated with differential degrees of preterm birth. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Augmented Citizen Science for Environmental Monitoring and Education

NASA Astrophysics Data System (ADS)

Albers, B.; de Lange, N.; Xu, S.

2017-09-01

Environmental monitoring and ecological studies detect and visualize changes of the environment over time. Some agencies are committed to document the development of conservation and status of geotopes and geosites, which is time-consuming and cost-intensive. Citizen science and crowd sourcing are modern approaches to collect data and at the same time to raise user awareness for environmental changes. Citizen scientists can take photographs of point of interests (POI) with smartphones and the PAN App, which is presented in this article. The user is navigated to a specific point and is then guided with an augmented reality approach to take a photo in a specific direction. The collected photographs are processed to time-lapse videos to visualize environmental changes. Users and experts in environmental agencies can use this data for long-term documentation.

Trend and change point analyses of annual precipitation in the Souss-Massa Region in Morocco during 1932-2010

NASA Astrophysics Data System (ADS)

Abahous, H.; Ronchail, J.; Sifeddine, A.; Kenny, L.; Bouchaou, L.

2017-11-01

In the context of an arid area such as Souss Massa Region, the availability of time series analysis of observed local data is vital to better characterize the regional rainfall configuration. In this paper, dataset of monthly precipitation collected from different local meteorological stations during 1932-2010, are quality controlled and analyzed to detect trend and change points. The temporal distribution of outliers shows an annual cycle and a decrease of their number since the 1980s. The results of the standard normal homogeneity test, penalized maximal t test, and Mann-Whitney-Pettit test show that 42% of the series are homogeneous. The analysis of annual precipitation in the region of Souss Massa during 1932-2010 shows wet conditions with a maximum between 1963 and 1965 followed by a decrease since 1973. The latter is identified as a statistically significant regional change point in Western High Atlas and Anti Atlas Mountains highlighting a decline in long-term average precipitation.

A point process approach to identifying and tracking transitions in neural spiking dynamics in the subthalamic nucleus of Parkinson's patients

NASA Astrophysics Data System (ADS)

Deng, Xinyi; Eskandar, Emad N.; Eden, Uri T.

2013-12-01

Understanding the role of rhythmic dynamics in normal and diseased brain function is an important area of research in neural electrophysiology. Identifying and tracking changes in rhythms associated with spike trains present an additional challenge, because standard approaches for continuous-valued neural recordings—such as local field potential, magnetoencephalography, and electroencephalography data—require assumptions that do not typically hold for point process data. Additionally, subtle changes in the history dependent structure of a spike train have been shown to lead to robust changes in rhythmic firing patterns. Here, we propose a point process modeling framework to characterize the rhythmic spiking dynamics in spike trains, test for statistically significant changes to those dynamics, and track the temporal evolution of such changes. We first construct a two-state point process model incorporating spiking history and develop a likelihood ratio test to detect changes in the firing structure. We then apply adaptive state-space filters and smoothers to track these changes through time. We illustrate our approach with a simulation study as well as with experimental data recorded in the subthalamic nucleus of Parkinson's patients performing an arm movement task. Our analyses show that during the arm movement task, neurons underwent a complex pattern of modulation of spiking intensity characterized initially by a release of inhibitory control at 20-40 ms after a spike, followed by a decrease in excitatory influence at 40-60 ms after a spike.

Novel Potential Interacting Partners of Fibronectin in Spontaneous Animal Model of Interstitial Cystitis

PubMed Central

Treutlein, Gudrun; Dorsch, Roswitha; Euler, Kerstin N.; Hauck, Stefanie M.; Amann, Barbara; Hartmann, Katrin; Deeg, Cornelia A.

2012-01-01

Feline idiopathic cystitis (FIC) is the only spontaneous animal model for human interstitial cystitis (IC), as both possess a distinctive chronical and relapsing character. Underlying pathomechanisms of both diseases are not clearly established yet. We recently detected increased urine fibronectin levels in FIC cases. The purpose of this study was to gain further insight into the pathogenesis by assessing interacting partners of fibronectin in urine of FIC affected cats. Several candidate proteins were identified via immunoprecipitation and mass spectrometry. Considerable changes in FIC conditions compared to physiological expression of co-purified proteins were detected by Western blot and immunohistochemistry. Compared to controls, complement C4a and thioredoxin were present in higher levels in urine of FIC patients whereas loss of signal intensity was detected in FIC affected tissue. Galectin-7 was exclusively detected in urine of FIC cats, pointing to an important role of this molecule in FIC pathogenesis. Moderate physiological signal intensity of galectin-7 in transitional epithelium shifted to distinct expression in transitional epithelium under pathophysiological conditions. I-FABP expression was reduced in urine and urinary bladder tissue of FIC cats. Additionally, transduction molecules of thioredoxin, NF-κB p65 and p38 MAPK, were examined. In FIC affected tissue, colocalization of thioredoxin and NF-κB p65 could be demonstrated compared to absent coexpression of thioredoxin and p38 MAPK. These considerable changes in expression level and pattern point to an important role for co-purified proteins of fibronectin and thioredoxin-regulated signal transduction pathways in FIC pathogenesis. These results could provide a promising starting point for novel therapeutic approaches in the future. PMID:23236492

Research on photodiode detector-based spatial transient light detection and processing system

NASA Astrophysics Data System (ADS)

Liu, Meiying; Wang, Hu; Liu, Yang; Zhao, Hui; Nan, Meng

2016-10-01

In order to realize real-time signal identification and processing of spatial transient light, the features and the energy of the captured target light signal are first described and quantitatively calculated. Considering that the transient light signal has random occurrence, a short duration and an evident beginning and ending, a photodiode detector based spatial transient light detection and processing system is proposed and designed in this paper. This system has a large field of view and is used to realize non-imaging energy detection of random, transient and weak point target under complex background of spatial environment. Weak signal extraction under strong background is difficult. In this paper, considering that the background signal changes slowly and the target signal changes quickly, filter is adopted for signal's background subtraction. A variable speed sampling is realized by the way of sampling data points with a gradually increased interval. The two dilemmas that real-time processing of large amount of data and power consumption required by the large amount of data needed to be stored are solved. The test results with self-made simulative signal demonstrate the effectiveness of the design scheme. The practical system could be operated reliably. The detection and processing of the target signal under the strong sunlight background was realized. The results indicate that the system can realize real-time detection of target signal's characteristic waveform and monitor the system working parameters. The prototype design could be used in a variety of engineering applications.

Automatic drawing for traffic marking with MMS LIDAR intensity

NASA Astrophysics Data System (ADS)

Takahashi, G.; Takeda, H.; Shimano, Y.

2014-05-01

Upgrading the database of CYBER JAPAN has been strategically promoted because the "Basic Act on Promotion of Utilization of Geographical Information", was enacted in May 2007. In particular, there is a high demand for road information that comprises a framework in this database. Therefore, road inventory mapping work has to be accurate and eliminate variation caused by individual human operators. Further, the large number of traffic markings that are periodically maintained and possibly changed require an efficient method for updating spatial data. Currently, we apply manual photogrammetry drawing for mapping traffic markings. However, this method is not sufficiently efficient in terms of the required productivity, and data variation can arise from individual operators. In contrast, Mobile Mapping Systems (MMS) and high-density Laser Imaging Detection and Ranging (LIDAR) scanners are rapidly gaining popularity. The aim in this study is to build an efficient method for automatically drawing traffic markings using MMS LIDAR data. The key idea in this method is extracting lines using a Hough transform strategically focused on changes in local reflection intensity along scan lines. However, also note that this method processes every traffic marking. In this paper, we discuss a highly accurate and non-human-operator-dependent method that applies the following steps: (1) Binarizing LIDAR points by intensity and extracting higher intensity points; (2) Generating a Triangulated Irregular Network (TIN) from higher intensity points; (3) Deleting arcs by length and generating outline polygons on the TIN; (4) Generating buffers from the outline polygons; (5) Extracting points from the buffers using the original LIDAR points; (6) Extracting local-intensity-changing points along scan lines using the extracted points; (7) Extracting lines from intensity-changing points through a Hough transform; and (8) Connecting lines to generate automated traffic marking mapping data.

Detecting a trend change in cross-border epidemic transmission

NASA Astrophysics Data System (ADS)

Maeno, Yoshiharu

2016-09-01

A method for a system of Langevin equations is developed for detecting a trend change in cross-border epidemic transmission. The equations represent a standard epidemiological SIR compartment model and a meta-population network model. The method analyzes a time series of the number of new cases reported in multiple geographical regions. The method is applicable to investigating the efficacy of the implemented public health intervention in managing infectious travelers across borders. It is found that the change point of the probability of travel movements was one week after the WHO worldwide alert on the SARS outbreak in 2003. The alert was effective in managing infectious travelers. On the other hand, it is found that the probability of travel movements did not change at all for the flu pandemic in 2009. The pandemic did not affect potential travelers despite the WHO alert.

Detection of change points in underlying earthquake rates, with application to global mega-earthquakes

NASA Astrophysics Data System (ADS)

Touati, Sarah; Naylor, Mark; Main, Ian

2016-02-01

The recent spate of mega-earthquakes since 2004 has led to speculation of an underlying change in the global `background' rate of large events. At a regional scale, detecting changes in background rate is also an important practical problem for operational forecasting and risk calculation, for example due to volcanic processes, seismicity induced by fluid injection or withdrawal, or due to redistribution of Coulomb stress after natural large events. Here we examine the general problem of detecting changes in background rate in earthquake catalogues with and without correlated events, for the first time using the Bayes factor as a discriminant for models of varying complexity. First we use synthetic Poisson (purely random) and Epidemic-Type Aftershock Sequence (ETAS) models (which also allow for earthquake triggering) to test the effectiveness of many standard methods of addressing this question. These fall into two classes: those that evaluate the relative likelihood of different models, for example using Information Criteria or the Bayes Factor; and those that evaluate the probability of the observations (including extreme events or clusters of events) under a single null hypothesis, for example by applying the Kolmogorov-Smirnov and `runs' tests, and a variety of Z-score tests. The results demonstrate that the effectiveness among these tests varies widely. Information Criteria worked at least as well as the more computationally expensive Bayes factor method, and the Kolmogorov-Smirnov and runs tests proved to be the relatively ineffective in reliably detecting a change point. We then apply the methods tested to events at different thresholds above magnitude M ≥ 7 in the global earthquake catalogue since 1918, after first declustering the catalogue. This is most effectively done by removing likely correlated events using a much lower magnitude threshold (M ≥ 5), where triggering is much more obvious. We find no strong evidence that the background rate of large events worldwide has increased in recent years.

Disruption of the lower food web in Lake Ontario: Did it affect alewife growth or condition?

USGS Publications Warehouse

O'Gorman, R.; Prindle, S.E.; Lantry, J.R.; Lantry, B.F.

2008-01-01

From the early 1980s to the late 1990s, a succession of non-native invertebrates colonized Lake Ontario and the suite of consequences caused by their colonization became known as "food web disruption". For example, the native burrowing amphipod Diporeia spp., a key link in the profundal food web, declined to near absence, exotic predaceous cladocerans with long spines proliferated, altering the zooplankton community, and depth distributions of fishes shifted. These changes had the potential to affect growth and condition of planktivorous alewife Alosa pseudoharengus, the most abundant fish in the lake. To determine if food web disruption affected alewife, we used change-point analysis to examine alewife growth and adult alewife condition during 1976-2006 and analysis-of-variance to determine if values between change points differed significantly. There were no change points in growth during the first year of life. Of three change points in growth during the second year of life, one coincided with the shift in springtime distribution of alewife to deeper water but it was not associated with a significant change in growth. After the second year of life, no change points in growth were evident, although growth in the third year of life spiked in those years when Bythotrephes, the largest of the exotic cladocerans, was abundant suggesting that it was a profitable prey item for age-2 fish. We detected two change points in condition of adult alewife in fall, but the first occurred in 1981, well before disruption began. A second change point occurred in 2003, well after disruption began. After the springtime distribution of alewife shifted deeper during 1992-1994, growth in the first two years of life became more variable, and growth in years of life two and older became correlated (P < 0.05). In conclusion, food web disruption had no negative affect on growth and condition of alewife in Lake Ontario although it appears to have resulted in growth in the first two years of life becoming more variable, growth in years of life two and older becoming correlated (P < 0.05), and growth spurts in year of life three. Copyright ?? 2008 AEHMS.

THE CHANDRA SURVEY OF THE COSMOS FIELD. II. SOURCE DETECTION AND PHOTOMETRY

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

Puccetti, S.; Vignali, C.; Cappelluti, N.

2009-12-01

The Chandra COSMOS Survey (C-COSMOS) is a large, 1.8 Ms, Chandra program that covers the central contiguous {approx}0.92 deg{sup 2} of the COSMOS field. C-COSMOS is the result of a complex tiling, with every position being observed in up to six overlapping pointings (four overlapping pointings in most of the central {approx}0.45 deg{sup 2} area with the best exposure, and two overlapping pointings in most of the surrounding area, covering an additional {approx}0.47 deg{sup 2}). Therefore, the full exploitation of the C-COSMOS data requires a dedicated and accurate analysis focused on three main issues: (1) maximizing the sensitivity when themore » point-spread function (PSF) changes strongly among different observations of the same source (from {approx}1 arcsec up to {approx}10 arcsec half-power radius); (2) resolving close pairs; and (3) obtaining the best source localization and count rate. We present here our treatment of four key analysis items: source detection, localization, photometry, and survey sensitivity. Our final procedure consists of a two step procedure: (1) a wavelet detection algorithm to find source candidates and (2) a maximum likelihood PSF fitting algorithm to evaluate the source count rates and the probability that each source candidate is a fluctuation of the background. We discuss the main characteristics of this procedure, which was the result of detailed comparisons between different detection algorithms and photometry tools, calibrated with extensive and dedicated simulations.« less

Electrical detection of single viruses

NASA Astrophysics Data System (ADS)

Patolsky, Fernando; Zheng, Gengfeng; Hayden, Oliver; Lakadamyali, Melike; Zhuang, Xiaowei; Lieber, Charles M.

2004-09-01

We report direct, real-time electrical detection of single virus particles with high selectivity by using nanowire field effect transistors. Measurements made with nanowire arrays modified with antibodies for influenza A showed discrete conductance changes characteristic of binding and unbinding in the presence of influenza A but not paramyxovirus or adenovirus. Simultaneous electrical and optical measurements using fluorescently labeled influenza A were used to demonstrate conclusively that the conductance changes correspond to binding/unbinding of single viruses at the surface of nanowire devices. pH-dependent studies further show that the detection mechanism is caused by a field effect, and that the nanowire devices can be used to determine rapidly isoelectric points and variations in receptor-virus binding kinetics for different conditions. Lastly, studies of nanowire devices modified with antibodies specific for either influenza or adenovirus show that multiple viruses can be selectively detected in parallel. The possibility of large-scale integration of these nanowire devices suggests potential for simultaneous detection of a large number of distinct viral threats at the single virus level.

Military Role in Countering Terrorist Use of Weapons of Mass Destruction

DTIC Science & Technology

1999-04-01

chemical and biological mobile point detection. “The M21 Remote Sensing Chemical Agent Alarm (RSCAAL) is an automatic scanning, passive infrared sensor...The M21 detects nerve and blister agent clouds based on changes in the background infrared spectra caused by the presence of the agent vapor.”15...required if greater than 3 years since last vaccine. VEE Yes Multiple vaccines required. VHF No Botulism Yes SEB No Ricin No Mycotoxin s No Source

Minimum Error Bounded Efficient L1 Tracker with Occlusion Detection (PREPRINT)

DTIC Science & Technology

2011-01-01

Minimum Error Bounded Efficient `1 Tracker with Occlusion Detection Xue Mei\\ ∗ Haibin Ling† Yi Wu†[ Erik Blasch‡ Li Bai] \\Assembly Test Technology...proposed BPR-L1 tracker is tested on several challenging benchmark sequences involving chal- lenges such as occlusion and illumination changes. In all...point method de - pends on the value of the regularization parameter λ. In the experiments, we found that the total number of PCG is a few hundred. The

Erosion monitoring along the Coosa River below Logan Martin Dam near Vincent, Alabama, using terrestrial light detection and ranging (T-LiDAR) technology

USGS Publications Warehouse

Kimbrow, Dustin R.; Lee, Kathryn G.

2013-01-01

Alabama Power operates a series of dams on the Coosa River in east central Alabama. These dams form six reservoirs that provide power generation, flood control, recreation, economic opportunity, and fish and wildlife habitats to the region. The Logan Martin Reservoir is located approximately 45 kilometers east of Birmingham and borders Saint Clair and Talladega Counties. Discharges below the reservoir are controlled by power generation at Logan Martin Dam, and there has been an ongoing concern about the stability of the streambanks downstream of the dam. The U.S. Geological Survey, in cooperation with Alabama Power conducted a scientific investigation of the geomorphic conditions of a 115-meter length of streambank along the Coosa River by using tripod-mounted terrestrial light detection and ranging technology. Two surveys were conducted before and after the winter flood season of 2010 to determine the extent and magnitude of geomorphic change. A comparison of the terrestrial light detection and ranging datasets indicated that approximately 40 cubic meters of material had been eroded from the upstream section of the study area. The terrestrial light detection and ranging data included in this report consist of electronic point cloud files containing several million georeferenced data points, as well as a surface model measuring changes between scans.

Point-of-Care Assay of Telomerase Activity at Single-Cell Level via Gas Pressure Readout.

PubMed

Wang, Yanjun; Yang, Luzhu; Li, Baoxin; Yang, Chaoyong James; Jin, Yan

2017-08-15

Detection of telomerase activity at the single-cell level is one of the central challenges in cancer diagnostics and therapy. Herein, we describe a facile and reliable point-of-care testing (POCT) strategy for detection of telomerase activity via a portable pressure meter. Telomerase primer (TS) was immobilized onto the surface of magnetic beads (MBs), and then was elongated to a long single-stranded DNA by telomerase. The elongated (TTAGGG) n repeat unit hybridized with several short PtNP-functionalized complementary DNA (PtNPs-cDNA), which specifically enriched PtNPs onto the surfaces of magnetic beads (MBs), which were separated using a magnet. Then, nanoparticle-catalyzed gas-generation reaction converted telomerase activity into significant change in gas pressure. Because of the self-amplification of telomerase and enrichment by magnetic separation, the diluted telomerase equivalent to a single HeLa cell was facilely detected. More importantly, the telomerase in the lysate of 1 HeLa cell can be reliably detected by monitoring change in gas pressure, indicating that it is feasible and possible to study differences between individual cells. The difference in relative activity between different kinds of cancer cells was easily and sensitively studied. Study of inhibition of telomerase activity demonstrated that our method has great potential in screening of telomerase-targeted antitumor drugs as well as in clinical diagnosis.

Robust Algorithms for Detecting a Change in a Stochastic Process with Infinite Memory

DTIC Science & Technology

1988-03-01

breakdown point and the additional assumption of 0-mixing on the nominal meas- influence function . The structure of the optimal algorithm ures. Then Huber’s...are i.i.d. sequences of Gaus- For the breakdown point and the influence function sian random variables, with identical variance o2 . Let we will use...algebraic sign for i=0,1. Here z will be chosen such = f nthat it leads to worst case or earliest breakdown. i (14) Next, the influence function measures

Development of ultrasound-assisted fluorescence imaging of indocyanine green.

PubMed

Morikawa, Hiroyasu; Toyota, Shin; Wada, Kenji; Uchida-Kobayashi, Sawako; Kawada, Norifumi; Horinaka, Hiromichi

2017-01-01

Indocyanine green (ICG) accumulation in hepatocellular carcinoma means tumors can be located by fluorescence. However, because of light scattering, it is difficult to detect ICG fluorescence from outside the body. We propose a new fluorescence imaging method that detects changes in the intensity of ICG fluorescence by ultrasound-induced temperature changes. ICG fluorescence intensity decreases as the temperature rises. Therefore, it should theoretically be possible to detect tissue distribution of ICG using ultrasound to heat tissue, moving the point of ultrasound transmission, and monitoring changes in fluorescence intensity. A new probe was adapted for clinical application. It consisted of excitation light from a laser, fluorescence sensing through a light pipe, and heating by ultrasound. We applied the probe to bovine liver to image the accumulation of ICG. ICG emits fluorescence (820 nm) upon light irradiation (783 nm). With a rise in temperature, the fluorescence intensity of ICG decreased by 0.85 %/°C. The distribution of fluorescent ICG was detected using an ultrasonic warming method in a new integrated probe. Modulating fluorescence by changing the temperature using ultrasound can determine where ICG accumulates at a depth, highlighting its potential as a means to locate hepatocellular carcinoma.

Structural Analysis of Single-Point Mutations Given an RNA Sequence: A Case Study with RNAMute

NASA Astrophysics Data System (ADS)

Churkin, Alexander; Barash, Danny

2006-12-01

We introduce here for the first time the RNAMute package, a pattern-recognition-based utility to perform mutational analysis and detect vulnerable spots within an RNA sequence that affect structure. Mutations in these spots may lead to a structural change that directly relates to a change in functionality. Previously, the concept was tried on RNA genetic control elements called "riboswitches" and other known RNA switches, without an organized utility that analyzes all single-point mutations and can be further expanded. The RNAMute package allows a comprehensive categorization, given an RNA sequence that has functional relevance, by exploring the patterns of all single-point mutants. For illustration, we apply the RNAMute package on an RNA transcript for which individual point mutations were shown experimentally to inactivate spectinomycin resistance in Escherichia coli. Functional analysis of mutations on this case study was performed experimentally by creating a library of point mutations using PCR and screening to locate those mutations. With the availability of RNAMute, preanalysis can be performed computationally before conducting an experiment.

Non-Verbal Communicative Signals Modulate Attention to Object Properties

PubMed Central

Marno, Hanna; Davelaar, Eddy J.; Csibra, Gergely

2015-01-01

We investigated whether the social context in which an object is experienced influences the encoding of its various properties. We hypothesized that when an object is observed in a communicative context, its intrinsic features (such as its shape) would be preferentially encoded at the expense of its extrinsic properties (such as its location). In the three experiments, participants were presented with brief movies, in which an actor either performed a non-communicative action towards one of five different meaningless objects, or communicatively pointed at one of them. A subsequent static image, in which either the location or the identity of an object changed, tested participants’ attention to these two kinds of information. Throughout the three experiments we found that communicative cues tended to facilitate identity change detection and to impede location change detection, while in the non-communicative contexts we did not find such a bidirectional effect of cueing. The results also revealed that the effect of the communicative context was due to the presence of ostensive-communicative signals before the object-directed action, and not to the pointing gesture per se. We propose that such an attentional bias forms an inherent part of human communication, and function to facilitate social learning by communication. PMID:24294871

Nonverbal communicative signals modulate attention to object properties.

PubMed

Marno, Hanna; Davelaar, Eddy J; Csibra, Gergely

2014-04-01

We investigated whether the social context in which an object is experienced influences the encoding of its various properties. We hypothesized that when an object is observed in a communicative context, its intrinsic features (such as its shape) would be preferentially encoded at the expense of its extrinsic properties (such as its location). In 3 experiments, participants were presented with brief movies, in which an actor either performed a noncommunicative action toward 1 of 5 different meaningless objects, or communicatively pointed at 1 of them. A subsequent static image, in which either the location or the identity of an object changed, tested participants' attention to these 2 kinds of information. Throughout the 3 experiments we found that communicative cues tended to facilitate identity change detection and to impede location change detection, whereas in the noncommunicative contexts we did not find such a bidirectional effect of cueing. The results also revealed that the effect of the communicative context was a result the presence of ostensive-communicative signals before the object-directed action, and not to the pointing gesture per se. We propose that such an attentional bias forms an inherent part of human communication, and function to facilitate social learning by communication.

Trends in Detection of Invasive Cancer and Ductal Carcinoma In Situ at Biennial Screening Mammography in Spain: A Retrospective Cohort Study

PubMed Central

Román, Marta; Rué, Montse; Sala, Maria; Ascunce, Nieves; Baré, Marisa; Baroja, Araceli; De la Vega, Mariola; Galcerán, Jaume; Natal, Carmen; Salas, Dolores; Sánchez-Jacob, Mercedes; Zubizarreta, Raquel; Castells, Xavier

2013-01-01

Background Breast cancer incidence has decreased in the last decade, while the incidence of ductal carcinoma in situ (DCIS) has increased substantially in the western world. The phenomenon has been attributed to the widespread adaption of screening mammography. The aim of the study was to evaluate the temporal trends in the rates of screen detected invasive cancers and DCIS, and to compare the observed trends with respect to hormone replacement therapy (HRT) use along the same study period. Methods Retrospective cohort study of 1,564,080 women aged 45–69 years who underwent 4,705,681 screening mammograms from 1992 to 2006. Age-adjusted rates of screen detected invasive cancer, DCIS, and HRT use were calculated for first and subsequent screenings. Poisson regression was used to evaluate the existence of a change-point in trend, and to estimate the adjusted trends in screen detected invasive breast cancer and DCIS over the study period. Results The rates of screen detected invasive cancer per 100.000 screened women were 394.0 at first screening, and 229.9 at subsequent screen. The rates of screen detected DCIS per 100.000 screened women were 66.8 at first screen and 43.9 at subsequent screens. No evidence of a change point in trend in the rates of DCIS and invasive cancers over the study period were found. Screen detected DCIS increased at a steady 2.5% per year (95% CI: 1.3; 3.8), while invasive cancers were stable. Conclusion Despite the observed decrease in breast cancer incidence in the population, the rates of screen detected invasive cancer remained stable during the study period. The proportion of DCIS among screen detected breast malignancies increased from 13% to 17% throughout the study period. The rates of screen detected invasive cancer and DCIS were independent of the decreasing trend in HRT use observed among screened women after 2002. PMID:24376649

Evaluation of experimental UAV video change detection

NASA Astrophysics Data System (ADS)

Bartelsen, J.; Saur, G.; Teutsch, C.

2016-10-01

During the last ten years, the availability of images acquired from unmanned aerial vehicles (UAVs) has been continuously increasing due to the improvements and economic success of flight and sensor systems. From our point of view, reliable and automatic image-based change detection may contribute to overcoming several challenging problems in military reconnaissance, civil security, and disaster management. Changes within a scene can be caused by functional activities, i.e., footprints or skid marks, excavations, or humidity penetration; these might be recognizable in aerial images, but are almost overlooked when change detection is executed manually. With respect to the circumstances, these kinds of changes may be an indication of sabotage, terroristic activity, or threatening natural disasters. Although image-based change detection is possible from both ground and aerial perspectives, in this paper we primarily address the latter. We have applied an extended approach to change detection as described by Saur and Kruger,1 and Saur et al.2 and have built upon the ideas of Saur and Bartelsen.3 The commercial simulation environment Virtual Battle Space 3 (VBS3) is used to simulate aerial "before" and "after" image acquisition concerning flight path, weather conditions and objects within the scene and to obtain synthetic videos. Video frames, which depict the same part of the scene, including "before" and "after" changes and not necessarily from the same perspective, are registered pixel-wise against each other by a photogrammetric concept, which is based on a homography. The pixel-wise registration is used to apply an automatic difference analysis, which, to a limited extent, is able to suppress typical errors caused by imprecise frame registration, sensor noise, vegetation and especially parallax effects. The primary concern of this paper is to seriously evaluate the possibilities and limitations of our current approach for image-based change detection with respect to the flight path, viewpoint change and parametrization. Hence, based on synthetic "before" and "after" videos of a simulated scene, we estimated the precision and recall of automatically detected changes. In addition and based on our approach, we illustrate the results showing the change detection in short, but real video sequences. Future work will improve the photogrammetric approach for frame registration, and extensive real video material, capable of change detection, will be acquired.

Feasibility of Multispectral Airborne Laser Scanning for Land Cover Classification, Road Mapping and Map Updating

NASA Astrophysics Data System (ADS)

Matikainen, L.; Karila, K.; Hyyppä, J.; Puttonen, E.; Litkey, P.; Ahokas, E.

2017-10-01

This article summarises our first results and experiences on the use of multispectral airborne laser scanner (ALS) data. Optech Titan multispectral ALS data over a large suburban area in Finland were acquired on three different dates in 2015-2016. We investigated the feasibility of the data from the first date for land cover classification and road mapping. Object-based analyses with segmentation and random forests classification were used. The potential of the data for change detection of buildings and roads was also demonstrated. The overall accuracy of land cover classification results with six classes was 96 % compared with validation points. The data also showed high potential for road detection, road surface classification and change detection. The multispectral intensity information appeared to be very important for automated classifications. Compared to passive aerial images, the intensity images have interesting advantages, such as the lack of shadows. Currently, we focus on analyses and applications with the multitemporal multispectral data. Important questions include, for example, the potential and challenges of the multitemporal data for change detection.

Image denoising based on noise detection

NASA Astrophysics Data System (ADS)

Jiang, Yuanxiang; Yuan, Rui; Sun, Yuqiu; Tian, Jinwen

2018-03-01

Because of the noise points in the images, any operation of denoising would change the original information of non-noise pixel. A noise detection algorithm based on fractional calculus was proposed to denoise in this paper. Convolution of the image was made to gain direction gradient masks firstly. Then, the mean gray was calculated to obtain the gradient detection maps. Logical product was made to acquire noise position image next. Comparisons in the visual effect and evaluation parameters after processing, the results of experiment showed that the denoising algorithms based on noise were better than that of traditional methods in both subjective and objective aspects.

[Endoscopic endonasal detection of cerebrospinal fluid leakage with topical fluorescein].

PubMed

Sato, Taku; Kishida, Yugo; Watanabe, Tadashi; Tani, Akiko; Tada, Yasuhiro; Tamura, Takamitsu; Ichikawa, Masahiro; Sakuma, Jun; Omori, Koichi; Saito, Kiyoshi

2013-08-01

We evaluated the effectiveness of intraoperative topical application of fluorescein to detect the leakage point of cerebrospinal fluid(CSF)rhinorrhea. Three patients with CSF rhinorrhea were treated with an endoscopic endonasal technique. Ten percent fluorescein was topically used for intraoperative localization of the leak site. A change of the fluorescein color from brown to green due to dilation of CSF were recognized as evidence of CSF rhinorrhea. We repeated the procedure to detect any small defects. All CSF rhinorrheas were successfully repaired by this endoscopic endonasal approach. Topical application of fluorescein is simple and sensitive for identifying intraoperative CSF rhinorrhea.

Model-based decoding, information estimation, and change-point detection techniques for multineuron spike trains.

PubMed

Pillow, Jonathan W; Ahmadian, Yashar; Paninski, Liam

2011-01-01

One of the central problems in systems neuroscience is to understand how neural spike trains convey sensory information. Decoding methods, which provide an explicit means for reading out the information contained in neural spike responses, offer a powerful set of tools for studying the neural coding problem. Here we develop several decoding methods based on point-process neural encoding models, or forward models that predict spike responses to stimuli. These models have concave log-likelihood functions, which allow efficient maximum-likelihood model fitting and stimulus decoding. We present several applications of the encoding model framework to the problem of decoding stimulus information from population spike responses: (1) a tractable algorithm for computing the maximum a posteriori (MAP) estimate of the stimulus, the most probable stimulus to have generated an observed single- or multiple-neuron spike train response, given some prior distribution over the stimulus; (2) a gaussian approximation to the posterior stimulus distribution that can be used to quantify the fidelity with which various stimulus features are encoded; (3) an efficient method for estimating the mutual information between the stimulus and the spike trains emitted by a neural population; and (4) a framework for the detection of change-point times (the time at which the stimulus undergoes a change in mean or variance) by marginalizing over the posterior stimulus distribution. We provide several examples illustrating the performance of these estimators with simulated and real neural data.

Spatial attention is attracted in a sustained fashion toward singular points in the optic flow.

PubMed

Wang, Shuo; Fukuchi, Masaki; Koch, Christof; Tsuchiya, Naotsugu

2012-01-01

While a single approaching object is known to attract spatial attention, it is unknown how attention is directed when the background looms towards the observer as s/he moves forward in a quasi-stationary environment. In Experiment 1, we used a cued speeded discrimination task to quantify where and how spatial attention is directed towards the target superimposed onto a cloud of moving dots. We found that when the motion was expansive, attention was attracted towards the singular point of the optic flow (the focus of expansion, FOE) in a sustained fashion. The effects were less pronounced when the motion was contractive. The more ecologically valid the motion features became (e.g., temporal expansion of each dot, spatial depth structure implied by distribution of the size of the dots), the stronger the attentional effects. Further, the attentional effects were sustained over 1000 ms. Experiment 2 quantified these attentional effects using a change detection paradigm by zooming into or out of photographs of natural scenes. Spatial attention was attracted in a sustained manner such that change detection was facilitated or delayed depending on the location of the FOE only when the motion was expansive. Our results suggest that focal attention is strongly attracted towards singular points that signal the direction of forward ego-motion.

Spatial Attention Is Attracted in a Sustained Fashion toward Singular Points in the Optic Flow

PubMed Central

Wang, Shuo; Fukuchi, Masaki; Koch, Christof; Tsuchiya, Naotsugu

2012-01-01

While a single approaching object is known to attract spatial attention, it is unknown how attention is directed when the background looms towards the observer as s/he moves forward in a quasi-stationary environment. In Experiment 1, we used a cued speeded discrimination task to quantify where and how spatial attention is directed towards the target superimposed onto a cloud of moving dots. We found that when the motion was expansive, attention was attracted towards the singular point of the optic flow (the focus of expansion, FOE) in a sustained fashion. The effects were less pronounced when the motion was contractive. The more ecologically valid the motion features became (e.g., temporal expansion of each dot, spatial depth structure implied by distribution of the size of the dots), the stronger the attentional effects. Further, the attentional effects were sustained over 1000 ms. Experiment 2 quantified these attentional effects using a change detection paradigm by zooming into or out of photographs of natural scenes. Spatial attention was attracted in a sustained manner such that change detection was facilitated or delayed depending on the location of the FOE only when the motion was expansive. Our results suggest that focal attention is strongly attracted towards singular points that signal the direction of forward ego-motion. PMID:22905096

Sensor data monitoring and decision level fusion scheme for early fire detection

NASA Astrophysics Data System (ADS)

Rizogiannis, Constantinos; Thanos, Konstantinos Georgios; Astyakopoulos, Alkiviadis; Kyriazanos, Dimitris M.; Thomopoulos, Stelios C. A.

2017-05-01

The aim of this paper is to present the sensor monitoring and decision level fusion scheme for early fire detection which has been developed in the context of the AF3 Advanced Forest Fire Fighting European FP7 research project, adopted specifically in the OCULUS-Fire control and command system and tested during a firefighting field test in Greece with prescribed real fire, generating early-warning detection alerts and notifications. For this purpose and in order to improve the reliability of the fire detection system, a two-level fusion scheme is developed exploiting a variety of observation solutions from air e.g. UAV infrared cameras, ground e.g. meteorological and atmospheric sensors and ancillary sources e.g. public information channels, citizens smartphone applications and social media. In the first level, a change point detection technique is applied to detect changes in the mean value of each measured parameter by the ground sensors such as temperature, humidity and CO2 and then the Rate-of-Rise of each changed parameter is calculated. In the second level the fire event Basic Probability Assignment (BPA) function is determined for each ground sensor using Fuzzy-logic theory and then the corresponding mass values are combined in a decision level fusion process using Evidential Reasoning theory to estimate the final fire event probability.

Test-retest reliability and minimal detectable change of two simplified 3-point balance measures in patients with stroke.

PubMed

Chen, Yi-Miau; Huang, Yi-Jing; Huang, Chien-Yu; Lin, Gong-Hong; Liaw, Lih-Jiun; Lee, Shih-Chieh; Hsieh, Ching-Lin

2017-10-01

The 3-point Berg Balance Scale (BBS-3P) and 3-point Postural Assessment Scale for Stroke Patients (PASS-3P) were simplified from the BBS and PASS to overcome the complex scoring systems. The BBS-3P and PASS-3P were more feasible in busy clinical practice and showed similarly sound validity and responsiveness to the original measures. However, the reliability of the BBS-3P and PASS-3P is unknown limiting their utility and the interpretability of scores. We aimed to examine the test-retest reliability and minimal detectable change (MDC) of the BBS-3P and PASS-3P in patients with stroke. Cross-sectional study. The rehabilitation departments of a medical center and a community hospital. A total of 51 chronic stroke patients (64.7% male). Both balance measures were administered twice 7 days apart. The test-retest reliability of both the BBS-3P and PASS-3P were examined by intraclass correlation coefficients (ICC). The MDC and its percentage over the total score (MDC%) of each measure was calculated for examining the random measurement errors. The ICC values of the BBS-3P and PASS-3P were 0.99 and 0.97, respectively. The MDC% (MDC) of the BBS-3P and PASS-3P were 9.1% (5.1 points) and 8.4% (3.0 points), respectively, indicating that both measures had small and acceptable random measurement errors. Our results showed that both the BBS-3P and the PASS-3P had good test-retest reliability, with small and acceptable random measurement error. These two simplified 3-level balance measures can provide reliable results over time. Our findings support the repeated administration of the BBS-3P and PASS-3P to monitor the balance of patients with stroke. The MDC values can help clinicians and researchers interpret the change scores more precisely.

Detection of longitudinal visual field progression in glaucoma using machine learning.

PubMed

Yousefi, Siamak; Kiwaki, Taichi; Zheng, Yuhui; Suigara, Hiroki; Asaoka, Ryo; Murata, Hiroshi; Lemij, Hans; Yamanishi, Kenji

2018-06-16

Global indices of standard automated perimerty are insensitive to localized losses, while point-wise indices are sensitive but highly variable. Region-wise indices sit in between. This study introduces a machine-learning-based index for glaucoma progression detection that outperforms global, region-wise, and point-wise indices. Development and comparison of a prognostic index. Visual fields from 2085 eyes of 1214 subjects were used to identify glaucoma progression patterns using machine learning. Visual fields from 133 eyes of 71 glaucoma patients were collected 10 times over 10 weeks to provide a no-change, test-retest dataset. The parameters of all methods were identified using visual field sequences in the test-retest dataset to meet fixed 95% specificity. An independent dataset of 270 eyes of 136 glaucoma patients and survival analysis were utilized to compare methods. The time to detect progression in 25% of the eyes in the longitudinal dataset using global mean deviation (MD) was 5.2 years (95% confidence interval, 4.1 - 6.5 years); 4.5 years (4.0 - 5.5) using region-wise, 3.9 years (3.5 - 4.6) using point-wise, and 3.5 years (3.1 - 4.0) using machine learning analysis. The time until 25% of eyes showed subsequently confirmed progression after two additional visits were included were 6.6 years (5.6 - 7.4 years), 5.7 years (4.8 - 6.7), 5.6 years (4.7 - 6.5), and 5.1 years (4.5 - 6.0) for global, region-wise, point-wise, and machine learning analyses, respectively. Machine learning analysis detects progressing eyes earlier than other methods consistently, with or without confirmation visits. In particular, machine learning detects more slowly progressing eyes than other methods. Copyright © 2018 Elsevier Inc. All rights reserved.

A density based algorithm to detect cavities and holes from planar points

NASA Astrophysics Data System (ADS)

Zhu, Jie; Sun, Yizhong; Pang, Yueyong

2017-12-01

Delaunay-based shape reconstruction algorithms are widely used in approximating the shape from planar points. However, these algorithms cannot ensure the optimality of varied reconstructed cavity boundaries and hole boundaries. This inadequate reconstruction can be primarily attributed to the lack of efficient mathematic formulation for the two structures (hole and cavity). In this paper, we develop an efficient algorithm for generating cavities and holes from planar points. The algorithm yields the final boundary based on an iterative removal of the Delaunay triangulation. Our algorithm is mainly divided into two steps, namely, rough and refined shape reconstructions. The rough shape reconstruction performed by the algorithm is controlled by a relative parameter. Based on the rough result, the refined shape reconstruction mainly aims to detect holes and pure cavities. Cavity and hole are conceptualized as a structure with a low-density region surrounded by the high-density region. With this structure, cavity and hole are characterized by a mathematic formulation called as compactness of point formed by the length variation of the edges incident to point in Delaunay triangulation. The boundaries of cavity and hole are then found by locating a shape gradient change in compactness of point set. The experimental comparison with other shape reconstruction approaches shows that the proposed algorithm is able to accurately yield the boundaries of cavity and hole with varying point set densities and distributions.

The Value of Changing Position in the Detection of CSF Leakage in Spontaneous Intracranial Hypotension Using Tc-99m DTPA Scintigraphy: Two Case Reports.

PubMed

Lu, Yu Yu; Wang, Hsin Yi; Lin, Ying; Lin, Wan Yu

2012-09-01

Radionuclide Cisternography (RNC) is of potential value in pointing out the sites of cerebrospinal fluid (CSF) leakage in patients with spontaneous intracranial hypotension (SIH). In the current report, we present two patients who underwent RNC for suspected CSF leakage. Both patients underwent magnetic resonance imaging (MRI) and RNC for evaluation. We describe a simple method to increase the detection ability of RNC for CSF leakage in patients with SIH.

Detection of blunt, sharp force and gunshot lesions on burnt remains: a cautionary note.

PubMed

Poppa, Pasquale; Porta, Davide; Gibelli, Daniele; Mazzucchi, Alessandra; Brandone, Alberto; Grandi, Marco; Cattaneo, Cristina

2011-09-01

The study of skin and bone lesions may give information concerning type and manner of production, but in burnt material modification of tissues by the high temperatures may considerably change the morphological characteristics of the lesions. This study aims at pointing out the effects of burning head of pigs with several types of lesions (blunt trauma, sharp force, and gunshot lesions) on soft tissues and bones, both from a morphological and chemical point of view. Results show that the charring process does not completely destroy signs of lesions on bones, which can often be recovered by cleaning bone surface from charred soft-tissue residues. Furthermore, neutron activation analysis test proved that antimony may be detectable also on gunshot entry wounds at the final stages of charring process.

Program Correctness, Verification and Testing for Exascale (Corvette)

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

Sen, Koushik; Iancu, Costin; Demmel, James W

The goal of this project is to provide tools to assess the correctness of parallel programs written using hybrid parallelism. There is a dire lack of both theoretical and engineering know-how in the area of finding bugs in hybrid or large scale parallel programs, which our research aims to change. In the project we have demonstrated novel approaches in several areas: 1. Low overhead automated and precise detection of concurrency bugs at scale. 2. Using low overhead bug detection tools to guide speculative program transformations for performance. 3. Techniques to reduce the concurrency required to reproduce a bug using partialmore » program restart/replay. 4. Techniques to provide reproducible execution of floating point programs. 5. Techniques for tuning the floating point precision used in codes.« less

Pedestrian Detection by Laser Scanning and Depth Imagery

NASA Astrophysics Data System (ADS)

Barsi, A.; Lovas, T.; Molnar, B.; Somogyi, A.; Igazvolgyi, Z.

2016-06-01

Pedestrian flow is much less regulated and controlled compared to vehicle traffic. Estimating flow parameters would support many safety, security or commercial applications. Current paper discusses a method that enables acquiring information on pedestrian movements without disturbing and changing their motion. Profile laser scanner and depth camera have been applied to capture the geometry of the moving people as time series. Procedures have been developed to derive complex flow parameters, such as count, volume, walking direction and velocity from laser scanned point clouds. Since no images are captured from the faces of pedestrians, no privacy issues raised. The paper includes accuracy analysis of the estimated parameters based on video footage as reference. Due to the dense point clouds, detailed geometry analysis has been conducted to obtain the height and shoulder width of pedestrians and to detect whether luggage has been carried or not. The derived parameters support safety (e.g. detecting critical pedestrian density in mass events), security (e.g. detecting prohibited baggage in endangered areas) and commercial applications (e.g. counting pedestrians at all entrances/exits of a shopping mall).

[Radiation biology of structurally different Drosophila melanogaster genes. Report I. The vestigial gene: molecular characteristic of "point" mutations].

PubMed

Aleksandrov, I D; Afanas'eva, K P; Aleksandrova, M V; Lapidus, I L

2012-01-01

The screening of PCR-detected DNA alterations in 9 spontaneous and 59 gamma-ray-, neutron - or neutron + gamma-ray-induced Drosophila vestigial (vg) gene/"point" mutations was carried out. The detected patterns of existence or absence of either of 16 overlapping fragments into which vg gene (15.1 kb, 8 exons, 7 introns) was divided enable us to subdivide all mutants into 4 classes: (i) PCR+ (40.7%) without the detected changes; (ii) "single-site" (33.9%) with the loss of a single fragment; (iii) partial detections (15.2%) as a loss of 2-9 adjacent fragments and (iv) "cluster" mutants (10.2%) having 2-3 independent changes of(ii) and/or (iii) classes. All spontaneous mutants except one were found to be classified as (ii) whereas radiation-induced mutants are represented by all 4 classes whose interrelation is determined by the dose and radiation quality. In particular, the efficacy of neutrons was found to be nine times as large as that of gamma-rays under the "cluster" mutant induction. Essentially, the distribution of DNA changes along the gene is uneven. CSGE-assay of PCR+-exon 3 revealed DNA heteroduplexes in 5 out of 17 PCR+-mutants studied, 2 of which had small deletions (5 and 11 b) and 3 others made transitions (A --> G) as shown by the sequencing. Therefore, gamma-rays and neutrons seem to be significant environmental agents increasing the SNP risk for the population through their action on the germ cells. The results obtained are also discussed within the framework of the track structure theory and the notion of quite different chromatin organization in somatic and germ cells.

Drawing for Traffic Marking Using Bidirectional Gradient-Based Detection with MMS LIDAR Intensity

NASA Astrophysics Data System (ADS)

Takahashi, G.; Takeda, H.; Nakamura, K.

2016-06-01

Recently, the development of autonomous cars is accelerating on the integration of highly advanced artificial intelligence, which increases demand for a digital map with high accuracy. In particular, traffic markings are required to be precisely digitized since automatic driving utilizes them for position detection. To draw traffic markings, we benefit from Mobile Mapping Systems (MMS) equipped with high-density Laser imaging Detection and Ranging (LiDAR) scanners, which produces large amount of data efficiently with XYZ coordination along with reflectance intensity. Digitizing this data, on the other hand, conventionally has been dependent on human operation, which thus suffers from human errors, subjectivity errors, and low reproductivity. We have tackled this problem by means of automatic extraction of traffic marking, which partially accomplished to draw several traffic markings (G. Takahashi et al., 2014). The key idea of the method was extracting lines using the Hough transform strategically focused on changes in local reflection intensity along scan lines. However, it failed to extract traffic markings properly in a densely marked area, especially when local changing points are close each other. In this paper, we propose a bidirectional gradient-based detection method where local changing points are labelled with plus or minus group. Given that each label corresponds to the boundary between traffic markings and background, we can identify traffic markings explicitly, meaning traffic lines are differentiated correctly by the proposed method. As such, our automated method, a highly accurate and non-human-operator-dependent method using bidirectional gradient-based algorithm, can successfully extract traffic lines composed of complex shapes such as a cross walk, resulting in minimizing cost and obtaining highly accurate results.

Gold-coated carbon nanotube electrode arrays: Immunosensors for impedimetric detection of bone biomarkers.

PubMed

Ramanathan, Madhumati; Patil, Mitali; Epur, Rigved; Yun, Yeoheung; Shanov, Vasselin; Schulz, Mark; Heineman, William R; Datta, Moni K; Kumta, Prashant N

2016-03-15

C-terminal telopeptide (cTx), a fragment generated during collagen degradation, is a key biomarker of bone resorption during the bone remodeling process. The presence of varying levels of cTx in the bloodstream can hence be indicative of abnormal bone metabolism. This study focuses on the development of an immunosensor utilizing carbon nanotube (CNT) electrodes coated with gold nanoparticles for the detection of cTx, which could ultimately lead to the development of an inexpensive and rapid point-of-care (POC) tool for bone metabolism detection and prognostics. Electrochemical impedance spectroscopy (EIS) was implemented to monitor and detect the antigen-antibody binding events occurring on the surface of the gold-deposited CNT electrode. Type I cTx was used as the model protein to test the developed sensor. The sensor was accordingly characterized at various stages of development for evaluation of the optimal sensor performance. The biosensor could detect cTx levels as low as 0.05 ng/mL. The feasibility of the sensor for point-of-care (POC) applications was further demonstrated by determining the single frequency showing maximum changes in impedance, which was determined to be 18.75 Hz. Copyright © 2015 Elsevier B.V. All rights reserved.

Assessment of error rates in acoustic monitoring with the R package monitoR

USGS Publications Warehouse

Katz, Jonathan; Hafner, Sasha D.; Donovan, Therese

2016-01-01

Detecting population-scale reactions to climate change and land-use change may require monitoring many sites for many years, a process that is suited for an automated system. We developed and tested monitoR, an R package for long-term, multi-taxa acoustic monitoring programs. We tested monitoR with two northeastern songbird species: black-throated green warbler (Setophaga virens) and ovenbird (Seiurus aurocapilla). We compared detection results from monitoR in 52 10-minute surveys recorded at 10 sites in Vermont and New York, USA to a subset of songs identified by a human that were of a single song type and had visually identifiable spectrograms (e.g. a signal:noise ratio of at least 10 dB: 166 out of 439 total songs for black-throated green warbler, 502 out of 990 total songs for ovenbird). monitoR’s automated detection process uses a ‘score cutoff’, which is the minimum match needed for an unknown event to be considered a detection and results in a true positive, true negative, false positive or false negative detection. At the chosen score cut-offs, monitoR correctly identified presence for black-throated green warbler and ovenbird in 64% and 72% of the 52 surveys using binary point matching, respectively, and 73% and 72% of the 52 surveys using spectrogram cross-correlation, respectively. Of individual songs, 72% of black-throated green warbler songs and 62% of ovenbird songs were identified by binary point matching. Spectrogram cross-correlation identified 83% of black-throated green warbler songs and 66% of ovenbird songs. False positive rates were  for song event detection.

Evidence of Cognitive Dysfunction after Soccer Playing with Ball Heading Using a Novel Tablet-Based Approach

PubMed Central

Lin, Angela H.; Patel, Saumil S.; Sereno, Anne B.

2013-01-01

Does frequent head-to-ball contact cause cognitive dysfunctions and brain injury to soccer players? An iPad-based experiment was designed to examine the impact of ball-heading among high school female soccer players. We examined both direct, stimulus-driven, or reflexive point responses (Pro-Point) as well as indirect, goal-driven, or voluntary point responses (Anti-Point), thought to require cognitive functions in the frontal lobe. The results show that soccer players were significantly slower than controls in the Anti-Point task but displayed no difference in Pro-Point latencies, indicating a disruption specific to voluntary responses. These findings suggest that even subconcussive blows in soccer can result in cognitive function changes that are consistent with mild traumatic brain injury of the frontal lobes. There is great clinical and practical potential of a tablet-based application for quick detection and monitoring of cognitive dysfunction. PMID:23460843

Montane-breeding bird distribution and abundance across national parks of southwestern Alaska

USGS Publications Warehouse

Amundson, Courtney L.; Handel, Colleen M.; Ruthrauff, Daniel R.; Tibbitts, T. Lee; Gill, Robert E.

2018-01-01

Between 2004 and 2008, biologists conducted an inventory of breeding birds during May–June primarily in montane areas (>100 m above sea level) in Aniakchak National Monument and Preserve (Aniakchak NMP), Katmai National Park and Preserve (Katmai NPP), and Lake Clark National Park and Preserve (Lake Clark NPP) in southwestern Alaska. Observers conducted 1,021 point counts along 169 transects within 63 10-km × 10-km plots that were randomly selected and stratified by ecological subsection. We created hierarchical N-mixture models to estimate detection probability and abundance for 15 species, including 12 passerines, 2 galliforms, and 1 shorebird. We first modeled detection probability relative to observer, date within season, and proportion of dense vegetation cover around the point, then modeled abundance as a function of land cover composition (proportion of seven coarse-scale land cover types) within 300 m of the survey point. Land cover relationships varied widely among species but most showed selection for low to tall shrubs (0.2–5 m tall) and an avoidance of alpine and 2 dwarf shrub–herbaceous cover types. After adjusting for species not observed, we estimated a minimum of 107 ± 9 species bred in the areas surveyed within the three parks combined. Species richness was negatively associated with elevation and associated land cover types. At comparable levels of survey effort (n = 721 birds detected), species richness was greatest in Lake Clark NPP (75 ± 12 species), lowest in Aniakchak NMP (45 ± 6 species), and intermediate at Katmai NPP (59 ± 10 species). Species richness was similar at equivalent survey effort (n = 973 birds detected) within the Lime Hills, Alaska Range, and Alaska Peninsula ecoregions (68 ± 8; 79 ± 11; 67 ± 11, respectively). Species composition was similar across all three parks and across the three major ecoregions (Alaska Range, Alaska Peninsula, Lime Hills) that encompass them. Our results provide baseline estimates of relative abundance and models of abundance and species richness relative to land cover that can be used to assess future changes in avian distribution. Additionally, these subarctic montane parks may serve as signals of landscape change and barometers for the assessment of population and distributional changes as a result of warming temperatures and changing precipitation patterns.

Increasing large scale windstorm damage in Western, Central and Northern European forests, 1951-2010

NASA Astrophysics Data System (ADS)

Gregow, H.; Laaksonen, A.; Alper, M. E.

2017-04-01

Using reports of forest losses caused directly by large scale windstorms (or primary damage, PD) from the European forest institute database (comprising 276 PD reports from 1951-2010), total growing stock (TGS) statistics of European forests and the daily North Atlantic Oscillation (NAO) index, we identify a statistically significant change in storm intensity in Western, Central and Northern Europe (17 countries). Using the validated set of storms, we found that the year 1990 represents a change-point at which the average intensity of the most destructive storms indicated by PD/TGS > 0.08% increased by more than a factor of three. A likelihood ratio test provides strong evidence that the change-point represents a real shift in the statistical behaviour of the time series. All but one of the seven catastrophic storms (PD/TGS > 0.2%) occurred since 1990. Additionally, we detected a related decrease in September-November PD/TGS and an increase in December-February PD/TGS. Our analyses point to the possibility that the impact of climate change on the North Atlantic storms hitting Europe has started during the last two and half decades.

Increasing large scale windstorm damage in Western, Central and Northern European forests, 1951–2010

PubMed Central

Gregow, H.; Laaksonen, A.; Alper, M. E.

2017-01-01

Using reports of forest losses caused directly by large scale windstorms (or primary damage, PD) from the European forest institute database (comprising 276 PD reports from 1951–2010), total growing stock (TGS) statistics of European forests and the daily North Atlantic Oscillation (NAO) index, we identify a statistically significant change in storm intensity in Western, Central and Northern Europe (17 countries). Using the validated set of storms, we found that the year 1990 represents a change-point at which the average intensity of the most destructive storms indicated by PD/TGS > 0.08% increased by more than a factor of three. A likelihood ratio test provides strong evidence that the change-point represents a real shift in the statistical behaviour of the time series. All but one of the seven catastrophic storms (PD/TGS > 0.2%) occurred since 1990. Additionally, we detected a related decrease in September–November PD/TGS and an increase in December–February PD/TGS. Our analyses point to the possibility that the impact of climate change on the North Atlantic storms hitting Europe has started during the last two and half decades. PMID:28401947

Use of change-point detection for friction-velocity threshold evaluation in eddy-covariance studies

Treesearch

A.G. Barr; A.D. Richardson; D.Y. Hollinger; D. Papale; M.A. Arain; T.A. Black; G. Bohrer; D. Dragoni; M.L. Fischer; L. Gu; B.E. Law; H.A. Margolis; J.H. McCaughey; J.W. Munger; W. Oechel; K. Schaeffer

2013-01-01

The eddy-covariance method often underestimates fluxes under stable, low-wind conditions at night when turbulence is not well developed. The most common approach to resolve the problem of nighttime flux underestimation is to identify and remove the deficit periods using friction-velocity (u∗) threshold filters (u∗

Performance analysis of ultrasono-therapy transducer with contact detection.

PubMed

Moreno, Eduardo; González, Gilberto; Leija, Lorenzo; Rodríguez, Orlando; Castillo, Martha; Fuentes, Martín

2003-06-01

The performance of ultrasono-therapy transducer with contact detection by using the impedance phase change is described. Usually a therapy transducer is designed with a lambda/2 frontal plate glued to a PZT-4 piezoceramic. This plate ensures a good mechanical protection of the piezoceramic with a corresponding high-transmission energy. Normally this transducer is operated at the minimum at the frequency of the impedance module of its input electric impedance, but this operation point is affected by the shift caused by the expected temperature increase. This shift could be higher than the narrow bandwidth presented. As a result we obtain a decrease in the power level for medical treatment. Usually it is designed electronic drivers with automatic control that follow the frequency change, but the relatively narrow bandwidth introduces difficulty in the design. Another frequency operation point is presented here and analyzed using the criteria of the maximum of the impedance phase with a wider bandwidth than in the previous case. Simulation with mechanical losses are presented with experimental results that show the convenience of this criteria for practical application.

Microarray characterization of gene expression changes in blood during acute ethanol exposure

PubMed Central

2013-01-01

Background As part of the civil aviation safety program to define the adverse effects of ethanol on flying performance, we performed a DNA microarray analysis of human whole blood samples from a five-time point study of subjects administered ethanol orally, followed by breathalyzer analysis, to monitor blood alcohol concentration (BAC) to discover significant gene expression changes in response to the ethanol exposure. Methods Subjects were administered either orange juice or orange juice with ethanol. Blood samples were taken based on BAC and total RNA was isolated from PaxGene™ blood tubes. The amplified cDNA was used in microarray and quantitative real-time polymerase chain reaction (RT-qPCR) analyses to evaluate differential gene expression. Microarray data was analyzed in a pipeline fashion to summarize and normalize and the results evaluated for relative expression across time points with multiple methods. Candidate genes showing distinctive expression patterns in response to ethanol were clustered by pattern and further analyzed for related function, pathway membership and common transcription factor binding within and across clusters. RT-qPCR was used with representative genes to confirm relative transcript levels across time to those detected in microarrays. Results Microarray analysis of samples representing 0%, 0.04%, 0.08%, return to 0.04%, and 0.02% wt/vol BAC showed that changes in gene expression could be detected across the time course. The expression changes were verified by qRT-PCR. The candidate genes of interest (GOI) identified from the microarray analysis and clustered by expression pattern across the five BAC points showed seven coordinately expressed groups. Analysis showed function-based networks, shared transcription factor binding sites and signaling pathways for members of the clusters. These include hematological functions, innate immunity and inflammation functions, metabolic functions expected of ethanol metabolism, and pancreatic and hepatic function. Five of the seven clusters showed links to the p38 MAPK pathway. Conclusions The results of this study provide a first look at changing gene expression patterns in human blood during an acute rise in blood ethanol concentration and its depletion because of metabolism and excretion, and demonstrate that it is possible to detect changes in gene expression using total RNA isolated from whole blood. The analysis approach for this study serves as a workflow to investigate the biology linked to expression changes across a time course and from these changes, to identify target genes that could serve as biomarkers linked to pilot performance. PMID:23883607

SU-E-T-144: Effective Analysis of VMAT QA Generated Trajectory Log Files for Medical Accelerator Predictive Maintenance

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

Able, CM; Baydush, AH; Nguyen, C

Purpose: To determine the effectiveness of SPC analysis for a model predictive maintenance process that uses accelerator generated parameter and performance data contained in trajectory log files. Methods: Each trajectory file is decoded and a total of 131 axes positions are recorded (collimator jaw position, gantry angle, each MLC, etc.). This raw data is processed and either axis positions are extracted at critical points during the delivery or positional change over time is used to determine axis velocity. The focus of our analysis is the accuracy, reproducibility and fidelity of each axis. A reference positional trace of the gantry andmore » each MLC is used as a motion baseline for cross correlation (CC) analysis. A total of 494 parameters (482 MLC related) were analyzed using Individual and Moving Range (I/MR) charts. The chart limits were calculated using a hybrid technique that included the use of the standard 3σ limits and parameter/system specifications. Synthetic errors/changes were introduced to determine the initial effectiveness of I/MR charts in detecting relevant changes in operating parameters. The magnitude of the synthetic errors/changes was based on: TG-142 and published analysis of VMAT delivery accuracy. Results: All errors introduced were detected. Synthetic positional errors of 2mm for collimator jaw and MLC carriage exceeded the chart limits. Gantry speed and each MLC speed are analyzed at two different points in the delivery. Simulated Gantry speed error (0.2 deg/sec) and MLC speed error (0.1 cm/sec) exceeded the speed chart limits. Gantry position error of 0.2 deg was detected by the CC maximum value charts. The MLC position error of 0.1 cm was detected by the CC maximum value location charts for every MLC. Conclusion: SPC I/MR evaluation of trajectory log file parameters may be effective in providing an early warning of performance degradation or component failure for medical accelerator systems.« less

Object-based analysis of multispectral airborne laser scanner data for land cover classification and map updating

NASA Astrophysics Data System (ADS)

Matikainen, Leena; Karila, Kirsi; Hyyppä, Juha; Litkey, Paula; Puttonen, Eetu; Ahokas, Eero

2017-06-01

During the last 20 years, airborne laser scanning (ALS), often combined with passive multispectral information from aerial images, has shown its high feasibility for automated mapping processes. The main benefits have been achieved in the mapping of elevated objects such as buildings and trees. Recently, the first multispectral airborne laser scanners have been launched, and active multispectral information is for the first time available for 3D ALS point clouds from a single sensor. This article discusses the potential of this new technology in map updating, especially in automated object-based land cover classification and change detection in a suburban area. For our study, Optech Titan multispectral ALS data over a suburban area in Finland were acquired. Results from an object-based random forests analysis suggest that the multispectral ALS data are very useful for land cover classification, considering both elevated classes and ground-level classes. The overall accuracy of the land cover classification results with six classes was 96% compared with validation points. The classes under study included building, tree, asphalt, gravel, rocky area and low vegetation. Compared to classification of single-channel data, the main improvements were achieved for ground-level classes. According to feature importance analyses, multispectral intensity features based on several channels were more useful than those based on one channel. Automatic change detection for buildings and roads was also demonstrated by utilising the new multispectral ALS data in combination with old map vectors. In change detection of buildings, an old digital surface model (DSM) based on single-channel ALS data was also used. Overall, our analyses suggest that the new data have high potential for further increasing the automation level in mapping. Unlike passive aerial imaging commonly used in mapping, the multispectral ALS technology is independent of external illumination conditions, and there are no shadows on intensity images produced from the data. These are significant advantages in developing automated classification and change detection procedures.

Pediatric vision screening using binocular retinal birefringencr scanning

NASA Astrophysics Data System (ADS)

Nassif, Deborah S.; Gramatikov, Boris; Guyton, David L.; Hunter, David G.

2003-07-01

Amblyopia, a leading cause of vision loss in childhood, is responsive to treatment if detected early in life. Risk factors for amblyopia, such as refractive error and strabismus, may be difficult to identify clinically in young children. Our laboratory has developed retinal birefringence scanning (RBS), in which a small spot of polarized light is scanned in a circle on the retina, and the returning light is measured for changes in polarization caused by the pattern of birefringent fibers that comprise the fovea. Binocular RBS (BRBS) detects the fixation of both eyes simultaneously and thus screens for strabismus, one of the risk factors of amblyopia. We have also developed a technique to automatically detect when the eye is in focus without measuring refractive error. This focus detection system utilizes a bull's eye photodetector optically conjugate to a point fixation source. Reflected light is focused back to the point source by the optical system of the eye, and if the subject focuses on the fixation source, the returning light will be focused on the detector. We have constructed a hand-held prototype combining BRBS and focus detection measurements in one quick (< 0.5 second) and accurate (theoretically detecting +/-1 of misalignment) measurement. This approach has the potential to reliably identify children at risk for amblyopia.

Multiplexed colorimetric detection of Kaposi's sarcoma associated herpesvirus and Bartonella DNA using gold and silver nanoparticles

NASA Astrophysics Data System (ADS)

Mancuso, Matthew; Jiang, Li; Cesarman, Ethel; Erickson, David

2013-01-01

Kaposi's sarcoma (KS) is an infectious cancer occurring most commonly in human immunodeficiency virus (HIV) positive patients and in endemic regions, such as Sub-Saharan Africa, where KS is among the top four most prevalent cancers. The cause of KS is the Kaposi's sarcoma-associated herpesvirus (KSHV, also called HHV-8), an oncogenic herpesvirus that while routinely diagnosed in developed nations, provides challenges to developing world medical providers and point-of-care detection. A major challenge in the diagnosis of KS is the existence of a number of other diseases with similar clinical presentation and histopathological features, requiring the detection of KSHV in a biopsy sample. In this work we develop an answer to this challenge by creating a multiplexed one-pot detection system for KSHV DNA and DNA from a frequently confounding disease, bacillary angiomatosis. Gold and silver nanoparticle aggregation reactions are tuned for each target and a multi-color change system is developed capable of detecting both targets down to levels between 1 nM and 2 nM. The system developed here could later be integrated with microfluidic sample processing to create a final device capable of solving the two major challenges in point-of-care KS detection.

Bayesian Inference for Functional Dynamics Exploring in fMRI Data.

PubMed

Guo, Xuan; Liu, Bing; Chen, Le; Chen, Guantao; Pan, Yi; Zhang, Jing

2016-01-01

This paper aims to review state-of-the-art Bayesian-inference-based methods applied to functional magnetic resonance imaging (fMRI) data. Particularly, we focus on one specific long-standing challenge in the computational modeling of fMRI datasets: how to effectively explore typical functional interactions from fMRI time series and the corresponding boundaries of temporal segments. Bayesian inference is a method of statistical inference which has been shown to be a powerful tool to encode dependence relationships among the variables with uncertainty. Here we provide an introduction to a group of Bayesian-inference-based methods for fMRI data analysis, which were designed to detect magnitude or functional connectivity change points and to infer their functional interaction patterns based on corresponding temporal boundaries. We also provide a comparison of three popular Bayesian models, that is, Bayesian Magnitude Change Point Model (BMCPM), Bayesian Connectivity Change Point Model (BCCPM), and Dynamic Bayesian Variable Partition Model (DBVPM), and give a summary of their applications. We envision that more delicate Bayesian inference models will be emerging and play increasingly important roles in modeling brain functions in the years to come.

Improving maximum power point tracking of partially shaded photovoltaic system by using IPSO-BELBIC

NASA Astrophysics Data System (ADS)

Al-Alim El-Garhy, M. Abd; Mubarak, R. I.; El-Bably, M.

2017-08-01

Solar photovoltaic (PV) arrays in remote applications are often related to the rapid changes in the partial shading pattern. Rapid changes of the partial shading pattern make the tracking of maximum power point (MPP) of the global peak through the local ones too difficult. An essential need to make a fast and efficient algorithm to detect the peaks values which always vary as the sun irradiance changes. This paper presents two algorithms based on the improved particle swarm optimization technique one of them with PID controller (IPSO-PID), and the other one with Brain Emotional Learning Based Intelligent Controller (IPSO-BELBIC). These techniques improve the maximum power point (MPP) tracking capabilities for photovoltaic (PV) system under partial shading circumstances. The main aim of these improved algorithms is to accelerate the velocity of IPSO to reach to (MPP) and increase its efficiency. These algorithms also improve the tracking time under complex irradiance conditions. Based on these conditions, the tracking time of these presented techniques improves to 2 msec, with an efficiency of 100%.

Electrokinetic Analysis of Cell Translocation in Low-Cost Microfluidic Cytometry for Tumor Cell Detection and Enumeration.

PubMed

Guo, Jinhong; Pui, Tze Sian; Ban, Yong-Ling; Rahman, Abdur Rub Abdur; Kang, Yuejun

2013-12-01

Conventional Coulter counters have been introduced as an important tool in biological cell assays since several decades ago. Recently, the emerging portable Coulter counter has demonstrated its merits in point of care diagnostics, such as on chip detection and enumeration of circulating tumor cells (CTC). The working principle is based on the cell translocation time and amplitude of electrical current change that the cell induces. In this paper, we provide an analysis of a Coulter counter that evaluates the hydrodynamic and electrokinetic properties of polystyrene microparticles in a microfluidic channel. The hydrodynamic force and electrokinetic force are concurrently analyzed to determine the translocation time and the electrical current pulses induced by the particles. Finally, we characterize the chip performance for CTC detection. The experimental results validate the numerical analysis of the microfluidic chip. The presented model can provide critical insight and guidance for developing micro-Coulter counter for point of care prognosis.

Detecting the tipping points in a three-state model of complex diseases by temporal differential networks.

PubMed

Chen, Pei; Li, Yongjun; Liu, Xiaoping; Liu, Rui; Chen, Luonan

2017-10-26

The progression of complex diseases, such as diabetes and cancer, is generally a nonlinear process with three stages, i.e., normal state, pre-disease state, and disease state, where the pre-disease state is a critical state or tipping point immediately preceding the disease state. Traditional biomarkers aim to identify a disease state by exploiting the information of differential expressions for the observed molecules, but may fail to detect a pre-disease state because there are generally little significant differences between the normal and pre-disease states. Thus, it is challenging to signal the pre-disease state, which actually implies the disease prediction. In this work, by exploiting the information of differential associations among the observed molecules between the normal and pre-disease states, we propose a temporal differential network based computational method to accurately signal the pre-disease state or predict the occurrence of severe disease. The theoretical foundation of this work is the quantification of the critical state using dynamical network biomarkers. Considering that there is one stationary Markov process before reaching the tipping point, a novel index, inconsistency score (I-score), is proposed to quantitatively measure the change of the stationary processes from the normal state so as to detect the onset of pre-disease state. In other words, a drastic increase of I-score implies the high inconsistency with the preceding stable state and thus signals the upcoming critical transition. This approach is applied to the simulated and real datasets of three diseases, which demonstrates the effectiveness of our method for predicting the deterioration into disease states. Both functional analysis and pathway enrichment also validate the computational results from the perspectives of both molecules and networks. At the molecular network level, this method provides a computational way of unravelling the underlying mechanism of the dynamical progression when a biological system is near the tipping point, and thus detecting the early-warning signal of the imminent critical transition, which may help to achieve timely intervention. Moreover, the rewiring of differential networks effectively extracts discriminatively interpretable features, and systematically demonstrates the dynamical change of a biological system.

Using peripheral blood circulating DNAs to detect CpG global methylation status and genetic mutations in patients with myelodysplastic syndrome

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

Iriyama, Chisako; Tomita, Akihiro, E-mail: atomita@med.nagoya-u.ac.jp; Hoshino, Hideaki

2012-03-23

Highlights: Black-Right-Pointing-Pointer Circulating DNAs (CDs) can be used to detect genetic/epigenetic abnormalities in MDS. Black-Right-Pointing-Pointer Epigenetic changes can be detected more sensitively when using plasma DNA than PBMNC. Black-Right-Pointing-Pointer Mutation ratio in CDs may reflect the ratio in stem cell population in bone marrow. Black-Right-Pointing-Pointer Using CDs can be a safer alternate strategy compared to bone marrow aspiration. -- Abstract: Myelodysplastic syndrome (MDS) is a hematopoietic stem cell disorder. Several genetic/epigenetic abnormalities are deeply associated with the pathogenesis of MDS. Although bone marrow (BM) aspiration is a common strategy to obtain MDS cells for evaluating their genetic/epigenetic abnormalities, BM aspirationmore » is difficult to perform repeatedly to obtain serial samples because of pain and safety concerns. Here, we report that circulating cell-free DNAs from plasma and serum of patients with MDS can be used to detect genetic/epigenetic abnormalities. The plasma DNA concentration was found to be relatively high in patients with higher blast cell counts in BM, and accumulation of DNA fragments from mono-/di-nucleosomes was confirmed. Using serial peripheral blood (PB) samples from patients treated with hypomethylating agents, global methylation analysis using bisulfite pyrosequencing was performed at the specific CpG sites of the LINE-1 promoter. The results confirmed a decrease of the methylation percentage after treatment with azacitidine (days 3-9) using DNAs from plasma, serum, and PB mono-nuclear cells (PBMNC). Plasma DNA tends to show more rapid change at days 3 and 6 compared with serum DNA and PBMNC. Furthermore, the TET2 gene mutation in DNAs from plasma, serum, and BM cells was quantitated by pyrosequencing analysis. The existence ratio of mutated genes in plasma and serum DNA showed almost equivalent level with that in the CD34+/38- stem cell population in BM. These data suggest that genetic/epigenetic analyses using PB circulating DNA can be a safer and painless alternative to using BM cells.« less

Process and apparatus for measuring degree of polarization and angle of major axis of polarized beam of light

DOEpatents

Decker, Derek E.; Toeppen, John S.

1994-01-01

Apparatus and process are disclosed for calibrating measurements of the phase of the polarization of a polarized beam and the angle of the polarized optical beam's major axis of polarization at a diagnostic point with measurements of the same parameters at a point of interest along the polarized beam path prior to the diagnostic point. The process is carried out by measuring the phase angle of the polarization of the beam and angle of the major axis at the point of interest, using a rotatable polarizer and a detector, and then measuring these parameters again at a diagnostic point where a compensation apparatus, including a partial polarizer, which may comprise a stack of glass plates, is disposed normal to the beam path between a rotatable polarizer and a detector. The partial polarizer is then rotated both normal to the beam path and around the axis of the beam path until the detected phase of the beam polarization equals the phase measured at the point of interest. The rotatable polarizer at the diagnostic point may then be rotated manually to determine the angle of the major axis of the beam and this is compared with the measured angle of the major axis of the beam at the point of interest during calibration. Thereafter, changes in the polarization phase, and in the angle of the major axis, at the point of interest can be monitored by measuring the changes in these same parameters at the diagnostic point.

Ecological scale of bird community response to piñon-juniper removal

USGS Publications Warehouse

Knick, Steven T.; Hanser, Steven E.; Leu, Matthias

2014-01-01

Piñon (Pinus spp.) and juniper (Juniperus spp.) removal is a common management approach to restore sagebrush (Artemisia spp.) vegetation in areas experiencing woodland expansion. Because many management treatments are conducted to benefit sagebrush-obligate birds, we surveyed bird communities to assess treatment effectiveness in establishing sagebrush bird communities at study sites in Utah, Nevada, Idaho, and Oregon. Our analyses included data from 1 or 2 yr prior to prescribed fire or mechanical treatment and 3 to 5 yr posttreatment. We used detrended correspondence analysis to 1) identify primary patterns of bird communities surveyed from 2006 to 2011 at point transects, 2) estimate ecological scale of change needed to achieve treatment objectives from the relative dissimilarity of survey points to the ordination region delineating sagebrush bird communities, and 3) measure changes in pre- and posttreatment bird communities. Birds associated with sagebrush, woodlands, and ecotones were detected on our surveys; increased dissimilarity of survey points to the sagebrush bird community was characterized by a gradient of increased juniper and decreased sagebrush cover. Prescribed fires burned between 30% and 97% of our bird survey points. However, from 6% to 24% cover of piñon-juniper still remained posttreatment on the four treatment plots. We measured only slight changes in bird communities, which responded primarily to current vegetation rather than relative amount of change from pretreatment vegetation structure. Bird communities at survey points located at greater ecological scales from the sagebrush bird community changed least and will require more significant impact to achieve changes. Sagebrush bird communities were established at only two survey points, which were adjacent to a larger sagebrush landscape and following almost complete juniper removal by mechanical treatment. Our results indicate that management treatments that leave residual woodland cover and are not adjacent to extensive sagebrush stands are unlikely to establish sagebrush birds.

Near Real Time Change-Point detection in Optical and Thermal Infrared Time Series Using Bayesian Inference over the Dry Chaco Forest

NASA Astrophysics Data System (ADS)

Barraza Bernadas, V.; Grings, F.; Roitberg, E.; Perna, P.; Karszenbaum, H.

2017-12-01

The Dry Chaco region (DCF) has the highest absolute deforestation rates of all Argentinian forests. The most recent report indicates a current deforestation rate of 200,000 Ha year-1. In order to better monitor this process, DCF was chosen to implement an early warning program for illegal deforestation. Although the area is intensively studied using medium resolution imagery (Landsat), the products obtained have a yearly pace and therefore unsuited for an early warning program. In this paper, we evaluated the performance of an online Bayesian change-point detection algorithm for MODIS Enhanced Vegetation Index (EVI) and Land Surface Temperature (LST) datasets. The goal was to to monitor the abrupt changes in vegetation dynamics associated with deforestation events. We tested this model by simulating 16-day EVI and 8-day LST time series with varying amounts of seasonality, noise, length of the time series and by adding abrupt changes with different magnitudes. This model was then tested on real satellite time series available through the Google Earth Engine, over a pilot area in DCF, where deforestation was common in the 2004-2016 period. A comparison with yearly benchmark products based on Landsat images is also presented (REDAF dataset). The results shows the advantages of using an automatic model to detect a changepoint in the time series than using only visual inspection techniques. Simulating time series with varying amounts of seasonality and noise, and by adding abrupt changes at different times and magnitudes, revealed that this model is robust against noise, and is not influenced by changes in amplitude of the seasonal component. Furthermore, the results compared favorably with REDAF dataset (near 65% of agreement). These results show the potential to combine LST and EVI to identify deforestation events. This work is being developed within the frame of the national Forest Law for the protection and sustainable development of Native Forest in Argentina in agreement with international legislation (REDD+).

Hydrogen gas concentration measurement in small area using raman lidar measurement technnology

NASA Astrophysics Data System (ADS)

Sugimoto, Sachiyo; Asahi, Ippei; Shiina, Tatuso

2018-04-01

When change of hydrogen(H2) gas concentration in a certain point is measured, non-contact measurement technology with high temporal and spatial resolution is necessary. In this study, H2 concentration in the small area of <1cm2 under the gas flow was measured by using a Raman lidar. Raman scattering light at the measurement point of 750mm ahead was detected by the Raman lidar. As a result, it was proved that the H2 concentration of more than 100ppm could be successfully measured.

SAR Interferometry as a Tool for Monitoring Coastal Changes in the Nile River Delta of Egypt

NASA Technical Reports Server (NTRS)

Aly, Mohamed H.; Klein, Andrew G.; Giardino, John R.

2005-01-01

The Nile River Delta is experiencing rapid rates of coastal change. The rate of both coastal retreat and accretion in the Eastern Nile Delta requires regular, accurate detection and measurement. Current techniques used to monitor coastal changes in the delta are point measurements and, thus, they provide a spatially limited view of the ongoing coastal changes. SAR interferometry can provide measurements of subtle coastal change at a significantly improved spatial resolution and over large areas (100 sq km). Using data provided by the ERS-1&2 satellites, monitoring can be accomplished as frequently as every 35 days when needed. Radar interferometry is employed in this study to detect segments of erosion and accretion during the 1993-2000 period. The average rates of erosion and accretion in the Eastern Nile Delta are measured to be -11.64 m/yr and +5.12 m/yr, respectively. The results of this interferometric study can be used effectively for coastal zone management and integrated sustainable development for the Nile River Delta.

Critical slowing down as early warning for the onset of collapse in mutualistic communities.

PubMed

Dakos, Vasilis; Bascompte, Jordi

2014-12-09

Tipping points are crossed when small changes in external conditions cause abrupt unexpected responses in the current state of a system. In the case of ecological communities under stress, the risk of approaching a tipping point is unknown, but its stakes are high. Here, we test recently developed critical slowing-down indicators as early-warning signals for detecting the proximity to a potential tipping point in structurally complex ecological communities. We use the structure of 79 empirical mutualistic networks to simulate a scenario of gradual environmental change that leads to an abrupt first extinction event followed by a sequence of species losses until the point of complete community collapse. We find that critical slowing-down indicators derived from time series of biomasses measured at the species and community level signal the proximity to the onset of community collapse. In particular, we identify specialist species as likely the best-indicator species for monitoring the proximity of a community to collapse. In addition, trends in slowing-down indicators are strongly correlated to the timing of species extinctions. This correlation offers a promising way for mapping species resilience and ranking species risk to extinction in a given community. Our findings pave the road for combining theory on tipping points with patterns of network structure that might prove useful for the management of a broad class of ecological networks under global environmental change.

Psychometric Properties of the Quantitative Myasthenia Gravis Score and the Myasthenia Gravis Composite Scale.

PubMed

Barnett, Carolina; Merkies, Ingemar S J; Katzberg, Hans; Bril, Vera

2015-09-02

The Quantitative Myasthenia Gravis Score and the Myasthenia Gravis Composite are two commonly used outcome measures in Myasthenia Gravis. So far, their measurement properties have not been compared, so we aimed to study their psychometric properties using the Rasch model. 251 patients with stable myasthenia gravis were assessed with both scales, and 211 patients returned for a second assessment. We studied fit to the Rasch model at the first visit, and compared item fit, thresholds, differential item functioning, local dependence, person separation index, and tests for unidimensionality. We also assessed test-retest reliability and estimated the Minimal Detectable Change. Neither scale fit the Rasch model (X2p <  0.05). The Myasthenia Gravis Composite had lower discrimination properties than the Quantitative Myasthenia Gravis Scale (Person Separation Index: 0.14 and 0.7). There was local dependence in both scales, as well as differential item functioning for ocular and generalized disease. Disordered thresholds were found in 6(60%) items of the Myasthenia Gravis Composite and in 4(31%) of the Quantitative Myasthenia Gravis Score. Both tools had adequate test-retest reliability (ICCs >0.8). The minimally detectable change was 4.9 points for the Myasthenia Gravis Composite and 4.3 points for the Quantitative Myasthenia Gravis Score. Neither scale fulfilled Rasch model expectations. The Quantitative Myasthenia Gravis Score has higher discrimination than the Myasthenia Gravis Composite. Both tools have items with disordered thresholds, differential item functioning and local dependency. There was evidence of multidimensionality in the QMGS. The minimal detectable change values are higher than previous studies on the minimal significant change. These findings might inform future modifications of these tools.

Diagnostic value of ST-segment deviations during cardiac exercise stress testing: Systematic comparison of different ECG leads and time-points.

PubMed

Puelacher, Christian; Wagener, Max; Abächerli, Roger; Honegger, Ursina; Lhasam, Nundsin; Schaerli, Nicolas; Prêtre, Gil; Strebel, Ivo; Twerenbold, Raphael; Boeddinghaus, Jasper; Nestelberger, Thomas; Rubini Giménez, Maria; Hillinger, Petra; Wildi, Karin; Sabti, Zaid; Badertscher, Patrick; Cupa, Janosch; Kozhuharov, Nikola; du Fay de Lavallaz, Jeanne; Freese, Michael; Roux, Isabelle; Lohrmann, Jens; Leber, Remo; Osswald, Stefan; Wild, Damian; Zellweger, Michael J; Mueller, Christian; Reichlin, Tobias

2017-07-01

Exercise ECG stress testing is the most widely available method for evaluation of patients with suspected myocardial ischemia. Its major limitation is the relatively poor accuracy of ST-segment changes regarding ischemia detection. Little is known about the optimal method to assess ST-deviations. A total of 1558 consecutive patients undergoing bicycle exercise stress myocardial perfusion imaging (MPI) were enrolled. Presence of inducible myocardial ischemia was adjudicated using MPI results. The diagnostic value of ST-deviations for detection of exercise-induced myocardial ischemia was systematically analyzed 1) for each individual lead, 2) at three different intervals after the J-point (J+40ms, J+60ms, J+80ms), and 3) at different time points during the test (baseline, maximal workload, 2min into recovery). Exercise-induced ischemia was detected in 481 (31%) patients. The diagnostic accuracy of ST-deviations was highest at +80ms after the J-point, and at 2min into recovery. At this point, ST-amplitude showed an AUC of 0.63 (95% CI 0.59-0.66) for the best-performing lead I. The combination of ST-amplitude and ST-slope in lead I did not increase the AUC. Lead I reached a sensitivity of 37% and a specificity of 83%, with similar sensitivity to manual ECG analysis (34%, p=0.31) but lower specificity (90%, p<0.001). When using ECG stress testing for evaluation of patients with suspected myocardial ischemia, the diagnostic accuracy of ST-deviations is highest when evaluated at +80ms after the J-point, and at 2min into recovery. Copyright © 2017 Elsevier B.V. All rights reserved.

Comparison of Two Methods for Estimating Adjustable One-Point Cane Length in Community-Dwelling Older Adults.

PubMed

Camara, Camila Thais Pinto; de Freitas, Sandra Maria Sbeghen Ferreira; de Lima, Waléria Paixão; Lima, Camila Astolphi; Amorim, César Ferreira; Perracini, Monica Rodrigues

2017-01-01

Our aim is to estimate inter-observer reliability, test-retest reliability, anthropometric and biomechanical adequacy and minimal detectable change when measuring the length of single-point adjustable canes in community-dwelling older adults. There are 112 participants in the study. They are men and women, aged 60 years and over, who were attending an outpatient community health centre. An exploratory study design was used. Participants underwent two assessments within the same day by two independent observers and by the same observer at an interval of 15-45 days. Two measures were used to establish the length of a single-point adjustable cane: the distance from the distal wrist crease to the floor (WF) and the distance from the top of the greater trochanter of the femur to the floor (TF). Each individual was fitted according to these two measures, and elbow flexion angle was measured. Inter-observer reliability and the test-retest reliability were high in both TF (ICC 3.1  = 0.918 and ICC 2.1  = 0.935) and WF measures (ICC 3.1  = 0.967 and ICC 2.1  = 0.960). Only 1% of the individuals kept an elbow flexion angle within the standard recommendation of 30° ± 10° when the cane length was determined by the TF measure, and 30% of the participants when the cane was determined by the WF measure. The minimal detectable cane length change was 2.2 cm. Our results suggest that, even though both measures are reliable, cane length determined by WF distance is more appropriate to keep the elbow flexion angle within the standard recommendation. The minimal detectable change corresponds to approximately a hole in the cane adjustment. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

A Personal Storm Warning Service

NASA Technical Reports Server (NTRS)

1994-01-01

Although lightning detection systems operated by government agencies, utilities and other businesses provide storm warnings, this information often does not reach the public until some time after the observations have been made. A low-cost personal lightning detector offers a significant safety advantage to private flyers, boaters, golfers and others. Developed by Airborne Research Associates, the detectors originated in Space Shuttle tests of an optical lightning detection technique. The commercial device is pointed toward a cloud to detect invisible intracloud lightning by sensing subtle changes in light presence. The majority of the sales have been to golf courses. Additional products and more advanced applications are in progress.

Dynamic changes in brain activity during prism adaptation.

PubMed

Luauté, Jacques; Schwartz, Sophie; Rossetti, Yves; Spiridon, Mona; Rode, Gilles; Boisson, Dominique; Vuilleumier, Patrik

2009-01-07

Prism adaptation does not only induce short-term sensorimotor plasticity, but also longer-term reorganization in the neural representation of space. We used event-related fMRI to study dynamic changes in brain activity during both early and prolonged exposure to visual prisms. Participants performed a pointing task before, during, and after prism exposure. Measures of trial-by-trial pointing errors and corrections allowed parametric analyses of brain activity as a function of performance. We show that during the earliest phase of prism exposure, anterior intraparietal sulcus was primarily implicated in error detection, whereas parieto-occipital sulcus was implicated in error correction. Cerebellum activity showed progressive increases during prism exposure, in accordance with a key role for spatial realignment. This time course further suggests that the cerebellum might promote neural changes in superior temporal cortex, which was selectively activated during the later phase of prism exposure and could mediate the effects of prism adaptation on cognitive spatial representations.

Water Vapor Uptake of Ultrathin Films of Biologically Derived Nanocrystals: Quantitative Assessment with Quartz Crystal Microbalance and Spectroscopic Ellipsometry.

PubMed

Niinivaara, Elina; Faustini, Marco; Tammelin, Tekla; Kontturi, Eero

2015-11-10

Despite the relevance of water interactions, explicit analysis of vapor adsorption on biologically derived surfaces is often difficult. Here, a system was introduced to study the vapor uptake on a native polysaccharide surface; namely, cellulose nanocrystal (CNC) ultrathin films were examined with a quartz crystal microbalance with dissipation monitoring (QCM-D) and spectroscopic ellipsometry (SE). A significant mass uptake of water vapor by the CNC films was detected using the QCM-D upon increasing relative humidity. In addition, thickness changes proportional to changes in relative humidity were detected using SE. Quantitative analysis of the results attained indicated that in preference to being soaked by water at the point of hydration each individual CNC in the film became enveloped by a 1 nm thick layer of adsorbed water vapor, resulting in the detected thickness response.

Cloud-point detection using a portable thickness shear mode crystal resonator

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

Mansure, A.J.; Spates, J.J.; Germer, J.W.

1997-08-01

The Thickness Shear Mode (TSM) crystal resonator monitors the crude oil by propagating a shear wave into the oil. The coupling of the shear wave and the crystal vibrations is a function of the viscosity of the oil. By driving the crystal with circuitry that incorporates feedback, it is possible to determine the change from Newtonian to non-Newtonian viscosity at the cloud point. A portable prototype TSM Cloud Point Detector (CPD) has performed flawlessly during field and lab tests proving the technique is less subjective or operator dependent than the ASTM standard. The TSM CPD, in contrast to standard viscositymore » techniques, makes the measurement in a closed container capable of maintaining up to 100 psi. The closed container minimizes losses of low molecular weight volatiles, allowing samples (25 ml) to be retested with the addition of chemicals. By cycling/thermal soaking the sample, the effects of thermal history can be investigated and eliminated as a source of confusion. The CPD is portable, suitable for shipping the field offices for use by personnel without special training or experience in cloud point measurements. As such, it can make cloud point data available without the delays and inconvenience of sending samples to special labs. The crystal resonator technology can be adapted to in-line monitoring of cloud point and deposition detection.« less

Last millennium Northern Hemisphere summer temperatures from tree rings: Part II, spatially resolved reconstructions

NASA Astrophysics Data System (ADS)

Anchukaitis, Kevin J.; Wilson, Rob; Briffa, Keith R.; Büntgen, Ulf; Cook, Edward R.; D'Arrigo, Rosanne; Davi, Nicole; Esper, Jan; Frank, David; Gunnarson, Björn E.; Hegerl, Gabi; Helama, Samuli; Klesse, Stefan; Krusic, Paul J.; Linderholm, Hans W.; Myglan, Vladimir; Osborn, Timothy J.; Zhang, Peng; Rydval, Milos; Schneider, Lea; Schurer, Andrew; Wiles, Greg; Zorita, Eduardo

2017-05-01

Climate field reconstructions from networks of tree-ring proxy data can be used to characterize regional-scale climate changes, reveal spatial anomaly patterns associated with atmospheric circulation changes, radiative forcing, and large-scale modes of ocean-atmosphere variability, and provide spatiotemporal targets for climate model comparison and evaluation. Here we use a multiproxy network of tree-ring chronologies to reconstruct spatially resolved warm season (May-August) mean temperatures across the extratropical Northern Hemisphere (40-90°N) using Point-by-Point Regression (PPR). The resulting annual maps of temperature anomalies (750-1988 CE) reveal a consistent imprint of volcanism, with 96% of reconstructed grid points experiencing colder conditions following eruptions. Solar influences are detected at the bicentennial (de Vries) frequency, although at other time scales the influence of insolation variability is weak. Approximately 90% of reconstructed grid points show warmer temperatures during the Medieval Climate Anomaly when compared to the Little Ice Age, although the magnitude varies spatially across the hemisphere. Estimates of field reconstruction skill through time and over space can guide future temporal extension and spatial expansion of the proxy network.

LSI-based amperometric sensor for bio-imaging and multi-point biosensing.

PubMed

Inoue, Kumi Y; Matsudaira, Masahki; Kubo, Reyushi; Nakano, Masanori; Yoshida, Shinya; Matsuzaki, Sakae; Suda, Atsushi; Kunikata, Ryota; Kimura, Tatsuo; Tsurumi, Ryota; Shioya, Toshihito; Ino, Kosuke; Shiku, Hitoshi; Satoh, Shiro; Esashi, Masayoshi; Matsue, Tomokazu

2012-09-21

We have developed an LSI-based amperometric sensor called "Bio-LSI" with 400 measurement points as a platform for electrochemical bio-imaging and multi-point biosensing. The system is comprised of a 10.4 mm × 10.4 mm CMOS sensor chip with 20 × 20 unit cells, an external circuit box, a control unit for data acquisition, and a DC power box. Each unit cell of the chip contains an operational amplifier with a switched-capacitor type I-V converter for in-pixel signal amplification. We successfully realized a wide dynamic range from ±1 pA to ±100 nA with a well-organized circuit design and operating software. In particular, in-pixel signal amplification and an original program to control the signal read-out contribute to the lower detection limit and wide detection range of Bio-LSI. The spacial resolution is 250 μm and the temporal resolution is 18-125 ms/400 points, which depends on the desired current detection range. The coefficient of variance of the current for 400 points is within 5%. We also demonstrated the real-time imaging of a biological molecule using Bio-LSI. The LSI coated with an Os-HRP film was successfully applied to the monitoring of the changes of hydrogen peroxide concentration in a flow. The Os-HRP-coated LSI was spotted with glucose oxidase and used for bioelectrochemical imaging of the glucose oxidase (GOx)-catalyzed oxidation of glucose. Bio-LSI is a promising platform for a wide range of analytical fields, including diagnostics, environmental measurements and basic biochemistry.

Rapid, Affordable, and Point-of-Care Water Monitoring Via a Microfluidic DNA Sensor and a Mobile Interface for Global Health

PubMed Central

Ghanbari, Sarah; Ravikumar, Anusha; Seubert, John; Figueira, Silvia

2013-01-01

Contaminated water is a serious concern in many developing countries with severe health consequences particularly for children. Current methods for monitoring waterborne pathogens are often time consuming, expensive, and labor intensive, making them not suitable for these regions. Electrochemical detection in a microfluidic platform offers many advantages such as portability, minimal use of instrumentation, and easy integration with electronics. In many parts of the world, however, the required equipment for pathogen detection through electrochemical sensors is either not available or insufficiently portable, and operators may not be trained to use these sensors and interpret results, ultimately preventing its wide adoption. Counterintuitively, these same regions often have an extensive mobile phone infrastructure, suggesting the possibility of integrating electrochemical detection of bacterial pathogens with a mobile platform. Toward a solution to water quality interventions, we demonstrate a microfluidic electrochemical sensor combined with a mobile interface that detects the sequences from bacterial pathogens, suitable for rapid, affordable, and point-of-care water monitoring. We employ the transduction of DNA hybridization into a readily detectable electric signal by means of a conformational change of DNA stem-loop structure. Using this platform, we successfully demonstrate the detection of as low as 100 nM E. coli sequences and the automatic interpretation and mapping of the detection results via a mobile application. PMID:27170858

Application of fluorescence spectroscopy and imaging in the detection of a photosensitizer in photodynamic therapy

NASA Astrophysics Data System (ADS)

Zang, Lixin; Zhao, Huimin; Zhang, Zhiguo; Cao, Wenwu

2017-02-01

Photodynamic therapy (PDT) is currently an advanced optical technology in medical applications. However, the application of PDT is limited by the detection of photosensitizers. This work focuses on the application of fluorescence spectroscopy and imaging in the detection of an effective photosenzitizer, hematoporphyrin monomethyl ether (HMME). Optical properties of HMME were measured and analyzed based on its absorption and fluorescence spectra. The production mechanism of its fluorescence emission was analyzed. The detection device for HMME based on fluorescence spectroscopy was designed. Ratiometric method was applied to eliminate the influence of intensity change of excitation sources, fluctuates of excitation sources and photo detectors, and background emissions. The detection limit of this device is 6 μg/L, and it was successfully applied to the diagnosis of the metabolism of HMME in the esophageal cancer cells. To overcome the limitation of the point measurement using fluorescence spectroscopy, a two-dimensional (2D) fluorescence imaging system was established. The algorithm of the 2D fluorescence imaging system is deduced according to the fluorescence ratiometric method using bandpass filters. The method of multiple pixel point addition (MPPA) was used to eliminate fluctuates of signals. Using the method of MPPA, SNR was improved by about 30 times. The detection limit of this imaging system is 1.9 μg/L. Our systems can be used in the detection of porphyrins to improve the PDT effect.

Change Detection in Uav Video Mosaics Combining a Feature Based Approach and Extended Image Differencing

NASA Astrophysics Data System (ADS)

Saur, Günter; Krüger, Wolfgang

2016-06-01

Change detection is an important task when using unmanned aerial vehicles (UAV) for video surveillance. We address changes of short time scale using observations in time distances of a few hours. Each observation (previous and current) is a short video sequence acquired by UAV in near-Nadir view. Relevant changes are, e.g., recently parked or moved vehicles. Examples for non-relevant changes are parallaxes caused by 3D structures of the scene, shadow and illumination changes, and compression or transmission artifacts. In this paper we present (1) a new feature based approach to change detection, (2) a combination with extended image differencing (Saur et al., 2014), and (3) the application to video sequences using temporal filtering. In the feature based approach, information about local image features, e.g., corners, is extracted in both images. The label "new object" is generated at image points, where features occur in the current image and no or weaker features are present in the previous image. The label "vanished object" corresponds to missing or weaker features in the current image and present features in the previous image. This leads to two "directed" change masks and differs from image differencing where only one "undirected" change mask is extracted which combines both label types to the single label "changed object". The combination of both algorithms is performed by merging the change masks of both approaches. A color mask showing the different contributions is used for visual inspection by a human image interpreter.

Adapting End Host Congestion Control for Mobility

NASA Technical Reports Server (NTRS)

Eddy, Wesley M.; Swami, Yogesh P.

2005-01-01

Network layer mobility allows transport protocols to maintain connection state, despite changes in a node's physical location and point of network connectivity. However, some congestion-controlled transport protocols are not designed to deal with these rapid and potentially significant path changes. In this paper we demonstrate several distinct problems that mobility-induced path changes can create for TCP performance. Our premise is that mobility events indicate path changes that require re-initialization of congestion control state at both connection end points. We present the application of this idea to TCP in the form of a simple solution (the Lightweight Mobility Detection and Response algorithm, that has been proposed in the IETF), and examine its effectiveness. In general, we find that the deficiencies presented are both relatively easily and painlessly fixed using this solution. We also find that this solution has the counter-intuitive property of being both more friendly to competing traffic, and simultaneously more aggressive in utilizing newly available capacity than unmodified TCP.

A fast image matching algorithm based on key points

NASA Astrophysics Data System (ADS)

Wang, Huilin; Wang, Ying; An, Ru; Yan, Peng

2014-05-01

Image matching is a very important technique in image processing. It has been widely used for object recognition and tracking, image retrieval, three-dimensional vision, change detection, aircraft position estimation, and multi-image registration. Based on the requirements of matching algorithm for craft navigation, such as speed, accuracy and adaptability, a fast key point image matching method is investigated and developed. The main research tasks includes: (1) Developing an improved celerity key point detection approach using self-adapting threshold of Features from Accelerated Segment Test (FAST). A method of calculating self-adapting threshold was introduced for images with different contrast. Hessian matrix was adopted to eliminate insecure edge points in order to obtain key points with higher stability. This approach in detecting key points has characteristics of small amount of computation, high positioning accuracy and strong anti-noise ability; (2) PCA-SIFT is utilized to describe key point. 128 dimensional vector are formed based on the SIFT method for the key points extracted. A low dimensional feature space was established by eigenvectors of all the key points, and each eigenvector was projected onto the feature space to form a low dimensional eigenvector. These key points were re-described by dimension-reduced eigenvectors. After reducing the dimension by the PCA, the descriptor was reduced to 20 dimensions from the original 128. This method can reduce dimensions of searching approximately near neighbors thereby increasing overall speed; (3) Distance ratio between the nearest neighbour and second nearest neighbour searching is regarded as the measurement criterion for initial matching points from which the original point pairs matched are obtained. Based on the analysis of the common methods (e.g. RANSAC (random sample consensus) and Hough transform cluster) used for elimination false matching point pairs, a heuristic local geometric restriction strategy is adopted to discard false matched point pairs further; and (4) Affine transformation model is introduced to correct coordinate difference between real-time image and reference image. This resulted in the matching of the two images. SPOT5 Remote sensing images captured at different date and airborne images captured with different flight attitude were used to test the performance of the method from matching accuracy, operation time and ability to overcome rotation. Results show the effectiveness of the approach.

Chronic Ethanol Exposure Produces Time- and Brain Region-Dependent Changes in Gene Coexpression Networks

PubMed Central

Osterndorff-Kahanek, Elizabeth A.; Becker, Howard C.; Lopez, Marcelo F.; Farris, Sean P.; Tiwari, Gayatri R.; Nunez, Yury O.; Harris, R. Adron; Mayfield, R. Dayne

2015-01-01

Repeated ethanol exposure and withdrawal in mice increases voluntary drinking and represents an animal model of physical dependence. We examined time- and brain region-dependent changes in gene coexpression networks in amygdala (AMY), nucleus accumbens (NAC), prefrontal cortex (PFC), and liver after four weekly cycles of chronic intermittent ethanol (CIE) vapor exposure in C57BL/6J mice. Microarrays were used to compare gene expression profiles at 0-, 8-, and 120-hours following the last ethanol exposure. Each brain region exhibited a large number of differentially expressed genes (2,000-3,000) at the 0- and 8-hour time points, but fewer changes were detected at the 120-hour time point (400-600). Within each region, there was little gene overlap across time (~20%). All brain regions were significantly enriched with differentially expressed immune-related genes at the 8-hour time point. Weighted gene correlation network analysis identified modules that were highly enriched with differentially expressed genes at the 0- and 8-hour time points with virtually no enrichment at 120 hours. Modules enriched for both ethanol-responsive and cell-specific genes were identified in each brain region. These results indicate that chronic alcohol exposure causes global ‘rewiring‘ of coexpression systems involving glial and immune signaling as well as neuronal genes. PMID:25803291

Reliable landmarks for precise topographical analyses of pathological structural changes of the ovine tibial plateau in 2-D and 3-D subspaces.

PubMed

Oláh, Tamás; Reinhard, Jan; Gao, Liang; Goebel, Lars K H; Madry, Henning

2018-01-08

Selecting identical topographical locations to analyse pathological structural changes of the osteochondral unit in translational models remains difficult. The specific aim of the study was to provide objectively defined reference points on the ovine tibial plateau based on 2-D sections of micro-CT images useful for reproducible sample harvesting and as standardized landmarks for landmark-based 3-D image registration. We propose 5 reference points, 11 reference lines and 12 subregions that are detectable macroscopically and on 2-D micro-CT sections. Their value was confirmed applying landmark-based rigid and affine 3-D registration methods. Intra- and interobserver comparison showed high reliabilities, and constant positions (standard errors < 1%). Spatial patterns of the thicknesses of the articular cartilage and subchondral bone plate were revealed by measurements in 96 individual points of the tibial plateau. As a case study, pathological phenomena 6 months following OA induction in vivo such as osteophytes and areas of OA development were mapped to the individual subregions. These new reference points and subregions are directly identifiable on tibial plateau specimens or macroscopic images, enabling a precise topographical location of pathological structural changes of the osteochondral unit in both 2-D and 3-D subspaces in a region-appropriate fashion relevant for translational investigations.

Fully electronic urine dipstick probe for combinatorial detection of inflammatory biomarkers

PubMed Central

Kamakoti, Vikramshankar; Kinnamon, David; Choi, Kang Hyeok; Jagannath, Badrinath; Prasad, Shalini

2018-01-01

Aim: An electrochemical urine dipstick probe biosensor has been demonstrated using molybdenum electrodes on nanoporous polyamide substrate for the quantitative detection of two inflammatory protein biomarkers, CRP and IL-6. Materials & methods: The electrode interface was characterized using ζ-potential and Fourier transform infrared spectroscopy. Detection of biomarkers was demonstrated by measuring impedance changes associated with the dose concentrations of the two biomarkers. A proof of feasibility of point-of-care implementation of the biosensor was demonstrated using a portable electronics platform. Results & conclusion: Limit of detection of 1 pg/ml was achieved for CRP and IL-6 in human urine and synthetic urine buffers. The developed portable hardware demonstrated close correlation with benchtop equipment results. PMID:29796304

Highly sensitive and specific colorimetric detection of cancer cells via dual-aptamer target binding strategy.

PubMed

Wang, Kun; Fan, Daoqing; Liu, Yaqing; Wang, Erkang

2015-11-15

Simple, rapid, sensitive and specific detection of cancer cells is of great importance for early and accurate cancer diagnostics and therapy. By coupling nanotechnology and dual-aptamer target binding strategies, we developed a colorimetric assay for visually detecting cancer cells with high sensitivity and specificity. The nanotechnology including high catalytic activity of PtAuNP and magnetic separation & concentration plays a vital role on the signal amplification and improvement of detection sensitivity. The color change caused by small amount of target cancer cells (10 cells/mL) can be clearly distinguished by naked eyes. The dual-aptamer target binding strategy guarantees the detection specificity that large amount of non-cancer cells and different cancer cells (10(4) cells/mL) cannot cause obvious color change. A detection limit as low as 10 cells/mL with detection linear range from 10 to 10(5) cells/mL was reached according to the experimental detections in phosphate buffer solution as well as serum sample. The developed enzyme-free and cost effective colorimetric assay is simple and no need of instrument while still provides excellent sensitivity, specificity and repeatability, having potential application on point-of-care cancer diagnosis. Copyright © 2015 Elsevier B.V. All rights reserved.

Which homogenisation method is appropriate for daily time series of relative humidity?

NASA Astrophysics Data System (ADS)

Chimani, Barbara; Nemec, Johanna; Auer, Ingeborg; Venema, Victor

2014-05-01

Data homogenisation is an essential part of reliable climate data analyses. Different tools for detecting and adjusting breaks in daily extreme temperatures (Tmin, Tmax) and daily precipitation sums were developed in the last years. Due to its influence on health, plants and construction relative humidity is another parameter of great importance. On the basis of 6 networks of measured (and homogenized with respect to the monthly means) relative humidity data, which cover different climatic areas in Austria, a synthetic data set for testing and validating homogenisation methods was built. Each network consists of 4 to 6 station time series with a minimum length of 5 years. The so-called surrogate networks resemble the statistical properties (e.g. distribution of parameter, auto- and cross correlation within the network) of the measured time series, but are extended to 100 year long time series, which are in a first step assumed to be homogeneous. For creating the best possible surrogate dataset of relative humidity detailed statistical information on potential inhomogeneities is decisive. Information on the potential breaks was taken from parallel measurements available for some Austrian locations, mostly representing changes in instrumentation and/or station relocation. Beside changes in the distribution of the parameter the analyses includes an estimation of changes in the number of missing data, global and local biases, both on a seasonal and annual basis. An additional break is to be expected in the Austrian time series due to a change in observation time in 1970/1971. Since this change occurred simultaneously at all Austrian climate stations, standard homogenisation methods, which rely on a comparison with reference stations, are not able to detect or correct this shift. Therefore an independent correction method for this type of break, to be applied before homogenisation was developed. This type of change point was not included in the surrogate network. Artificial inhomogenities were introduced to the dataset in three steps: (1) deterministic change points: within one homogeneous sub-period (HSP) a constant perturbation is added to each relative humidity values, (2) deterministic + random changes: random changes do not change the mean of the HSP but can affect the distribution of the parameter, (3) in addition realistic changes in break frequency and missing data. In order to tests the efficiency of homogenisation methods, the procedure was separated in break detection and adjustment of inhomogenities. The methods MASH (Szentimrey, 1999), ACMANT (Domonkos, 2011), PRODIGE (Caussinus and Mestre, 2004), SNHT (Alexandersson, 1986), Vincent (Vincent, 1998), E-P method (Easterling and Peterson, 1995) and Bivariate test (Maronna and Yohai, 1978) were selected for break detection. Break detection is in all methods restricted to monthly, seasonal or annual data. Since we are dealing with daily data, the amount of methods for break correction is reduced and we concentrate on the following methods: MASH, Vincent, SPLIDHOM (Mestre et al., 2011) and the percentile method (Stepanek, 2009). Information on the statistical characteristics of breaks in relative humidity series, the correction method concerning the changed observation times and first results concerning break detection will be presented.

Spatial and temporal variations of aridity indices in Iraq

NASA Astrophysics Data System (ADS)

Şarlak, Nermin; Mahmood Agha, Omar M. A.

2017-06-01

This study investigates the spatial and temporal variations of the aridity indices to reveal the desertification vulnerability of Iraq region. Relying on temperature and precipitation data taken from 28 meteorological stations for 31 years, the study aims to determine (1) dry land types and their delineating boundaries and (2) temporal change in aridity conditions in Iraq. Lang's aridity (Im), De Martonne's aridity (Am), United Nations Environmental Program (UNEP) aridity (AIu), and Erinç aridity (IE) indices were selected in this study because of the scarcity of the observed data. The analysis of the spatial variation of aridity indices exhibited that the arid and semi-arid regions cover about 97% of the country's areas. As for temporal variations, it was observed that the aridity indices tend to decrease (statistically significant or not) for all stations. The cumulative sum charts (CUSUMs) were applied to detect the year on which the climate pattern of aridity indices had changed from one pattern to another. The abrupt change point was detected around year 1997 for the majority of the stations. Thus, the spatial and temporal aridity characteristics in Iraq were examined for the two periods 1980-1997 and 1998-2011 (before and after the change-point year) to observe the influence of abrupt change point on aridity phenomena. The spatial variation after 1997 was observed from semi-arid (dry sub humid) to arid (semi-arid) especially at the stations located in northern Iraq, while hyper-arid and arid climatic conditions were still dominant over southern and central Iraq. Besides, the negative temporal variations of the two periods 1980-1997 and 1998-2011 were obtained for almost every station. As a result, it was emphasized that Iraq region, like other Middle East regions, has become drier after 1997. The observed reduction in precipitation and increase in temperature for this region seem to make the situation worse in future.

Longitudinal Study of the Transition From Healthy Aging to Alzheimer Disease

PubMed Central

Johnson, David K.; Storandt, Martha; Morris, John C.; Galvin, James E.

2009-01-01

Background Detection of the earliest cognitive changes signifying Alzheimer disease is difficult. Objective To model the cognitive decline in preclinical Alzheimer disease. Design Longitudinal archival study comparing individuals who became demented during follow-up and people who remained nondemented on each of 4 cognitive factors: global, verbal memory, visuospatial, and working memory. Setting Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, Missouri. Participants One hundred thirty-four individuals who became demented during follow-up and 310 who remained nondemented. Main Outcome Measures Inflection point in longitudinal cognitive performance. Results The best-fitting model for each of the 4 factors in the stable group was linear, with a very slight downward trend on all but the Visuospatial factor. In contrast, a piecewise model with accelerated slope after a sharp inflection point provided the best fit for the group that progressed. The optimal inflection point for all 4 factors was prior to diagnosis of dementia: Global, 2 years; Verbal and Working Memory, 1 year; and Visuospatial, 3 years. These results were also obtained when data were limited to the subset (n=44) with autopsy-confirmed Alzheimer disease. Conclusions There is a sharp inflection point followed by accelerating decline in multiple domains of cognition, not just memory, in the preclinical period in Alzheimer disease when there is insufficient cognitive decline to warrant clinical diagnosis using conventional criteria. Early change was seen in tests of visuospatial ability, most of which were speeded. Research into early detection of cognitive disorders using only episodic memory tasks may not be sensitive to all of the early manifestations of disease. PMID:19822781

Updating the Standard Spatial Observer for Contrast Detection

NASA Technical Reports Server (NTRS)

Ahumada, Albert J.; Watson, Andrew B.

2011-01-01

Watson and Ahmuada (2005) constructed a Standard Spatial Observer (SSO) model for foveal luminance contrast signal detection based on the Medelfest data (Watson, 1999). Here we propose two changes to the model, dropping the oblique effect from the CSF and using the cone density data of Curcio et al. (1990) to estimate the variation of sensitivity with eccentricity. Dropping the complex images, and using medians to exclude outlier data points, the SSO model now accounts for essentially all the predictable variance in the data, with an RMS prediction error of only 0.67 dB.

Soil Carbon Variability and Change Detection in the Forest Inventory Analysis Database of the United States

NASA Astrophysics Data System (ADS)

Wu, A. M.; Nater, E. A.; Dalzell, B. J.; Perry, C. H.

2014-12-01

The USDA Forest Service's Forest Inventory Analysis (FIA) program is a national effort assessing current forest resources to ensure sustainable management practices, to assist planning activities, and to report critical status and trends. For example, estimates of carbon stocks and stock change in FIA are reported as the official United States submission to the United Nations Framework Convention on Climate Change. While the main effort in FIA has been focused on aboveground biomass, soil is a critical component of this system. FIA sampled forest soils in the early 2000s and has remeasurement now underway. However, soil sampling is repeated on a 10-year interval (or longer), and it is uncertain what magnitude of changes in soil organic carbon (SOC) may be detectable with the current sampling protocol. We aim to identify the sensitivity and variability of SOC in the FIA database, and to determine the amount of SOC change that can be detected with the current sampling scheme. For this analysis, we attempt to answer the following questions: 1) What is the sensitivity (power) of SOC data in the current FIA database? 2) How does the minimum detectable change in forest SOC respond to changes in sampling intervals and/or sample point density? Soil samples in the FIA database represent 0-10 cm and 10-20 cm depth increments with a 10-year sampling interval. We are investigating the variability of SOC and its change over time for composite soil data in each FIA region (Pacific Northwest, Interior West, Northern, and Southern). To guide future sampling efforts, we are employing statistical power analysis to examine the minimum detectable change in SOC storage. We are also investigating the sensitivity of SOC storage changes under various scenarios of sample size and/or sample frequency. This research will inform the design of future FIA soil sampling schemes and improve the information available to international policy makers, university and industry partners, and the public.

A multi points ultrasonic detection method for material flow of belt conveyor

NASA Astrophysics Data System (ADS)

Zhang, Li; He, Rongjun

2018-03-01

For big detection error of single point ultrasonic ranging technology used in material flow detection of belt conveyor when coal distributes unevenly or is large, a material flow detection method of belt conveyor is designed based on multi points ultrasonic counter ranging technology. The method can calculate approximate sectional area of material by locating multi points on surfaces of material and belt, in order to get material flow according to running speed of belt conveyor. The test results show that the method has smaller detection error than single point ultrasonic ranging technology under the condition of big coal with uneven distribution.

Detection of increased vasa vasorum in artery walls: improving CT number accuracy using image deconvolution

NASA Astrophysics Data System (ADS)

Rajendran, Kishore; Leng, Shuai; Jorgensen, Steven M.; Abdurakhimova, Dilbar; Ritman, Erik L.; McCollough, Cynthia H.

2017-03-01

Changes in arterial wall perfusion are an indicator of early atherosclerosis. This is characterized by an increased spatial density of vasa vasorum (VV), the micro-vessels that supply oxygen and nutrients to the arterial wall. Detection of increased VV during contrast-enhanced computed tomography (CT) imaging is limited due to contamination from blooming effect from the contrast-enhanced lumen. We report the application of an image deconvolution technique using a measured system point-spread function, on CT data obtained from a photon-counting CT system to reduce blooming and to improve the CT number accuracy of arterial wall, which enhances detection of increased VV. A phantom study was performed to assess the accuracy of the deconvolution technique. A porcine model was created with enhanced VV in one carotid artery; the other carotid artery served as a control. CT images at an energy range of 25-120 keV were reconstructed. CT numbers were measured for multiple locations in the carotid walls and for multiple time points, pre and post contrast injection. The mean CT number in the carotid wall was compared between the left (increased VV) and right (control) carotid arteries. Prior to deconvolution, results showed similar mean CT numbers in the left and right carotid wall due to the contamination from blooming effect, limiting the detection of increased VV in the left carotid artery. After deconvolution, the mean CT number difference between the left and right carotid arteries was substantially increased at all the time points, enabling detection of the increased VV in the artery wall.

Neural-Net Based Optical NDE Method for Structural Health Monitoring

NASA Technical Reports Server (NTRS)

Decker, Arthur J.; Weiland, Kenneth E.

2003-01-01

This paper answers some performance and calibration questions about a non-destructive-evaluation (NDE) procedure that uses artificial neural networks to detect structural damage or other changes from sub-sampled characteristic patterns. The method shows increasing sensitivity as the number of sub-samples increases from 108 to 6912. The sensitivity of this robust NDE method is not affected by noisy excitations of the first vibration mode. A calibration procedure is proposed and demonstrated where the output of a trained net can be correlated with the outputs of the point sensors used for vibration testing. The calibration procedure is based on controlled changes of fastener torques. A heterodyne interferometer is used as a displacement sensor for a demonstration of the challenges to be handled in using standard point sensors for calibration.

Responsiveness of two Persian-versions of shoulder outcome measures following physiotherapy intervention in patients with shoulder disorders.

PubMed

Negahban, Hossein; Behtash, Zeinab; Sohani, Soheil Mansour; Salehi, Reza

2015-01-01

To identify the ability of the Persian-version of the Shoulder Pain and Disability Index (SPADI) and the Disabilities of the Arm, Shoulder, and Hand (DASH) to detect changes in shoulder function following physiotherapy intervention (i.e. responsiveness) and to determine the change score that indicates a meaningful change in functional ability of the patient (i.e. Minimally Clinically Important Difference (MCID)). A convenient sample of 200 Persian-speaking patients with shoulder disorders completed the SPADI and the DASH at baseline and then again 4 weeks after physiotherapy intervention. Furthermore, patients were asked to rate their global rating of shoulder function at follow-up. The responsiveness was evaluated using two methods: the receiver operating characteristics (ROC) method and the correlation analysis. Two useful statistics extracted from the ROC method are the area under curve (AUC) and the optimal cutoff point called as MCID. Both the SPADI and the DASH showed the AUC of greater than 0.70 (AUC ranges = 0.77-0.82). The best cutoff points (or change scores) for the SPADI-total, SPADI-pain, SPADI-disability and the DASH were 14.88, 26.36, 23.86, and 25.41, respectively. Additionally, moderate to good correlations (Gamma = -0.51 to -0.58) were found between the changes in SPADI/DASH and changes in global rating scale. The Persian SPADI and DASH have adequate responsiveness to clinical changes in patients with shoulder disorders. Moreover, the MCIDs obtained in this study will help the clinicians and researchers to determine if a Persian-speaking patient with shoulder disorder has experienced a true change following a physiotherapy intervention. Implications for Rehabilitation Responsiveness was evaluated using two methods; the receiver operating characteristics (ROC) method and the correlation analysis. The Persian SPADI and DASH can be used as two responsive instruments in both clinical practice and research settings. The MCIDs of 14.88 and 25.41 points obtained for the SPADI-total and DASH indicated that the change scores of at least 14.88 points on the SPADI-total and 25.41 points on the DASH is necessary to certain that a true change has occurred following a physiotherapy intervention.

Relationships among participant international prostate symptom score, benign prostatic hyperplasia impact index changes and global ratings of change in a trial of phytotherapy in men with lower urinary tract symptoms.

PubMed

Barry, Michael J; Cantor, Alan; Roehrborn, Claus G

2013-03-01

We related changes in American Urological Association symptom index scores with bother measures and global ratings of change in men with lower urinary tract symptoms who were enrolled in a saw palmetto trial. To be eligible for study men were 45 years old or older, and had a peak uroflow of 4 ml per second or greater and an American Urological Association symptom index score of 8 to 24. Participants self-administered the American Urological Association symptom index, International Prostate Symptom Score quality of life item, Benign Prostatic Hyperplasia Impact Index and 2 global change questions at baseline, and at 24, 48 and 72 weeks. In 357 participants global ratings of a little better were associated with a mean decrease in American Urological Association symptom index scores from 2.8 to 4.1 points across 3 time points. The analogous range for mean decreases in Benign Prostatic Hyperplasia Impact Index scores was 1.0 to 1.7 points and for the International Prostate Symptom Score quality of life item it was 0.5 to 0.8 points. At 72 weeks for the first global change question each change measure discriminated between participants who rated themselves at least a little better vs unchanged or worse 70% to 72% of the time. A multivariate model increased discrimination to 77%. For the second global change question each change measure correctly discriminated ratings of at least a little better vs unchanged or worse 69% to 74% of the time and a multivariate model increased discrimination to 79%. Changes in American Urological Association symptom index scores could discriminate between participants rating themselves at least a little better vs unchanged or worse. Our findings support the practice of powering studies to detect group mean differences in American Urological Association symptom index scores of at least 3 points. Copyright © 2013 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

Visual perception of fatigued lifting actions.

PubMed

Fischer, Steven L; Albert, Wayne J; McGarry, Tim

2012-12-01

Fatigue-related changes in lifting kinematics may expose workers to undue injury risks. Early detection of accumulating fatigue offers the prospect of intervention strategies to mitigate such fatigue-related risks. In a first step towards this objective, this study investigated whether fatigue detection was accessible to visual perception and, if so, what was the key visual information required for successful fatigue discrimination. Eighteen participants were tasked with identifying fatigued lifts when viewing 24 trials presented using both video and point-light representations. Each trial comprised a pair of lifting actions containing a fresh and a fatigued lift from the same individual presented in counter-balanced sequence. Confidence intervals demonstrated that the frequency of correct responses for both sexes exceeded chance expectations (50%) for both video (68%±12%) and point-light representations (67%±10%), demonstrating that fatigued lifting kinematics are open to visual perception. There were no significant differences between sexes or viewing condition, the latter result indicating kinematic dynamics as providing sufficient information for successful fatigue discrimination. Moreover, results from single viewer investigation reported fatigue detection (75%) from point-light information describing only the kinematics of the box lifted. These preliminary findings may have important workplace applications if fatigue discrimination rates can be improved upon through future research. Copyright © 2012 Elsevier B.V. All rights reserved.

Detection and modeling of the acoustic perturbation produced by the launch of the Space Shuttle using the Global Positioning System

NASA Astrophysics Data System (ADS)

Bowling, T. J.; Calais, E.; Dautermann, T.

2010-12-01

Rocket launches are known to produce infrasonic pressure waves that propagate into the ionosphere where coupling between electrons and neutral particles induces fluctuations in ionospheric electron density observable in GPS measurements. We have detected ionospheric perturbations following the launch of space shuttle Atlantis on 11 May 2009 using an array of continually operating GPS stations across the Southeastern coast of the United States and in the Caribbean. Detections are prominent to the south of the westward shuttle trajectory in the area of maximum coupling between the acoustic wave and Earth’s magnetic field, move at speeds consistent with the speed of sound, and show coherency between stations covering a large geographic range. We model the perturbation as an explosive source located at the point of closest approach between the shuttle path and each sub-ionospheric point. The neutral pressure wave is propagated using ray tracing, resultant changes in electron density are calculated at points of intersection between rays and satellite-to-reciever line-of-sight, and synthetic integrated electron content values are derived. Arrival times of the observed and synthesized waveforms match closely, with discrepancies related to errors in the apriori sound speed model used for ray tracing. Current work includes the estimation of source location and energy.

Analysis of surface deformation during the eruptive process of El Hierro Island (Canary Islands, Spain): Detection, Evolution and Forecasting.

NASA Astrophysics Data System (ADS)

Berrocoso, M.; Fernandez-Ros, A.; Prates, G.; Martin, M.; Hurtado, R.; Pereda, J.; Garcia, M. J.; Garcia-Cañada, L.; Ortiz, R.; Garcia, A.

2012-04-01

The surface deformation has been an essential parameter for the onset and evolution of the eruptive process of the island of El Hierro (October 2011) as well as for forecasting changes in seismic and volcanic activity during the crisis period. From GNSS-GPS observations the reactivation is early detected by analizing the change in the deformation of the El Hierro Island regional geodynamics. It is found that the surface deformation changes are detected before the occurrence of seismic activity using the station FRON (GRAFCAN). The evolution of the process has been studied by the analysis of time series of topocentric coordinates and the variation of the distance between stations on the island of El Hierro (GRAFCAN station;IGN network; and UCA-CSIC points) and LPAL-IGS station on the island of La Palma. In this work the main methodologies and their results are shown: •The location (and its changes) of the litospheric pressure source obtained by applying the Mogi model. •Kalman filtering technique for high frequency time series, used to make the forecasts issued for volcanic emergency management. •Correlations between deformation of the different GPS stations and their relationship with seismovolcanic settings.

A megahertz-frequency tunable piecewise-linear electromechanical resonator realized via nonlinear feedback

NASA Astrophysics Data System (ADS)

Bajaj, Nikhil; Chiu, George T.-C.; Rhoads, Jeffrey F.

2018-07-01

Vibration-based sensing modalities traditionally have relied upon monitoring small shifts in natural frequency in order to detect structural changes (such as those in mass or stiffness). In contrast, bifurcation-based sensing schemes rely on the detection of a qualitative change in the behavior of a system as a parameter is varied. This can produce easy-to-detect changes in response amplitude with high sensitivity to structural change, but requires resonant devices with specific dynamic behavior which is not always easily reproduced. Desirable behavior for such devices can be produced reliably via nonlinear feedback circuitry, but has in past efforts been largely limited to sub-MHz operation, partially due to the time delay limitations present in certain nonlinear feedback circuits, such as multipliers. This work demonstrates the design and implementation of a piecewise-linear resonator realized via diode- and integrated circuit-based feedback electronics and a quartz crystal resonator. The proposed system is fabricated and characterized, and the creation and selective placement of the bifurcation points of the overall electromechanical system is demonstrated by tuning the circuit gains. The demonstrated circuit operates at 16 MHz. Preliminary modeling and analysis is presented that qualitatively agrees with the experimentally-observed behavior.

Geomorphic Change Detection and Quantification Using LiDAR, SONAR and RTK-GPS of Sandbars along the Snake River in Hells Canyon

NASA Astrophysics Data System (ADS)

Morehead, M. D.; Wilson, T.; Butler, M.; Seal, N.

2012-12-01

Sediment depletion downstream of large dams causes long-term geomorphic change along a river reach. Short- and long-term, natural and human-altered discharge patterns cause additional geomorphic change. Annual high-resolution, topobathymetry data are being collected on sandbars to track patterns of geomorphic and volumetric change through time. The sandbars are located along the Hells Canyon reach of the Snake River on the Oregon/Idaho border. The bars are downstream of a number of dams that have cut off the upstream source of sand to the Hells Canyon reach. We are combining LiDAR data for above water areas, multibeam SONAR data for below water areas and RTK-GPS data for the water/land interface and densely vegetated areas. Idaho Power has installed and surveyed a control point network to allow accurate positioning of the data and aligning of the various data sets. Data densities are a few points per square meter with the RTK-GPS, tens of points per square meter with the SONAR, and up to hundreds of points per square meter with the ground-based LiDAR. Automated and manual methods are being used to clean the point cloud data. A number of techniques are being used to convert the point clouds to grids, typically utilizing a unique technique for each data type (GPS, LiDAR, and SONAR). Surface roughness data are being used to determine the edges of the sand region, especially in the underwater area where we do not have visual confirmation of the boundary. After the different data types are gridded, they are combined to create seamless surfaces which are then analyzed. The morphologies of the central crest and the back channel of the sandbars are changing between years. In years with higher than average spring flows, the central crest of the sandbars increases in elevation and the back channels deepen. In years with moderate and low spring flows, the height of the crests decline and the back channels fill in. The flattening of the sandbars is attributed to natural redistribution processes and anthropogenic use. The cut-banks behind the sandbars have typically not retreated during the study period (8 years). Volumetric differences show that the cut/fill patterns are consistent over large areas of each bar. The annual morphologic changes are consistent among the sampled bars. The time series is just starting to be long enough to assess long-term trends in bar volume and morphology as opposed to inter-annual variability. The increased availability of high-density SONAR and LiDAR data has substantially aided our efforts to detect and quantify geomorphic change along the Snake River. The data editing and analysis techniques for these high-density data sets are advancing rapidly. Improvements in error analysis and within grid cell data proprieties are being developed to document the accuracy of the results and determine other morphological properties.

Allele quantification using molecular inversion probes (MIP)

PubMed Central

Wang, Yuker; Moorhead, Martin; Karlin-Neumann, George; Falkowski, Matthew; Chen, Chunnuan; Siddiqui, Farooq; Davis, Ronald W.; Willis, Thomas D.; Faham, Malek

2005-01-01

Detection of genomic copy number changes has been an important research area, especially in cancer. Several high-throughput technologies have been developed to detect these changes. Features that are important for the utility of technologies assessing copy number changes include the ability to interrogate regions of interest at the desired density as well as the ability to differentiate the two homologs. In addition, assessing formaldehyde fixed and paraffin embedded (FFPE) samples allows the utilization of the vast majority of cancer samples. To address these points we demonstrate the use of molecular inversion probe (MIP) technology to the study of copy number. MIP is a high-throughput genotyping technology capable of interrogating >20 000 single nucleotide polymorphisms in the same tube. We have shown the ability of MIP at this multiplex level to provide copy number measurements while obtaining the allele information. In addition we have demonstrated a proof of principle for copy number analysis in FFPE samples. PMID:16314297

Monitoring Coral Growth - the Dichotomy Between Underwater Photogrammetry and Geodetic Control Network

NASA Astrophysics Data System (ADS)

Neyer, F.; Nocerino, E.; Gruen, A.

2018-05-01

Creating 3-dimensional (3D) models of underwater scenes has become a common approach for monitoring coral reef changes and its structural complexity. Also in underwater archeology, 3D models are often created using underwater optical imagery. In this paper, we focus on the aspect of detecting small changes in the coral reef using a multi-temporal photogrammetric modelling approach, which requires a high quality control network. We show that the quality of a good geodetic network limits the direct change detection, i.e., without any further registration process. As the photogrammetric accuracy is expected to exceed the geodetic network accuracy by at least one order of magnitude, we suggest to do a fine registration based on a number of signalized points. This work is part of the Moorea Island Digital Ecosystem Avatar (IDEA) project that has been initiated in 2013 by a group of international researchers (https://mooreaidea.ethz.ch/).

Electromagnetic nondestructive evaluation of tempering process in AISI D2 tool steel

NASA Astrophysics Data System (ADS)

Kahrobaee, Saeed; Kashefi, Mehrdad

2015-05-01

The present paper investigates the potential of using eddy current technique as a reliable nondestructive tool to detect microstructural changes during the different stages of tempering treatment in AISI D2 tool steel. Five stages occur in tempering of the steel: precipitation of ɛ carbides, formation of cementite, retained austenite decomposition, secondary hardening effect and spheroidization of carbides. These stages were characterized by destructive methods, including dilatometry, differential scanning calorimetry, X-ray diffraction, scanning electron microscopic observations, and hardness measurements. The microstructural changes alter the electrical resistivity/magnetic saturation, which, in turn, influence the eddy current signals. Two EC parameters, induced voltage sensed by pickup coil and impedance point detected by excitation coil, were evaluated as a function of tempering temperature to characterize the microstructural features, nondestructively. The study revealed that a good correlation exists between the EC parameters and the microstructural changes.

Erosion and Channel Incision Analysis with High-Resolution Lidar

NASA Astrophysics Data System (ADS)

Potapenko, J.; Bookhagen, B.

2013-12-01

High-resolution LiDAR (LIght Detection And Ranging) provides a new generation of sub-meter topographic data that is still to be fully exploited by the Earth science communities. We make use of multi-temporal airborne and terrestrial lidar scans in the south-central California and Santa Barbara area. Specifically, we have investigated the Mission Canyon and Channel Islands regions from 2009-2011 to study changes in erosion and channel incision on the landscape. In addition to gridding the lidar data into digital elevation models (DEMs), we also make use of raw lidar point clouds and triangulated irregular networks (TINs) for detailed analysis of heterogeneously spaced topographic data. Using recent advancements in lidar point cloud processing from information technology disciplines, we have employed novel lidar point cloud processing and feature detection algorithms to automate the detection of deeply incised channels and gullies, vegetation, and other derived metrics (e.g. estimates of eroded volume). Our analysis compares topographically-derived erosion volumes to field-derived cosmogenic radionuclide age and in-situ sediment-flux measurements. First results indicate that gully erosion accounts for up to 60% of the sediment volume removed from the Mission Canyon region. Furthermore, we observe that gully erosion and upstream arroyo propagation accelerated after fires, especially in regions where vegetation was heavily burned. The use of high-resolution lidar point cloud data for topographic analysis is still a novel method that needs more precedent and we hope to provide a cogent example of this approach with our research.

Use of marker ion and cationic surfactant plastic membrane electrode for potentiometric titration of cationic polyelectrolytes.

PubMed

Masadome, Takashi; Imato, Toshihiko

2003-07-04

A plasticized poly (vinyl chloride) (PVC) membrane electrode sensitive to stearyltrimethylammonium (STA) ion is applied to the determination of cationic polyelectrolytes such as poly (diallyldimethylammonium chloride) (Cat-floc) by potentiometric titration, using a potassium poly (vinyl sulfate) (PVSK) solution as a titrant. The end-point of the titration is detected as the potential change of the plasticized PVC membrane electrode caused by decrease in the concentration of STA ion added to the sample solution as a marker ion due to the ion association reaction between the STA ion and PVSK. The effects of the concentration of STA ion, coexisting electrolytes in the sample solution and pH of the sample on the degree of the potential change at the end-point were examined. A linear relationship between the concentration of cationic polyelectrolyte and the end-point volume of the titrant exists in the concentration range from 2x10(-5) to 4x10(-4) N for Cat-floc, glycol chitosan, and methylglycol chitosan.

A single point mutation in Tomato spotted wilt virus NSs protein is sufficient to overcome Tsw-gene-mediated resistance in pepper.

PubMed

Almási, Asztéria; Nemes, Katalin; Csömör, Zsófia; Tóbiás, István; Palkovics, László; Salánki, Katalin

2017-06-01

The nonstructural protein (NSs) of Tomato spotted wilt virus (TSWV) was previously identified as an avirulence determinant for Tsw-based resistance on pepper. The NSs of wild-type (WT) and resistance-breaking (RB) TSWV strains isolated in Hungary had only two amino acid substitutions (104, 461). We have analysed the ability of the NSs and their point mutant variants to trigger Tsw-mediated hypersensitive responses and RNA silencing suppressor (RSS) activity in patch assays. We identified a single amino acid change at position 104 (T-A) that was responsible for the necrosis induction or loss, while a significant difference was not detected in the RSS activity of the two parental strains. We have successfully complemented the infection of the WT strain on resistant pepper cultivar with the infectious S RNA transcript of the RB strain and the WT-T104A point mutant. Our work provides direct evidence that a single amino acid change can induce an RB phenotype.

The influence of biological and technical factors on quantitative analysis of amyloid PET: Points to consider and recommendations for controlling variability in longitudinal data.

PubMed

Schmidt, Mark E; Chiao, Ping; Klein, Gregory; Matthews, Dawn; Thurfjell, Lennart; Cole, Patricia E; Margolin, Richard; Landau, Susan; Foster, Norman L; Mason, N Scott; De Santi, Susan; Suhy, Joyce; Koeppe, Robert A; Jagust, William

2015-09-01

In vivo imaging of amyloid burden with positron emission tomography (PET) provides a means for studying the pathophysiology of Alzheimer's and related diseases. Measurement of subtle changes in amyloid burden requires quantitative analysis of image data. Reliable quantitative analysis of amyloid PET scans acquired at multiple sites and over time requires rigorous standardization of acquisition protocols, subject management, tracer administration, image quality control, and image processing and analysis methods. We review critical points in the acquisition and analysis of amyloid PET, identify ways in which technical factors can contribute to measurement variability, and suggest methods for mitigating these sources of noise. Improved quantitative accuracy could reduce the sample size necessary to detect intervention effects when amyloid PET is used as a treatment end point and allow more reliable interpretation of change in amyloid burden and its relationship to clinical course. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

A Newly Updated Database of Elevation-changes of the Greenand Ice Sheet to Study Surface Processes and Ice Dynamics

NASA Astrophysics Data System (ADS)

Schenk, A. F.; Csatho, B. M.; van den Broeke, M.; Kuipers Munneke, P.

2015-12-01

This paper reports about important upgrades of the Greenland Ice Sheet (GrIS) surface elevation and elevation-change database obtained with our Surface Elevation And Change detection (SERAC) software suite. We have developed SERAC to derive information from laser altimetry data, particularly time series of elevation changes and their partitioning into changes caused by ice dynamics. This allows direct investigation of ice dynamic processes that is much needed for improving the predictive power of ice sheet models. SERAC is different from most other change detection methods. It is based on detecting changes of surface patches, about 1 km by 1 km in size, rather than deriving elevation changes from individual laser points. The current database consists of ~100,000 time series with satellite laser altimetry data from ICESat, airborne laser observations obtained by NASA's Airborne Topographic Mapper (ATM) and the Land, Vegetation and Ice Sensor (LVIS). The upgrade is significant, because not only new observations from 2013 and 2014 have been added but also a number of improvements lead to a more comprehensive and consistent record of elevation-changes. First, we used the model that gives in addition to ice sheet also information about ice caps and glaciers (Rastner et al., 2012) for deciding if a laser point is on the ice sheet or ice cap. Then we added small gaps that exist in the ICESat GLA12 data set because the ice sheet mask is not wide enough. The new database is now more complete and will facilitate more accurate comparisons of mass balance studies obtained from the Gravity Recovery and Climate Experiment system (GRACE). For determining the part of a time series caused by ice dynamics we used the new firn compaction model and Surface Mass Balance (SMB) estimates from RACMO2.3. The new database spans the time period from 1993 to 2014. Adding new observations amounts to a spatial densification of the old record and at the same time extends the time domain by two years. Our presentation will show the improvement of the reconstruction of the total changes, those caused by SMB and ice dynamic during the ICESat mission (2003-2009). Moreover we will review changes on scales from individual outlet glaciers to drainage basins and the entire ice sheet.

[Image processing applying in analysis of motion features of cultured cardiac myocyte in rat].

PubMed

Teng, Qizhi; He, Xiaohai; Luo, Daisheng; Wang, Zhengrong; Zhou, Beiyi; Yuan, Zhirun; Tao, Dachang

2007-02-01

Study of mechanism of medicine actions, by quantitative analysis of cultured cardiac myocyte, is one of the cutting edge researches in myocyte dynamics and molecular biology. The characteristics of cardiac myocyte auto-beating without external stimulation make the research sense. Research of the morphology and cardiac myocyte motion using image analysis can reveal the fundamental mechanism of medical actions, increase the accuracy of medicine filtering, and design the optimal formula of medicine for best medical treatments. A system of hardware and software has been built with complete sets of functions including living cardiac myocyte image acquisition, image processing, motion image analysis, and image recognition. In this paper, theories and approaches are introduced for analysis of living cardiac myocyte motion images and implementing quantitative analysis of cardiac myocyte features. A motion estimation algorithm is used for motion vector detection of particular points and amplitude and frequency detection of a cardiac myocyte. Beatings of cardiac myocytes are sometimes very small. In such case, it is difficult to detect the motion vectors from the particular points in a time sequence of images. For this reason, an image correlation theory is employed to detect the beating frequencies. Active contour algorithm in terms of energy function is proposed to approximate the boundary and detect the changes of edge of myocyte.

Illumination Profile & Dispersion Variation Effects on Radial Velocity Measurements

NASA Astrophysics Data System (ADS)

Grieves, Nolan; Ge, Jian; Thomas, Neil B.; Ma, Bo; Li, Rui; SDSS-III

2015-01-01

The Multi-object APO Radial-Velocity Exoplanet Large-Area Survey (MARVELS) measures radial velocities using a fiber-fed dispersed fixed-delay interferometer (DFDI) with a moderate dispersion spectrograph. This setup allows a unique insight into the 2D illumination profile from the fiber on to the dispersion grating. Illumination profile investigations show large changes in the profile over time and fiber location. These profile changes are correlated with dispersion changes and long-term radial velocity offsets, a major problem within the MARVELS radial velocity data. Characterizing illumination profiles creates a method to both detect and correct radial velocity offsets, allowing for better planet detection. Here we report our early results from this study including improvement of radial velocity data points from detected giant planet candidates. We also report an illumination profile experiment conducted at the Kitt Peak National Observatory using the EXPERT instrument, which has a DFDI mode similar to MARVELS. Using profile controlling octagonal-shaped fibers, long term offsets over a 3 month time period were reduced from ~50 m/s to within the photon limit of ~4 m/s.

Visual-Spatial Attention Aids the Maintenance of Object Representations in Visual Working Memory

PubMed Central

Williams, Melonie; Pouget, Pierre; Boucher, Leanne; Woodman, Geoffrey F.

2013-01-01

Theories have proposed that the maintenance of object representations in visual working memory is aided by a spatial rehearsal mechanism. In this study, we used two different approaches to test the hypothesis that overt and covert visual-spatial attention mechanisms contribute to the maintenance of object representations in visual working memory. First, we tracked observers’ eye movements while remembering a variable number of objects during change-detection tasks. We observed that during the blank retention interval, participants spontaneously shifted gaze to the locations that the objects had occupied in the memory array. Next, we hypothesized that if attention mechanisms contribute to the maintenance of object representations, then drawing attention away from the object locations during the retention interval would impair object memory during these change-detection tasks. Supporting this prediction, we found that attending to the fixation point in anticipation of a brief probe stimulus during the retention interval reduced change-detection accuracy even on the trials in which no probe occurred. These findings support models of working memory in which visual-spatial selection mechanisms contribute to the maintenance of object representations. PMID:23371773

Building Change Detection from Harvey using Unmanned Aerial System (UAS)

NASA Astrophysics Data System (ADS)

Chang, A.; Yeom, J.; Jung, J.; Choi, I.

2017-12-01

Unmanned Aerial System (UAS) is getting to be the most important technique in recent days since the fine spatial and high temporal resolution data previously unobtainable from traditional remote sensing platforms. Advanced UAS data can provide a great opportunity for disaster monitoring. Especially, building change detection is the one of the most important topics for damage assessment and recovery from disasters. This study is proposing a method to monitor building change with UAS data for Holiday Beach in Texas, where was directly hit by Harvey on 25 August 2017. This study adopted 3D change detection to monitor building damage and recovery levels with building height as well as natural color information. We used a rotorcraft UAS to collect RGB data twice on 9 September and 18 October 2017 after the hurricane. The UAS data was processed using Agisoft Photoscan Pro Software to generate super high resolution dataset including orthomosaic, DSM (Digital Surface Model), and 3D point cloud. We compared the processed dataset with an airborne image considerable as before-hurricane data, which was acquired on January 2016. Building damage and recovery levels were determined by height and color change. The result will show that UAS data is useful to assess building damage and recovery for affected area by the natural disaster such as Harvey.

A Method for Automatic Surface Inspection Using a Model-Based 3D Descriptor.

PubMed

Madrigal, Carlos A; Branch, John W; Restrepo, Alejandro; Mery, Domingo

2017-10-02

Automatic visual inspection allows for the identification of surface defects in manufactured parts. Nevertheless, when defects are on a sub-millimeter scale, detection and recognition are a challenge. This is particularly true when the defect generates topological deformations that are not shown with strong contrast in the 2D image. In this paper, we present a method for recognizing surface defects in 3D point clouds. Firstly, we propose a novel 3D local descriptor called the Model Point Feature Histogram (MPFH) for defect detection. Our descriptor is inspired from earlier descriptors such as the Point Feature Histogram (PFH). To construct the MPFH descriptor, the models that best fit the local surface and their normal vectors are estimated. For each surface model, its contribution weight to the formation of the surface region is calculated and from the relative difference between models of the same region a histogram is generated representing the underlying surface changes. Secondly, through a classification stage, the points on the surface are labeled according to five types of primitives and the defect is detected. Thirdly, the connected components of primitives are projected to a plane, forming a 2D image. Finally, 2D geometrical features are extracted and by a support vector machine, the defects are recognized. The database used is composed of 3D simulated surfaces and 3D reconstructions of defects in welding, artificial teeth, indentations in materials, ceramics and 3D models of defects. The quantitative and qualitative results showed that the proposed method of description is robust to noise and the scale factor, and it is sufficiently discriminative for detecting some surface defects. The performance evaluation of the proposed method was performed for a classification task of the 3D point cloud in primitives, reporting an accuracy of 95%, which is higher than for other state-of-art descriptors. The rate of recognition of defects was close to 94%.

A Method for Automatic Surface Inspection Using a Model-Based 3D Descriptor

PubMed Central

Branch, John W.

2017-01-01

Automatic visual inspection allows for the identification of surface defects in manufactured parts. Nevertheless, when defects are on a sub-millimeter scale, detection and recognition are a challenge. This is particularly true when the defect generates topological deformations that are not shown with strong contrast in the 2D image. In this paper, we present a method for recognizing surface defects in 3D point clouds. Firstly, we propose a novel 3D local descriptor called the Model Point Feature Histogram (MPFH) for defect detection. Our descriptor is inspired from earlier descriptors such as the Point Feature Histogram (PFH). To construct the MPFH descriptor, the models that best fit the local surface and their normal vectors are estimated. For each surface model, its contribution weight to the formation of the surface region is calculated and from the relative difference between models of the same region a histogram is generated representing the underlying surface changes. Secondly, through a classification stage, the points on the surface are labeled according to five types of primitives and the defect is detected. Thirdly, the connected components of primitives are projected to a plane, forming a 2D image. Finally, 2D geometrical features are extracted and by a support vector machine, the defects are recognized. The database used is composed of 3D simulated surfaces and 3D reconstructions of defects in welding, artificial teeth, indentations in materials, ceramics and 3D models of defects. The quantitative and qualitative results showed that the proposed method of description is robust to noise and the scale factor, and it is sufficiently discriminative for detecting some surface defects. The performance evaluation of the proposed method was performed for a classification task of the 3D point cloud in primitives, reporting an accuracy of 95%, which is higher than for other state-of-art descriptors. The rate of recognition of defects was close to 94%. PMID:28974037

Voronoi distance based prospective space-time scans for point data sets: a dengue fever cluster analysis in a southeast Brazilian town

PubMed Central

2011-01-01

Background The Prospective Space-Time scan statistic (PST) is widely used for the evaluation of space-time clusters of point event data. Usually a window of cylindrical shape is employed, with a circular or elliptical base in the space domain. Recently, the concept of Minimum Spanning Tree (MST) was applied to specify the set of potential clusters, through the Density-Equalizing Euclidean MST (DEEMST) method, for the detection of arbitrarily shaped clusters. The original map is cartogram transformed, such that the control points are spread uniformly. That method is quite effective, but the cartogram construction is computationally expensive and complicated. Results A fast method for the detection and inference of point data set space-time disease clusters is presented, the Voronoi Based Scan (VBScan). A Voronoi diagram is built for points representing population individuals (cases and controls). The number of Voronoi cells boundaries intercepted by the line segment joining two cases points defines the Voronoi distance between those points. That distance is used to approximate the density of the heterogeneous population and build the Voronoi distance MST linking the cases. The successive removal of edges from the Voronoi distance MST generates sub-trees which are the potential space-time clusters. Finally, those clusters are evaluated through the scan statistic. Monte Carlo replications of the original data are used to evaluate the significance of the clusters. An application for dengue fever in a small Brazilian city is presented. Conclusions The ability to promptly detect space-time clusters of disease outbreaks, when the number of individuals is large, was shown to be feasible, due to the reduced computational load of VBScan. Instead of changing the map, VBScan modifies the metric used to define the distance between cases, without requiring the cartogram construction. Numerical simulations showed that VBScan has higher power of detection, sensitivity and positive predicted value than the Elliptic PST. Furthermore, as VBScan also incorporates topological information from the point neighborhood structure, in addition to the usual geometric information, it is more robust than purely geometric methods such as the elliptic scan. Those advantages were illustrated in a real setting for dengue fever space-time clusters. PMID:21513556

Detection of Antibodies in Blood Plasma Using Bioluminescent Sensor Proteins and a Smartphone.

PubMed

Arts, Remco; den Hartog, Ilona; Zijlema, Stefan E; Thijssen, Vito; van der Beelen, Stan H E; Merkx, Maarten

2016-04-19

Antibody detection is of fundamental importance in many diagnostic and bioanalytical assays, yet current detection techniques tend to be laborious and/or expensive. We present a new sensor platform (LUMABS) based on bioluminescence resonance energy transfer (BRET) that allows detection of antibodies directly in solution using a smartphone as the sole piece of equipment. LUMABS are single-protein sensors that consist of the blue-light emitting luciferase NanoLuc connected via a semiflexible linker to the green fluorescent acceptor protein mNeonGreen, which are kept close together using helper domains. Binding of an antibody to epitope sequences flanking the linker disrupts the interaction between the helper domains, resulting in a large decrease in BRET efficiency. The resulting change in color of the emitted light from green-blue to blue can be detected directly in blood plasma, even at picomolar concentrations of antibody. Moreover, the modular architecture of LUMABS allows changing of target specificity by simple exchange of epitope sequences, as demonstrated here for antibodies against HIV1-p17, hemagglutinin (HA), and dengue virus type I. The combination of sensitive ratiometric bioluminescent detection and the intrinsic modularity of the LUMABS design provides an attractive generic platform for point-of-care antibody detection that avoids the complex liquid handling steps associated with conventional immunoassays.

Thorough statistical comparison of machine learning regression models and their ensembles for sub-pixel imperviousness and imperviousness change mapping

NASA Astrophysics Data System (ADS)

Drzewiecki, Wojciech

2017-12-01

We evaluated the performance of nine machine learning regression algorithms and their ensembles for sub-pixel estimation of impervious areas coverages from Landsat imagery. The accuracy of imperviousness mapping in individual time points was assessed based on RMSE, MAE and R2. These measures were also used for the assessment of imperviousness change intensity estimations. The applicability for detection of relevant changes in impervious areas coverages at sub-pixel level was evaluated using overall accuracy, F-measure and ROC Area Under Curve. The results proved that Cubist algorithm may be advised for Landsat-based mapping of imperviousness for single dates. Stochastic gradient boosting of regression trees (GBM) may be also considered for this purpose. However, Random Forest algorithm is endorsed for both imperviousness change detection and mapping of its intensity. In all applications the heterogeneous model ensembles performed at least as well as the best individual models or better. They may be recommended for improving the quality of sub-pixel imperviousness and imperviousness change mapping. The study revealed also limitations of the investigated methodology for detection of subtle changes of imperviousness inside the pixel. None of the tested approaches was able to reliably classify changed and non-changed pixels if the relevant change threshold was set as one or three percent. Also for fi ve percent change threshold most of algorithms did not ensure that the accuracy of change map is higher than the accuracy of random classifi er. For the threshold of relevant change set as ten percent all approaches performed satisfactory.

Real-time stereo vision-based lane detection system

NASA Astrophysics Data System (ADS)

Fan, Rui; Dahnoun, Naim

2018-07-01

The detection of multiple curved lane markings on a non-flat road surface is still a challenging task for vehicular systems. To make an improvement, depth information can be used to enhance the robustness of the lane detection systems. In this paper, a proposed lane detection system is developed from our previous work where the estimation of the dense vanishing point is further improved using the disparity information. However, the outliers in the least squares fitting severely affect the accuracy when estimating the vanishing point. Therefore, in this paper we use random sample consensus to update the parameters of the road model iteratively until the percentage of the inliers exceeds our pre-set threshold. This significantly helps the system to overcome some suddenly changing conditions. Furthermore, we propose a novel lane position validation approach which computes the energy of each possible solution and selects all satisfying lane positions for visualisation. The proposed system is implemented on a heterogeneous system which consists of an Intel Core i7-4720HQ CPU and an NVIDIA GTX 970M GPU. A processing speed of 143 fps has been achieved, which is over 38 times faster than our previous work. Moreover, in order to evaluate the detection precision, we tested 2495 frames including 5361 lanes. It is shown that the overall successful detection rate is increased from 98.7% to 99.5%.

Neural network-based feature point descriptors for registration of optical and SAR images

NASA Astrophysics Data System (ADS)

Abulkhanov, Dmitry; Konovalenko, Ivan; Nikolaev, Dmitry; Savchik, Alexey; Shvets, Evgeny; Sidorchuk, Dmitry

2018-04-01

Registration of images of different nature is an important technique used in image fusion, change detection, efficient information representation and other problems of computer vision. Solving this task using feature-based approaches is usually more complex than registration of several optical images because traditional feature descriptors (SIFT, SURF, etc.) perform poorly when images have different nature. In this paper we consider the problem of registration of SAR and optical images. We train neural network to build feature point descriptors and use RANSAC algorithm to align found matches. Experimental results are presented that confirm the method's effectiveness.

Smartphone based point-of-care detector of urine albumin

NASA Astrophysics Data System (ADS)

Cmiel, Vratislav; Svoboda, Ondrej; Koscova, Pavlina; Provaznik, Ivo

2016-03-01

Albumin plays an important role in human body. Its changed level in urine may indicate serious kidney disorders. We present a new point-of-care solution for sensitive detection of urine albumin - the miniature optical adapter for iPhone with in-built optical filters and a sample slot. The adapter exploits smart-phone flash to generate excitation light and camera to measure the level of emitted light. Albumin Blue 580 is used as albumin reagent. The proposed light-weight adapter can be produced at low cost using a 3D printer. Thus, the miniaturized detector is easy to use out of lab.

Trend analysis of precipitation in Jharkhand State, India. Investigating precipitation variability in Jharkhand State

NASA Astrophysics Data System (ADS)

Chandniha, Surendra Kumar; Meshram, Sarita Gajbhiye; Adamowski, Jan Franklin; Meshram, Chandrashekhar

2017-10-01

Jharkhand is one of the eastern states of India which has an agriculture-based economy. Uncertain and erratic distribution of precipitation as well as a lack of state water resources planning is the major limitation to crop growth in the region. In this study, the spatial and temporal variability in precipitation in the state was examined using a monthly precipitation time series of 111 years (1901-2011) from 18 meteorological stations. Autocorrelation and Mann-Kendall/modified Mann-Kendall tests were utilized to detect possible trends, and the Theil and Sen slope estimator test was used to determine the magnitude of change over the entire time series. The most probable change year (change point) was detected using the Pettitt-Mann-Whitney test, and the entire time series was sub-divided into two parts: before and after the change point. Arc-Map 9.3 software was utilized to assess the spatial patterns of the trends over the entire state. Annual precipitation exhibited a decreasing trend in 5 out of 18 stations during the whole period. For annual, monsoon and winter periods of precipitation, the slope test indicated a decreasing trend for all stations during 1901-2011. The highest variability was observed in post-monsoon precipitation (77.87 %) and the lowest variability was observed in the annual series (15.76 %) over the 111 years. An increasing trend in precipitation in the state was found during the period 1901-1949, which was reversed during the subsequent period (1950-2011).

Prototype global burnt area algorithm using the AVHRR-LTDR time series

NASA Astrophysics Data System (ADS)

López-Saldaña, Gerardo; Pereira, José Miguel; Aires, Filipe

2013-04-01

One of the main limitations of products derived from remotely-sensed data is the length of the data records available for climate studies. The Advanced Very High Resolution Radiometer (AVHRR) long-term data record (LTDR) comprises a daily global atmospherically-corrected surface reflectance dataset at 0.05° spatial resolution and is available for the 1981-1999 time period. Fire is strong cause of land surface change and emissions of greenhouse gases around the globe. A global long-term identification of areas affected by fire is needed to analyze trends and fire-clime relationships. A burnt area algorithm can be seen as a change point detection problem where there is an abrupt change in the surface reflectance due to the biomass burning. Using the AVHRR-LTDR dataset, a time series of bidirectional reflectance distribution function (BRDF) corrected surface reflectance was generated using the daily observations and constraining the BRDF model inversion using a climatology of BRDF parameters derived from 12 years of MODIS data. The identification of the burnt area was performed using a t-test in the pre- and post-fire reflectance values and a change point detection algorithm, then spectral constraints were applied to flag changes caused by natural land processes like vegetation seasonality or flooding. Additional temporal constraints are applied focusing in the persistence of the affected areas. Initial results for year 1998, which was selected because of a positive fire anomaly, show spatio-temporal coherence but further analysis is required and a formal rigorous validation will be applied using burn scars identified from high-resolution datasets.

Ability of the Masimo pulse CO-Oximeter to detect changes in hemoglobin.

PubMed

Colquhoun, Douglas A; Forkin, Katherine T; Durieux, Marcel E; Thiele, Robert H

2012-04-01

The decision to administer blood products is complex and multifactorial. Accurate assessment of the concentration of hemoglobin [Hgb] is a key component of this evaluation. Recently a noninvasive method of continuously measuring hemoglobin (SpHb) has become available with multi-wavelength Pulse CO-Oximetry. The accuracy of this device is well documented, but the trending ability of this monitor has not been previously described. Twenty patients undergoing major thoracic and lumbar spine surgery were recruited. All patients received radial arterial lines. On the contralateral index finger, a R1 25 sensor (Rev E) was applied and connected to a Radical-7 Pulse CO-Oximeter (both Masimo Corp, Irvine, CA). Blood samples were drawn intermittently at the anesthesia provider's discretion and were analyzed by the operating room satellite laboratory CO-Oximeter. The value of Hgb and SpHb at that time point was compared. Trend analysis was performed by the four quadrant plot technique, testing directionality of change, and Critchley's polar plot method testing both directionality and magnitude of the change in values. Eighty-eight samples recorded at times of sufficient signal quality were available for analysis. Four quadrant plot analysis revealed 94% of data within the quadrants associated with the correct direction change, and 90% of data points lay within the analysis bounds proposed by Critchley. Pulse CO-Oximetry offers an acceptable trend monitor in patients undergoing major spine surgery. Future work should explore the ability of this device to detect large changes in hemoglobin, as well as its applicability in additional surgical and non-surgical patient populations.

Palila abundance estimates and trends

USGS Publications Warehouse

Banko, Paul C.; Brink, Kevin W.; Camp, Richard

2014-01-01

The palila (Loxioides bailleui) population was surveyed annually during 1998−2014 on Mauna Kea Volcano to determine abundance, population trend, and spatial distribution. In the latest surveys, the 2013 population was estimated at 1,492−2,132 birds (point estimate: 1,799) and the 2014 population was estimated at 1,697−2,508 (point estimate: 2,070). Similar numbers of palila were detected during the first and subsequent counts within each year during 2012−2014, and there was no difference in their detection probability due to count sequence. This suggests that greater precision in population estimates can be achieved if future surveys include repeat visits. No palila were detected outside the core survey area in 2013 or 2014, suggesting that most if not all palila inhabit the western slope during the survey period. Since 2003, the size of the area containing all annual palila detections do not indicate a significant change among years, suggesting that the range of the species has remained stable; although this area represents only about 5% of its historical extent. During 1998−2003, palila numbers fluctuated moderately (coefficient of variation [CV] = 0.21). After peaking in 2003, population estimates declined steadily through 2011; since 2010, estimates have fluctuated moderately above the 2011 minimum (CV = 0.18). The average rate of decline during 1998−2014 was 167 birds per year with very strong statistical support for an overall declining trend in abundance. Over the 16-year monitoring period, the estimated rate of change equated to a 68% decline in the population.

Building a LiDAR point cloud simulator: Testing algorithms for high resolution topographic change

NASA Astrophysics Data System (ADS)

Carrea, Dario; Abellán, Antonio; Derron, Marc-Henri; Jaboyedoff, Michel

2014-05-01

Terrestrial laser technique (TLS) is becoming a common tool in Geosciences, with clear applications ranging from the generation of a high resolution 3D models to the monitoring of unstable slopes and the quantification of morphological changes. Nevertheless, like every measurement techniques, TLS still has some limitations that are not clearly understood and affect the accuracy of the dataset (point cloud). A challenge in LiDAR research is to understand the influence of instrumental parameters on measurement errors during LiDAR acquisition. Indeed, different critical parameters interact with the scans quality at different ranges: the existence of shadow areas, the spatial resolution (point density), and the diameter of the laser beam, the incidence angle and the single point accuracy. The objective of this study is to test the main limitations of different algorithms usually applied on point cloud data treatment, from alignment to monitoring. To this end, we built in MATLAB(c) environment a LiDAR point cloud simulator able to recreate the multiple sources of errors related to instrumental settings that we normally observe in real datasets. In a first step we characterized the error from single laser pulse by modelling the influence of range and incidence angle on single point data accuracy. In a second step, we simulated the scanning part of the system in order to analyze the shifting and angular error effects. Other parameters have been added to the point cloud simulator, such as point spacing, acquisition window, etc., in order to create point clouds of simple and/or complex geometries. We tested the influence of point density and vitiating point of view on the Iterative Closest Point (ICP) alignment and also in some deformation tracking algorithm with same point cloud geometry, in order to determine alignment and deformation detection threshold. We also generated a series of high resolution point clouds in order to model small changes on different environments (erosion, landslide monitoring, etc) and we then tested the use of filtering techniques using 3D moving windows along the space and time, which considerably reduces data scattering due to the benefits of data redundancy. In conclusion, the simulator allowed us to improve our different algorithms and to understand how instrumental error affects final results. And also, improve the methodology of scans acquisition to find the best compromise between point density, positioning and acquisition time with the best accuracy possible to characterize the topographic change.

Detectability of Forest Birds from Stationary Points in Northern Wisconsin

Treesearch

Amy T. Wolf; Robert W. Howe; Gregory J. Davis

1995-01-01

Estimation of avian densities from point counts requires information about the distance at which birds can be detected by the observer. Detection distances also are important for designing the spacing of point counts in a regional sampling scheme. We examined the relationship between distance and detectability for forest songbirds in northern Wisconsin. Like previous...

Detection and attribution of streamflow timing changes to climate change in the Western United States

USGS Publications Warehouse

Hidalgo, H.G.; Das, T.; Dettinger, M.D.; Cayan, D.R.; Pierce, D.W.; Barnett, T.P.; Bala, G.; Mirin, A.; Wood, A.W.; Bonfils, Celine; Santer, B.D.; Nozawa, T.

2009-01-01

This article applies formal detection and attribution techniques to investigate the nature of observed shifts in the timing of streamflow in the western United States. Previous studies have shown that the snow hydrology of the western United States has changed in the second half of the twentieth century. Such changes manifest themselves in the form of more rain and less snow, in reductions in the snow water contents, and in earlier snowmelt and associated advances in streamflow "center" timing (the day in the "water-year" on average when half the water-year flow at a point has passed). However, with one exception over a more limited domain, no other study has attempted to formally attribute these changes to anthropogenic increases of greenhouse gases in the atmosphere. Using the observations together with a set of global climate model simulations and a hydrologic model (applied to three major hydrological regions of the western United States_the California region, the upper Colorado River basin, and the Columbia River basin), it is found that the observed trends toward earlier "center" timing of snowmelt-driven streamflows in the western United States since 1950 are detectably different from natural variability (significant at the p < 0.05 level). Furthermore, the nonnatural parts of these changes can be attributed confidently to climate changes induced by anthropogenic greenhouse gases, aerosols, ozone, and land use. The signal from the Columbia dominates the analysis, and it is the only basin that showed a detectable signal when the analysis was performed on individual basins. It should be noted that although climate change is an important signal, other climatic processes have also contributed to the hydrologic variability of large basins in the western United States. ?? 2009 American Meteorological Society.

Efficient, Decentralized Detection of Qualitative Spatial Events in a Dynamic Scalar Field

PubMed Central

Jeong, Myeong-Hun; Duckham, Matt

2015-01-01

This paper describes an efficient, decentralized algorithm to monitor qualitative spatial events in a dynamic scalar field. The events of interest involve changes to the critical points (i.e., peak, pits and passes) and edges of the surface network derived from the field. Four fundamental types of event (appearance, disappearance, movement and switch) are defined. Our algorithm is designed to rely purely on qualitative information about the neighborhoods of nodes in the sensor network and does not require information about nodes’ coordinate positions. Experimental investigations confirm that our algorithm is efficient, with O(n) overall communication complexity (where n is the number of nodes in the sensor network), an even load balance and low operational latency. The accuracy of event detection is comparable to established centralized algorithms for the identification of critical points of a surface network. Our algorithm is relevant to a broad range of environmental monitoring applications of sensor networks. PMID:26343672

Point-of-care diagnostic tools to detect circulating microRNAS as biomarkers of disease.

PubMed

Vaca, Luis

2014-05-22

MicroRNAs or miRNAs are a form of small non-coding RNAs (ncRNAs) of 19-22 nucleotides in length in their mature form. miRNAs are transcribed in the nucleus of all cells from large precursors, many of which have several kilobases in length. Originally identified as intracellular modulators of protein synthesis via posttranscriptional gene silencing, more recently it has been found that miRNAs can travel in extracellular human fluids inside specialized vesicles known as exosomes. We will be referring to this miRNAs as circulating microRNAs. More interestingly, the miRNA content inside exosomes changes during pathological events. In the present review we analyze the literature about circulating miRNAs and their possible use as biomarkers. Furthermore, we explore their future in point-of-care (POC) diagnostics and provide an example of a portable POC apparatus useful in the detection of circulating miRNAs.

Urban forest topographical mapping using UAV LIDAR

NASA Astrophysics Data System (ADS)

Putut Ash Shidiq, Iqbal; Wibowo, Adi; Kusratmoko, Eko; Indratmoko, Satria; Ardhianto, Ronni; Prasetyo Nugroho, Budi

2017-12-01

Topographical data is highly needed by many parties, such as government institution, mining companies and agricultural sectors. It is not just about the precision, the acquisition time and data processing are also carefully considered. In relation with forest management, a high accuracy topographic map is necessary for planning, close monitoring and evaluating forest changes. One of the solution to quickly and precisely mapped topography is using remote sensing system. In this study, we test high-resolution data using Light Detection and Ranging (LiDAR) collected from unmanned aerial vehicles (UAV) to map topography and differentiate vegetation classes based on height in urban forest area of University of Indonesia (UI). The semi-automatic and manual classifications were applied to divide point clouds into two main classes, namely ground and vegetation. There were 15,806,380 point clouds obtained during the post-process, in which 2.39% of it were detected as ground.

Efficient, Decentralized Detection of Qualitative Spatial Events in a Dynamic Scalar Field.

PubMed

Jeong, Myeong-Hun; Duckham, Matt

2015-08-28

This paper describes an efficient, decentralized algorithm to monitor qualitative spatial events in a dynamic scalar field. The events of interest involve changes to the critical points (i.e., peak, pits and passes) and edges of the surface network derived from the field. Four fundamental types of event (appearance, disappearance, movement and switch) are defined. Our algorithm is designed to rely purely on qualitative information about the neighborhoods of nodes in the sensor network and does not require information about nodes' coordinate positions. Experimental investigations confirm that our algorithm is efficient, with O(n) overall communication complexity (where n is the number of nodes in the sensor network), an even load balance and low operational latency. The accuracy of event detection is comparable to established centralized algorithms for the identification of critical points of a surface network. Our algorithm is relevant to a broad range of environmental monitoring applications of sensor networks.

Recent stability of resident and migratory landbird populations in National Parks of the Pacific Northwest

USGS Publications Warehouse

Ray, Chris; Saracco, James; Holmgren, Mandy; Wilkerson, Robert; Siegel, Rodney; Jenkins, Kurt J.; Ransom, Jason I.; Happe, Patricia J.; Boetsch, John; Huff, Mark

2017-01-01

Monitoring species in National Parks facilitates inference regarding effects of climate change on population dynamics because parks are relatively unaffected by other forms of anthropogenic disturbance. Even at early points in a monitoring program, identifying climate covariates of population density can suggest vulnerabilities to future change. Monitoring landbird populations in parks during the breeding season brings the added benefit of allowing a comparative approach to inference across a large suite of species with diverse requirements. For example, comparing resident and migratory species that vary in exposure to non-park habitats can reveal the relative importance of park effects, such as those related to local climate. We monitored landbirds using breeding-season point-count data collected during 2005–2014 in three wilderness areas of the Pacific Northwest (Mount Rainier, North Cascades, and Olympic National Parks). For 39 species, we estimated recent trends in population density while accounting for individual detection probability using Bayesian hierarchical N-mixture models. Our analyses integrated several recent developments in N-mixture modeling, incorporating interval and distance sampling to estimate distinct components of detection probability while also accommodating count intervals of varying duration, annual variation in the length and number of point-count transects, spatial autocorrelation, random effects, and covariates of detection and density. As covariates of density, we considered metrics of precipitation and temperature hypothesized to affect breeding success. We also considered effects of park and elevational stratum on trend. Regardless of model structure, we estimated stable or increasing densities during 2005–2014 for most populations. Mean trends across species were positive for migrants in every park and for residents in one park. A recent snowfall deficit in this region might have contributed to the positive trend, because population density varied inversely with precipitation-as-snow for both migrants and residents. Densities varied directly but much more weakly with mean spring temperature. Our approach exemplifies an analytical framework for estimating trends from point-count data, and for assessing the role of climatic and other spatiotemporal variables in driving those trends. Understanding population trends and the factors that drive them is critical for adaptive management and resource stewardship in the context of climate change.

Intersection Detection Based on Qualitative Spatial Reasoning on Stopping Point Clusters

NASA Astrophysics Data System (ADS)

Zourlidou, S.; Sester, M.

2016-06-01

The purpose of this research is to propose and test a method for detecting intersections by analysing collectively acquired trajectories of moving vehicles. Instead of solely relying on the geometric features of the trajectories, such as heading changes, which may indicate turning points and consequently intersections, we extract semantic features of the trajectories in form of sequences of stops and moves. Under this spatiotemporal prism, the extracted semantic information which indicates where vehicles stop can reveal important locations, such as junctions. The advantage of the proposed approach in comparison with existing turning-points oriented approaches is that it can detect intersections even when not all the crossing road segments are sampled and therefore no turning points are observed in the trajectories. The challenge with this approach is that first of all, not all vehicles stop at the same location - thus, the stop-location is blurred along the direction of the road; this, secondly, leads to the effect that nearby junctions can induce similar stop-locations. As a first step, a density-based clustering is applied on the layer of stop observations and clusters of stop events are found. Representative points of the clusters are determined (one per cluster) and in a last step the existence of an intersection is clarified based on spatial relational cluster reasoning, with which less informative geospatial clusters, in terms of whether a junction exists and where its centre lies, are transformed in more informative ones. Relational reasoning criteria, based on the relative orientation of the clusters with their adjacent ones are discussed for making sense of the relation that connects them, and finally for forming groups of stop events that belong to the same junction.

A Deformable Smart Skin for Continuous Sensing Based on Electrical Impedance Tomography.

PubMed

Visentin, Francesco; Fiorini, Paolo; Suzuki, Kenji

2016-11-16

In this paper, we present a low-cost, adaptable, and flexible pressure sensor that can be applied as a smart skin over both stiff and deformable media. The sensor can be easily adapted for use in applications related to the fields of robotics, rehabilitation, or costumer electronic devices. In order to remove most of the stiff components that block the flexibility of the sensor, we based the sensing capability on the use of a tomographic technique known as Electrical Impedance Tomography. The technique allows the internal structure of the domain under study to be inferred by reconstructing its conductivity map. By applying the technique to a material that changes its resistivity according to applied forces, it is possible to identify these changes and then localise the area where the force was applied. We tested the system when applied to flat and curved surfaces. For all configurations, we evaluate the artificial skin capabilities to detect forces applied over a single point, over multiple points, and changes in the underlying geometry. The results are all promising, and open the way for the application of such sensors in different robotic contexts where deformability is the key point.

A Deformable Smart Skin for Continuous Sensing Based on Electrical Impedance Tomography

PubMed Central

Visentin, Francesco; Fiorini, Paolo; Suzuki, Kenji

2016-01-01

In this paper, we present a low-cost, adaptable, and flexible pressure sensor that can be applied as a smart skin over both stiff and deformable media. The sensor can be easily adapted for use in applications related to the fields of robotics, rehabilitation, or costumer electronic devices. In order to remove most of the stiff components that block the flexibility of the sensor, we based the sensing capability on the use of a tomographic technique known as Electrical Impedance Tomography. The technique allows the internal structure of the domain under study to be inferred by reconstructing its conductivity map. By applying the technique to a material that changes its resistivity according to applied forces, it is possible to identify these changes and then localise the area where the force was applied. We tested the system when applied to flat and curved surfaces. For all configurations, we evaluate the artificial skin capabilities to detect forces applied over a single point, over multiple points, and changes in the underlying geometry. The results are all promising, and open the way for the application of such sensors in different robotic contexts where deformability is the key point. PMID:27854325

Demonstration of Technologies for Remote and in Situ Sensing of Atmospheric Methane Abundances - a Controlled Release Experiment

NASA Astrophysics Data System (ADS)

Aubrey, A. D.; Thorpe, A. K.; Christensen, L. E.; Dinardo, S.; Frankenberg, C.; Rahn, T. A.; Dubey, M.

2013-12-01

It is critical to constrain both natural and anthropogenic sources of methane to better predict the impact on global climate change. Critical technologies for this assessment include those that can detect methane point and concentrated diffuse sources over large spatial scales. Airborne spectrometers can potentially fill this gap for large scale remote sensing of methane while in situ sensors, both ground-based and mounted on aerial platforms, can monitor and quantify at small to medium spatial scales. The Jet Propulsion Laboratory (JPL) and collaborators recently conducted a field test located near Casper, WY, at the Rocky Mountain Oilfield Test Center (RMOTC). These tests were focused on demonstrating the performance of remote and in situ sensors for quantification of point-sourced methane. A series of three controlled release points were setup at RMOTC and over the course of six experiment days, the point source flux rates were varied from 50 LPM to 2400 LPM (liters per minute). During these releases, in situ sensors measured real-time methane concentration from field towers (downwind from the release point) and using a small Unmanned Aerial System (sUAS) to characterize spatiotemporal variability of the plume structure. Concurrent with these methane point source controlled releases, airborne sensor overflights were conducted using three aircraft. The NASA Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) participated with a payload consisting of a Fourier Transform Spectrometer (FTS) and an in situ methane sensor. Two imaging spectrometers provided assessment of optical and thermal infrared detection of methane plumes. The AVIRIS-next generation (AVIRIS-ng) sensor has been demonstrated for detection of atmospheric methane in the short wave infrared region, specifically using the absorption features at ~2.3 μm. Detection of methane in the thermal infrared region was evaluated by flying the Hyperspectral Thermal Emission Spectrometer (HyTES), retrievals which interrogate spectral features in the 7.5 to 8.5 μm region. Here we discuss preliminary results from the JPL activities during the RMOTC controlled release experiment, including capabilities of airborne sensors for total columnar atmospheric methane detection and comparison to results from ground measurements and dispersion models. Potential application areas for these remote sensing technologies include assessment of anthropogenic and natural methane sources over wide spatial scales that represent significant unconstrained factors to the global methane budget.

Image and Processing Models for Satellite Detection in Images Acquired by Space-based Surveillance-of-Space Sensors

DTIC Science & Technology

2010-09-01

external sources ‘L1’ like zodiacal light (or diffuse nebula ) or stray light ‘L2’ and these components change with the telescope pointing. Bk (T,t...Astronomical scene background (zodiacal light, diffuse nebulae , etc.). L2(P A(tk), t): Image background component caused by stray light. MS

An experiment to test in-field pointing for Elisa

NASA Astrophysics Data System (ADS)

Brugger, Christina; Broll, Bernhard; Fitzsimons, Ewan; Johann, Ulrich; Jonke, Wouter; Lucarelli, Stefano; Nikolov, Susanne; Voert, Martijn; Weise, Dennis; Witvoet, Gert

2017-11-01

The evolved Laser Interferometer Space Antenna (eLISA) Mission is being developed to detect and characterise gravitational waves by measuring pathlength changes between free flying inertial test masses over a baseline of order 1 Gm. Here the observed astrophysical events and objects lie in a frequency range between 30 μHz and 1 Hz (the LISA measurement band, LMB).

Experimental study of digital image processing techniques for LANDSAT data

NASA Technical Reports Server (NTRS)

Rifman, S. S. (Principal Investigator); Allendoerfer, W. B.; Caron, R. H.; Pemberton, L. J.; Mckinnon, D. M.; Polanski, G.; Simon, K. W.

1976-01-01

The author has identified the following significant results. Results are reported for: (1) subscene registration, (2) full scene rectification and registration, (3) resampling techniques, (4) and ground control point (GCP) extraction. Subscenes (354 pixels x 234 lines) were registered to approximately 1/4 pixel accuracy and evaluated by change detection imagery for three cases: (1) bulk data registration, (2) precision correction of a reference subscene using GCP data, and (3) independently precision processed subscenes. Full scene rectification and registration results were evaluated by using a correlation technique to measure registration errors of 0.3 pixel rms thoughout the full scene. Resampling evaluations of nearest neighbor and TRW cubic convolution processed data included change detection imagery and feature classification. Resampled data were also evaluated for an MSS scene containing specular solar reflections.

Change Detection of Mobile LIDAR Data Using Cloud Computing

NASA Astrophysics Data System (ADS)

Liu, Kun; Boehm, Jan; Alis, Christian

2016-06-01

Change detection has long been a challenging problem although a lot of research has been conducted in different fields such as remote sensing and photogrammetry, computer vision, and robotics. In this paper, we blend voxel grid and Apache Spark together to propose an efficient method to address the problem in the context of big data. Voxel grid is a regular geometry representation consisting of the voxels with the same size, which fairly suites parallel computation. Apache Spark is a popular distributed parallel computing platform which allows fault tolerance and memory cache. These features can significantly enhance the performance of Apache Spark and results in an efficient and robust implementation. In our experiments, both synthetic and real point cloud data are employed to demonstrate the quality of our method.

A 3D clustering approach for point clouds to detect and quantify changes at a rock glacier front

NASA Astrophysics Data System (ADS)

Micheletti, Natan; Tonini, Marj; Lane, Stuart N.

2016-04-01

Terrestrial Laser Scanners (TLS) are extensively used in geomorphology to remotely-sense landforms and surfaces of any type and to derive digital elevation models (DEMs). Modern devices are able to collect many millions of points, so that working on the resulting dataset is often troublesome in terms of computational efforts. Indeed, it is not unusual that raw point clouds are filtered prior to DEM creation, so that only a subset of points is retained and the interpolation process becomes less of a burden. Whilst this procedure is in many cases necessary, it implicates a considerable loss of valuable information. First, and even without eliminating points, the common interpolation of points to a regular grid causes a loss of potentially useful detail. Second, it inevitably causes the transition from 3D information to only 2.5D data where each (x,y) pair must have a unique z-value. Vector-based DEMs (e.g. triangulated irregular networks) partially mitigate these issues, but still require a set of parameters to be set and a considerable burden in terms of calculation and storage. Because of the reasons above, being able to perform geomorphological research directly on point clouds would be profitable. Here, we propose an approach to identify erosion and deposition patterns on a very active rock glacier front in the Swiss Alps to monitor sediment dynamics. The general aim is to set up a semiautomatic method to isolate mass movements using 3D-feature identification directly from LiDAR data. An ultra-long range LiDAR RIEGL VZ-6000 scanner was employed to acquire point clouds during three consecutive summers. In order to isolate single clusters of erosion and deposition we applied the Density-Based Scan Algorithm with Noise (DBSCAN), previously successfully employed by Tonini and Abellan (2014) in a similar case for rockfall detection. DBSCAN requires two input parameters, strongly influencing the number, shape and size of the detected clusters: the minimum number of points (i) at a maximum distance (ii) around each core-point. Under this condition, seed points are said to be density-reachable by a core point delimiting a cluster around it. A chain of intermediate seed-points can connect contiguous clusters allowing clusters of arbitrary shape to be defined. The novelty of the proposed approach consists in the implementation of the DBSCAN 3D-module, where the xyz-coordinates identify each point and the density of points within a sphere is considered. This allows detecting volumetric features with a higher accuracy, depending only on actual sampling resolution. The approach is truly 3D and exploits all TLS measurements without the need of interpolation or data reduction. Using this method, enhanced geomorphological activity during the summer of 2015 in respect to the previous two years was observed. We attribute this result to the exceptionally high temperatures of that summer, which we deem responsible for accelerating the melting process at the rock glacier front and probably also increasing creep velocities. References: - Tonini, M. and Abellan, A. (2014). Rockfall detection from terrestrial LiDAR point clouds: A clustering approach using R. Journal of Spatial Information Sciences. Number 8, pp95-110 - Hennig, C. Package fpc: Flexible procedures for clustering. https://cran.r-project.org/web/packages/fpc/index.html, 2015. Accessed 2016-01-12.

Shining a light on LAMP assays--a comparison of LAMP visualization methods including the novel use of berberine.

PubMed

Fischbach, Jens; Xander, Nina Carolin; Frohme, Marcus; Glökler, Jörn Felix

2015-04-01

The need for simple and effective assays for detecting nucleic acids by isothermal amplification reactions has led to a great variety of end point and real-time monitoring methods. Here we tested direct and indirect methods to visualize the amplification of potato spindle tuber viroid (PSTVd) by loop-mediated isothermal amplification (LAMP) and compared features important for one-pot in-field applications. We compared the performance of magnesium pyrophosphate, hydroxynaphthol blue (HNB), calcein, SYBR Green I, EvaGreen, and berberine. All assays could be used to distinguish between positive and negative samples in visible or UV light. Precipitation of magnesium-pyrophosphate resulted in a turbid reaction solution. The use of HNB resulted in a color change from violet to blue, whereas calcein induced a change from orange to yellow-green. We also investigated berberine as a nucleic acid-specific dye that emits a fluorescence signal under UV light after a positive LAMP reaction. It has a comparable sensitivity to SYBR Green I and EvaGreen. Based on our results, an optimal detection method can be chosen easily for isothermal real-time or end point screening applications.

Video shot boundary detection using region-growing-based watershed method

NASA Astrophysics Data System (ADS)

Wang, Jinsong; Patel, Nilesh; Grosky, William

2004-10-01

In this paper, a novel shot boundary detection approach is presented, based on the popular region growing segmentation method - Watershed segmentation. In image processing, gray-scale pictures could be considered as topographic reliefs, in which the numerical value of each pixel of a given image represents the elevation at that point. Watershed method segments images by filling up basins with water starting at local minima, and at points where water coming from different basins meet, dams are built. In our method, each frame in the video sequences is first transformed from the feature space into the topographic space based on a density function. Low-level features are extracted from frame to frame. Each frame is then treated as a point in the feature space. The density of each point is defined as the sum of the influence functions of all neighboring data points. The height function that is originally used in Watershed segmentation is then replaced by inverting the density at the point. Thus, all the highest density values are transformed into local minima. Subsequently, Watershed segmentation is performed in the topographic space. The intuitive idea under our method is that frames within a shot are highly agglomerative in the feature space and have higher possibilities to be merged together, while those frames between shots representing the shot changes are not, hence they have less density values and are less likely to be clustered by carefully extracting the markers and choosing the stopping criterion.

Methodological demonstration of laser beam pointing control for space gravitational wave detection missions.

PubMed

Dong, Yu-Hui; Liu, He-Shan; Luo, Zi-Ren; Li, Yu-Qiong; Jin, Gang

2014-07-01

In space laser interferometer gravitational wave (G.W.) detection missions, the stability of the laser beam pointing direction has to be kept at 10 nrad/√Hz. Otherwise, the beam pointing jitter noise will dominate the noise budget and make the detection of G.W. impossible. Disturbed by the residue non-conservative forces, the fluctuation of the laser beam pointing direction could be a few μrad/√Hz at frequencies from 0.1 mHz to 10 Hz. Therefore, the laser beam pointing control system is an essential requirement for those space G.W. detection missions. An on-ground test of such beam pointing control system is performed, where the Differential Wave-front Sensing technique is used to sense the beams pointing jitter. An active controlled steering mirror is employed to adjust the beam pointing direction to compensate the jitter. The experimental result shows that the pointing control system can be used for very large dynamic range up to 5 μrad. At the interested frequencies of space G.W. detection missions, between 1 mHz and 1 Hz, beam pointing stability of 6 nrad/√Hz is achieved.

Methodological demonstration of laser beam pointing control for space gravitational wave detection missions

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

Dong, Yu-Hui; Liu, He-Shan; University of Chinese Academy of Sciences, Beijing 100190

In space laser interferometer gravitational wave (G.W.) detection missions, the stability of the laser beam pointing direction has to be kept at 10 nrad/√Hz. Otherwise, the beam pointing jitter noise will dominate the noise budget and make the detection of G.W. impossible. Disturbed by the residue non-conservative forces, the fluctuation of the laser beam pointing direction could be a few μrad/√Hz at frequencies from 0.1 mHz to 10 Hz. Therefore, the laser beam pointing control system is an essential requirement for those space G.W. detection missions. An on-ground test of such beam pointing control system is performed, where the Differentialmore » Wave-front Sensing technique is used to sense the beams pointing jitter. An active controlled steering mirror is employed to adjust the beam pointing direction to compensate the jitter. The experimental result shows that the pointing control system can be used for very large dynamic range up to 5 μrad. At the interested frequencies of space G.W. detection missions, between 1 mHz and 1 Hz, beam pointing stability of 6 nrad/√Hz is achieved.« less

SU-F-R-17: Advancing Glioblastoma Multiforme (GBM) Recurrence Detection with MRI Image Texture Feature Extraction and Machine Learning

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

Yu, V; Ruan, D; Nguyen, D

Purpose: To test the potential of early Glioblastoma Multiforme (GBM) recurrence detection utilizing image texture pattern analysis in serial MR images post primary treatment intervention. Methods: MR image-sets of six time points prior to the confirmed recurrence diagnosis of a GBM patient were included in this study, with each time point containing T1 pre-contrast, T1 post-contrast, T2-Flair, and T2-TSE images. Eight Gray-level co-occurrence matrix (GLCM) texture features including Contrast, Correlation, Dissimilarity, Energy, Entropy, Homogeneity, Sum-Average, and Variance were calculated from all images, resulting in a total of 32 features at each time point. A confirmed recurrent volume was contoured, alongmore » with an adjacent non-recurrent region-of-interest (ROI) and both volumes were propagated to all prior time points via deformable image registration. A support vector machine (SVM) with radial-basis-function kernels was trained on the latest time point prior to the confirmed recurrence to construct a model for recurrence classification. The SVM model was then applied to all prior time points and the volumes classified as recurrence were obtained. Results: An increase in classified volume was observed over time as expected. The size of classified recurrence maintained at a stable level of approximately 0.1 cm{sup 3} up to 272 days prior to confirmation. Noticeable volume increase to 0.44 cm{sup 3} was demonstrated at 96 days prior, followed by significant increase to 1.57 cm{sup 3} at 42 days prior. Visualization of the classified volume shows the merging of recurrence-susceptible region as the volume change became noticeable. Conclusion: Image texture pattern analysis in serial MR images appears to be sensitive to detecting the recurrent GBM a long time before the recurrence is confirmed by a radiologist. The early detection may improve the efficacy of targeted intervention including radiosurgery. More patient cases will be included to create a generalizable classification model applicable to a larger patient cohort. NIH R43CA183390 and R01CA188300.NSF Graduate Research Fellowship DGE-1144087.« less

Necrosulfonamide Attenuates Spinal Cord Injury via Necroptosis Inhibition.

PubMed

Wang, Yongxiang; Wang, Jingcheng; Wang, Hua; Feng, Xinmin; Tao, Yuping; Yang, Jiandong; Cai, Jun

2018-06-01

Spinal cord injury (SCI) is a serious trauma without efficient treatment currently. Necroptosis can be blocked post injury by special inhibitors. This study is to investigate the effects, mechanism, and potential benefit of necrosulfonamide (NSA) for SCI therapy. Pathologic condition was detected using hematoxylin-eosin staining on injured spinal cord and other major organs. Necroptosis-related factors-RIP1, RIP3, and MLKL-were detected using Western blot. Detections on mitochondrial functions such as adenosine triphosphate generation and activities of superoxide dismutase and caspase-3 were also performed. Finally, ethologic performance was detected using a 21-point open-field locomotion test. Reduced lesions and protected neurons were found in the injured spinal cord after treatment with NSA using hematoxylin-eosin staining for pathologic detection. No obvious toxicity on rat liver, kidney, heart, and spleen was detected. Rather than RIP1 and RIP3, MLKL was significantly inhibited by the NSA using Western blot detection. Adenosine triphosphate generation was obviously decreased post injury but slightly increased after the NSA treatment, especially 24 hours post injury. No significant changes were found on activities of superoxide dismutase and caspase-3 after the treatment of NSA. Ethologic performance was significantly improved using a 21-point, open-field locomotion test. Our research indicates NSA attenuates the spinal cord injury via necroptosis inhibition. It might be a potential and safe chemical benefit for SCI therapy. To our knowledge, this is the first study on the effects of NSA as treatment of traumatic SCI. Copyright © 2018 Elsevier Inc. All rights reserved.

Real-Time, Label-Free, All-Electrical Detection of Salmonella typhimurium Using Lead Zirconate Titanate/Gold-Coated Glass Cantilevers at any Relative Humidity

PubMed Central

Zhu, Qing; Shih, Wan Y.; Shih, Wei-Heng

2007-01-01

We have examined non-insulated PZT/gold-coated glass cantilevers for real-time, label-free detection of Salmonella t. by partial dipping at any relative humidity. The PZT/gold-coated glass cantilevers were consisted of a 0.127 mm thick PZT layer about 0.8 mm long, 2 mm wide bonded to a 0.15 mm thick gold-coated glass layer with a 3.0 mm long gold-coated glass tip for detection. We showed that by placing the water level at the nodal point, about 0.8 mm from the free end of the gold-glass tip, there was a 1-hr window in which the resonance frequency was stable despite the water level change by evaporation at 20% relative humidity or higher. By dipping the cantilevers to their nodal point, we were able to do real-time, label-free detection without background resonance frequency corrections at any relative humidity. The partially dipped PZT/gold-coated glass cantilever exhibited mass detection sensitivity, Δm/Δf = −5×10−11g/Hz, and a detection concentration sensitivity, 5×103 cells/ml in 2 ml of liquid, which was about two orders of magnitude lower than that of a 5 MHz QCM. It was also about two orders of magnitude lower than the infection dosage and one order of magnitude lower that the detection limit of a commercial Raptor sensor. PMID:22872784

Detection of nuclei in 4D Nomarski DIC microscope images of early Caenorhabditis elegans embryos using local image entropy and object tracking

PubMed Central

Hamahashi, Shugo; Onami, Shuichi; Kitano, Hiroaki

2005-01-01

Background The ability to detect nuclei in embryos is essential for studying the development of multicellular organisms. A system of automated nuclear detection has already been tested on a set of four-dimensional (4D) Nomarski differential interference contrast (DIC) microscope images of Caenorhabditis elegans embryos. However, the system needed laborious hand-tuning of its parameters every time a new image set was used. It could not detect nuclei in the process of cell division, and could detect nuclei only from the two- to eight-cell stages. Results We developed a system that automates the detection of nuclei in a set of 4D DIC microscope images of C. elegans embryos. Local image entropy is used to produce regions of the images that have the image texture of the nucleus. From these regions, those that actually detect nuclei are manually selected at the first and last time points of the image set, and an object-tracking algorithm then selects regions that detect nuclei in between the first and last time points. The use of local image entropy makes the system applicable to multiple image sets without the need to change its parameter values. The use of an object-tracking algorithm enables the system to detect nuclei in the process of cell division. The system detected nuclei with high sensitivity and specificity from the one- to 24-cell stages. Conclusion A combination of local image entropy and an object-tracking algorithm enabled highly objective and productive detection of nuclei in a set of 4D DIC microscope images of C. elegans embryos. The system will facilitate genomic and computational analyses of C. elegans embryos. PMID:15910690

Detection of ferromagnetic target based on mobile magnetic gradient tensor system

NASA Astrophysics Data System (ADS)

Gang, Y. I. N.; Yingtang, Zhang; Zhining, Li; Hongbo, Fan; Guoquan, Ren

2016-03-01

Attitude change of mobile magnetic gradient tensor system critically affects the precision of gradient measurements, thereby increasing ambiguity in target detection. This paper presents a rotational invariant-based method for locating and identifying ferromagnetic targets. Firstly, unit magnetic moment vector was derived based on the geometrical invariant, such that the intermediate eigenvector of the magnetic gradient tensor is perpendicular to the magnetic moment vector and the source-sensor displacement vector. Secondly, unit source-sensor displacement vector was derived based on the characteristic that the angle between magnetic moment vector and source-sensor displacement is a rotational invariant. By introducing a displacement vector between two measurement points, the magnetic moment vector and the source-sensor displacement vector were theoretically derived. To resolve the problem of measurement noises existing in the realistic detection applications, linear equations were formulated using invariants corresponding to several distinct measurement points and least square solution of magnetic moment vector and source-sensor displacement vector were obtained. Results of simulation and principal verification experiment showed the correctness of the analytical method, along with the practicability of the least square method.

CRF-Based Model for Instrument Detection and Pose Estimation in Retinal Microsurgery.

PubMed

Alsheakhali, Mohamed; Eslami, Abouzar; Roodaki, Hessam; Navab, Nassir

2016-01-01

Detection of instrument tip in retinal microsurgery videos is extremely challenging due to rapid motion, illumination changes, the cluttered background, and the deformable shape of the instrument. For the same reason, frequent failures in tracking add the overhead of reinitialization of the tracking. In this work, a new method is proposed to localize not only the instrument center point but also its tips and orientation without the need of manual reinitialization. Our approach models the instrument as a Conditional Random Field (CRF) where each part of the instrument is detected separately. The relations between these parts are modeled to capture the translation, rotation, and the scale changes of the instrument. The tracking is done via separate detection of instrument parts and evaluation of confidence via the modeled dependence functions. In case of low confidence feedback an automatic recovery process is performed. The algorithm is evaluated on in vivo ophthalmic surgery datasets and its performance is comparable to the state-of-the-art methods with the advantage that no manual reinitialization is needed.

An ultra-small, multi-point, and multi-color photo-detection system with high sensitivity and high dynamic range.

PubMed

Anazawa, Takashi; Yamazaki, Motohiro

2017-12-05

Although multi-point, multi-color fluorescence-detection systems are widely used in various sciences, they would find wider applications if they are miniaturized. Accordingly, an ultra-small, four-emission-point and four-color fluorescence-detection system was developed. Its size (space between emission points and a detection plane) is 15 × 10 × 12 mm, which is three-orders-of-magnitude smaller than that of a conventional system. Fluorescence from four emission points with an interval of 1 mm on the same plane was respectively collimated by four lenses and split into four color fluxes by four dichroic mirrors. Then, a total of sixteen parallel color fluxes were directly input into an image sensor and simultaneously detected. The emission-point plane and the detection plane (the image-sensor surface) were parallel and separated by a distance of only 12 mm. The developed system was applied to four-capillary array electrophoresis and successfully achieved Sanger DNA sequencing. Moreover, compared with a conventional system, the developed system had equivalent high fluorescence-detection sensitivity (lower detection limit of 17 pM dROX) and 1.6-orders-of-magnitude higher dynamic range (4.3 orders of magnitude).

Electrochemical techniques on sequence-specific PCR amplicon detection for point-of-care applications.

PubMed

Luo, Xiaoteng; Hsing, I-Ming

2009-10-01

Nucleic acid based analysis provides accurate differentiation among closely affiliated species and this species- and sequence-specific detection technique would be particularly useful for point-of-care (POC) testing for prevention and early detection of highly infectious and damaging diseases. Electrochemical (EC) detection and polymerase chain reaction (PCR) are two indispensable steps, in our view, in a nucleic acid based point-of-care testing device as the former, in comparison with the fluorescence counterpart, provides inherent advantages of detection sensitivity, device miniaturization and operation simplicity, and the latter offers an effective way to boost the amount of targets to a detectable quantity. In this mini-review, we will highlight some of the interesting investigations using the combined EC detection and PCR amplification approaches for end-point detection and real-time monitoring. The promise of current approaches and the direction for future investigations will be discussed. It would be our view that the synergistic effect of the combined EC-PCR steps in a portable device provides a promising detection technology platform that will be ready for point-of-care applications in the near future.

Building Development Monitoring in Multitemporal Remotely Sensed Image Pairs with Stochastic Birth-Death Dynamics.

PubMed

Benedek, C; Descombes, X; Zerubia, J

2012-01-01

In this paper, we introduce a new probabilistic method which integrates building extraction with change detection in remotely sensed image pairs. A global optimization process attempts to find the optimal configuration of buildings, considering the observed data, prior knowledge, and interactions between the neighboring building parts. We present methodological contributions in three key issues: 1) We implement a novel object-change modeling approach based on Multitemporal Marked Point Processes, which simultaneously exploits low-level change information between the time layers and object-level building description to recognize and separate changed and unaltered buildings. 2) To answer the challenges of data heterogeneity in aerial and satellite image repositories, we construct a flexible hierarchical framework which can create various building appearance models from different elementary feature-based modules. 3) To simultaneously ensure the convergence, optimality, and computation complexity constraints raised by the increased data quantity, we adopt the quick Multiple Birth and Death optimization technique for change detection purposes, and propose a novel nonuniform stochastic object birth process which generates relevant objects with higher probability based on low-level image features.

Integrated microfluidic technology for sub-lethal and behavioral marine ecotoxicity biotests

NASA Astrophysics Data System (ADS)

Huang, Yushi; Reyes Aldasoro, Constantino Carlos; Persoone, Guido; Wlodkowic, Donald

2015-06-01

Changes in behavioral traits exhibited by small aquatic invertebrates are increasingly postulated as ethically acceptable and more sensitive endpoints for detection of water-born ecotoxicity than conventional mortality assays. Despite importance of such behavioral biotests, their implementation is profoundly limited by the lack of appropriate biocompatible automation, integrated optoelectronic sensors, and the associated electronics and analysis algorithms. This work outlines development of a proof-of-concept miniaturized Lab-on-a-Chip (LOC) platform for rapid water toxicity tests based on changes in swimming patterns exhibited by Artemia franciscana (Artoxkit M™) nauplii. In contrast to conventionally performed end-point analysis based on counting numbers of dead/immobile specimens we performed a time-resolved video data analysis to dynamically assess impact of a reference toxicant on swimming pattern of A. franciscana. Our system design combined: (i) innovative microfluidic device keeping free swimming Artemia sp. nauplii under continuous microperfusion as a mean of toxin delivery; (ii) mechatronic interface for user-friendly fluidic actuation of the chip; and (iii) miniaturized video acquisition for movement analysis of test specimens. The system was capable of performing fully programmable time-lapse and video-microscopy of multiple samples for rapid ecotoxicity analysis. It enabled development of a user-friendly and inexpensive test protocol to dynamically detect sub-lethal behavioral end-points such as changes in speed of movement or distance traveled by each animal.

A removal model for estimating detection probabilities from point-count surveys

USGS Publications Warehouse

Farnsworth, G.L.; Pollock, K.H.; Nichols, J.D.; Simons, T.R.; Hines, J.E.; Sauer, J.R.

2002-01-01

Use of point-count surveys is a popular method for collecting data on abundance and distribution of birds. However, analyses of such data often ignore potential differences in detection probability. We adapted a removal model to directly estimate detection probability during point-count surveys. The model assumes that singing frequency is a major factor influencing probability of detection when birds are surveyed using point counts. This may be appropriate for surveys in which most detections are by sound. The model requires counts to be divided into several time intervals. Point counts are often conducted for 10 min, where the number of birds recorded is divided into those first observed in the first 3 min, the subsequent 2 min, and the last 5 min. We developed a maximum-likelihood estimator for the detectability of birds recorded during counts divided into those intervals. This technique can easily be adapted to point counts divided into intervals of any length. We applied this method to unlimited-radius counts conducted in Great Smoky Mountains National Park. We used model selection criteria to identify whether detection probabilities varied among species, throughout the morning, throughout the season, and among different observers. We found differences in detection probability among species. Species that sing frequently such as Winter Wren (Troglodytes troglodytes) and Acadian Flycatcher (Empidonax virescens) had high detection probabilities (∼90%) and species that call infrequently such as Pileated Woodpecker (Dryocopus pileatus) had low detection probability (36%). We also found detection probabilities varied with the time of day for some species (e.g. thrushes) and between observers for other species. We used the same approach to estimate detection probability and density for a subset of the observations with limited-radius point counts.

Sensitivity and Calibration of Non-Destructive Evaluation Method That Uses Neural-Net Processing of Characteristic Fringe Patterns

NASA Technical Reports Server (NTRS)

Decker, Arthur J.; Weiland, Kenneth E.

2003-01-01

This paper answers some performance and calibration questions about a non-destructive-evaluation (NDE) procedure that uses artificial neural networks to detect structural damage or other changes from sub-sampled characteristic patterns. The method shows increasing sensitivity as the number of sub-samples increases from 108 to 6912. The sensitivity of this robust NDE method is not affected by noisy excitations of the first vibration mode. A calibration procedure is proposed and demonstrated where the output of a trained net can be correlated with the outputs of the point sensors used for vibration testing. The calibration procedure is based on controlled changes of fastener torques. A heterodyne interferometer is used as a displacement sensor for a demonstration of the challenges to be handled in using standard point sensors for calibration.

Segmentation and clustering as complementary sources of information

NASA Astrophysics Data System (ADS)

Dale, Michael B.; Allison, Lloyd; Dale, Patricia E. R.

2007-03-01

This paper examines the effects of using a segmentation method to identify change-points or edges in vegetation. It identifies coherence (spatial or temporal) in place of unconstrained clustering. The segmentation method involves change-point detection along a sequence of observations so that each cluster formed is composed of adjacent samples; this is a form of constrained clustering. The protocol identifies one or more models, one for each section identified, and the quality of each is assessed using a minimum message length criterion, which provides a rational basis for selecting an appropriate model. Although the segmentation is less efficient than clustering, it does provide other information because it incorporates textural similarity as well as homogeneity. In addition it can be useful in determining various scales of variation that may apply to the data, providing a general method of small-scale pattern analysis.

Locating and characterizing a crack in concrete with diffuse ultrasound: A four-point bending test.

PubMed

Larose, Eric; Obermann, Anne; Digulescu, Angela; Planès, Thomas; Chaix, Jean-Francois; Mazerolle, Frédéric; Moreau, Gautier

2015-07-01

This paper describes an original imaging technique, named Locadiff, that benefits from the diffuse effect of ultrasound waves in concrete to detect and locate mechanical changes associated with the opening of pre-existing cracks, and/or to the development of diffuse damage at the tip of the crack. After giving a brief overview of the theoretical model to describe the decorrelation of diffuse waveforms induced by a local change, the article introduces the inversion procedure that produces the three dimensional maps of density of changes. These maps are interpreted in terms of mechanical changes, fracture opening, and damage development. In addition, each fracture is characterized by its effective scattering cross section.

Photoacoustic infrared spectroscopy for conducting gas tracer tests and measuring water saturations in landfills

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

Jung, Yoojin; Han, Byunghyun; Mostafid, M. Erfan

2012-02-15

Highlights: Black-Right-Pointing-Pointer Photoacoustic infrared spectroscopy tested for measuring tracer gas in landfills. Black-Right-Pointing-Pointer Measurement errors for tracer gases were 1-3% in landfill gas. Black-Right-Pointing-Pointer Background signals from landfill gas result in elevated limits of detection. Black-Right-Pointing-Pointer Technique is much less expensive and easier to use than GC. - Abstract: Gas tracer tests can be used to determine gas flow patterns within landfills, quantify volatile contaminant residence time, and measure water within refuse. While gas chromatography (GC) has been traditionally used to analyze gas tracers in refuse, photoacoustic spectroscopy (PAS) might allow real-time measurements with reduced personnel costs and greater mobilitymore » and ease of use. Laboratory and field experiments were conducted to evaluate the efficacy of PAS for conducting gas tracer tests in landfills. Two tracer gases, difluoromethane (DFM) and sulfur hexafluoride (SF{sub 6}), were measured with a commercial PAS instrument. Relative measurement errors were invariant with tracer concentration but influenced by background gas: errors were 1-3% in landfill gas but 4-5% in air. Two partitioning gas tracer tests were conducted in an aerobic landfill, and limits of detection (LODs) were 3-4 times larger for DFM with PAS versus GC due to temporal changes in background signals. While higher LODs can be compensated by injecting larger tracer mass, changes in background signals increased the uncertainty in measured water saturations by up to 25% over comparable GC methods. PAS has distinct advantages over GC with respect to personnel costs and ease of use, although for field applications GC analyses of select samples are recommended to quantify instrument interferences.« less

Automated Detection and Closing of Holes in Aerial Point Clouds Using AN Uas

NASA Astrophysics Data System (ADS)

Fiolka, T.; Rouatbi, F.; Bender, D.

2017-08-01

3D terrain models are an important instrument in areas like geology, agriculture and reconnaissance. Using an automated UAS with a line-based LiDAR can create terrain models fast and easily even from large areas. But the resulting point cloud may contain holes and therefore be incomplete. This might happen due to occlusions, a missed flight route due to wind or simply as a result of changes in the ground height which would alter the swath of the LiDAR system. This paper proposes a method to detect holes in 3D point clouds generated during the flight and adjust the course in order to close them. First, a grid-based search for holes in the horizontal ground plane is performed. Then a check for vertical holes mainly created by buildings walls is done. Due to occlusions and steep LiDAR angles, closing the vertical gaps may be difficult or even impossible. Therefore, the current approach deals with holes in the ground plane and only marks the vertical holes in such a way that the operator can decide on further actions regarding them. The aim is to efficiently create point clouds which can be used for the generation of complete 3D terrain models.

A novel infrared small moving target detection method based on tracking interest points under complicated background

NASA Astrophysics Data System (ADS)

Dong, Xiabin; Huang, Xinsheng; Zheng, Yongbin; Bai, Shengjian; Xu, Wanying

2014-07-01

Infrared moving target detection is an important part of infrared technology. We introduce a novel infrared small moving target detection method based on tracking interest points under complicated background. Firstly, Difference of Gaussians (DOG) filters are used to detect a group of interest points (including the moving targets). Secondly, a sort of small targets tracking method inspired by Human Visual System (HVS) is used to track these interest points for several frames, and then the correlations between interest points in the first frame and the last frame are obtained. Last, a new clustering method named as R-means is proposed to divide these interest points into two groups according to the correlations, one is target points and another is background points. In experimental results, the target-to-clutter ratio (TCR) and the receiver operating characteristics (ROC) curves are computed experimentally to compare the performances of the proposed method and other five sophisticated methods. From the results, the proposed method shows a better discrimination of targets and clutters and has a lower false alarm rate than the existing moving target detection methods.

Supervised segmentation of microelectrode recording artifacts using power spectral density.

PubMed

Bakstein, Eduard; Schneider, Jakub; Sieger, Tomas; Novak, Daniel; Wild, Jiri; Jech, Robert

2015-08-01

Appropriate detection of clean signal segments in extracellular microelectrode recordings (MER) is vital for maintaining high signal-to-noise ratio in MER studies. Existing alternatives to manual signal inspection are based on unsupervised change-point detection. We present a method of supervised MER artifact classification, based on power spectral density (PSD) and evaluate its performance on a database of 95 labelled MER signals. The proposed method yielded test-set accuracy of 90%, which was close to the accuracy of annotation (94%). The unsupervised methods achieved accuracy of about 77% on both training and testing data.

Investigations on vertical crustal movements in the Venezuelan Andes by gravimetric methods

NASA Technical Reports Server (NTRS)

Drewes, H.

1978-01-01

A precise gravimetric network has been installed in the Venezuelan Andes to study eventual gravity changes due to vertical tectonic movements. The design and the measurements of the network are described and the accuracy is estimated. In the center of the region a local gravity network has been reobserved three times. The detected variations are discussed. In order to obtain a genuine statement as far as possible about the significance of observed gravity changes, requirements for the procedure of monitoring precise gravity networks are pointed out.

Singularity detection by wavelet approach: application to electrocardiogram signal

NASA Astrophysics Data System (ADS)

Jalil, Bushra; Beya, Ouadi; Fauvet, Eric; Laligant, Olivier

2010-01-01

In signal processing, the region of abrupt changes contains the most of the useful information about the nature of the signal. The region or the points where these changes occurred are often termed as singular point or singular region. The singularity is considered to be an important character of the signal, as it refers to the discontinuity and interruption present in the signal and the main purpose of the detection of such singular point is to identify the existence, location and size of those singularities. Electrocardiogram (ECG) signal is used to analyze the cardiovascular activity in the human body. However the presence of noise due to several reasons limits the doctor's decision and prevents accurate identification of different pathologies. In this work we attempt to analyze the ECG signal with energy based approach and some heuristic methods to segment and identify different signatures inside the signal. ECG signal has been initially denoised by empirical wavelet shrinkage approach based on Steins Unbiased Risk Estimate (SURE). At the second stage, the ECG signal has been analyzed by Mallat approach based on modulus maximas and Lipschitz exponent computation. The results from both approaches has been discussed and important aspects has been highlighted. In order to evaluate the algorithm, the analysis has been done on MIT-BIH Arrhythmia database; a set of ECG data records sampled at a rate of 360 Hz with 11 bit resolution over a 10mv range. The results have been examined and approved by medical doctors.

Algorithms for Autonomous Plume Detection on Outer Planet Satellites

NASA Astrophysics Data System (ADS)

Lin, Y.; Bunte, M. K.; Saripalli, S.; Greeley, R.

2011-12-01

We investigate techniques for automated detection of geophysical events (i.e., volcanic plumes) from spacecraft images. The algorithms presented here have not been previously applied to detection of transient events on outer planet satellites. We apply Scale Invariant Feature Transform (SIFT) to raw images of Io and Enceladus from the Voyager, Galileo, Cassini, and New Horizons missions. SIFT produces distinct interest points in every image; feature descriptors are reasonably invariant to changes in illumination, image noise, rotation, scaling, and small changes in viewpoint. We classified these descriptors as plumes using the k-nearest neighbor (KNN) algorithm. In KNN, an object is classified by its similarity to examples in a training set of images based on user defined thresholds. Using the complete database of Io images and a selection of Enceladus images where 1-3 plumes were manually detected in each image, we successfully detected 74% of plumes in Galileo and New Horizons images, 95% in Voyager images, and 93% in Cassini images. Preliminary tests yielded some false positive detections; further iterations will improve performance. In images where detections fail, plumes are less than 9 pixels in size or are lost in image glare. We compared the appearance of plumes and illuminated mountain slopes to determine the potential for feature classification. We successfully differentiated features. An advantage over other methods is the ability to detect plumes in non-limb views where they appear in the shadowed part of the surface; improvements will enable detection against the illuminated background surface where gradient changes would otherwise preclude detection. This detection method has potential applications to future outer planet missions for sustained plume monitoring campaigns and onboard automated prioritization of all spacecraft data. The complementary nature of this method is such that it could be used in conjunction with edge detection algorithms to increase effectiveness. We have demonstrated an ability to detect transient events above the planetary limb and on the surface and to distinguish feature classes in spacecraft images.

Applications of 3D-EDGE Detection for ALS Point Cloud

NASA Astrophysics Data System (ADS)

Ni, H.; Lin, X. G.; Zhang, J. X.

2017-09-01

Edge detection has been one of the major issues in the field of remote sensing and photogrammetry. With the fast development of sensor technology of laser scanning system, dense point clouds have become increasingly common. Precious 3D-edges are able to be detected from these point clouds and a great deal of edge or feature line extraction methods have been proposed. Among these methods, an easy-to-use 3D-edge detection method, AGPN (Analyzing Geometric Properties of Neighborhoods), has been proposed. The AGPN method detects edges based on the analysis of geometric properties of a query point's neighbourhood. The AGPN method detects two kinds of 3D-edges, including boundary elements and fold edges, and it has many applications. This paper presents three applications of AGPN, i.e., 3D line segment extraction, ground points filtering, and ground breakline extraction. Experiments show that the utilization of AGPN method gives a straightforward solution to these applications.

SAR Coherence Change Detection of Urban Areas Affected by Disasters Using SENTINEL-1 Imagery

NASA Astrophysics Data System (ADS)

Washaya, P.; Balz, T.

2018-04-01

The study focuses on two study areas: San Juan in Puerto Rico, which was affected by Hurricane Maria in September 2017, and Sarpol Zahab in Iran, which was one of the towns affected by an earthquake in November 2017. In our study, we generate coherence images, and classify them into areas of `change' and `no-change'. A statistical analysis is made by converting the coherence results into point data, creating street blocks for the study areas and integrating the point data into the street blocks to calculate the standard deviation over the whole stack of images. Additionally, Landsat imagery is used to create land-use classes, convert them to polygons and integrate the polygon classes to the coherence maps to determine the average coherence loss per class for each disaster. Results show 65 % loss in coherence after the earthquake in Sarpol-e-Zahab and 75 % loss in Puerto Rico after the Hurricane. Land-use classes show coherence losses to below 0.5 for each disaster.

Application of glas laser altimetry to detect elevation changes in East Antarctica

NASA Astrophysics Data System (ADS)

Scaioni, M.; Tong, X.; Li, R.

2013-10-01

In this paper the use of ICESat/GLAS laser altimeter for estimating multi-temporal elevation changes on polar ice sheets is afforded. Due to non-overlapping laser spots during repeat passes, interpolation methods are required to make comparisons. After reviewing the main methods described in the literature (crossover point analysis, cross-track DEM projection, space-temporal regressions), the last one has been chosen for its capability of providing more elevation change rate measurements. The standard implementation of the space-temporal linear regression technique has been revisited and improved to better cope with outliers and to check the estimability of model's parameters. GLAS data over the PANDA route in East Antarctica have been used for testing. Obtained results have been quite meaningful from a physical point of view, confirming the trend reported by the literature of a constant snow accumulation in the area during the two past decades, unlike the most part of the continent that has been losing mass.

Identifying influential data points in hydrological model calibration and their impact on streamflow predictions

NASA Astrophysics Data System (ADS)

Wright, David; Thyer, Mark; Westra, Seth

2015-04-01

Highly influential data points are those that have a disproportionately large impact on model performance, parameters and predictions. However, in current hydrological modelling practice the relative influence of individual data points on hydrological model calibration is not commonly evaluated. This presentation illustrates and evaluates several influence diagnostics tools that hydrological modellers can use to assess the relative influence of data. The feasibility and importance of including influence detection diagnostics as a standard tool in hydrological model calibration is discussed. Two classes of influence diagnostics are evaluated: (1) computationally demanding numerical "case deletion" diagnostics; and (2) computationally efficient analytical diagnostics, based on Cook's distance. These diagnostics are compared against hydrologically orientated diagnostics that describe changes in the model parameters (measured through the Mahalanobis distance), performance (objective function displacement) and predictions (mean and maximum streamflow). These influence diagnostics are applied to two case studies: a stage/discharge rating curve model, and a conceptual rainfall-runoff model (GR4J). Removing a single data point from the calibration resulted in differences to mean flow predictions of up to 6% for the rating curve model, and differences to mean and maximum flow predictions of up to 10% and 17%, respectively, for the hydrological model. When using the Nash-Sutcliffe efficiency in calibration, the computationally cheaper Cook's distance metrics produce similar results to the case-deletion metrics at a fraction of the computational cost. However, Cooks distance is adapted from linear regression with inherit assumptions on the data and is therefore less flexible than case deletion. Influential point detection diagnostics show great potential to improve current hydrological modelling practices by identifying highly influential data points. The findings of this study establish the feasibility and importance of including influential point detection diagnostics as a standard tool in hydrological model calibration. They provide the hydrologist with important information on whether model calibration is susceptible to a small number of highly influent data points. This enables the hydrologist to make a more informed decision of whether to (1) remove/retain the calibration data; (2) adjust the calibration strategy and/or hydrological model to reduce the susceptibility of model predictions to a small number of influential observations.

Simultaneous Detection and Tracking of Pedestrian from Panoramic Laser Scanning Data

NASA Astrophysics Data System (ADS)

Xiao, Wen; Vallet, Bruno; Schindler, Konrad; Paparoditis, Nicolas

2016-06-01

Pedestrian traffic flow estimation is essential for public place design and construction planning. Traditional data collection by human investigation is tedious, inefficient and expensive. Panoramic laser scanners, e.g. Velodyne HDL-64E, which scan surroundings repetitively at a high frequency, have been increasingly used for 3D object tracking. In this paper, a simultaneous detection and tracking (SDAT) method is proposed for precise and automatic pedestrian trajectory recovery. First, the dynamic environment is detected using two different methods, Nearest-point and Max-distance. Then, all the points on moving objects are transferred into a space-time (x, y, t) coordinate system. The pedestrian detection and tracking amounts to assign the points belonging to pedestrians into continuous trajectories in space-time. We formulate the point assignment task as an energy function which incorporates the point evidence, trajectory number, pedestrian shape and motion. A low energy trajectory will well explain the point observations, and have plausible trajectory trend and length. The method inherently filters out points from other moving objects and false detections. The energy function is solved by a two-step optimization process: tracklet detection in a short temporal window; and global tracklet association through the whole time span. Results demonstrate that the proposed method can automatically recover the pedestrians trajectories with accurate positions and low false detections and mismatches.

Automated terrestrial laser scanning with near-real-time change detection - monitoring of the Séchilienne landslide

NASA Astrophysics Data System (ADS)

Kromer, Ryan A.; Abellán, Antonio; Hutchinson, D. Jean; Lato, Matt; Chanut, Marie-Aurelie; Dubois, Laurent; Jaboyedoff, Michel

2017-05-01

We present an automated terrestrial laser scanning (ATLS) system with automatic near-real-time change detection processing. The ATLS system was tested on the Séchilienne landslide in France for a 6-week period with data collected at 30 min intervals. The purpose of developing the system was to fill the gap of high-temporal-resolution TLS monitoring studies of earth surface processes and to offer a cost-effective, light, portable alternative to ground-based interferometric synthetic aperture radar (GB-InSAR) deformation monitoring. During the study, we detected the flux of talus, displacement of the landslide and pre-failure deformation of discrete rockfall events. Additionally, we found the ATLS system to be an effective tool in monitoring landslide and rockfall processes despite missing points due to poor atmospheric conditions or rainfall. Furthermore, such a system has the potential to help us better understand a wide variety of slope processes at high levels of temporal detail.

Automatic updating and 3D modeling of airport information from high resolution images using GIS and LIDAR data

NASA Astrophysics Data System (ADS)

Lv, Zheng; Sui, Haigang; Zhang, Xilin; Huang, Xianfeng

2007-11-01

As one of the most important geo-spatial objects and military establishment, airport is always a key target in fields of transportation and military affairs. Therefore, automatic recognition and extraction of airport from remote sensing images is very important and urgent for updating of civil aviation and military application. In this paper, a new multi-source data fusion approach on automatic airport information extraction, updating and 3D modeling is addressed. Corresponding key technologies including feature extraction of airport information based on a modified Ostu algorithm, automatic change detection based on new parallel lines-based buffer detection algorithm, 3D modeling based on gradual elimination of non-building points algorithm, 3D change detecting between old airport model and LIDAR data, typical CAD models imported and so on are discussed in detail. At last, based on these technologies, we develop a prototype system and the results show our method can achieve good effects.

Water Vapor Winds and Their Application to Climate Change Studies

NASA Technical Reports Server (NTRS)

Jedlovec, Gary J.; Lerner, Jeffrey A.

2000-01-01

The retrieval of satellite-derived winds and moisture from geostationary water vapor imagery has matured to the point where it may be applied to better understanding longer term climate changes that were previously not possible using conventional measurements or model analysis in data-sparse regions. In this paper, upper-tropospheric circulation features and moisture transport covering ENSO periods are presented and discussed. Precursors and other detectable interannual climate change signals are analyzed and compared to model diagnosed features. Estimates of winds and humidity over data-rich regions are used to show the robustness of the data and its value over regions that have previously eluded measurement.

Optimization of a Viability PCR Method for the Detection of Listeria monocytogenes in Food Samples.

PubMed

Agustí, Gemma; Fittipaldi, Mariana; Codony, Francesc

2018-06-01

Rapid detection of Listeria and other microbial pathogens in food is an essential part of quality control and it is critical for ensuring the safety of consumers. Culture-based methods for detecting foodborne pathogens are time-consuming, laborious and cannot detect viable but non-culturable microorganism, whereas viability PCR methodology provides quick results; it is able to detect viable but non-culturable cells, and allows for easier handling of large amount of samples. Although the most critical point to use viability PCR technique is achieving the complete exclusion of dead cell amplification signals, many improvements are being introduced to overcome this. In the present work, the yield of dead cell DNA neutralization was enhanced by incorporating two new sample treatment strategies: tube change combined with a double light treatment. This procedure was successfully tested using artificially contaminated food samples, showing improved neutralization of dead cell DNA.

Overview of the "epigenetic end points in toxicologic pathology and relevance to human health" session of the 2014 Society Of Toxicologic Pathology Annual Symposium.

PubMed

Hoenerhoff, Mark J; Hartke, James

2015-01-01

The theme of the Society of Toxicologic Pathology 2014 Annual Symposium was "Translational Pathology: Relevance of Toxicologic Pathology to Human Health." The 5th session focused on epigenetic end points in biology, toxicity, and carcinogenicity, and how those end points are relevant to human exposures. This overview highlights the various presentations in this session, discussing integration of epigenetics end points in toxicologic pathology studies, investigating the role of epigenetics in product safety assessment, epigenetic changes in cancers, methodologies to detect them, and potential therapies, chromatin remodeling in development and disease, and epigenomics and the microbiome. The purpose of this overview is to discuss the application of epigenetics to toxicologic pathology and its utility in preclinical or mechanistic based safety, efficacy, and carcinogenicity studies. © 2014 by The Author(s).

Reference point detection for camera-based fingerprint image based on wavelet transformation.

PubMed

Khalil, Mohammed S

2015-04-30

Fingerprint recognition systems essentially require core-point detection prior to fingerprint matching. The core-point is used as a reference point to align the fingerprint with a template database. When processing a larger fingerprint database, it is necessary to consider the core-point during feature extraction. Numerous core-point detection methods are available and have been reported in the literature. However, these methods are generally applied to scanner-based images. Hence, this paper attempts to explore the feasibility of applying a core-point detection method to a fingerprint image obtained using a camera phone. The proposed method utilizes a discrete wavelet transform to extract the ridge information from a color image. The performance of proposed method is evaluated in terms of accuracy and consistency. These two indicators are calculated automatically by comparing the method's output with the defined core points. The proposed method is tested on two data sets, controlled and uncontrolled environment, collected from 13 different subjects. In the controlled environment, the proposed method achieved a detection rate 82.98%. In uncontrolled environment, the proposed method yield a detection rate of 78.21%. The proposed method yields promising results in a collected-image database. Moreover, the proposed method outperformed compare to existing method.

Individual Rocks Segmentation in Terrestrial Laser Scanning Point Cloud Using Iterative Dbscan Algorithm

NASA Astrophysics Data System (ADS)

Walicka, A.; Jóźków, G.; Borkowski, A.

2018-05-01

The fluvial transport is an important aspect of hydrological and geomorphologic studies. The knowledge about the movement parameters of different-size fractions is essential in many applications, such as the exploration of the watercourse changes, the calculation of the river bed parameters or the investigation of the frequency and the nature of the weather events. Traditional techniques used for the fluvial transport investigations do not provide any information about the long-term horizontal movement of the rocks. This information can be gained by means of terrestrial laser scanning (TLS). However, this is a complex issue consisting of several stages of data processing. In this study the methodology for individual rocks segmentation from TLS point cloud has been proposed, which is the first step for the semi-automatic algorithm for movement detection of individual rocks. The proposed algorithm is executed in two steps. Firstly, the point cloud is classified as rocks or background using only geometrical information. Secondly, the DBSCAN algorithm is executed iteratively on points classified as rocks until only one stone is detected in each segment. The number of rocks in each segment is determined using principal component analysis (PCA) and simple derivative method for peak detection. As a result, several segments that correspond to individual rocks are formed. Numerical tests were executed on two test samples. The results of the semi-automatic segmentation were compared to results acquired by manual segmentation. The proposed methodology enabled to successfully segment 76 % and 72 % of rocks in the test sample 1 and test sample 2, respectively.

Experimental investigation of leak detection using mobile distributed monitoring system

NASA Astrophysics Data System (ADS)

Chen, Jiang; Zheng, Junli; Xiong, Feng; Ge, Qi; Yan, Qixiang; Cheng, Fei

2018-01-01

The leak detection of rockfill dams is currently hindered by spatial and temporal randomness and wide monitoring range. The spatial resolution of fiber Bragg grating (FBG) temperature sensing technology is related to the distance between measuring points. As a result, the number of measuring points should be increased to ensure that the precise location of the leak is detected. However, this leads to a higher monitoring cost. Consequently, it is difficult to promote and apply this technology to effectively monitor rockfill dam leakage. In this paper, a practical mobile distributed monitoring system with dual-tubes is used by combining the FBG sensing system and hydrothermal cycling system. This dual-tube structure is composed of an outer polyethylene of raised temperature resistance heating pipe, an inner polytetrafluoroethylene tube, and a FBG sensor string, among which, the FBG sensor string can be dragged freely in the internal tube to change the position of the measuring points and improve the spatial resolution. In order to test the effectiveness of the system, the large-scale model test of concentrated leakage in 13 working conditions is carried out by identifying the location, quantity, and leakage rate of leakage passage. Based on Newton’s law of cooling, the leakage state is identified using the seepage identification index ζ v that was confirmed according to the cooling curve. Results suggested that the monitoring system shows high sensitivity and can improve the spatial resolution with limited measuring points, and thus better locate the leakage area. In addition, the seepage identification index ζ v correlated well with the leakage rate qualitatively.

Probabilistic model for quick detection of dissimilar binary images

NASA Astrophysics Data System (ADS)

Mustafa, Adnan A. Y.

2015-09-01

We present a quick method to detect dissimilar binary images. The method is based on a "probabilistic matching model" for image matching. The matching model is used to predict the probability of occurrence of distinct-dissimilar image pairs (completely different images) when matching one image to another. Based on this model, distinct-dissimilar images can be detected by matching only a few points between two images with high confidence, namely 11 points for a 99.9% successful detection rate. For image pairs that are dissimilar but not distinct-dissimilar, more points need to be mapped. The number of points required to attain a certain successful detection rate or confidence depends on the amount of similarity between the compared images. As this similarity increases, more points are required. For example, images that differ by 1% can be detected by mapping fewer than 70 points on average. More importantly, the model is image size invariant; so, images of any sizes will produce high confidence levels with a limited number of matched points. As a result, this method does not suffer from the image size handicap that impedes current methods. We report on extensive tests conducted on real images of different sizes.

Distribution majorization of corner points by reinforcement learning for moving object detection

NASA Astrophysics Data System (ADS)

Wu, Hao; Yu, Hao; Zhou, Dongxiang; Cheng, Yongqiang

2018-04-01

Corner points play an important role in moving object detection, especially in the case of free-moving camera. Corner points provide more accurate information than other pixels and reduce the computation which is unnecessary. Previous works only use intensity information to locate the corner points, however, the information that former and the last frames provided also can be used. We utilize the information to focus on more valuable area and ignore the invaluable area. The proposed algorithm is based on reinforcement learning, which regards the detection of corner points as a Markov process. In the Markov model, the video to be detected is regarded as environment, the selections of blocks for one corner point are regarded as actions and the performance of detection is regarded as state. Corner points are assigned to be the blocks which are seperated from original whole image. Experimentally, we select a conventional method which uses marching and Random Sample Consensus algorithm to obtain objects as the main framework and utilize our algorithm to improve the result. The comparison between the conventional method and the same one with our algorithm show that our algorithm reduce 70% of the false detection.

Online elemental analysis of process gases with ICP-OES: A case study on waste wood combustion

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

Wellinger, Marco, E-mail: marco.wellinger@gmail.com; Ecole Polytechnique Federale de Lausanne; Wochele, Joerg

2012-10-15

Highlights: Black-Right-Pointing-Pointer Simultaneous measurements of 23 elements in process gases of a waste wood combustor. Black-Right-Pointing-Pointer Mobile ICP spectrometer allows measurements of high quality at industrial plants. Black-Right-Pointing-Pointer Continuous online measurements with high temporal resolution. Black-Right-Pointing-Pointer Linear correlations among element concentrations in the raw flue gas were detected. Black-Right-Pointing-Pointer Novel sampling and calibration methods for ICP-OES analysis of process gases. - Abstract: A mobile sampling and measurement system for the analysis of gaseous and liquid samples in the field was developed. An inductively coupled plasma optical emission spectrometer (ICP-OES), which is built into a van, was used as detector. Themore » analytical system was calibrated with liquid and/or gaseous standards. It was shown that identical mass flows of either gaseous or liquid standards resulted in identical ICP-OES signal intensities. In a field measurement campaign trace and minor elements in the raw flue gas of a waste wood combustor were monitored. Sampling was performed with a highly transport efficient liquid quench system, which allowed to observe temporal variations in the elemental process gas composition. After a change in feedstock an immediate change of the element concentrations in the flue gas was detected. A comparison of the average element concentrations during the combustion of the two feedstocks showed a high reproducibility for matrix elements that are expected to be present in similar concentrations. On the other hand elements that showed strong differences in their concentration in the feedstock were also represented by a higher concentration in the flue gas. Following the temporal variations of different elements revealed strong correlations between a number of elements, such as chlorine with sodium, potassium and zinc, as well as arsenic with lead, and calcium with strontium.« less

A Robust False Matching Points Detection Method for Remote Sensing Image Registration

NASA Astrophysics Data System (ADS)

Shan, X. J.; Tang, P.

2015-04-01

Given the influences of illumination, imaging angle, and geometric distortion, among others, false matching points still occur in all image registration algorithms. Therefore, false matching points detection is an important step in remote sensing image registration. Random Sample Consensus (RANSAC) is typically used to detect false matching points. However, RANSAC method cannot detect all false matching points in some remote sensing images. Therefore, a robust false matching points detection method based on Knearest- neighbour (K-NN) graph (KGD) is proposed in this method to obtain robust and high accuracy result. The KGD method starts with the construction of the K-NN graph in one image. K-NN graph can be first generated for each matching points and its K nearest matching points. Local transformation model for each matching point is then obtained by using its K nearest matching points. The error of each matching point is computed by using its transformation model. Last, L matching points with largest error are identified false matching points and removed. This process is iterative until all errors are smaller than the given threshold. In addition, KGD method can be used in combination with other methods, such as RANSAC. Several remote sensing images with different resolutions and terrains are used in the experiment. We evaluate the performance of KGD method, RANSAC + KGD method, RANSAC, and Graph Transformation Matching (GTM). The experimental results demonstrate the superior performance of the KGD and RANSAC + KGD methods.

Interpretability of Change Scores in Measures of Balance in People With COPD.

PubMed

Beauchamp, Marla K; Harrison, Samantha L; Goldstein, Roger S; Brooks, Dina

2016-03-01

Balance deficits and an increased fall risk are well documented in individuals with COPD. Despite evidence that balance training programs can improve performance on clinical balance tests, their minimal clinically important difference (MCID) is unknown. The aim of this study was to determine the MCID of the Berg Balance Scale (BBS), Balance Evaluation Systems Test (BESTest), and Activities-Specific Balance Confidence (ABC) scale in patients with COPD undergoing pulmonary rehabilitation. We performed a secondary analysis of data from two studies of balance training in COPD (n = 55). The MCID for each balance measure was estimated using the following anchor and distribution-based approaches: (1) mean change scores on a patient-reported global change in balance scale, (2) optimal cut-point from receiver operating characteristic curves (ROCs), and (3) the minimal detectable change with 95% confidence (MDC95). Data from 55 patients with COPD (mean age, 71.2 ± 7.1 y; mean FEV1, 39.2 ± 15.8% predicted) were used in the analysis. The smallest estimate of MCID was from the ROC method. Anchor-based estimates of the MCID ranged from 3.5 to 7.1 for the BBS, 10.2 to 17.4 for the BESTest, and 14.2 to 18.5 for the ABC scale; their MDC95 values were 5.0, 13.1, and 18.9, respectively. Among patients with COPD undergoing pulmonary rehabilitation, a change of 5 to 7 points for the BBS, 13 to 17 points for the BESTest, and 19 points for the ABC scale is required to be both perceptible to patients and beyond measurement error. Copyright © 2016 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.

Thermal Effects on the "Ice-Cube Puzzle"

ERIC Educational Resources Information Center

Lima, F. M. S.; Monteiro, F. F.

2012-01-01

When an ice cube floating on water in a container melts, it is said in some textbooks that the water level does not change. However, as pointed out by Lan in a recent work, when the buoyant force from a less dense fluid resting above the waterline is taken into account, one should expect a detectable "increase" in the volume of water. Here in this…

4D Near Real-Time Environmental Monitoring Using Highly Temporal LiDAR

NASA Astrophysics Data System (ADS)

Höfle, Bernhard; Canli, Ekrem; Schmitz, Evelyn; Crommelinck, Sophie; Hoffmeister, Dirk; Glade, Thomas

2016-04-01

The last decade has witnessed extensive applications of 3D environmental monitoring with the LiDAR technology, also referred to as laser scanning. Although several automatic methods were developed to extract environmental parameters from LiDAR point clouds, only little research has focused on highly multitemporal near real-time LiDAR (4D-LiDAR) for environmental monitoring. Large potential of applying 4D-LiDAR is given for landscape objects with high and varying rates of change (e.g. plant growth) and also for phenomena with sudden unpredictable changes (e.g. geomorphological processes). In this presentation we will report on the most recent findings of the research projects 4DEMON (http://uni-heidelberg.de/4demon) and NoeSLIDE (https://geomorph.univie.ac.at/forschung/projekte/aktuell/noeslide/). The method development in both projects is based on two real-world use cases: i) Surface parameter derivation of agricultural crops (e.g. crop height) and ii) change detection of landslides. Both projects exploit the "full history" contained in the LiDAR point cloud time series. One crucial initial step of 4D-LiDAR analysis is the co-registration over time, 3D-georeferencing and time-dependent quality assessment of the LiDAR point cloud time series. Due to the high amount of datasets (e.g. one full LiDAR scan per day), the procedure needs to be performed fully automatically. Furthermore, the online near real-time 4D monitoring system requires to set triggers that can detect removal or moving of tie reflectors (used for co-registration) or the scanner itself. This guarantees long-term data acquisition with high quality. We will present results from a georeferencing experiment for 4D-LiDAR monitoring, which performs benchmarking of co-registration, 3D-georeferencing and also fully automatic detection of events (e.g. removal/moving of reflectors or scanner). Secondly, we will show our empirical findings of an ongoing permanent LiDAR observation of a landslide (Gresten, Austria) and an agricultural maize crop stand (Heidelberg, Germany). This research demonstrates the potential and also limitations of fully automated, near real-time 4D LiDAR monitoring in geosciences.

Estimating indices of range shifts in birds using dynamic models when detection is imperfect

USGS Publications Warehouse

Clement, Matthew J.; Hines, James E.; Nichols, James D.; Pardieck, Keith L.; Ziolkowski, David J.

2016-01-01

There is intense interest in basic and applied ecology about the effect of global change on current and future species distributions. Projections based on widely used static modeling methods implicitly assume that species are in equilibrium with the environment and that detection during surveys is perfect. We used multiseason correlated detection occupancy models, which avoid these assumptions, to relate climate data to distributional shifts of Louisiana Waterthrush in the North American Breeding Bird Survey (BBS) data. We summarized these shifts with indices of range size and position and compared them to the same indices obtained using more basic modeling approaches. Detection rates during point counts in BBS surveys were low, and models that ignored imperfect detection severely underestimated the proportion of area occupied and slightly overestimated mean latitude. Static models indicated Louisiana Waterthrush distribution was most closely associated with moderate temperatures, while dynamic occupancy models indicated that initial occupancy was associated with diurnal temperature ranges and colonization of sites was associated with moderate precipitation. Overall, the proportion of area occupied and mean latitude changed little during the 1997–2013 study period. Near-term forecasts of species distribution generated by dynamic models were more similar to subsequently observed distributions than forecasts from static models. Occupancy models incorporating a finite mixture model on detection – a new extension to correlated detection occupancy models – were better supported and may reduce bias associated with detection heterogeneity. We argue that replacing phenomenological static models with more mechanistic dynamic models can improve projections of future species distributions. In turn, better projections can improve biodiversity forecasts, management decisions, and understanding of global change biology.

Comparison of Birds Detected from Roadside and Off-Road Point Counts in the Shenandoah National Park

Treesearch

Cherry M.E. Keller; Mark R. Fuller

1995-01-01

Roadside point counts are generally used for large surveys to increase the number of samples. We examined differences in species detected from roadside versus off-road (200-m and 400-m) point counts in the Shenandoah National Park. We also compared the list of species detected in the first 3 minutes to those detected in 10 minutes for potential species biases. Results...

Nanoswitch-linked immunosorbent assay (NLISA) for fast, sensitive, and specific protein detection.

PubMed

Hansen, Clinton H; Yang, Darren; Koussa, Mounir A; Wong, Wesley P

2017-09-26

Protein detection and quantification play critical roles in both basic research and clinical practice. Current detection platforms range from the widely used ELISA to more sophisticated, and more expensive, approaches such as digital ELISA. Despite advances, there remains a need for a method that combines the simplicity and cost-effectiveness of ELISA with the sensitivity and speed of modern approaches in a format suitable for both laboratory and rapid, point-of-care applications. Building on recent developments in DNA structural nanotechnology, we introduce the nanoswitch-linked immunosorbent assay (NLISA), a detection platform based on easily constructed DNA nanodevices that change conformation upon binding to a target protein with the results read out by gel electrophoresis. NLISA is surface-free and includes a kinetic-proofreading step for purification, enabling both enhanced sensitivity and reduced cross-reactivity. We demonstrate femtomolar-level detection of prostate-specific antigen in biological fluids, as well as reduced cross-reactivity between different serotypes of dengue and also between a single-mutation and wild-type protein. NLISA is less expensive, uses less sample volume, is more rapid, and, with no washes, includes fewer hands-on steps than ELISA, while also achieving superior sensitivity. Our approach also has the potential to enable rapid point-of-care assays, as we demonstrate by performing NLISA with an iPad/iPhone camera for imaging.

Continuous section extraction and over-underbreak detection of tunnel based on 3D laser technology and image analysis

NASA Astrophysics Data System (ADS)

Wang, Weixing; Wang, Zhiwei; Han, Ya; Li, Shuang; Zhang, Xin

2015-03-01

In order to ensure safety, long term stability and quality control in modern tunneling operations, the acquisition of geotechnical information about encountered rock conditions and detailed installed support information is required. The limited space and time in an operational tunnel environment make the acquiring data challenging. The laser scanning in a tunneling environment, however, shows a great potential. The surveying and mapping of tunnels are crucial for the optimal use after construction and in routine inspections. Most of these applications focus on the geometric information of the tunnels extracted from the laser scanning data. There are two kinds of applications widely discussed: deformation measurement and feature extraction. The traditional deformation measurement in an underground environment is performed with a series of permanent control points installed around the profile of an excavation, which is unsuitable for a global consideration of the investigated area. Using laser scanning for deformation analysis provides many benefits as compared to traditional monitoring techniques. The change in profile is able to be fully characterized and the areas of the anomalous movement can easily be separated from overall trends due to the high density of the point cloud data. Furthermore, monitoring with a laser scanner does not require the permanent installation of control points, therefore the monitoring can be completed more quickly after excavation, and the scanning is non-contact, hence, no damage is done during the installation of temporary control points. The main drawback of using the laser scanning for deformation monitoring is that the point accuracy of the original data is generally the same magnitude as the smallest level of deformations that are to be measured. To overcome this, statistical techniques and three dimensional image processing techniques for the point clouds must be developed. For safely, effectively and easily control the problem of Over Underbreak detection of road and solve the problemof the roadway data collection difficulties, this paper presents a new method of continuous section extraction and Over Underbreak detection of road based on 3D laser scanning technology and image processing, the method is divided into the following three steps: based on Canny edge detection, local axis fitting, continuous extraction section and Over Underbreak detection of section. First, after Canny edge detection, take the least-squares curve fitting method to achieve partial fitting in axis. Then adjust the attitude of local roadway that makes the axis of the roadway be consistent with the direction of the extraction reference, and extract section along the reference direction. Finally, we compare the actual cross-sectional view and the cross-sectional design to complete Overbreak detected. Experimental results show that the proposed method have a great advantage in computing costs and ensure cross-section orthogonal intercept terms compared with traditional detection methods.

Efficient quantitative assessment of facial paralysis using iris segmentation and active contour-based key points detection with hybrid classifier.

PubMed

Barbosa, Jocelyn; Lee, Kyubum; Lee, Sunwon; Lodhi, Bilal; Cho, Jae-Gu; Seo, Woo-Keun; Kang, Jaewoo

2016-03-12

Facial palsy or paralysis (FP) is a symptom that loses voluntary muscles movement in one side of the human face, which could be very devastating in the part of the patients. Traditional methods are solely dependent to clinician's judgment and therefore time consuming and subjective in nature. Hence, a quantitative assessment system becomes apparently invaluable for physicians to begin the rehabilitation process; and to produce a reliable and robust method is challenging and still underway. We introduce a novel approach for a quantitative assessment of facial paralysis that tackles classification problem for FP type and degree of severity. Specifically, a novel method of quantitative assessment is presented: an algorithm that extracts the human iris and detects facial landmarks; and a hybrid approach combining the rule-based and machine learning algorithm to analyze and prognosticate facial paralysis using the captured images. A method combining the optimized Daugman's algorithm and Localized Active Contour (LAC) model is proposed to efficiently extract the iris and facial landmark or key points. To improve the performance of LAC, appropriate parameters of initial evolving curve for facial features' segmentation are automatically selected. The symmetry score is measured by the ratio between features extracted from the two sides of the face. Hybrid classifiers (i.e. rule-based with regularized logistic regression) were employed for discriminating healthy and unhealthy subjects, FP type classification, and for facial paralysis grading based on House-Brackmann (H-B) scale. Quantitative analysis was performed to evaluate the performance of the proposed approach. Experiments show that the proposed method demonstrates its efficiency. Facial movement feature extraction on facial images based on iris segmentation and LAC-based key point detection along with a hybrid classifier provides a more efficient way of addressing classification problem on facial palsy type and degree of severity. Combining iris segmentation and key point-based method has several merits that are essential for our real application. Aside from the facial key points, iris segmentation provides significant contribution as it describes the changes of the iris exposure while performing some facial expressions. It reveals the significant difference between the healthy side and the severe palsy side when raising eyebrows with both eyes directed upward, and can model the typical changes in the iris region.

CNV-TV: a robust method to discover copy number variation from short sequencing reads.

PubMed

Duan, Junbo; Zhang, Ji-Gang; Deng, Hong-Wen; Wang, Yu-Ping

2013-05-02

Copy number variation (CNV) is an important structural variation (SV) in human genome. Various studies have shown that CNVs are associated with complex diseases. Traditional CNV detection methods such as fluorescence in situ hybridization (FISH) and array comparative genomic hybridization (aCGH) suffer from low resolution. The next generation sequencing (NGS) technique promises a higher resolution detection of CNVs and several methods were recently proposed for realizing such a promise. However, the performances of these methods are not robust under some conditions, e.g., some of them may fail to detect CNVs of short sizes. There has been a strong demand for reliable detection of CNVs from high resolution NGS data. A novel and robust method to detect CNV from short sequencing reads is proposed in this study. The detection of CNV is modeled as a change-point detection from the read depth (RD) signal derived from the NGS, which is fitted with a total variation (TV) penalized least squares model. The performance (e.g., sensitivity and specificity) of the proposed approach are evaluated by comparison with several recently published methods on both simulated and real data from the 1000 Genomes Project. The experimental results showed that both the true positive rate and false positive rate of the proposed detection method do not change significantly for CNVs with different copy numbers and lengthes, when compared with several existing methods. Therefore, our proposed approach results in a more reliable detection of CNVs than the existing methods.

Removal of oxides from alkali metal melts by reductive titration to electrical resistance-change end points

DOEpatents

Tsang, Floris Y.

1980-01-01

Alkali metal oxides dissolved in alkali metal melts are reduced with soluble metals which are converted to insoluble oxides. The end points of the reduction is detected as an increase in electrical resistance across an alkali metal ion-conductive membrane interposed between the oxide-containing melt and a material capable of accepting the alkali metal ions from the membrane when a difference in electrical potential, of the appropriate polarity, is established across it. The resistance increase results from blocking of the membrane face by ions of the excess reductant metal, to which the membrane is essentially non-conductive.

Integration of multitemporal and multisource data using point cloud based methods to quantify landscape change at the Mill Gulch earthflow, California

NASA Astrophysics Data System (ADS)

DeLong, S. B.; Avdievitch, N. N.

2014-12-01

As high-resolution topographic data become increasingly available, comparison of multitemporal and disparate datasets (e.g. airborne and terrestrial lidar) enable high-accuracy quantification of landscape change and detailed mapping of surface processes. However, if these data are not properly managed and aligned with maximum precision, results may be spurious. Often this is due to slight differences in coordinate systems that require complex geographic transformations and systematic error that is difficult to diagnose and correct. Here we present an analysis of four airborne and three terrestrial lidar datasets collected between 2003 and 2014 that we use to quantify change at an active earthflow in Mill Gulch, Sonoma County, California. We first identify and address systematic error internal to each dataset, such as registration offset between flight lines or scan positions. We then use a variant of an iterative closest point (ICP) algorithm to align point cloud data by maximizing use of stable portions of the landscape with minimal internal error. Using products derived from the aligned point clouds, we make our geomorphic analyses. These methods may be especially useful for change detection analyses in which accurate georeferencing is unavailable, as is often the case with some terrestrial lidar or "structure from motion" data. Our results show that the Mill Gulch earthflow has been active throughout the study period. We see continuous downslope flow, ongoing incorporation of new hillslope material into the flow, sediment loss from hillslopes, episodic fluvial erosion of the earthflow toe, and an indication of increased activity during periods of high precipitation.

Detecting insider activity using enhanced directory virtualization.

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

Shin, Dongwan; Claycomb, William R.

2010-07-01

Insider threats often target authentication and access control systems, which are frequently based on directory services. Detecting these threats is challenging, because malicious users with the technical ability to modify these structures often have sufficient knowledge and expertise to conceal unauthorized activity. The use of directory virtualization to monitor various systems across an enterprise can be a valuable tool for detecting insider activity. The addition of a policy engine to directory virtualization services enhances monitoring capabilities by allowing greater flexibility in analyzing changes for malicious intent. The resulting architecture is a system-based approach, where the relationships and dependencies between datamore » sources and directory services are used to detect an insider threat, rather than simply relying on point solutions. This paper presents such an architecture in detail, including a description of implementation results.« less

Effects of sampling strategy, detection probability, and independence of counts on the use of point counts

USGS Publications Warehouse

Pendleton, G.W.; Ralph, C. John; Sauer, John R.; Droege, Sam

1995-01-01

Many factors affect the use of point counts for monitoring bird populations, including sampling strategies, variation in detection rates, and independence of sample points. The most commonly used sampling plans are stratified sampling, cluster sampling, and systematic sampling. Each of these might be most useful for different objectives or field situations. Variation in detection probabilities and lack of independence among sample points can bias estimates and measures of precision. All of these factors should be con-sidered when using point count methods.

Generating Impact Maps from Automatically Detected Bomb Craters in Aerial Wartime Images Using Marked Point Processes

NASA Astrophysics Data System (ADS)

Kruse, Christian; Rottensteiner, Franz; Hoberg, Thorsten; Ziems, Marcel; Rebke, Julia; Heipke, Christian

2018-04-01

The aftermath of wartime attacks is often felt long after the war ended, as numerous unexploded bombs may still exist in the ground. Typically, such areas are documented in so-called impact maps which are based on the detection of bomb craters. This paper proposes a method for the automatic detection of bomb craters in aerial wartime images that were taken during the Second World War. The object model for the bomb craters is represented by ellipses. A probabilistic approach based on marked point processes determines the most likely configuration of objects within the scene. Adding and removing new objects to and from the current configuration, respectively, changing their positions and modifying the ellipse parameters randomly creates new object configurations. Each configuration is evaluated using an energy function. High gradient magnitudes along the border of the ellipse are favored and overlapping ellipses are penalized. Reversible Jump Markov Chain Monte Carlo sampling in combination with simulated annealing provides the global energy optimum, which describes the conformance with a predefined model. For generating the impact map a probability map is defined which is created from the automatic detections via kernel density estimation. By setting a threshold, areas around the detections are classified as contaminated or uncontaminated sites, respectively. Our results show the general potential of the method for the automatic detection of bomb craters and its automated generation of an impact map in a heterogeneous image stock.

Prototype Global Burnt Area Algorithm Using a Multi-sensor Approach

NASA Astrophysics Data System (ADS)

López Saldaña, G.; Pereira, J.; Aires, F.

2013-05-01

One of the main limitations of products derived from remotely-sensed data is the length of the data records available for climate studies. The Advanced Very High Resolution Radiometer (AVHRR) long-term data record (LTDR) comprises a daily global atmospherically-corrected surface reflectance dataset at 0.05Deg spatial resolution and is available for the 1981-1999 time period. The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument has been on orbit in the Terra platform since late 1999 and in Aqua since mid 2002; surface reflectance products, MYD09CMG and MOD09CMG, are available at 0.05Deg spatial resolution. Fire is strong cause of land surface change and emissions of greenhouse gases around the globe. A global long-term identification of areas affected by fire is needed to analyze trends and fire-clime relationships. A burnt area algorithm can be seen as a change point detection problem where there is an abrupt change in the surface reflectance due to the biomass burning. Using the AVHRR-LTDR and the aforementioned MODIS products, a time series of bidirectional reflectance distribution function (BRDF) corrected surface reflectance was generated using the daily observations and constraining the BRDF model inversion using a climatology of BRDF parameters derived from 12 years of MODIS data. The identification of the burnt area was performed using a t-test in the pre- and post-fire reflectance values and a change point detection algorithm, then spectral constraints were applied to flag changes caused by natural land processes like vegetation seasonality or flooding. Additional temporal constraints are applied focusing in the persistence of the affected areas. Initial results for years 1998 to 2002, show spatio-temporal coherence but further analysis is required and a formal rigorous validation will be applied using burn scars identified from high-resolution datasets.

A double-observer approach for estimating detection probability and abundance from point counts

USGS Publications Warehouse

Nichols, J.D.; Hines, J.E.; Sauer, J.R.; Fallon, F.W.; Fallon, J.E.; Heglund, P.J.

2000-01-01

Although point counts are frequently used in ornithological studies, basic assumptions about detection probabilities often are untested. We apply a double-observer approach developed to estimate detection probabilities for aerial surveys (Cook and Jacobson 1979) to avian point counts. At each point count, a designated 'primary' observer indicates to another ('secondary') observer all birds detected. The secondary observer records all detections of the primary observer as well as any birds not detected by the primary observer. Observers alternate primary and secondary roles during the course of the survey. The approach permits estimation of observer-specific detection probabilities and bird abundance. We developed a set of models that incorporate different assumptions about sources of variation (e.g. observer, bird species) in detection probability. Seventeen field trials were conducted, and models were fit to the resulting data using program SURVIV. Single-observer point counts generally miss varying proportions of the birds actually present, and observer and bird species were found to be relevant sources of variation in detection probabilities. Overall detection probabilities (probability of being detected by at least one of the two observers) estimated using the double-observer approach were very high (>0.95), yielding precise estimates of avian abundance. We consider problems with the approach and recommend possible solutions, including restriction of the approach to fixed-radius counts to reduce the effect of variation in the effective radius of detection among various observers and to provide a basis for using spatial sampling to estimate bird abundance on large areas of interest. We believe that most questions meriting the effort required to carry out point counts also merit serious attempts to estimate detection probabilities associated with the counts. The double-observer approach is a method that can be used for this purpose.

Comparison of birds detected from roadside and off-road point counts in the Shenandoah National Park

USGS Publications Warehouse

Keller, C.M.E.; Fuller, M.R.; Ralph, C. John; Sauer, John R.; Droege, Sam

1995-01-01

Roadside point counts are generally used for large surveys to increase the number of samples. We examined differences in species detected from roadside versus off-road (200-m and 400-ha) point counts in the Shenandoah National Park. We also compared the list of species detected in the first 3 minutes to those detected in 10 minutes for potential species biases. Results from 81 paired roadside and off-road counts indicated that roadside counts had higher numbers of several edge species but did not have lower numbers of nonedge forest species. More individuals and species were detected from roadside points because of this increase in edge species. Sixty-five percent of the species detected in 10 minutes were recorded in the first 3 minutes.

Terrestrial laser scanning for geometry extraction and change monitoring of rubble mound breakwaters

NASA Astrophysics Data System (ADS)

Puente, I.; Lindenbergh, R.; González-Jorge, H.; Arias, P.

2014-05-01

Rubble mound breakwaters are coastal defense structures that protect harbors and beaches from the impacts of both littoral drift and storm waves. They occasionally break, leading to catastrophic damage to surrounding human populations and resulting in huge economic and environmental losses. Ensuring their stability is considered to be of vital importance and the major reason for setting up breakwater monitoring systems. Terrestrial laser scanning has been recognized as a monitoring technique of existing infrastructures. Its capability for measuring large amounts of accurate points in a short period of time is also well proven. In this paper we first introduce a method for the automatic extraction of face geometry of concrete cubic blocks, as typically used in breakwaters. Point clouds are segmented based on their orientation and location. Then we compare corresponding cuboids of three co-registered point clouds to estimate their transformation parameters over time. The first method is demonstrated on scan data from the Baiona breakwater (Spain) while the change detection is demonstrated on repeated scan data of concrete bricks, where the changing scenario was simulated. The application of the presented methodology has verified its effectiveness for outlining the 3D breakwater units and analyzing their changes at the millimeter level. Breakwater management activities could benefit from this initial version of the method in order to improve their productivity.

Cone-beam CT of traumatic brain injury using statistical reconstruction with a post-artifact-correction noise model

NASA Astrophysics Data System (ADS)

Dang, H.; Stayman, J. W.; Sisniega, A.; Xu, J.; Zbijewski, W.; Yorkston, J.; Aygun, N.; Koliatsos, V.; Siewerdsen, J. H.

2015-03-01

Traumatic brain injury (TBI) is a major cause of death and disability. The current front-line imaging modality for TBI detection is CT, which reliably detects intracranial hemorrhage (fresh blood contrast 30-50 HU, size down to 1 mm) in non-contrast-enhanced exams. Compared to CT, flat-panel detector (FPD) cone-beam CT (CBCT) systems offer lower cost, greater portability, and smaller footprint suitable for point-of-care deployment. We are developing FPD-CBCT to facilitate TBI detection at the point-of-care such as in emergent, ambulance, sports, and military applications. However, current FPD-CBCT systems generally face challenges in low-contrast, soft-tissue imaging. Model-based reconstruction can improve image quality in soft-tissue imaging compared to conventional filtered back-projection (FBP) by leveraging high-fidelity forward model and sophisticated regularization. In FPD-CBCT TBI imaging, measurement noise characteristics undergo substantial change following artifact correction, resulting in non-negligible noise amplification. In this work, we extend the penalized weighted least-squares (PWLS) image reconstruction to include the two dominant artifact corrections (scatter and beam hardening) in FPD-CBCT TBI imaging by correctly modeling the variance change following each correction. Experiments were performed on a CBCT test-bench using an anthropomorphic phantom emulating intra-parenchymal hemorrhage in acute TBI, and the proposed method demonstrated an improvement in blood-brain contrast-to-noise ratio (CNR = 14.2) compared to FBP (CNR = 9.6) and PWLS using conventional weights (CNR = 11.6) at fixed spatial resolution (1 mm edge-spread width at the target contrast). The results support the hypothesis that FPD-CBCT can fulfill the image quality requirements for reliable TBI detection, using high-fidelity artifact correction and statistical reconstruction with accurate post-artifact-correction noise models.

[MPLW515L point mutation in patients with myeloproliferative disease].

PubMed

Xia, Jun; Xu, Wei; Zhang, Su-Jiang; Fan, Lei; Qiao, Chun; Li, Jian-Yong

2008-12-01

In order to investigate the frequency of MPLW515L and JAK2V617F point mutations of the patients with myeloproliferative disease (MPD) in Nanjing area, MPLW515L and JAK2V617F point mutations were simultaneously detected by alleles specific polymerase chain reaction (AS-PCR) and sequencing in 190 MPD patients. The results showed that MPLW515L point mutation was detected in 1 out of 102 essential thrombocythemia (ET) patients (1.0%) and was not detected in 32 polycythemia vera (PV) patients, 13 idiopathic myelofibrosis (IMF) patients, 43 chronic myelogenous leukemia (CML) patients. JAK2V617F point mutation was detected in 20 out of 32 PV patients (62.5%), 43 out of 102 ET patients (42.2%), 5 out of 13 IMF patients (38.5%), and was not detected in 43 CML patients. It is concluded that MPLW515L point mutation exists in ET patient, but is not found in PV, IMF and CML. JAK2V617F point mutation exists in PV, ET and IMF, but not in CML.

Detection of changes in bone quality of osteoporotic model induced by sciatic nerve resection by using Raman spectroscopy

NASA Astrophysics Data System (ADS)

Ishimaru, Yasumitsu; Oshima, Yusuke; Imai, Yuuki; Iimura, Tadahiro; Takanezawa, Sota; Hino, Kazunori; Miura, Hiromasa

2018-02-01

To detect the bone quality loss in osteoporosis, we performed Raman spectroscopic analysis of sciatic nerve resection (NX) mice. Eight months after surgery, lower limbs were collected from the mice and fixed with 70% ethanol. Raman spectra of anterior cortical surface of the proximal tibia at 5 points in each bone were measured by RENISHAW inVia Raman Microscope. Excitation wave length was 785 nm. We also performed DXA and micro CT measurement to confirm the bone mineral density and bone microstructure in the osteoporotic model induced by sciatic nerve resection. In the result of Raman spectroscopy, we detected changes of Raman peak intensity ratio in carbonate/phosphate, mineral/combined proline and hydroxyproline and mineral/phenylalanine. In addition, in the result of micro CT, we found significant changes in VOX BV/TV, Trabecular number, thickness, cancellous bone mineral density, cortical thickness and cortical bone mineral density. The results suggest that not only the bone mineral density but also bone quality reduced in the NX mice. We conclude that Raman spectroscopy is a useful for bone quality assessment as a complementary technique for conventional diagnostics.

Detection of morphological changes in cliff face surrounding a waterfall using terrestrial laser scanning and unmanned aerial system

NASA Astrophysics Data System (ADS)

Hayakawa, Yuichi S.; Obanawa, Hiroyuki

2015-04-01

Waterfall or bedrock knickpoint appears as an erosional front in bedrock rivers forming deep v-shaped valley downstream. Following the rapid fluvial erosion of waterfall, rockfalls and gravita-tional collapses often occur in surrounding steep cliffs. Although morphological changes of such steep cliffs are sometimes visually observed, quantitative and precise measurements of their spatio-temporal distribution have been limited due to the difficulties in direct access to such cliffs if with classical measurement methods. However, for the clarification of geomorphological processes oc-curring in the cliffs, multi-temporal mapping of the cliff face at a high resolution is necessary. Re-mote sensing approaches are therefore suitable for the topographic measurements and detection of changes in such inaccessible cliffs. To achieve accurate topographic mapping of cliffs around a wa-terfall, here we perform multi-temporal terrestrial laser scanning (TLS), as well as structure-from-motion multi-view stereo (SfM-MVS) photogrammetry based on unmanned aerial system (UAS). The study site is Kegon Falls in central Japan, having a vertical drop of surface water from top of its overhanging cliff, as well as groundwater outflows from its lower portions. The bedrock is composed of alternate layers of andesite lava and conglomerates. Minor rockfalls in the cliffs are often ob-served by local people. The latest major rockfall occurred in 1986, causing ca. 8-m upstream propa-gation of the waterfall lip. This provides a good opportunity to examine the changes in the surround-ing cliffs following the waterfall recession. Multi-time point clouds were obtained by TLS measure-ment over years, and the three-dimensional changes of the rock surface were detected, uncovering the locus of small rockfalls and gully developments. Erosion seems particularly frequent in relatively weak the conglomerates layer, whereas small rockfalls seems to have occurred in the andesite layers. Also, shadows in the TLS point clouds are effectively filled by complementary data of UAS-based SfM-MVS photogrammetry, which can improve the mapping quality of the cliff morphology. The point clouds are also projected on a vertical plane to generate a digital elevation model (DEM). Cross-sectional profiles extracted from the DEM show the presence of a distinct, 5-10-m depression at the mid of the cliff (bottom of the upper andesite layer), which appears to have been formed by freeze-thaw and/or wet-dry weathering following the waterfall recession in 1986.

Brain changes detected by functional magnetic resonance imaging and spectroscopy in patients with Crohn's disease.

PubMed

Lv, Kun; Fan, Yi-Hong; Xu, Li; Xu, Mao-Sheng

2017-05-28

Crohn's disease (CD) is a chronic, non-specific granulomatous inflammatory disorder that commonly affects the small intestine and is a phenotype of inflammatory bowel disease (IBD). CD is prone to relapse, and its incidence displays a persistent increase in developing countries. However, the pathogenesis of CD is poorly understood, with some studies emphasizing the link between CD and the intestinal microbiota. Specifically, studies point to the brain-gut-enteric microbiota axis as a key player in the occurrence and development of CD. Furthermore, investigations have shown white-matter lesions and neurologic deficits in patients with IBD. Based on these findings, brain activity changes in CD patients have been detected by blood oxygenation level dependent functional magnetic resonance imaging (BOLD-fMRI). BOLD-fMRI functions by detecting a local increase in relative blood oxygenation that results from neurotransmitter activity and thus reflects local neuronal firing rates. Therefore, biochemical concentrations of neurotransmitters or metabolites may change in corresponding brain regions of CD patients. To further study this phenomenon, brain changes of CD patients can be detected non-invasively, effectively and accurately by BOLD-fMRI combined with magnetic resonance spectroscopy (MRS). This approach can further shed light on the mechanisms of the occurrence and development of neurological CD. Overall, this paper reviews the current status and prospects on fMRI and MRS for evaluation of patients with CD based on the brain-gut-enteric microbiota axis.

CMOS image sensor-based immunodetection by refractive-index change.

PubMed

Devadhasan, Jasmine P; Kim, Sanghyo

2012-01-01

A complementary metal oxide semiconductor (CMOS) image sensor is an intriguing technology for the development of a novel biosensor. Indeed, the CMOS image sensor mechanism concerning the detection of the antigen-antibody (Ag-Ab) interaction at the nanoscale has been ambiguous so far. To understand the mechanism, more extensive research has been necessary to achieve point-of-care diagnostic devices. This research has demonstrated a CMOS image sensor-based analysis of cardiovascular disease markers, such as C-reactive protein (CRP) and troponin I, Ag-Ab interactions on indium nanoparticle (InNP) substrates by simple photon count variation. The developed sensor is feasible to detect proteins even at a fg/mL concentration under ordinary room light. Possible mechanisms, such as dielectric constant and refractive-index changes, have been studied and proposed. A dramatic change in the refractive index after protein adsorption on an InNP substrate was observed to be a predominant factor involved in CMOS image sensor-based immunoassay.

Robust Observation Detection for Single Object Tracking: Deterministic and Probabilistic Patch-Based Approaches

PubMed Central

Zulkifley, Mohd Asyraf; Rawlinson, David; Moran, Bill

2012-01-01

In video analytics, robust observation detection is very important as the content of the videos varies a lot, especially for tracking implementation. Contrary to the image processing field, the problems of blurring, moderate deformation, low illumination surroundings, illumination change and homogenous texture are normally encountered in video analytics. Patch-Based Observation Detection (PBOD) is developed to improve detection robustness to complex scenes by fusing both feature- and template-based recognition methods. While we believe that feature-based detectors are more distinctive, however, for finding the matching between the frames are best achieved by a collection of points as in template-based detectors. Two methods of PBOD—the deterministic and probabilistic approaches—have been tested to find the best mode of detection. Both algorithms start by building comparison vectors at each detected points of interest. The vectors are matched to build candidate patches based on their respective coordination. For the deterministic method, patch matching is done in 2-level test where threshold-based position and size smoothing are applied to the patch with the highest correlation value. For the second approach, patch matching is done probabilistically by modelling the histograms of the patches by Poisson distributions for both RGB and HSV colour models. Then, maximum likelihood is applied for position smoothing while a Bayesian approach is applied for size smoothing. The result showed that probabilistic PBOD outperforms the deterministic approach with average distance error of 10.03% compared with 21.03%. This algorithm is best implemented as a complement to other simpler detection methods due to heavy processing requirement. PMID:23202226

Improving power to detect changes in blood miRNA expression by accounting for sources of variability in experimental designs.

PubMed

Daniels, Sarah I; Sillé, Fenna C M; Goldbaum, Audrey; Yee, Brenda; Key, Ellen F; Zhang, Luoping; Smith, Martyn T; Thomas, Reuben

2014-12-01

Blood miRNAs are a new promising area of disease research, but variability in miRNA measurements may limit detection of true-positive findings. Here, we measured sources of miRNA variability and determine whether repeated measures can improve power to detect fold-change differences between comparison groups. Blood from healthy volunteers (N = 12) was collected at three time points. The miRNAs were extracted by a method predetermined to give the highest miRNA yield. Nine different miRNAs were quantified using different qPCR assays and analyzed using mixed models to identify sources of variability. A larger number of miRNAs from a publicly available blood miRNA microarray dataset with repeated measures were used for a bootstrapping procedure to investigate effects of repeated measures on power to detect fold changes in miRNA expression for a theoretical case-control study. Technical variability in qPCR replicates was identified as a significant source of variability (P < 0.05) for all nine miRNAs tested. Variability was larger in the TaqMan qPCR assays (SD = 0.15-0.61) versus the qScript qPCR assays (SD = 0.08-0.14). Inter- and intraindividual and extraction variability also contributed significantly for two miRNAs. The bootstrapping procedure demonstrated that repeated measures (20%-50% of N) increased detection of a 2-fold change for approximately 10% to 45% more miRNAs. Statistical power to detect small fold changes in blood miRNAs can be improved by accounting for sources of variability using repeated measures and choosing appropriate methods to minimize variability in miRNA quantification. This study demonstrates the importance of including repeated measures in experimental designs for blood miRNA research. See all the articles in this CEBP Focus section, "Biomarkers, Biospecimens, and New Technologies in Molecular Epidemiology." ©2014 American Association for Cancer Research.

Monotonic trends in spatio-temporal distribution and concentration of monsoon precipitation (1901-2002), West Bengal, India

NASA Astrophysics Data System (ADS)

Chatterjee, Soumendu; Khan, Ansar; Akbari, Hashem; Wang, Yupeng

2016-12-01

This paper intended to investigate spatio-temporal monotonic trend and shift in concentration of monsoon precipitation across West Bengal, India, by analysing the time series of monthly precipitation from 18 weather stations during the period from 1901 to 2002. In dealing with, the inhomogeneity in the precipitation series, RHtestsV4 software package is used to detect, and adjust for, multiple change points (shifts) that could exist in data series. Finally, the cumulative deviation test was applied at 5% significant level to check the homogeneity (presence of historic changes by cumulative deviations test). Afterward, non-parametric Mann-Kendall (MK) test and Theil-Sen estimator (TSE) was applied to detect of nature and slope of trends; and, Sequential Mann Kendall (SQMK) test was applied for detection of turning point and magnitude of change in trends. Prior to the application of statistical tests, the pre-whitening technique was used to eliminate the effect of autocorrelation in precipitation data series. Four indices- precipitation concentration index (PCI), precipitation concentration degree (PCD), precipitation concentration period (PCP) and fulcrum (centre of gravity) were used to detect precipitation concentration and the spatial pattern in it. The application of the above-mentioned procedures has shown very notable statewide monotonic trend for monsoon precipitation time series. Regional cluster analysis by SQMK found increasing precipitation in mountain and coastal regions in general, except during the non- monsoon seasons. The results show that higher PCI values were mainly observed in South Bengal, whereas lower PCI values were mostly detected in North Bengal. The PCI values are noticeably larger in places where both monsoon total precipitation and span of rainy season are lower. The results of PCP reveal that precipitation in Gangetic Bengal mostly occurs in summer (monsoon season), and the rainy season arrives earlier in North Bengal than South Bengal, whereas the results of PCD also indicate that the precipitation in North Bengal was more dispersed within a year than that in South Bengal. The concentration characteristic of precipitation could be detected by fulcrum analysis, and significant concentration over most of West Bengal was obvious within July month band. Precipitation trend observed in West Bengal is compared with that in Central India (CI) region and comparison of precipitation departure with Indian monsoon and Gangetic Bengal can be explained by forecasting ensemble.

Thermocouple design for measuring temperatures of small insects.

PubMed

Hanson, A A; Venette, R C

2013-01-01

Contact thermocouples often are used to measure surface body temperature changes of insects during cold exposure. However, small temperature changes of minute insects can be difficult to detect, particularly during the measurement of supercooling points. We developed two thermocouple designs, which use 0.51 mm diameter or 0.127 mm diameter copper-constantan wires, to improve our ability to resolve insect exotherms. We tested the designs with adults from three parasitoid species: Tetrastichus planipennisi, Spathius agrili, and S. floridanus. These species are <3 mm long and <0.1 mg. Mean exotherms were greater for fine-gauge thermocouples than thick-gauge thermocouples for the smallest species tested, T. planipennisi. This difference was not apparent for larger species S. agrili and S. floridanus. Thermocouple design did not affect the mean supercooling point for any of the species. The cradle thermocouple design developed with the fine gauge wire was reusable and allowed for easy insect recovery after cold exposure.

Altered expression of talin 1 in peripheral immune cells points to a significant role of the innate immune system in spontaneous autoimmune uveitis.

PubMed

Degroote, Roxane L; Hauck, Stefanie M; Kremmer, Elisabeth; Amann, Barbara; Ueffing, Marius; Deeg, Cornelia A

2012-07-19

The molecular mechanism which enables activated immune cells to cross the blood-retinal barrier in spontaneous autoimmune uveitis is yet to be unraveled. Equine recurrent uveitis is the only spontaneous animal model allowing us to investigate the autoimmune mediated transformation of leukocytes in the course of this sight threatening disease. Hypothesizing that peripheral blood immune cells change their protein expression pattern in spontaneous autoimmune uveitis, we used DIGE to detect proteins with altered abundance comparing peripheral immune cells of healthy and ERU diseased horses. Among others, we found a significant downregulation of talin 1 in peripheral blood granulocytes of ERU specimen, pointing to changes in β integrin activation and indicating a significant role of the innate immune system in spontaneous autoimmune diseases. Copyright © 2012. Published by Elsevier B.V.

The organisation of spatial and temporal relations in memory.

PubMed

Rondina, Renante; Curtiss, Kaitlin; Meltzer, Jed A; Barense, Morgan D; Ryan, Jennifer D

2017-04-01

Episodic memories are comprised of details of "where" and "when"; spatial and temporal relations, respectively. However, evidence from behavioural, neuropsychological, and neuroimaging studies has provided mixed interpretations about how memories for spatial and temporal relations are organised-they may be hierarchical, fully interactive, or independent. In the current study, we examined the interaction of memory for spatial and temporal relations. Using explicit reports and eye-tracking, we assessed younger and older adults' memory for spatial and temporal relations of objects that were presented singly across time in unique spatial locations. Explicit change detection of spatial relations was affected by a change in temporal relations, but explicit change detection of temporal relations was not affected by a change in spatial relations. Younger and older adults showed eye movement evidence of incidental memory for temporal relations, but only younger adults showed eye movement evidence of incidental memory for spatial relations. Together, these findings point towards a hierarchical organisation of relational memory. The implications of these findings are discussed in the context of the neural mechanisms that may support such a hierarchical organisation of memory.

Analytical Incorporation of Velocity Parameters into Ice Sheet Elevation Change Rate Computations

NASA Astrophysics Data System (ADS)

Nagarajan, S.; Ahn, Y.; Teegavarapu, R. S. V.

2014-12-01

NASA, ESA and various other agencies have been collecting laser, optical and RADAR altimetry data through various missions to study the elevation changes of the Cryosphere. The laser altimetry collected by various airborne and spaceborne missions provides multi-temporal coverage of Greenland and Antarctica since 1993 to now. Though these missions have increased the data coverage, considering the dynamic nature of the ice surface, it is still sparse both spatially and temporally for accurate elevation change detection studies. The temporal and spatial gaps are usually filled by interpolation techniques. This presentation will demonstrate a method to improve the temporal interpolation. Considering the accuracy, repeat coverage and spatial distribution, the laser scanning data has been widely used to compute elevation change rate of Greenland and Antarctica ice sheets. A major problem with these approaches is non-consideration of ice sheet velocity dynamics into change rate computations. Though the correlation between velocity and elevation change rate have been noticed by Hurkmans et al., 2012, the corrections for velocity changes were applied after computing elevation change rates by assuming linear or higher polynomial relationship. This research will discuss the possibilities of parameterizing ice sheet dynamics as unknowns (dX and dY) in the adjustment mathematical model that computes elevation change (dZ) rates. It is a simultaneous computation of changes in all three directions of the ice surface. Also, the laser points between two time epochs in a crossover area have different distribution and count. Therefore, a registration method that does not require point-to-point correspondence is required to recover the unknown elevation and velocity parameters. This research will experiment the possibilities of registering multi-temporal datasets using volume minimization algorithm, which determines the unknown dX, dY and dZ that minimizes the volume between two or more time-epoch point clouds. In order to make use of other existing data as well as to constrain the adjustment, InSAR velocity will be used as initial values for the parameters dX and dY. The presentation will discuss the results of analytical incorporation of parameters and the volume based registration method for a test site in Greenland.

Microscopic heat pulses induce contraction of cardiomyocytes without calcium transients

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

Oyama, Kotaro; Mizuno, Akari; Shintani, Seine A.

Highlights: Black-Right-Pointing-Pointer Infra-red laser beam generates microscopic heat pulses. Black-Right-Pointing-Pointer Heat pulses induce contraction of cardiomyocytes. Black-Right-Pointing-Pointer Ca{sup 2+} transients during the contraction were not detected. Black-Right-Pointing-Pointer Skinned cardiomyocytes in free Ca{sup 2+} solution also contracted. Black-Right-Pointing-Pointer Heat pulses regulated the contractions without Ca{sup 2+} dynamics. -- Abstract: It was recently demonstrated that laser irradiation can control the beating of cardiomyocytes and hearts, however, the precise mechanism remains to be clarified. Among the effects induced by laser irradiation on biological tissues, temperature change is one possible effect which can alter physiological functions. Therefore, we investigated the mechanism by which heatmore » pulses, produced by infra-red laser light under an optical microscope, induce contractions of cardiomyocytes. Here we show that microscopic heat pulses induce contraction of rat adult cardiomyocytes. The temperature increase, {Delta}T, required for inducing contraction of cardiomyocytes was dependent upon the ambient temperature; that is, {Delta}T at physiological temperature was lower than that at room temperature. Ca{sup 2+} transients, which are usually coupled to contraction, were not detected. We confirmed that the contractions of skinned cardiomyocytes were induced by the heat pulses even in free Ca{sup 2+} solution. This heat pulse-induced Ca{sup 2+}-decoupled contraction technique has the potential to stimulate heart and skeletal muscles in a manner different from the conventional electrical stimulations.« less

Point process methods in epidemiology: application to the analysis of human immunodeficiency virus/acquired immunodeficiency syndrome mortality in urban areas.

PubMed

Quesada, Jose Antonio; Melchor, Inmaculada; Nolasco, Andreu

2017-05-26

The analysis of spatio-temporal patterns of disease or death in urban areas has been developed mainly from the ecological studies approach. These designs may have some limitations like the ecological fallacy and instability with few cases. The objective of this study was to apply the point process methodology, as a complement to that of aggregated data, to study HIV/AIDS mortality in men in the city of Alicante (Spain). A case-control study in residents in the city during the period 2004-2011 was designed. Cases were men who died from HIV/AIDS and controls represented the general population, matched by age to cases. The risk surfaces of death over the city were estimated using the log-risk function of intensities, and we contrasted their temporal variations over the two periods. High risk significant areas of death by HIV/AIDS, which coincide with the most deprived areas in the city, were detected. Significant spatial change of the areas at risk between the periods studied was not detected. The point process methodology is a useful tool to analyse the patterns of death by HIV/AIDS in urban areas.

Meal Detection in Patients With Type 1 Diabetes: A New Module for the Multivariable Adaptive Artificial Pancreas Control System.

PubMed

Turksoy, Kamuran; Samadi, Sediqeh; Feng, Jianyuan; Littlejohn, Elizabeth; Quinn, Laurie; Cinar, Ali

2016-01-01

A novel meal-detection algorithm is developed based on continuous glucose measurements. Bergman's minimal model is modified and used in an unscented Kalman filter for state estimations. The estimated rate of appearance of glucose is used for meal detection. Data from nine subjects are used to assess the performance of the algorithm. The results indicate that the proposed algorithm works successfully with high accuracy. The average change in glucose levels between the meals and the detection points is 16(±9.42) [mg/dl] for 61 successfully detected meals and snacks. The algorithm is developed as a new module of an integrated multivariable adaptive artificial pancreas control system. Meal detection with the proposed method is used to administer insulin boluses and prevent most of postprandial hyperglycemia without any manual meal announcements. A novel meal bolus calculation method is proposed and tested with the UVA/Padova simulator. The results indicate significant reduction in hyperglycemia.

Gross Olfaction Before and After Laparoscopic Gastric Bypass.

PubMed

Zerrweck, Carlos; Gallardo, Vannia Castañeda; Calleja, Carmen; Sepúlveda, Elisa; Guilber, Lizbeth

2017-11-01

Obesity leads to olfaction alterations, and this can further impact food choices, appetite, and nutritional status. Bariatric procedures induce weight loss and change in taste and smell perception, but more information is needed, especially using objective olfaction tests. A prospective study was conducted during 6 months, with candidates to laparoscopic gastric bypass at a single institution. A preoperative nasofibroscopy and gross smell identification test (The Pocket Smell Test ®) were performed in those meeting the inclusion criteria. After 6 months, a new test was performed, and the primary objective was to determine if there was an improvement in the olfaction score. Weight loss and comorbidities improvement were also analyzed. From the 30 patients with morbid obesity enrolled, 21 met the inclusion criteria and ENT evaluation. At baseline, 42.8% of patients scored 3 points, 53.3% scored 2 points, and 4.7% scored 1 point. After 6 months, there was a -81.1% of change. Seventeen patients scored 3 points (p = 0.002 vs initial) and two scored 2 points (p = 0.006 vs initial). There were no patients with less than 2 points. Weight and comorbidities had a significant improvement as well. Laparoscopic gastric bypass improves the olfaction scores of the Pocket Smell Test in morbidly obese patients 6 months after their procedure. More complex tests can be used in candidates to bariatric surgery if low scores are detected initially. Other causes of olfaction dysfunctions should be determined if there is no improvement after weight loss.

Gulf War agent exposure causes impairment of long-term memory formation and neuropathological changes in a mouse model of Gulf War Illness.

PubMed

Zakirova, Zuchra; Tweed, Miles; Crynen, Gogce; Reed, Jon; Abdullah, Laila; Nissanka, Nadee; Mullan, Myles; Mullan, Michael J; Mathura, Venkatarajan; Crawford, Fiona; Ait-Ghezala, Ghania

2015-01-01

Gulf War Illness (GWI) is a chronic multisymptom illness with a central nervous system component such as memory deficits, neurological, and musculoskeletal problems. There are ample data that demonstrate that exposure to Gulf War (GW) agents, such as pyridostigmine bromide (PB) and pesticides such as permethrin (PER), were key contributors to the etiology of GWI post deployment to the Persian GW. In the current study, we examined the consequences of acute (10 days) exposure to PB and PER in C57BL6 mice. Learning and memory tests were performed at 18 days and at 5 months post-exposure. We investigated the relationship between the cognitive phenotype and neuropathological changes at short and long-term time points post-exposure. No cognitive deficits were observed at the short-term time point, and only minor neuropathological changes were detected. However, cognitive deficits emerged at the later time point and were associated with increased astrogliosis and reduction of synaptophysin staining in the hippocampi and cerebral cortices of exposed mice, 5 months post exposure. In summary, our findings in this mouse model of GW agent exposure are consistent with some GWI symptom manifestations, including delayed onset of symptoms and CNS disturbances observed in GWI veterans.

Gulf War Agent Exposure Causes Impairment of Long-Term Memory Formation and Neuropathological Changes in a Mouse Model of Gulf War Illness

PubMed Central

Zakirova, Zuchra; Tweed, Miles; Crynen, Gogce; Reed, Jon; Abdullah, Laila; Nissanka, Nadee; Mullan, Myles; Mullan, Michael J.; Mathura, Venkatarajan; Crawford, Fiona; Ait-Ghezala, Ghania

2015-01-01

Gulf War Illness (GWI) is a chronic multisymptom illness with a central nervous system component such as memory deficits, neurological, and musculoskeletal problems. There are ample data that demonstrate that exposure to Gulf War (GW) agents, such as pyridostigmine bromide (PB) and pesticides such as permethrin (PER), were key contributors to the etiology of GWI post deployment to the Persian GW. In the current study, we examined the consequences of acute (10 days) exposure to PB and PER in C57BL6 mice. Learning and memory tests were performed at 18 days and at 5 months post-exposure. We investigated the relationship between the cognitive phenotype and neuropathological changes at short and long-term time points post-exposure. No cognitive deficits were observed at the short-term time point, and only minor neuropathological changes were detected. However, cognitive deficits emerged at the later time point and were associated with increased astrogliosis and reduction of synaptophysin staining in the hippocampi and cerebral cortices of exposed mice, 5 months post exposure. In summary, our findings in this mouse model of GW agent exposure are consistent with some GWI symptom manifestations, including delayed onset of symptoms and CNS disturbances observed in GWI veterans. PMID:25785457

Distributed optical fiber vibration sensor based on Sagnac interference in conjunction with OTDR.

PubMed

Pan, Chao; Liu, Xiaorui; Zhu, Hui; Shan, Xuekang; Sun, Xiaohan

2017-08-21

A real-time distributed optical fiber vibration sensing prototype based on the Sagnac interference in conjunction with the optical time domain reflectometry (OTDR) was developed. The sensing mechanism for single- and multi-points vibrations along the sensing fiber was analyzed theoretically and demonstrated experimentally. The experimental results show excellent agreement with the theoretical models. It is verified that single-point vibration induces a significantly abrupt and monotonous power change in the corresponding position of OTDR trace. As to multi-points vibrations, the detection of the following vibration is influenced by all previous ones. However, if the distance between the adjacent two vibrations is larger than half of the input optical pulse width, abrupt power changes induced by them are separate and still monotonous. A time-shifting differential module was developed and carried out to convert vibration-induced power changes to pulses. Consequently, vibrations can be located accurately by measuring peak or valley positions of the vibration-induced pulses. It is demonstrated that when the width and peak power of input optical pulse are set to 1 μs and 35 mW, respectively, the position error is less than ± 0.5 m in a sensing range of more than 16 km, with the spatial resolution of ~110 m.

Single quantum dot analysis enables multiplexed point mutation detection by gap ligase chain reaction.

PubMed

Song, Yunke; Zhang, Yi; Wang, Tza-Huei

2013-04-08

Gene point mutations present important biomarkers for genetic diseases. However, existing point mutation detection methods suffer from low sensitivity, specificity, and a tedious assay processes. In this report, an assay technology is proposed which combines the outstanding specificity of gap ligase chain reaction (Gap-LCR), the high sensitivity of single-molecule coincidence detection, and the superior optical properties of quantum dots (QDs) for multiplexed detection of point mutations in genomic DNA. Mutant-specific ligation products are generated by Gap-LCR and subsequently captured by QDs to form DNA-QD nanocomplexes that are detected by single-molecule spectroscopy (SMS) through multi-color fluorescence burst coincidence analysis, allowing for multiplexed mutation detection in a separation-free format. The proposed assay is capable of detecting zeptomoles of KRAS codon 12 mutation variants with near 100% specificity. Its high sensitivity allows direct detection of KRAS mutation in crude genomic DNA without PCR pre-amplification. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Detection method of visible and invisible nipples on digital breast tomosynthesis

NASA Astrophysics Data System (ADS)

Chae, Seung-Hoon; Jeong, Ji-Wook; Lee, Sooyeul; Chae, Eun Young; Kim, Hak Hee; Choi, Young-Wook

2015-03-01

Digital Breast Tomosynthesis(DBT) with 3D breast image can improve detection sensitivity of breast cancer more than 2D mammogram on dense breast. The nipple location information is needed to analyze DBT. The nipple location is invaluable information in registration and as a reference point for classifying mass or micro-calcification clusters. Since there are visible nipple and invisible nipple in 2D mammogram or DBT, the nipple detection of breast must be possible to detect visible and invisible nipple of breast. The detection method of visible nipple using shape information of nipple is simple and highly efficient. However, it is difficult to detect invisible nipple because it doesn't have prominent shape. Mammary glands in breast connect nipple, anatomically. The nipple location is detected through analyzing location of mammary glands in breast. In this paper, therefore, we propose a method to detect the nipple on a breast, which has a visible or invisible nipple using changes of breast area and mammary glands, respectively. The result shows that our proposed method has average error of 2.54+/-1.47mm.

Responsiveness of the VISA-P scale for patellar tendinopathy in athletes.

PubMed

Hernandez-Sanchez, Sergio; Hidalgo, Ma Dolores; Gomez, Antonia

2014-03-01

Patient-reported outcome measures are increasingly used in sports medicine to assess results after treatment, but interpretability of change for many instruments remains unclear. To define the minimum clinically important difference (MCID) for the Victorian Institute of Sport Assessment scale (VISA-P) in athletes with patellar tendinopathy (PT) who underwent conservative treatment. Ninety-eight athletes with PT were enrolled in the study. Each participant completed the VISA-P at admission, after 1 week, and at the final visit. Athletes also assessed their clinical change at discharge on a 15-point Likert scale. We equated important change with a score of ≥3 (somewhat better). Receiver-operating characteristic (ROC) curve analysis and mean change score were used to determine MCID. Minimal detectable change was calculated. The effect of baseline scores on MCID and different criteria used to define important change were investigated. A Bayesian analysis was used to establish the posterior probability of reporting clinical changes related to MCID value. Athletes with PT who showed an absolute change greater than 13 points in the VISA-P score or 15.4-27% of relative change achieved a minimal important change in their clinical status. This value depended on baseline scores. The probability of a clinical change in a patient was 98% when this threshold was achieved and 45% when MCID was not achieved. Definition of the MCID will enhance the interpretability of changes in the VISA-P score in the athletes with PT, but caution is required when these values are used.

Effect of pregnancy and embryonic mortality on milk production in dromedary camels (Camelus dromedarius).

PubMed

Nagy, P; Faigl, V; Reiczigel, J; Juhasz, J

2015-02-01

The main objective of the present study was to compare milk production in pregnant versus nonpregnant dromedary camels. In addition, we described the effect of embryonic mortality on lactation and measured serum progesterone levels until d 60 to 90 of gestation. Twenty-five multiparous camels were selected in midlactation for 2 studies in consecutive years. Camels were mated naturally when the size of the dominant follicle reached 1.2 to 1.5cm. Pregnancy was diagnosed by ultrasonography and progesterone determination. In the first experiment (Exp 1), 8 of 11 animals conceived at 284±21.5d postpartum. Three pregnant dromedaries were given PGF2α to induce luteolysis and pregnancy loss on d 62 and spontaneous embryonic loss was detected in 2 camels (on d 27 and 60). Animals were allotted to 3 groups retrospectively: nonpregnant camels (group 1, n=4), pregnant camels (group 2; n=3), and camels with embryonic loss after d 55 (group 3; n=4). In the second study (Exp 2), 14 dromedaries were mated during midlactation. Seven of them failed to conceive (group 1) and 7 became pregnant (group 2). No embryonic loss was detected in Exp 2. Turning points in milk production were identified by change point analysis. In nonpregnant dromedaries (group 1), milk decreased slowly over time without significant change point. In pregnant camels (group 2), a gradual decline until 4 wk after mating was followed by a sudden drop, and the change point model resulted in one breakpoint at d 28±7 and 35±3 of gestation in Exp 1 and Exp 2, respectively. In camels with embryonic mortality (group 3, Exp 1), milk yield started to decline similarly as in pregnant animals, but milk production increased gradually after embryonic loss and reached similar levels as in their nonpregnant herdmates. Change point analysis for group 3 resulted in 2 turning points at 30±4 and 48±4d after conception. Mean length of lactation was shorter by 230 (34.2%) and by 249d (37.6%) and mean total lactation production was decreased by 1,532 (31.6%) and 2,151 kg (44.3%) in pregnant compared with nonpregnant camels in Exp 1 and Exp 2, respectively. We concluded that the calving interval can be shortened by mating during midlactation. However, pregnancy has a strong negative effect on milk production as dromedaries stop lactating by the fourth month of gestation. Following embryonic mortality within 3mo of conception, milk production is restored. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Analysis of U. S. Forest Service bird point-count monitoring database - implications for designing and implementing avian monitoring

Treesearch

Eric T. Linder; David A. Buehler

2005-01-01

In 1996, Region 8 of the U. S. Forest Service implemented a program to monitor landbirds on southeastern U.S. national forests. The goal was to develop a monitoring system that could document population trends and bird-habitat relationships. Using power analysis, we examined the ability of the monitoring program to detect population trends (3 percent annual change) at...

FRP debonding monitoring using OTDR techniques

NASA Astrophysics Data System (ADS)

Hou, Shuang; Cai, C. S. Steve; Ou, Jinping

2009-07-01

Debonding failure has been reported as the dominant failure mode for FRP strengthening in flexure. This paper explores a novel debonding monitoring method for FRP strengthened structures by means of OTDR-based fiber optic technology. Interface slip as a key factor in debonding failures will be measured through sensing optic fibers, which is instrumented in the interface between FRP and concrete in the direction perpendicular to the FRP filaments. Slip in the interface will induce power losses in the optic fiber signals at the intersection point of the FRP strip and the sensing optic fiber and the signal change will be detected through OTDR device. The FRP double shear tests and three-point bending tests were conducted to verify the effectiveness of the proposed monitoring method. It is found that the early bebonding can be detected before it causes the interface failure. The sensing optic fiber shows signal changes in the slip value at about 36~156 micrometer which is beyond sensing capacity of the conventional sensors. The tests results show that the proposed method is feasible in slip measurement with high sensitivity, and would be cost effective because of the low price of sensors used, which shows its potential of large-scale applications in civil infrastructures, especially for bridges.

Absence of 60-Hz, 0.1-mT magnetic field-induced changes in oncogene transcription rates or levels in CEM-CM3 cells.

PubMed

Jahreis, G P; Johnson, P G; Zhao, Y L; Hui, S W

1998-12-22

Our objective was to assess the reproducibility of the 60-Hz magnetic field-induced, time-dependent transcription changes of c-fos, c-jun and c-myc oncogenes in CEM-CM3 cells reported by Phillips et al. (Biochim. Biophys. Acta, 1132 (1992) 140-144). Cells were exposed to a 60-Hz magnetic field (MF) at 0.1 mT (rms), generated by a pair of Helmholtz coils energized in a reinforcing (MF) mode, or to a null magnetic field when the coils were energized in a bucking (sham) mode. After MF or sham exposure for 15, 30, 60 or 120 min, nuclei and cytoplasmic RNA were extracted. Transcription rates were measured by a nuclear run-on assay, and values were normalized against either their zero-time exposure values, or against those of the c-G3PDH (housekeeping) gene at the same time points. There was no significant difference, at P=0.05, detected between MF and either sham-exposed or control cells at any time point. Transcript levels of the oncogenes were measured by Northern analysis and normalized as above. No significant difference (P=0.05) in transcript levels between MF and either sham-exposed or control cells was detected.

16 CFR Figure 5 to Subpart A of... - Zero Reference Point Related to Detecting Plane

Code of Federal Regulations, 2013 CFR

2013-01-01

... 16 Commercial Practices 2 2013-01-01 2013-01-01 false Zero Reference Point Related to Detecting Plane 5 Figure 5 to Subpart A of Part 1209 Commercial Practices CONSUMER PRODUCT SAFETY COMMISSION.... 1209, Subpt. A, Fig. 5 Figure 5 to Subpart A of Part 1209—Zero Reference Point Related to Detecting...

16 CFR Figure 5 to Subpart A of... - Zero Reference Point Related to Detecting Plane

Code of Federal Regulations, 2012 CFR

2012-01-01

... 16 Commercial Practices 2 2012-01-01 2012-01-01 false Zero Reference Point Related to Detecting Plane 5 Figure 5 to Subpart A of Part 1209 Commercial Practices CONSUMER PRODUCT SAFETY COMMISSION.... 1209, Subpt. A, Fig. 5 Figure 5 to Subpart A of Part 1209—Zero Reference Point Related to Detecting...

16 CFR Figure 5 to Subpart A of... - Zero Reference Point Related to Detecting Plane

Code of Federal Regulations, 2014 CFR

2014-01-01

... 16 Commercial Practices 2 2014-01-01 2014-01-01 false Zero Reference Point Related to Detecting Plane 5 Figure 5 to Subpart A of Part 1209 Commercial Practices CONSUMER PRODUCT SAFETY COMMISSION.... 1209, Subpt. A, Fig. 5 Figure 5 to Subpart A of Part 1209—Zero Reference Point Related to Detecting...

Ghost imaging with bucket detection and point detection

NASA Astrophysics Data System (ADS)

Zhang, De-Jian; Yin, Rao; Wang, Tong-Biao; Liao, Qing-Hua; Li, Hong-Guo; Liao, Qinghong; Liu, Jiang-Tao

2018-04-01

We experimentally investigate ghost imaging with bucket detection and point detection in which three types of illuminating sources are applied: (a) pseudo-thermal light source; (b) amplitude modulated true thermal light source; (c) amplitude modulated laser source. Experimental results show that the quality of ghost images reconstructed with true thermal light or laser beam is insensitive to the usage of bucket or point detector, however, the quality of ghost images reconstructed with pseudo-thermal light in bucket detector case is better than that in point detector case. Our theoretical analysis shows that the reason for this is due to the first order transverse coherence of the illuminating source.

Hydro-meteorological trends in the Gidabo catchment of the Rift Valley Lakes Basin of Ethiopia

NASA Astrophysics Data System (ADS)

Belihu, Mamuye; Abate, Brook; Tekleab, Sirak; Bewket, Woldeamlak

2018-04-01

The global and regional variability and changes of climate and stream flows are likely to have significant influence on water resource availability. The magnitude and impacts of climate variability and change differs spatially and temporally. This study examines the long term hydroclimatic changes, analyses of the hydro-climate variability and detect whether there exist significant trend or not in the Gidabo catchment, rift valley lakes basin of Ethiopia. Precipitation, temperature and stream flow time series data were used in monthly, seasonal and annual time scales. The precipitation and temperature data span is between 1982 and 2014 and that of stream flow is between 1976 and 2006. To detect trends the analysis were done by using Mann Kendal (MK), Sen's graphical method and to detect change point using the Pettit test. The comparison of trend analysis between MK trend test and Sen graphical method results depict mostly similar pattern. The annual rainfall trends exhibited a significant decrease by about 12 mm per year in the upstream, which is largely driven by the significant decrease in the peak season rainfall. The Pettit test revealed that the years 1997 and 2007 were the change points. It is noted that the rise of temperature over a catchment might have decreased the availability of soil moisture which resulted in less runoff. The temperature analyses also revealed that the catchment was getting warmer; particularly in the upstream. The minimum temperature trend showed a significant increase about 0.08°c per annum. There is generally a decreasing trend in stream flow. The monthly stream flow also exhibited a decreasing trend in February, March and September. The decline in annual and seasonal rainfall and the increase in temperature lead to more evaporation and directly affecting the stream flow negatively. This trend compounded with the growth of population and increasing demand for irrigation water exacerbates the competing demand for water resources. It thus calls for prudence in devising appropriate intervention in the planning and sustainable development of the basin water resources.

A preclinical murine model for the early detection of radiation-induced brain injury using magnetic resonance imaging and behavioral tests for learning and memory: with applications for the evaluation of possible stem cell imaging agents and therapies.

PubMed

Ngen, Ethel J; Wang, Lee; Gandhi, Nishant; Kato, Yoshinori; Armour, Michael; Zhu, Wenlian; Wong, John; Gabrielson, Kathleen L; Artemov, Dmitri

2016-06-01

Stem cell therapies are being developed for radiotherapy-induced brain injuries (RIBI). Magnetic resonance imaging (MRI) offers advantages for imaging transplanted stem cells. However, most MRI cell-tracking techniques employ superparamagnetic iron oxide particles (SPIOs), which are difficult to distinguish from hemorrhage. In current preclinical RIBI models, hemorrhage occurs concurrently with other injury markers. This makes the evaluation of the recruitment of transplanted SPIO-labeled stem cells to injury sites difficult. Here, we developed a RIBI model, with early injury markers reflective of hippocampal dysfunction, which can be detected noninvasively with MRI and behavioral tests. Lesions were generated by sub-hemispheric irradiation of mouse hippocampi with single X-ray beams of 80 Gy. Lesion formation was monitored with anatomical and contrast-enhanced MRI and changes in memory and learning were assessed with fear-conditioning tests. Early injury markers were detected 2 weeks after irradiation. These included an increase in the permeability of the blood-brain barrier, demonstrated by a 92 ± 20 % contrast enhancement of the irradiated versus the non-irradiated brain hemispheres, within 15 min of the administration of an MRI contrast agent. A change in short-term memory was also detected, as demonstrated by a 40.88 ± 5.03 % decrease in the freezing time measured during the short-term memory context test at this time point, compared to that before irradiation. SPIO-labeled stem cells transplanted contralateral to the lesion migrated toward the lesion at this time point. No hemorrhage was detected up to 10 weeks after irradiation. This model can be used to evaluate SPIO-based stem cell-tracking agents, short-term.

Shaking video stabilization with content completion

NASA Astrophysics Data System (ADS)

Peng, Yi; Ye, Qixiang; Liu, Yanmei; Jiao, Jianbin

2009-01-01

A new stabilization algorithm to counterbalance the shaking motion in a video based on classical Kandade-Lucas- Tomasi (KLT) method is presented in this paper. Feature points are evaluated with law of large numbers and clustering algorithm to reduce the side effect of moving foreground. Analysis on the change of motion direction is also carried out to detect the existence of shaking. For video clips with detected shaking, an affine transformation is performed to warp the current frame to the reference one. In addition, the missing content of a frame during the stabilization is completed with optical flow analysis and mosaicking operation. Experiments on video clips demonstrate the effectiveness of the proposed algorithm.

A Robust Gradient Based Method for Building Extraction from LiDAR and Photogrammetric Imagery.

PubMed

Siddiqui, Fasahat Ullah; Teng, Shyh Wei; Awrangjeb, Mohammad; Lu, Guojun

2016-07-19

Existing automatic building extraction methods are not effective in extracting buildings which are small in size and have transparent roofs. The application of large area threshold prohibits detection of small buildings and the use of ground points in generating the building mask prevents detection of transparent buildings. In addition, the existing methods use numerous parameters to extract buildings in complex environments, e.g., hilly area and high vegetation. However, the empirical tuning of large number of parameters reduces the robustness of building extraction methods. This paper proposes a novel Gradient-based Building Extraction (GBE) method to address these limitations. The proposed method transforms the Light Detection And Ranging (LiDAR) height information into intensity image without interpolation of point heights and then analyses the gradient information in the image. Generally, building roof planes have a constant height change along the slope of a roof plane whereas trees have a random height change. With such an analysis, buildings of a greater range of sizes with a transparent or opaque roof can be extracted. In addition, a local colour matching approach is introduced as a post-processing stage to eliminate trees. This stage of our proposed method does not require any manual setting and all parameters are set automatically from the data. The other post processing stages including variance, point density and shadow elimination are also applied to verify the extracted buildings, where comparatively fewer empirically set parameters are used. The performance of the proposed GBE method is evaluated on two benchmark data sets by using the object and pixel based metrics (completeness, correctness and quality). Our experimental results show the effectiveness of the proposed method in eliminating trees, extracting buildings of all sizes, and extracting buildings with and without transparent roof. When compared with current state-of-the-art building extraction methods, the proposed method outperforms the existing methods in various evaluation metrics.

A Robust Gradient Based Method for Building Extraction from LiDAR and Photogrammetric Imagery

PubMed Central

Siddiqui, Fasahat Ullah; Teng, Shyh Wei; Awrangjeb, Mohammad; Lu, Guojun

2016-01-01

Existing automatic building extraction methods are not effective in extracting buildings which are small in size and have transparent roofs. The application of large area threshold prohibits detection of small buildings and the use of ground points in generating the building mask prevents detection of transparent buildings. In addition, the existing methods use numerous parameters to extract buildings in complex environments, e.g., hilly area and high vegetation. However, the empirical tuning of large number of parameters reduces the robustness of building extraction methods. This paper proposes a novel Gradient-based Building Extraction (GBE) method to address these limitations. The proposed method transforms the Light Detection And Ranging (LiDAR) height information into intensity image without interpolation of point heights and then analyses the gradient information in the image. Generally, building roof planes have a constant height change along the slope of a roof plane whereas trees have a random height change. With such an analysis, buildings of a greater range of sizes with a transparent or opaque roof can be extracted. In addition, a local colour matching approach is introduced as a post-processing stage to eliminate trees. This stage of our proposed method does not require any manual setting and all parameters are set automatically from the data. The other post processing stages including variance, point density and shadow elimination are also applied to verify the extracted buildings, where comparatively fewer empirically set parameters are used. The performance of the proposed GBE method is evaluated on two benchmark data sets by using the object and pixel based metrics (completeness, correctness and quality). Our experimental results show the effectiveness of the proposed method in eliminating trees, extracting buildings of all sizes, and extracting buildings with and without transparent roof. When compared with current state-of-the-art building extraction methods, the proposed method outperforms the existing methods in various evaluation metrics. PMID:27447631

Bayesian analyses of time-interval data for environmental radiation monitoring.

PubMed

Luo, Peng; Sharp, Julia L; DeVol, Timothy A

2013-01-01

Time-interval (time difference between two consecutive pulses) analysis based on the principles of Bayesian inference was investigated for online radiation monitoring. Using experimental and simulated data, Bayesian analysis of time-interval data [Bayesian (ti)] was compared with Bayesian and a conventional frequentist analysis of counts in a fixed count time [Bayesian (cnt) and single interval test (SIT), respectively]. The performances of the three methods were compared in terms of average run length (ARL) and detection probability for several simulated detection scenarios. Experimental data were acquired with a DGF-4C system in list mode. Simulated data were obtained using Monte Carlo techniques to obtain a random sampling of the Poisson distribution. All statistical algorithms were developed using the R Project for statistical computing. Bayesian analysis of time-interval information provided a similar detection probability as Bayesian analysis of count information, but the authors were able to make a decision with fewer pulses at relatively higher radiation levels. In addition, for the cases with very short presence of the source (< count time), time-interval information is more sensitive to detect a change than count information since the source data is averaged by the background data over the entire count time. The relationships of the source time, change points, and modifications to the Bayesian approach for increasing detection probability are presented.

Investigating the Influence of Anthropogenic Forcing on Observed Mean and Extreme Sea Level Pressure Trends over the Mediterranean Region

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

Barkhordarian, Armineh

We investigate whether the observed mean sea level pressure (SLP) trends over the Mediterranean region in the period from 1975 to 2004 are significantly consistent with what 17 models projected as response of SLP to anthropogenic forcing (greenhouse gases and sulphate aerosols, GS). Obtained results indicate that the observed trends in mean SLP cannot be explained by natural (internal) variability. Externally forced changes are detectable in all seasons, except spring. The large-scale component (spatial mean) of the GS signal is detectable in all the 17 models in winter and in 12 of the 17 models in summer. However, the small-scalemore » component (spatial anomalies about the spatial mean) of GS signal is only detectable in winter within 11 of the 17 models. We also show that GS signal has a detectable influence on observed decreasing (increasing) tendency in the frequencies of extremely low (high) SLP days in winter and that these changes cannot be explained by internal climate variability. While the detection of GS forcing is robust in winter and summer, there are striking inconsistencies in autumn, where analysis points to the presence of an external forcing, which is not GS forcing.« less

Investigating the Influence of Anthropogenic Forcing on Observed Mean and Extreme Sea Level Pressure Trends over the Mediterranean Region

DOE PAGES

Barkhordarian, Armineh

2012-01-01

We investigate whether the observed mean sea level pressure (SLP) trends over the Mediterranean region in the period from 1975 to 2004 are significantly consistent with what 17 models projected as response of SLP to anthropogenic forcing (greenhouse gases and sulphate aerosols, GS). Obtained results indicate that the observed trends in mean SLP cannot be explained by natural (internal) variability. Externally forced changes are detectable in all seasons, except spring. The large-scale component (spatial mean) of the GS signal is detectable in all the 17 models in winter and in 12 of the 17 models in summer. However, the small-scalemore » component (spatial anomalies about the spatial mean) of GS signal is only detectable in winter within 11 of the 17 models. We also show that GS signal has a detectable influence on observed decreasing (increasing) tendency in the frequencies of extremely low (high) SLP days in winter and that these changes cannot be explained by internal climate variability. While the detection of GS forcing is robust in winter and summer, there are striking inconsistencies in autumn, where analysis points to the presence of an external forcing, which is not GS forcing.« less

Recent Advances in the Cellular and Molecular Mechanisms of Hypothalamic Neuronal Glucose Detection.

PubMed

Fioramonti, Xavier; Chrétien, Chloé; Leloup, Corinne; Pénicaud, Luc

2017-01-01

The hypothalamus have been recognized for decades as one of the major brain centers for the control of energy homeostasis. This area contains specialized neurons able to detect changes in nutrients level. Among them, glucose-sensing neurons use glucose as a signaling molecule in addition to its fueling role. In this review we will describe the different sub-populations of glucose-sensing neurons present in the hypothalamus and highlight their nature in terms of neurotransmitter/neuropeptide expression. This review will particularly discuss whether pro-opiomelanocortin (POMC) neurons from the arcuate nucleus are directly glucose-sensing. In addition, recent observations in glucose-sensing suggest a subtle system with different mechanisms involved in the detection of changes in glucose level and their involvement in specific physiological functions. Several data point out the critical role of reactive oxygen species (ROS) and mitochondria dynamics in the detection of increased glucose. This review will also highlight that ATP-dependent potassium (K ATP ) channels are not the only channels mediating glucose-sensing and discuss the new role of transient receptor potential canonical channels (TRPC). We will discuss the recent advances in the determination of glucose-sensing machinery and propose potential line of research needed to further understand the regulation of brain glucose detection.

Anisotropic-Scale Junction Detection and Matching for Indoor Images.

PubMed

Xue, Nan; Xia, Gui-Song; Bai, Xiang; Zhang, Liangpei; Shen, Weiming

Junctions play an important role in characterizing local geometrical structures of images, and the detection of which is a longstanding but challenging task. Existing junction detectors usually focus on identifying the location and orientations of junction branches while ignoring their scales, which, however, contain rich geometries of images. This paper presents a novel approach for junction detection and characterization, which especially exploits the locally anisotropic geometries of a junction and estimates its scales by relying on an a-contrario model. The output junctions are with anisotropic scales, saying that a scale parameter is associated with each branch of a junction and are thus named as anisotropic-scale junctions (ASJs). We then apply the new detected ASJs for matching indoor images, where there are dramatic changes of viewpoints and the detected local visual features, e.g., key-points, are usually insufficient and lack distinctive ability. We propose to use the anisotropic geometries of our junctions to improve the matching precision of indoor images. The matching results on sets of indoor images demonstrate that our approach achieves the state-of-the-art performance on indoor image matching.Junctions play an important role in characterizing local geometrical structures of images, and the detection of which is a longstanding but challenging task. Existing junction detectors usually focus on identifying the location and orientations of junction branches while ignoring their scales, which, however, contain rich geometries of images. This paper presents a novel approach for junction detection and characterization, which especially exploits the locally anisotropic geometries of a junction and estimates its scales by relying on an a-contrario model. The output junctions are with anisotropic scales, saying that a scale parameter is associated with each branch of a junction and are thus named as anisotropic-scale junctions (ASJs). We then apply the new detected ASJs for matching indoor images, where there are dramatic changes of viewpoints and the detected local visual features, e.g., key-points, are usually insufficient and lack distinctive ability. We propose to use the anisotropic geometries of our junctions to improve the matching precision of indoor images. The matching results on sets of indoor images demonstrate that our approach achieves the state-of-the-art performance on indoor image matching.

Assessing carotid atherosclerosis by fiber-optic multispectral photoacoustic tomography

NASA Astrophysics Data System (ADS)

Hui, Jie; Li, Rui; Wang, Pu; Phillips, Evan; Bruning, Rebecca; Liao, Chien-Sheng; Sturek, Michael; Goergen, Craig J.; Cheng, Ji-Xin

2015-03-01

Atherosclerotic plaque at the carotid bifurcation is the underlying cause of the majority of ischemic strokes. Noninvasive imaging and quantification of the compositional changes preceding gross anatomic changes within the arterial wall is essential for diagnosis of disease. Current imaging modalities such as duplex ultrasound, computed tomography, positron emission tomography are limited by the lack of compositional contrast and the detection of flow-limiting lesions. Although high-resolution magnetic resonance imaging has been developed to characterize atherosclerotic plaque composition, its accessibility for wide clinical use is limited. Here, we demonstrate a fiber-based multispectral photoacoustic tomography system for excitation of lipids and external acoustic detection of the generated ultrasound. Using sequential ultrasound imaging of ex vivo preparations we achieved ~2 cm imaging depth and chemical selectivity for assessment of human arterial plaques. A multivariate curve resolution alternating least squares analysis method was applied to resolve the major chemical components, including intravascular lipid, intramuscular fat, and blood. These results show the promise of detecting carotid plaque in vivo through esophageal fiber-optic excitation of lipids and external acoustic detection of the generated ultrasound. This imaging system has great potential for serving as a point-ofcare device for early diagnosis of carotid artery disease in the clinic.

Utilization of ERTS-1 data in the Houston area

NASA Technical Reports Server (NTRS)

Erb, R. B. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Using clustering techniques, several large lakes in Texas have been accurately delineated in computer printout graymaps. It was also found that small bodies of water (one to two acres in size) could be detected by searching for small reflectance values in the infrared data. A graymap printout of a lake described a shore outline that was not consistent with available maps. Field examination revealed that the actual level of the lake was below that for which the map was drawn. The current lake configuration agrees in shape and relative size with the ERTS-1 data printout. Water turbidity causes reflectance changes which are detectable in ERTS-1 band 7 data. A comparison has been made of the Monterey Bay, California area using 1971 aerial color infrared photography and a 1972 ERTS-1 band 7 infrared image. This comparison revealed that some event has occurred to impound a significant amount of water in the area since the infrared photography was taken. Data values in the ERTS-1 infrared image exhibit detectable changes in brightness at inflow points, where high turbidity would be present. Researchers had not expected to detect water turbidity patterns in band 7 (800 to 1100 nanometers).

Images from Galileo of the Venus cloud deck

USGS Publications Warehouse

Belton, M.J.S.; Gierasch, P.J.; Smith, M.D.; Helfenstein, P.; Schinder, P.J.; Pollack, James B.; Rages, K.A.; Ingersoll, A.P.; Klaasen, K.P.; Veverka, J.; Anger, C.D.; Carr, M.H.; Chapman, C.R.; Davies, M.E.; Fanale, F.P.; Greeley, R.; Greenberg, R.; Head, J. W.; Morrison, D.; Neukum, G.; Pilcher, C.B.

1991-01-01

Images of Venus taken at 418 (violet) and 986 [near-infrared (NIR)] nanometers show that the morphology and motions of large-scale features change with depth in the cloud deck. Poleward meridional velocities, seen in both spectral regions, are much reduced in the NIR. In the south polar region the markings in the two wavelength bands are strongly anticorrelated. The images follow the changing state of the upper cloud layer downwind of the subsolar point, and the zonal flow field shows a longitudinal periodicity that may be coupled to the formation of large-scale planetary waves. No optical lightning was detected.

Intra-day response of foreign exchange markets after the Tohoku-Oki earthquake

NASA Astrophysics Data System (ADS)

Nakano, Shuhei; Hirata, Yoshito; Iwayama, Koji; Aihara, Kazuyuki

2015-02-01

Although an economy is influenced by a natural disaster, the market response to the disaster during the first 24 hours is not clearly understood. Here we show that an earthquake quickly causes temporal changes in a foreign exchange market by examining the case of the Tohoku-Oki earthquake. Recurrence plots and statistical change point detection independently show that the United States dollar-Japanese yen market responded to the earthquake activity without delay and with the delay of about 2 minutes, respectively. These findings support that the efficient market hypothesis nearly holds now in the time scale of minutes.

Robust Spacecraft Component Detection in Point Clouds.

PubMed

Wei, Quanmao; Jiang, Zhiguo; Zhang, Haopeng

2018-03-21

Automatic component detection of spacecraft can assist in on-orbit operation and space situational awareness. Spacecraft are generally composed of solar panels and cuboidal or cylindrical modules. These components can be simply represented by geometric primitives like plane, cuboid and cylinder. Based on this prior, we propose a robust automatic detection scheme to automatically detect such basic components of spacecraft in three-dimensional (3D) point clouds. In the proposed scheme, cylinders are first detected in the iteration of the energy-based geometric model fitting and cylinder parameter estimation. Then, planes are detected by Hough transform and further described as bounded patches with their minimum bounding rectangles. Finally, the cuboids are detected with pair-wise geometry relations from the detected patches. After successive detection of cylinders, planar patches and cuboids, a mid-level geometry representation of the spacecraft can be delivered. We tested the proposed component detection scheme on spacecraft 3D point clouds synthesized by computer-aided design (CAD) models and those recovered by image-based reconstruction, respectively. Experimental results illustrate that the proposed scheme can detect the basic geometric components effectively and has fine robustness against noise and point distribution density.

Robust Spacecraft Component Detection in Point Clouds

PubMed Central

Wei, Quanmao; Jiang, Zhiguo

2018-01-01

Automatic component detection of spacecraft can assist in on-orbit operation and space situational awareness. Spacecraft are generally composed of solar panels and cuboidal or cylindrical modules. These components can be simply represented by geometric primitives like plane, cuboid and cylinder. Based on this prior, we propose a robust automatic detection scheme to automatically detect such basic components of spacecraft in three-dimensional (3D) point clouds. In the proposed scheme, cylinders are first detected in the iteration of the energy-based geometric model fitting and cylinder parameter estimation. Then, planes are detected by Hough transform and further described as bounded patches with their minimum bounding rectangles. Finally, the cuboids are detected with pair-wise geometry relations from the detected patches. After successive detection of cylinders, planar patches and cuboids, a mid-level geometry representation of the spacecraft can be delivered. We tested the proposed component detection scheme on spacecraft 3D point clouds synthesized by computer-aided design (CAD) models and those recovered by image-based reconstruction, respectively. Experimental results illustrate that the proposed scheme can detect the basic geometric components effectively and has fine robustness against noise and point distribution density. PMID:29561828

Analysis of trend changes in Northern African palaeo-climate by using Bayesian inference

NASA Astrophysics Data System (ADS)

Schütz, Nadine; Trauth, Martin H.; Holschneider, Matthias

2010-05-01

Climate variability of Northern Africa is of high interest due to climate-evolutionary linkages under study. The reconstruction of the palaeo-climate over long time scales, including the expected linkages (> 3 Ma), is mainly accessible by proxy data from deep sea drilling cores. By concentrating on published data sets, we try to decipher rhythms and trends to detect correlations between different proxy time series by advanced mathematical methods. Our preliminary data is dust concentration, as an indicator for climatic changes such as humidity, from the ODP sites 659, 721 and 967 situated around Northern Africa. Our interest is in challenging the available time series with advanced statistical methods to detect significant trend changes and to compare different model assumptions. For that purpose, we want to avoid the rescaling of the time axis to obtain equidistant time steps for filtering methods. Additionally we demand an plausible description of the errors for the estimated parameters, in terms of confidence intervals. Finally, depending on what model we restrict on, we also want an insight in the parameter structure of the assumed models. To gain this information, we focus on Bayesian inference by formulating the problem as a linear mixed model, so that the expectation and deviation are of linear structure. By using the Bayesian method we can formulate the posteriori density as a function of the model parameters and calculate this probability density in the parameter space. Depending which parameters are of interest, we analytically and numerically marginalize the posteriori with respect to the remaining parameters of less interest. We apply a simple linear mixed model to calculate the posteriori densities of the ODP sites 659 and 721 concerning the last 5 Ma at maximum. From preliminary calculations on these data sets, we can confirm results gained by the method of breakfit regression combined with block bootstrapping ([1]). We obtain a significant change point around (1.63 - 1.82) Ma, which correlates with a global climate transition due to the establishment of the Walker circulation ([2]). Furthermore we detect another significant change point around (2.7 - 3.2) Ma, which correlates with the end of the Pliocene warm period (permanent El Niño-like conditions) and the onset of a colder global climate ([3], [4]). The discussion on the algorithm, the results of calculated confidence intervals, the available information about the applied model in the parameter space and the comparison of multiple change point models will be presented. [1] Trauth, M.H., et al., Quaternary Science Reviews, 28, 2009 [2] Wara, M.W., et al., Science, Vol. 309, 2005 [3] Chiang, J.C.H., Annual Review of Earth and Planetary Sciences, Vol. 37, 2009 [4] deMenocal, P., Earth and Planetary Science Letters, 220, 2004

Meaningful Improvement in Gait Speed in Hip Fracture Recovery

PubMed Central

Alley, Dawn E.; Hicks, Gregory E.; Shardell, Michelle; Hawkes, William; Miller, Ram; Craik, Rebecca L.; Mangione, Kathleen K.; Orwig, Denise; Hochberg, Marc; Resnick, Barbara; Magaziner, Jay

2011-01-01

OBJECTIVES To estimate meaningful improvements in gait speed observed during recovery from hip fracture and to evaluate the sensitivity and specificity of gait speed changes in detecting change in self-reported mobility. DESIGN Secondary longitudinal data analysis from two randomized controlled trials SETTING Twelve hospitals in the Baltimore, Maryland, area. PARTICIPANTS Two hundred seventeen women admitted with hip fracture. MEASUREMENTS Usual gait speed and self-reported mobility (ability to walk 1 block and climb 1 flight of stairs) measured 2 and 12 months after fracture. RESULTS Effect size–based estimates of meaningful differences were 0.03 for small differences and 0.09 for substantial differences. Depending on the anchor (stairs vs walking) and method (mean difference vs regression), anchor-based estimates ranged from 0.10 to 0.17 m/s for small meaningful improvements and 0.17 to 0.26 m/s for substantial meaningful improvement. Optimal gait speed cut-points yielded low sensitivity (0.39–0.62) and specificity (0.57–0.76) for improvements in self-reported mobility. CONCLUSION Results from this sample of women recovering from hip fracture provide only limited support for the 0.10-m/s cut point for substantial meaningful change previously identified in community-dwelling older adults experiencing declines in walking abilities. Anchor-based estimates and cut points derived from receiver operating characteristic curve analysis suggest that greater improvements in gait speed may be required for substantial perceived mobility improvement in female hip fracture patients. Furthermore, gait speed change performed poorly in discriminating change in self-reported mobility. Estimates of meaningful change in gait speed may differ based on the direction of change (improvement vs decline) or between patient populations. PMID:21883109

Assessment of changes in formations of non-forest woody vegetation in southern Denmark based on airborne LiDAR.

PubMed

Angelidis, Ioannis; Levin, Gregor; Díaz-Varela, Ramón Alberto; Malinowski, Radek

2017-09-01

LiDAR (Light Detection and Ranging) is a remote sensing technology that uses light in the form of pulses to measure the range between a sensor and the Earth's surface. Recent increase in availability of airborne LiDAR scanning (ALS) data providing national coverage with high point densities has opened a wide range of possibilities for monitoring landscape elements and their changes at broad geographical extent. We assessed the dynamics of the spatial extent of non-forest woody vegetation (NFW) in a study area of approx. 2500 km 2 in southern Jutland, Denmark, based on two acquisitions of ALS data for 2006 and 2014 in combination with other spatial data. Our results show a net-increase (4.8%) in the total area of NFW. Furthermore, this net change comprises of both areas with a decrease and areas with an increase of NFW. An accuracy assessment based on visual interpretation of aerial photos indicates high accuracy (>95%) in the delineation of NFW without changes during the study period. For NFW that changed between 2006 and 2014, accuracies were lower (90 and 82% in removed and new features, respectively), which is probably due to lower point densities of the 2006 ALS data (0.5 pts./m 2 ) compared to the 2014 data (4-5 pts./m 2 ). We conclude that ALS data, if combined with other spatial data, in principle are highly suitable for detailed assessment of changes in landscape features, such as formations of NFW at broad geographical extent. However, in change assessment based on multi-temporal ALS data with different point densities errors occur, particularly when examining small or narrow NFW objects.

A Monocular Vision Sensor-Based Obstacle Detection Algorithm for Autonomous Robots.

PubMed

Lee, Tae-Jae; Yi, Dong-Hoon; Cho, Dong-Il Dan

2016-03-01

This paper presents a monocular vision sensor-based obstacle detection algorithm for autonomous robots. Each individual image pixel at the bottom region of interest is labeled as belonging either to an obstacle or the floor. While conventional methods depend on point tracking for geometric cues for obstacle detection, the proposed algorithm uses the inverse perspective mapping (IPM) method. This method is much more advantageous when the camera is not high off the floor, which makes point tracking near the floor difficult. Markov random field-based obstacle segmentation is then performed using the IPM results and a floor appearance model. Next, the shortest distance between the robot and the obstacle is calculated. The algorithm is tested by applying it to 70 datasets, 20 of which include nonobstacle images where considerable changes in floor appearance occur. The obstacle segmentation accuracies and the distance estimation error are quantitatively analyzed. For obstacle datasets, the segmentation precision and the average distance estimation error of the proposed method are 81.4% and 1.6 cm, respectively, whereas those for a conventional method are 57.5% and 9.9 cm, respectively. For nonobstacle datasets, the proposed method gives 0.0% false positive rates, while the conventional method gives 17.6%.

Imaging monitoring techniques applications in the transient gratings detection

NASA Astrophysics Data System (ADS)

Zhao, Qing-ming

2009-07-01

Experimental studies of Degenerate four-wave mixing (DFWM) in iodine vapor at atmospheric pressure and 0℃ and 25℃ are reported. The Laser-induced grating (LIG) studies are carried out by generating the thermal grating using a pulsed, narrow bandwidth, dye laser .A new image processing system for detecting forward DFWM spectroscopy on iodine vapor is reported. This system is composed of CCD camera, imaging processing card and the related software. With the help of the detecting system, phase matching can be easily achieved in the optical arrangement by crossing the two pumps and the probe as diagonals linking opposite corners of a rectangular box ,and providing a way to position the PhotoMultiplier Tube (PMT) . Also it is practical to know the effect of the pointing stability on the optical path by monitoring facula changing with the laser beam pointing and disturbs of the environment. Finally the effects of Photostability of dye laser on the ration of signal to noise in DFWM using forward geometries have been investigated in iodine vapor. This system makes it feasible that the potential application of FG-DFWM is used as a diagnostic tool in combustion research and environment monitoring.

Transit detection of a `starshade' at the inner lagrange point of an exoplanet

NASA Astrophysics Data System (ADS)

Gaidos, E.

2017-08-01

All water-covered rocky planets in the inner habitable zones of solar-type stars will inevitably experience a catastrophic runaway climate due to increasing stellar luminosity and limits to outgoing infrared radiation from wet greenhouse atmospheres. Reflectors or scatterers placed near Earth's inner Lagrange point (L_1) have been proposed as a "geoengineering' solution to anthropogenic climate change and an advanced version of this could modulate incident irradiation over many Gyr or `rescue' a planet from the interior of the habitable zone. The distance of the starshade from the planet that minimizes its mass is 1.6 times the Earth-L_1 distance. Such a starshade would have to be similar in size to the planet and the mutual occultations during planetary transits could produce a characteristic maximum at mid-transit in the light curve. Because of a fortuitous ratio of densities, Earth-size planets around G dwarf stars present the best opportunity to detect such an artefact. The signal would be persistent and is potentially detectable by a future space photometry mission to characterize transiting planets. The signal could be distinguished from natural phenomenon, I.e. starspots or cometary dust clouds, by its shape, persistence and transmission spectrum.

Hierarchical clustering of EMD based interest points for road sign detection

NASA Astrophysics Data System (ADS)

Khan, Jesmin; Bhuiyan, Sharif; Adhami, Reza

2014-04-01

This paper presents an automatic road traffic signs detection and recognition system based on hierarchical clustering of interest points and joint transform correlation. The proposed algorithm consists of the three following stages: interest points detection, clustering of those points and similarity search. At the first stage, good discriminative, rotation and scale invariant interest points are selected from the image edges based on the 1-D empirical mode decomposition (EMD). We propose a two-step unsupervised clustering technique, which is adaptive and based on two criterion. In this context, the detected points are initially clustered based on the stable local features related to the brightness and color, which are extracted using Gabor filter. Then points belonging to each partition are reclustered depending on the dispersion of the points in the initial cluster using position feature. This two-step hierarchical clustering yields the possible candidate road signs or the region of interests (ROIs). Finally, a fringe-adjusted joint transform correlation (JTC) technique is used for matching the unknown signs with the existing known reference road signs stored in the database. The presented framework provides a novel way to detect a road sign from the natural scenes and the results demonstrate the efficacy of the proposed technique, which yields a very low false hit rate.

When Dijkstra Meets Vanishing Point: A Stereo Vision Approach for Road Detection.

PubMed

Zhang, Yigong; Su, Yingna; Yang, Jian; Ponce, Jean; Kong, Hui

2018-05-01

In this paper, we propose a vanishing-point constrained Dijkstra road model for road detection in a stereo-vision paradigm. First, the stereo-camera is used to generate the u- and v-disparity maps of road image, from which the horizon can be extracted. With the horizon and ground region constraints, we can robustly locate the vanishing point of road region. Second, a weighted graph is constructed using all pixels of the image, and the detected vanishing point is treated as the source node of the graph. By computing a vanishing-point constrained Dijkstra minimum-cost map, where both disparity and gradient of gray image are used to calculate cost between two neighbor pixels, the problem of detecting road borders in image is transformed into that of finding two shortest paths that originate from the vanishing point to two pixels in the last row of image. The proposed approach has been implemented and tested over 2600 grayscale images of different road scenes in the KITTI data set. The experimental results demonstrate that this training-free approach can detect horizon, vanishing point, and road regions very accurately and robustly. It can achieve promising performance.

Planetary Crater Detection and Registration Using Marked Point Processes, Multiple Birth and Death Algorithms, and Region-Based Analysis

NASA Technical Reports Server (NTRS)

Solarna, David; Moser, Gabriele; Le Moigne-Stewart, Jacqueline; Serpico, Sebastiano B.

2017-01-01

Because of the large variety of sensors and spacecraft collecting data, planetary science needs to integrate various multi-sensor and multi-temporal images. These multiple data represent a precious asset, as they allow the study of targets spectral responses and of changes in the surface structure; because of their variety, they also require accurate and robust registration. A new crater detection algorithm, used to extract features that will be integrated in an image registration framework, is presented. A marked point process-based method has been developed to model the spatial distribution of elliptical objects (i.e. the craters) and a birth-death Markov chain Monte Carlo method, coupled with a region-based scheme aiming at computational efficiency, is used to find the optimal configuration fitting the image. The extracted features are exploited, together with a newly defined fitness function based on a modified Hausdorff distance, by an image registration algorithm whose architecture has been designed to minimize the computational time.

Electric field mill network products to improve detection of the lightning hazard

NASA Technical Reports Server (NTRS)

Maier, Launa M.

1987-01-01

An electric field mill network has been used at Kennedy Space Center for over 10 years as part of the thunderstorm detection system. Several algorithms are currently available to improve the informational output of the electric field mill data. The charge distributions of roughly 50 percent of all lightning can be modeled as if they reduced the charged cloud by a point charge or a point dipole. Using these models, the spatial differences in the lightning induced electric field changes, and a least squares algorithm to obtain an optimum solution, the three-dimensional locations of the lightning charge centers can be located. During the lifetime of a thunderstorm, dynamically induced charging, modeled as a current source, can be located spatially with measurements of Maxwell current density. The electric field mills can be used to calculate the Maxwell current density at times when it is equal to the displacement current density. These improvements will produce more accurate assessments of the potential electrical activity, identify active cells, and forecast thunderstorm termination.

a Performance Comparison of Feature Detectors for Planetary Rover Mapping and Localization

NASA Astrophysics Data System (ADS)

Wan, W.; Peng, M.; Xing, Y.; Wang, Y.; Liu, Z.; Di, K.; Teng, B.; Mao, X.; Zhao, Q.; Xin, X.; Jia, M.

2017-07-01

Feature detection and matching are key techniques in computer vision and robotics, and have been successfully implemented in many fields. So far there is no performance comparison of feature detectors and matching methods for planetary mapping and rover localization using rover stereo images. In this research, we present a comprehensive evaluation and comparison of six feature detectors, including Moravec, Förstner, Harris, FAST, SIFT and SURF, aiming for optimal implementation of feature-based matching in planetary surface environment. To facilitate quantitative analysis, a series of evaluation criteria, including distribution evenness of matched points, coverage of detected points, and feature matching accuracy, are developed in the research. In order to perform exhaustive evaluation, stereo images, simulated under different baseline, pitch angle, and interval of adjacent rover locations, are taken as experimental data source. The comparison results show that SIFT offers the best overall performance, especially it is less sensitive to changes of image taken at adjacent locations.

Camera system considerations for geomorphic applications of SfM photogrammetry

USGS Publications Warehouse

Mosbrucker, Adam; Major, Jon J.; Spicer, Kurt R.; Pitlick, John

2017-01-01

The availability of high-resolution, multi-temporal, remotely sensed topographic data is revolutionizing geomorphic analysis. Three-dimensional topographic point measurements acquired from structure-from-motion (SfM) photogrammetry have been shown to be highly accurate and cost-effective compared to laser-based alternatives in some environments. Use of consumer-grade digital cameras to generate terrain models and derivatives is becoming prevalent within the geomorphic community despite the details of these instruments being largely overlooked in current SfM literature. This article is protected by copyright. All rights reserved.A practical discussion of camera system selection, configuration, and image acquisition is presented. The hypothesis that optimizing source imagery can increase digital terrain model (DTM) accuracy is tested by evaluating accuracies of four SfM datasets conducted over multiple years of a gravel bed river floodplain using independent ground check points with the purpose of comparing morphological sediment budgets computed from SfM- and lidar-derived DTMs. Case study results are compared to existing SfM validation studies in an attempt to deconstruct the principle components of an SfM error budget. This article is protected by copyright. All rights reserved.Greater information capacity of source imagery was found to increase pixel matching quality, which produced 8 times greater point density and 6 times greater accuracy. When propagated through volumetric change analysis, individual DTM accuracy (6–37 cm) was sufficient to detect moderate geomorphic change (order 100,000 m3) on an unvegetated fluvial surface; change detection determined from repeat lidar and SfM surveys differed by about 10%. Simple camera selection criteria increased accuracy by 64%; configuration settings or image post-processing techniques increased point density by 5–25% and decreased processing time by 10–30%. This article is protected by copyright. All rights reserved.Regression analysis of 67 reviewed datasets revealed that the best explanatory variable to predict accuracy of SfM data is photographic scale. Despite the prevalent use of object distance ratios to describe scale, nominal ground sample distance is shown to be a superior metric, explaining 68% of the variability in mean absolute vertical error.

Feedback dew-point sensor utilizing optimally cut plastic optical fibres

NASA Astrophysics Data System (ADS)

Hadjiloucas, S.; Irvine, J.; Keating, D. A.

2000-01-01

A plastic optical fibre reflectance sensor that makes full use of the critical angle of the fibres is implemented to monitor dew formation on a Peltier-cooled reflector surface. The optical configuration permits isolation of optoelectronic components from the sensing head and better light coupling between the reflector and the detecting fibre, giving a better signal of the onset of dew formation on the reflector. Continuous monitoring of the rate of change in reflectance as well as the absolute reflectance signals, the use of a novel polymethyl-methacrylate-coated hydrophobic film reflector on the Peltier element and the application of feedback around the point of dew formation, further reduces the possibility of contamination of the sensor head. Under closed-loop operation, the sensor is capable of cycling around the point of dew formation at a frequency of 2.5 Hz.

Identification and agreement of first turn point by mathematical analysis applied to heart rate, carbon dioxide output and electromyography

PubMed Central

Zamunér, Antonio R.; Catai, Aparecida M.; Martins, Luiz E. B.; Sakabe, Daniel I.; Silva, Ester Da

2013-01-01

Background The second heart rate (HR) turn point has been extensively studied, however there are few studies determining the first HR turn point. Also, the use of mathematical and statistical models for determining changes in dynamic characteristics of physiological variables during an incremental cardiopulmonary test has been suggested. Objectives To determine the first turn point by analysis of HR, surface electromyography (sEMG), and carbon dioxide output () using two mathematical models and to compare the results to those of the visual method. Method Ten sedentary middle-aged men (53.9±3.2 years old) were submitted to cardiopulmonary exercise testing on an electromagnetic cycle ergometer until exhaustion. Ventilatory variables, HR, and sEMG of the vastus lateralis were obtained in real time. Three methods were used to determine the first turn point: 1) visual analysis based on loss of parallelism between and oxygen uptake (); 2) the linear-linear model, based on fitting the curves to the set of data (Lin-Lin ); 3) a bi-segmental linear regression of Hinkley' s algorithm applied to HR (HMM-HR), (HMM- ), and sEMG data (HMM-RMS). Results There were no differences between workload, HR, and ventilatory variable values at the first ventilatory turn point as determined by the five studied parameters (p>0.05). The Bland-Altman plot showed an even distribution of the visual analysis method with Lin-Lin , HMM-HR, HMM-CO2, and HMM-RMS. Conclusion The proposed mathematical models were effective in determining the first turn point since they detected the linear pattern change and the deflection point of , HR responses, and sEMG. PMID:24346296

Identification and agreement of first turn point by mathematical analysis applied to heart rate, carbon dioxide output and electromyography.

PubMed

Zamunér, Antonio R; Catai, Aparecida M; Martins, Luiz E B; Sakabe, Daniel I; Da Silva, Ester

2013-01-01

The second heart rate (HR) turn point has been extensively studied, however there are few studies determining the first HR turn point. Also, the use of mathematical and statistical models for determining changes in dynamic characteristics of physiological variables during an incremental cardiopulmonary test has been suggested. To determine the first turn point by analysis of HR, surface electromyography (sEMG), and carbon dioxide output (VCO2) using two mathematical models and to compare the results to those of the visual method. Ten sedentary middle-aged men (53.9 ± 3.2 years old) were submitted to cardiopulmonary exercise testing on an electromagnetic cycle ergometer until exhaustion. Ventilatory variables, HR, and sEMG of the vastus lateralis were obtained in real time. Three methods were used to determine the first turn point: 1) visual analysis based on loss of parallelism between VCO2 and oxygen uptake (VO2); 2) the linear-linear model, based on fitting the curves to the set of VCO2 data (Lin-LinVCO2); 3) a bi-segmental linear regression of Hinkley's algorithm applied to HR (HMM-HR), VCO2 (HMM-VCO2), and sEMG data (HMM-RMS). There were no differences between workload, HR, and ventilatory variable values at the first ventilatory turn point as determined by the five studied parameters (p>0.05). The Bland-Altman plot showed an even distribution of the visual analysis method with Lin-LinVCO2, HMM-HR, HMM-VCO2, and HMM-RMS. The proposed mathematical models were effective in determining the first turn point since they detected the linear pattern change and the deflection point of VCO2, HR responses, and sEMG.

CIEF separation, UV detection, and quantification of ampholytic antibiotics and bacteria from different matrices.

PubMed

Horká, Marie; Vykydalová, Marie; Růžička, Filip; Šalplachta, Jiří; Holá, Veronika; Dvořáčková, Milada; Kubesová, Anna; Šlais, Karel

2014-10-01

The effect of antibiotics on the microbial cells and concentration of antibiotics in the human body is essential for the effective use of antimicrobial therapy. The capillary isoelectric focusing is a suitable technique for the separation and the detection of bacteria, and amphoteric substances from nature. However, the determination of isoelectric points of ampholytic antibiotics by conventional techniques is time consuming. For this reason, capillary isoelectric focusing seems to be appropriate as a simple and reliable way for establishing them. The separation conditions for the capillary isoelectric focusing of selected ampholytic antibiotics with known isoelectric points and pK as, ampicillin (pI 4.9), ciprofloxacin (pI 7.4), ofloxacin (pI 7.1), tetracycline (pI 5.4), tigecycline (pI 9.7), and vancomycin (pI 8.1), were found and optimized in the suitable pH ranges pH 2.0-5.3, 2.0-9.6, and 9.0-10.4. The established values of isoelectric points correspond with those found in the literature except tigecycline. Its pI was not found in the literature. As an example of a possible procedure for direct detection of both ampholytic antibiotics and bacteria, Staphylococcus epidermidis, in the presence of culture media or whole human blood, was found. The changes of the bacterial cells after their treatment with tetracycline were confirmed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Capillary isoelectric focusing allows the fast and simple determination of isoelectric points of relevant antibiotics, their quantification from the environment, as well as studying their effectiveness on microorganisms in biological samples.

Estimating the Effects of Detection Heterogeneity and Overdispersion on Trends Estimated from Avian Point Counts

EPA Science Inventory

Point counts are a common method for sampling avian distribution and abundance. Though methods for estimating detection probabilities are available, many analyses use raw counts and do not correct for detectability. We use a removal model of detection within an N-mixture approa...

Modeling seasonal detection patterns for burrowing owl surveys

Treesearch

Quresh S. Latif; Kathleen D. Fleming; Cameron Barrows; John T. Rotenberry

2012-01-01

To guide monitoring of burrowing owls (Athene cunicularia) in the Coachella Valley, California, USA, we analyzed survey-method-specific seasonal variation in detectability. Point-based call-broadcast surveys yielded high early season detectability that then declined through time, whereas detectability on driving surveys increased through the season. Point surveys...

Experimental results for the rapid determination of the freezing point of fuels

NASA Technical Reports Server (NTRS)

Mathiprakasam, B.

1984-01-01

Two methods for the rapid determination of the freezing point of fuels were investigated: an optical method, which detected the change in light transmission from the disappearance of solid particles in the melted fuel; and a differential thermal analysis (DTA) method, which sensed the latent heat of fusion. A laboratory apparatus was fabricated to test the two methods. Cooling was done by thermoelectric modules using an ice-water bath as a heat sink. The DTA method was later modified to eliminate the reference fuel. The data from the sample were digitized and a point of inflection, which corresponds to the ASTM D-2386 freezing point (final melting point), was identified from the derivative. The apparatus was modifified to cool the fuel to -60 C and controls were added for maintaining constant cooling rate, rewarming rate, and hold time at minimum temperature. A parametric series of tests were run for twelve fuels with freezing points from -10 C to -50 C, varying cooling rate, rewarming rate, and hold time. Based on the results, an optimum test procedure was established. The results showed good agreement with ASTM D-2386 freezing point and differential scanning calorimetry results.

A method to calculate the gamma ray detection efficiency of a cylindrical NaI (Tl) crystal

NASA Astrophysics Data System (ADS)

Ahmadi, S.; Ashrafi, S.; Yazdansetad, F.

2018-05-01

Given a wide range application of NaI(Tl) detector in industrial and medical sectors, computation of the related detection efficiency in different distances of a radioactive source, especially for calibration purposes, is the subject of radiation detection studies. In this work, a 2in both in radius and height cylindrical NaI (Tl) scintillator was used, and by changing the radial, axial, and diagonal positions of an isotropic 137Cs point source relative to the detector, the solid angles and the interaction probabilities of gamma photons with the detector's sensitive area have been calculated. The calculations present the geometric and intrinsic efficiency as the functions of detector's dimensions and the position of the source. The calculation model is in good agreement with experiment, and MCNPX simulation.

Gradual cut detection using low-level vision for digital video

NASA Astrophysics Data System (ADS)

Lee, Jae-Hyun; Choi, Yeun-Sung; Jang, Ok-bae

1996-09-01

Digital video computing and organization is one of the important issues in multimedia system, signal compression, or database. Video should be segmented into shots to be used for identification and indexing. This approach requires a suitable method to automatically locate cut points in order to separate shot in a video. Automatic cut detection to isolate shots in a video has received considerable attention due to many practical applications; our video database, browsing, authoring system, retrieval and movie. Previous studies are based on a set of difference mechanisms and they measured the content changes between video frames. But they could not detect more special effects which include dissolve, wipe, fade-in, fade-out, and structured flashing. In this paper, a new cut detection method for gradual transition based on computer vision techniques is proposed. And then, experimental results applied to commercial video are presented and evaluated.

Optimizing Probability of Detection Point Estimate Demonstration

NASA Technical Reports Server (NTRS)

Koshti, Ajay M.

2017-01-01

Probability of detection (POD) analysis is used in assessing reliably detectable flaw size in nondestructive evaluation (NDE). MIL-HDBK-18231and associated mh18232POD software gives most common methods of POD analysis. Real flaws such as cracks and crack-like flaws are desired to be detected using these NDE methods. A reliably detectable crack size is required for safe life analysis of fracture critical parts. The paper provides discussion on optimizing probability of detection (POD) demonstration experiments using Point Estimate Method. POD Point estimate method is used by NASA for qualifying special NDE procedures. The point estimate method uses binomial distribution for probability density. Normally, a set of 29 flaws of same size within some tolerance are used in the demonstration. The optimization is performed to provide acceptable value for probability of passing demonstration (PPD) and achieving acceptable value for probability of false (POF) calls while keeping the flaw sizes in the set as small as possible.

On-line Flagging of Anomalies and Adaptive Sequential Hypothesis Testing for Fine-feature Characterization of Geosynchronous Satellites

NASA Astrophysics Data System (ADS)

Chaudhary, A.; Payne, T.; Kinateder, K.; Dao, P.; Beecher, E.; Boone, D.; Elliott, B.

The objective of on-line flagging in this paper is to perform interactive assessment of geosynchronous satellites anomalies such as cross-tagging of a satellites in a cluster, solar panel offset change, etc. This assessment will utilize a Bayesian belief propagation procedure and will include automated update of baseline signature data for the satellite, while accounting for the seasonal changes. Its purpose is to enable an ongoing, automated assessment of satellite behavior through its life cycle using the photometry data collected during the synoptic search performed by a ground or space-based sensor as a part of its metrics mission. The change in the satellite features will be reported along with the probabilities of Type I and Type II errors. The objective of adaptive sequential hypothesis testing in this paper is to define future sensor tasking for the purpose of characterization of fine features of the satellite. The tasking will be designed in order to maximize new information with the least number of photometry data points to be collected during the synoptic search by a ground or space-based sensor. Its calculation is based on the utilization of information entropy techniques. The tasking is defined by considering a sequence of hypotheses in regard to the fine features of the satellite. The optimal observation conditions are then ordered in order to maximize new information about a chosen fine feature. The combined objective of on-line flagging and adaptive sequential hypothesis testing is to progressively discover new information about the features of a geosynchronous satellites by leveraging the regular but sparse cadence of data collection during the synoptic search performed by a ground or space-based sensor. Automated Algorithm to Detect Changes in Geostationary Satellite's Configuration and Cross-Tagging Phan Dao, Air Force Research Laboratory/RVB By characterizing geostationary satellites based on photometry and color photometry, analysts can evaluate satellite operational status and affirm its true identity. The process of ingesting photometry data and deriving satellite physical characteristics can be directed by analysts in a batch mode, meaning using a batch of recent data, or by automated algorithms in an on-line mode in which the assessment is updated with each new data point. Tools used for detecting change to satellite's status or identity, whether performed with a human in the loop or automated algorithms, are generally not built to detect with minimum latency and traceable confidence intervals. To alleviate those deficiencies, we investigate the use of Hidden Markov Models (HMM), in a Bayesian Network framework, to infer the hidden state (changed or unchanged) of a three-axis stabilized geostationary satellite using broadband and color photometry. Unlike frequentist statistics which exploit only the stationary statistics of the observables in the database, HMM also exploits the temporal pattern of the observables as well. The algorithm also operates in “learning” mode to gradually evolve the HMM and accommodate natural changes such as due to the seasonal dependence of GEO satellite's light curve. Our technique is designed to operate with missing color data. The version that ingests both panchromatic and color data can accommodate gaps in color photometry data. That attribute is important because while color indices, e.g. Johnson R and B, enhance the belief (probability) of a hidden state, in real world situations, flux data is collected sporadically in an untasked collect, and color data is limited and sometimes absent. Fluxes are measured with experimental error whose effect on the algorithm will be studied. Photometry data in the AFRL's Geo Color Photometry Catalog and Geo Observations with Latitudinal Diversity Simultaneously (GOLDS) data sets are used to simulate a wide variety of operational changes and identity cross tags. The algorithm is tested against simulated sequences of observed magnitudes, mimicking both the cadence of untasked SSN and other ground sensors, occasional operational changes and possible occurrence of cross tags of in-cluster satellites. We would like to show that the on-line algorithm can detect change; sometimes right after the first post-change data point is analyzed, for zero latency. We also want to show the unsupervised “learning” capability that allows the HMM to evolve with time without user's assistance. For example, the users are not required to “label” the true state of the data points.

Evaluating the accuracy of low cost UAV generated topography and its effectiveness for geomorphic change detection

NASA Astrophysics Data System (ADS)

Cook, Kristen

2015-04-01

With the recent explosion in the use and availability of unmanned aerial vehicle platforms and development of easy to use structure from motion (SfM) software, UAV based photogrammetry is increasingly being adopted to produce high resolution topography for the study of surface processes. UAV systems can vary substantially in price and complexity, but the tradeoffs between these and the quality of the resulting data are not well constrained. We look at one end of this spectrum and evaluate the effectiveness of a simple low cost UAV setup for obtaining high resolution topography in a challenging field setting. Our study site is the Daan River gorge in western Taiwan, a rapidly eroding bedrock gorge that we have monitored with terrestrial Lidar since 2009. The site presents challenges for the generation and analysis of high resolution topography, including vertical gorge walls, vegetation, wide variation in surface roughness, and a complicated 3D morphology. In order to evaluate the accuracy of the UAV-derived topography, we compare it with terrestrial Lidar data collected during the same survey period. Our UAV setup combines a DJI Phantom 2 quadcopter with a 16 megapixel Canon Powershot camera for a total platform cost of less than 850. The quadcopter is flown manually, and the camera is programmed to take a photograph every 4 seconds, yielding 200-250 pictures per flight. We measured ground control points and targets for both the Lidar scans and the aerial surveys using a Leica RTK GPS with 1-2 cm accuracy. UAV derived point clouds were obtained using Agisoft Photoscan software. We conducted both Lidar and UAV surveys before and after the 2014 typhoon season, allowing us to evaluate the reliability of the UAV survey to detect geomorphic changes in the range of one to several meters. The accuracy of the SfM point clouds depends strongly on the characteristics of the surface being considered, with vegetation and small scale texture causing inaccuracies. However, we find that this simple UAV setup can yield point clouds with 78% of points within 20 cm and 60% within 10 cm of the Lidar point clouds, with the higher errors dominated by vegetation effects. Well-distributed and accurately located ground control points are critical, but we achieve good accuracy with even with relatively few ground control points (25) over a 150,000 sq m area. The large number of photographs taken during each flight also allows us to explore the reproducibility of the UAV-derived topography by generating point clouds from different subsets of photographs taken of the same area during a single survey. These results show the same pattern of higher errors due to vegetation, but bedrock surfaces generally have errors of less than 4 cm. These results suggest that even very basic UAV surveys can yield data suitable for measuring geomorphic change on the scale of a channel reach.

Towards BirthAlert—A Clinical Device Intended for Early Preterm Birth Detection

PubMed Central

Etemadi, Mozziyar; Chung, Philip; Heller, J. Alex; Liu, Jonathan A.; Rand, Larry; Roy, Shuvo

2015-01-01

Preterm birth causes 1 million infant deaths worldwide every year, making it the leading cause of infant mortality. Existing diagnostic tests such as transvaginal ultrasound or fetal fibronectin either cannot determine if preterm birth will occur in the future or can only predict the occurrence once cervical shortening has begun, at which point it is too late to reverse the accelerated parturition process. Using iterative and rapid prototyping techniques, we have developed an intravaginal proof-of-concept device that measures both cervical bioimpedance and cervical fluorescence to characterize microstructural changes in a pregnant woman's cervix in hopes of detecting preterm birth before macroscopic changes manifest in the tissue. If successful, such an early alert during this “silent phase” of the preterm birth syndrome may open a new window of opportunity for interventions that may reverse and avoid preterm birth altogether. PMID:23893706

Person detection and tracking with a 360° lidar system

NASA Astrophysics Data System (ADS)

Hammer, Marcus; Hebel, Marcus; Arens, Michael

2017-10-01

Today it is easily possible to generate dense point clouds of the sensor environment using 360° LiDAR (Light Detection and Ranging) sensors which are available since a number of years. The interpretation of these data is much more challenging. For the automated data evaluation the detection and classification of objects is a fundamental task. Especially in urban scenarios moving objects like persons or vehicles are of particular interest, for instance in automatic collision avoidance, for mobile sensor platforms or surveillance tasks. In literature there are several approaches for automated person detection in point clouds. While most techniques show acceptable results in object detection, the computation time is often crucial. The runtime can be problematic, especially due to the amount of data in the panoramic 360° point clouds. On the other hand, for most applications an object detection and classification in real time is needed. The paper presents a proposal for a fast, real-time capable algorithm for person detection, classification and tracking in panoramic point clouds.

Evaluating the effectiveness of low cost UAV generated topography for geomorphic change detection

NASA Astrophysics Data System (ADS)

Cook, K. L.

2014-12-01

With the recent explosion in the use and availability of unmanned aerial vehicle platforms and development of easy to use structure from motion software, UAV based photogrammetry is increasingly being adopted to produce high resolution topography for the study of surface processes. UAV systems can vary substantially in price and complexity, but the tradeoffs between these and the quality of the resulting data are not well constrained. We look at one end of this spectrum and evaluate the effectiveness of a simple low cost UAV setup for obtaining high resolution topography in a challenging field setting. Our study site is the Daan River gorge in western Taiwan, a rapidly eroding bedrock gorge that we have monitored with terrestrial Lidar since 2009. The site presents challenges for the generation and analysis of high resolution topography, including vertical gorge walls, vegetation, wide variation in surface roughness, and a complicated 3D morphology. In order to evaluate the accuracy of the UAV-derived topography, we compare it with terrestrial Lidar data collected during the same survey period. Our UAV setup combines a DJI Phantom 2 quadcopter with a 16 megapixel Canon Powershot camera for a total platform cost of less than $850. The quadcopter is flown manually, and the camera is programmed to take a photograph every 5 seconds, yielding 200-250 pictures per flight. We measured ground control points and targets for both the Lidar scans and the aerial surveys using a Leica RTK GPS with 1-2 cm accuracy. UAV derived point clouds were obtained using Agisoft Photoscan software. We conducted both Lidar and UAV surveys before and after a summer typhoon season, allowing us to evaluate the reliability of the UAV survey to detect geomorphic changes in the range of one to several meters. We find that this simple UAV setup can yield point clouds with an average accuracy on the order of 10 cm compared to the Lidar point clouds. Well-distributed and accurately located ground control points are critical, but we achieve good accuracy with even with relatively few ground control points (25) over a 150,000 sq m area. The large number of photographs taken during each flight also allows us to explore the reproducibility of the UAV-derived topography by generating point clouds from different subsets of photographs taken of the same area during a single survey.

Detecting determinism from point processes.

PubMed

Andrzejak, Ralph G; Mormann, Florian; Kreuz, Thomas

2014-12-01

The detection of a nonrandom structure from experimental data can be crucial for the classification, understanding, and interpretation of the generating process. We here introduce a rank-based nonlinear predictability score to detect determinism from point process data. Thanks to its modular nature, this approach can be adapted to whatever signature in the data one considers indicative of deterministic structure. After validating our approach using point process signals from deterministic and stochastic model dynamics, we show an application to neuronal spike trains recorded in the brain of an epilepsy patient. While we illustrate our approach in the context of temporal point processes, it can be readily applied to spatial point processes as well.

Landsat Based Woody Vegetation Loss Detection in Queensland, Australia Using the Google Earth Engine

NASA Astrophysics Data System (ADS)

Johansen, K.; Phinn, S. R.; Taylor, M.

2014-12-01

Land clearing detection and woody Foliage Projective Cover (FPC) monitoring at the state and national level in Australia has mainly been undertaken by state governments and the Terrestrial Ecosystem Research Network (TERN) because of the considerable expense, expertise, sustained duration of activities and staffing levels needed. Only recently have services become available, providing low budget, generalized access to change detection tools suited to this task. The objective of this research was to examine if a globally available service, Google Earth Engine Beta, could be used to predict woody vegetation loss with accuracies approaching the methods used by TERN and the government of the state of Queensland, Australia. Two change detection approaches were investigated using Landsat Thematic Mapper time series and the Google Earth Engine Application Programming Interface: (1) CART and Random Forest classifiers; and (2) a normalized time series of Foliage Projective Cover (FPC) and NDVI combined with a spectral index. The CART and Random Forest classifiers produced high user's and producer's mapping accuracies of clearing (77-92% and 54-77%, respectively) when detecting change within epochs for which training data were available, but extrapolation to epochs without training data reduced the mapping accuracies. The use of FPC and NDVI time series provided a more robust approach for calculation of a clearing probability, as it did not rely on training data but instead on the difference of the normalized FPC / NDVI mean and standard deviation of a single year at the change point in relation to the remaining time series. However, the FPC and NDVI time series approach represented a trade-off between user's and producer's accuracies. Both change detection approaches explored in this research were sensitive to ephemeral greening and drying of the landscape. However, the developed normalized FPC and NDVI time series approach can be tuned to provide automated alerts for large woody vegetation clearing events by selecting suitable thresholds to identify very likely clearing. This research provides a comprehensive foundation to build further capacity to use globally accessible, free, online image datasets and processing tools to accurately detect woody vegetation clearing in an automated and rapid manner.

A removal model for estimating detection probabilities from point-count surveys

USGS Publications Warehouse

Farnsworth, G.L.; Pollock, K.H.; Nichols, J.D.; Simons, T.R.; Hines, J.E.; Sauer, J.R.

2000-01-01

We adapted a removal model to estimate detection probability during point count surveys. The model assumes one factor influencing detection during point counts is the singing frequency of birds. This may be true for surveys recording forest songbirds when most detections are by sound. The model requires counts to be divided into several time intervals. We used time intervals of 2, 5, and 10 min to develop a maximum-likelihood estimator for the detectability of birds during such surveys. We applied this technique to data from bird surveys conducted in Great Smoky Mountains National Park. We used model selection criteria to identify whether detection probabilities varied among species, throughout the morning, throughout the season, and among different observers. The overall detection probability for all birds was 75%. We found differences in detection probability among species. Species that sing frequently such as Winter Wren and Acadian Flycatcher had high detection probabilities (about 90%) and species that call infrequently such as Pileated Woodpecker had low detection probability (36%). We also found detection probabilities varied with the time of day for some species (e.g. thrushes) and between observers for other species. This method of estimating detectability during point count surveys offers a promising new approach to using count data to address questions of the bird abundance, density, and population trends.

Study of Laser Reflectivity on Skin

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

Oidor-Garcia, J. J. J.; Trevino-Palacios, C. G.

2008-08-11

The response to the light on the skin can be manifested as temperature increase or creation of biochemical byproducts, in which further studies are required to asset the light effect. This response changes the average response over time and can produce discrepancies between similar studies. In this work we present a Low Level Laser Therapy (LLLT) study with feedback. We study the time response reflectivity of a 980 nm laser diode of 25 mW modulated at frequencies close to 40 kHz and detect the reflected light on a silicon photodiode, finding no direct correlation between different test points or individuals,more » while finding reproducible responses within the same individual and test point.« less

Optical signatures of deep level defects in Ga2O3

NASA Astrophysics Data System (ADS)

Gao, Hantian; Muralidharan, Shreyas; Pronin, Nicholas; Karim, Md Rezaul; White, Susan M.; Asel, Thaddeus; Foster, Geoffrey; Krishnamoorthy, Sriram; Rajan, Siddharth; Cao, Lei R.; Higashiwaki, Masataka; von Wenckstern, Holger; Grundmann, Marius; Zhao, Hongping; Look, David C.; Brillson, Leonard J.

2018-06-01

We used depth-resolved cathodoluminescence spectroscopy and surface photovoltage spectroscopy to measure the effects of near-surface plasma processing and neutron irradiation on native point defects in β-Ga2O3. The near-surface sensitivity and depth resolution of these optical techniques enabled us to identify spectral changes associated with removing or creating these defects, leading to identification of one oxygen vacancy-related and two gallium vacancy-related energy levels in the β-Ga2O3 bandgap. The combined near-surface detection and processing of Ga2O3 suggests an avenue for identifying the physical nature and reducing the density of native point defects in this and other semiconductors.

Research on infrared dim-point target detection and tracking under sea-sky-line complex background

NASA Astrophysics Data System (ADS)

Dong, Yu-xing; Li, Yan; Zhang, Hai-bo

2011-08-01

Target detection and tracking technology in infrared image is an important part of modern military defense system. Infrared dim-point targets detection and recognition under complex background is a difficulty and important strategic value and challenging research topic. The main objects that carrier-borne infrared vigilance system detected are sea-skimming aircrafts and missiles. Due to the characteristics of wide field of view of vigilance system, the target is usually under the sea clutter. Detection and recognition of the target will be taken great difficulties .There are some traditional point target detection algorithms, such as adaptive background prediction detecting method. When background has dispersion-decreasing structure, the traditional target detection algorithms would be more useful. But when the background has large gray gradient, such as sea-sky-line, sea waves etc .The bigger false-alarm rate will be taken in these local area .It could not obtain satisfactory results. Because dim-point target itself does not have obvious geometry or texture feature ,in our opinion , from the perspective of mathematics, the detection of dim-point targets in image is about singular function analysis .And from the perspective image processing analysis , the judgment of isolated singularity in the image is key problem. The foregoing points for dim-point targets detection, its essence is a separation of target and background of different singularity characteristics .The image from infrared sensor usually accompanied by different kinds of noise. These external noises could be caused by the complicated background or from the sensor itself. The noise might affect target detection and tracking. Therefore, the purpose of the image preprocessing is to reduce the effects from noise, also to raise the SNR of image, and to increase the contrast of target and background. According to the low sea-skimming infrared flying small target characteristics , the median filter is used to eliminate noise, improve signal-to-noise ratio, then the multi-point multi-storey vertical Sobel algorithm will be used to detect the sea-sky-line ,so that we can segment sea and sky in the image. Finally using centroid tracking method to capture and trace target. This method has been successfully used to trace target under the sea-sky complex background.

Motion-Based Immunological Detection of Zika Virus Using Pt-Nanomotors and a Cellphone.

PubMed

Draz, Mohamed Shehata; Lakshminaraasimulu, Nivethitha Kota; Krishnakumar, Sanchana; Battalapalli, Dheerendranath; Vasan, Anish; Kanakasabapathy, Manoj Kumar; Sreeram, Aparna; Kallakuri, Shantanu; Thirumalaraju, Prudhvi; Li, Yudong; Hua, Stephane; Yu, Xu G; Kuritzkes, Daniel R; Shafiee, Hadi

2018-05-16

Zika virus (ZIKV) infection is an emerging pandemic threat to humans that can be fatal in newborns. Advances in digital health systems and nanoparticles can facilitate the development of sensitive and portable detection technologies for timely management of emerging viral infections. Here we report a nanomotor-based bead-motion cellphone (NBC) system for the immunological detection of ZIKV. The presence of virus in a testing sample results in the accumulation of platinum (Pt)-nanomotors on the surface of beads, causing their motion in H 2 O 2 solution. Then the virus concentration is detected in correlation with the change in beads motion. The developed NBC system was capable of detecting ZIKV in samples with virus concentrations as low as 1 particle/μL. The NBC system allowed a highly specific detection of ZIKV in the presence of the closely related dengue virus and other neurotropic viruses, such as herpes simplex virus type 1 and human cytomegalovirus. The NBC platform technology has the potential to be used in the development of point-of-care diagnostics for pathogen detection and disease management in developed and developing countries.

Graphene planar lightwave circuit sensors for chemical detection

NASA Astrophysics Data System (ADS)

Maliakal, Ashok; Husaini, Saima; Reith, Leslie; Bollond, Paul; Cabot, Steve; Sheehan, Paul; Hangartar, Sandra; Walton, Scott; Tamanaha, Cy

2017-02-01

Sensing devices based on Graphene Field Effect Transistors (G-FET) have been demonstrated by several groups to show excellent sensitivity for a variety of chemical agents. These devices are based on measuring changes in the electrical conductivity of graphene when exposed to various chemicals. However, because of its unique band structure, graphene also exhibits changes in its optical response upon chemical exposure. The conical intersection of the valence and conduction bands results in a low density of states near the Dirac point. At this point, chemical doping resulting from molecular binding to graphene can result in dramatic changes in graphene's optical absorption. Here we will discuss our recent work in developing a graphene planar lightwave circuit (PLC) sensor which exploits these optical and electronic properties of graphene to demonstrate chemical sensitivity. The devices are based on a strong evanescent coupling of graphene via electrically gated silicon nanowire waveguides. A strong response in the form of a reversible optical attenuation change of 6 dB is shown when these devices interact with toxic industrial chemicals such as iodine and ammonia. The optical transition can also be tuned to the optical c-band (1530-1565 nm) which enables these devices to operate at telecom wavelengths.

Experimental application of simulation tools for evaluating UAV video change detection

NASA Astrophysics Data System (ADS)

Saur, Günter; Bartelsen, Jan

2015-10-01

Change detection is one of the most important tasks when unmanned aerial vehicles (UAV) are used for video reconnaissance and surveillance. In this paper, we address changes on short time scale, i.e. the observations are taken within time distances of a few hours. Each observation is a short video sequence corresponding to the near-nadir overflight of the UAV above the interesting area and the relevant changes are e.g. recently added or removed objects. The change detection algorithm has to distinguish between relevant and non-relevant changes. Examples for non-relevant changes are versatile objects like trees and compression or transmission artifacts. To enable the usage of an automatic change detection within an interactive workflow of an UAV video exploitation system, an evaluation and assessment procedure has to be performed. Large video data sets which contain many relevant objects with varying scene background and altering influence parameters (e.g. image quality, sensor and flight parameters) including image metadata and ground truth data are necessary for a comprehensive evaluation. Since the acquisition of real video data is limited by cost and time constraints, from our point of view, the generation of synthetic data by simulation tools has to be considered. In this paper the processing chain of Saur et al. (2014) [1] and the interactive workflow for video change detection is described. We have selected the commercial simulation environment Virtual Battle Space 3 (VBS3) to generate synthetic data. For an experimental setup, an example scenario "road monitoring" has been defined and several video clips have been produced with varying flight and sensor parameters and varying objects in the scene. Image registration and change mask extraction, both components of the processing chain, are applied to corresponding frames of different video clips. For the selected examples, the images could be registered, the modelled changes could be extracted and the artifacts of the image rendering considered as noise (slight differences of heading angles, disparity of vegetation, 3D parallax) could be suppressed. We conclude that these image data could be considered to be realistic enough to serve as evaluation data for the selected processing components. Future work will extend the evaluation to other influence parameters and may include the human operator for mission planning and sensor control.

Comparison of methods for accurate end-point detection of potentiometric titrations

NASA Astrophysics Data System (ADS)

Villela, R. L. A.; Borges, P. P.; Vyskočil, L.

2015-01-01

Detection of the end point in potentiometric titrations has wide application on experiments that demand very low measurement uncertainties mainly for certifying reference materials. Simulations of experimental coulometric titration data and consequential error analysis of the end-point values were conducted using a programming code. These simulations revealed that the Levenberg-Marquardt method is in general more accurate than the traditional second derivative technique used currently as end-point detection for potentiometric titrations. Performance of the methods will be compared and presented in this paper.

Strand Displacement Amplification Reaction on Quantum Dot-Encoded Silica Bead for Visual Detection of Multiplex MicroRNAs.

PubMed

Qu, Xiaojun; Jin, Haojun; Liu, Yuqian; Sun, Qingjiang

2018-03-06

The combination of microbead array, isothermal amplification, and molecular signaling enables the continuous development of next-generation molecular diagnostic techniques. Herein we reported the implementation of nicking endonuclease-assisted strand displacement amplification reaction on quantum dots-encoded microbead (Qbead), and demonstrated its feasibility for multiplexed miRNA assay in real sample. The Qbead featured with well-defined core-shell superstructure with dual-colored quantum dots loaded in silica core and shell, respectively, exhibiting remarkably high optical encoding stability. Specially designed stem-loop-structured probes were immobilized onto the Qbead for specific target recognition and amplification. In the presence of low abundance of miRNA target, the target triggered exponential amplification, producing a large quantity of stem-G-quadruplexes, which could be selectively signaled by a fluorescent G-quadruplex intercalator. In one-step operation, the Qbead-based isothermal amplification and signaling generated emissive "core-shell-satellite" superstructure, changing the Qbead emission-color. The target abundance-dependent emission-color changes of the Qbead allowed direct, visual detection of specific miRNA target. This visualization method achieved limit of detection at the subfemtomolar level with a linear dynamic range of 4.5 logs, and point-mutation discrimination capability for precise miRNA analyses. The array of three encoded Qbeads could simultaneously quantify three miRNA biomarkers in ∼500 human hepatoma carcinoma cells. With the advancements in ease of operation, multiplexing, and visualization capabilities, the isothermal amplification-on-Qbead assay could potentially enable the development of point-of-care diagnostics.