Feature extraction and identification in distributed optical-fiber vibration sensing system for oil pipeline safety monitoring

NASA Astrophysics Data System (ADS)

Wu, Huijuan; Qian, Ya; Zhang, Wei; Tang, Chenghao

2017-12-01

High sensitivity of a distributed optical-fiber vibration sensing (DOVS) system based on the phase-sensitivity optical time domain reflectometry (Φ-OTDR) technology also brings in high nuisance alarm rates (NARs) in real applications. In this paper, feature extraction methods of wavelet decomposition (WD) and wavelet packet decomposition (WPD) are comparatively studied for three typical field testing signals, and an artificial neural network (ANN) is built for the event identification. The comparison results prove that the WPD performs a little better than the WD for the DOVS signal analysis and identification in oil pipeline safety monitoring. The identification rate can be improved up to 94.4%, and the nuisance alarm rate can be effectively controlled as low as 5.6% for the identification network with the wavelet packet energy distribution features.

Fiber-Optic Refractometer Based on an Etched High-Q π-Phase-Shifted Fiber-Bragg-Grating

PubMed Central

Zhang, Qi; Ianno, Natale J.; Han, Ming

2013-01-01

We present a compact and highly-sensitive fiber-optic refractometer based on a high-Q π-phase-shifted fiber-Bragg-grating (πFBG) that is chemically etched to the core of the fiber. Due to the π phase-shift, a strong πFBG forms a high-Q optical resonator and the reflection spectrum features an extremely narrow notch that can be used for highly sensitivity refractive index measurement. The etched πFBG demonstrated here has a diameter of ∼9.3 μm and a length of only 7 mm, leading to a refractive index responsivity of 2.9 nm/RIU (RIU: refractive index unit) at an ambient refractive index of 1.318. The reflection spectrum of the etched πFBG features an extremely narrow notch with a linewidth of only 2.1 pm in water centered at ∼1,550 nm, corresponding to a Q-factor of 7.4 × 105, which allows for potentially significantly improved sensitivity over refractometers based on regular fiber Bragg gratings. PMID:23845932

HIGHLY SENSITIVE ASSAY FOR ANTICHOLINESTERASE COMPOUNDS USING 96 WELL PLATE FORMAT

EPA Science Inventory

The rapid and sensitive detection of organophosphate insecticides using a 96 well plate format is reported. Several features of this assay make it attractive for development as a laboratory-based or field screening assay. Acetylcholinesterase (AChE) was stabilized in a gelati...

High-Sensitivity Ionization Trace-Species Detector

NASA Technical Reports Server (NTRS)

Bernius, Mark T.; Chutjian, Ara

1990-01-01

Features include high ion-extraction efficiency, compactness, and light weight. Improved version of previous ionization detector features in-line geometry that enables extraction of almost every ion from region of formation. Focusing electrodes arranged and shaped into compact system of space-charge-limited reversal electron optics and ion-extraction optics. Provides controllability of ionizing electron energies, greater efficiency of ionization, and nearly 100 percent ion-collection efficiency.

Hyperpolarized 15N-pyridine Derivatives as pH-Sensitive MRI Agents

PubMed Central

Jiang, Weina; Lumata, Lloyd; Chen, Wei; Zhang, Shanrong; Kovacs, Zoltan; Sherry, A. Dean; Khemtong, Chalermchai

2015-01-01

Highly sensitive MR imaging agents that can accurately and rapidly monitor changes in pH would have diagnostic and prognostic value for many diseases. Here, we report an investigation of hyperpolarized 15N-pyridine derivatives as ultrasensitive pH-sensitive imaging probes. These molecules are easily polarized to high levels using standard dynamic nuclear polarization (DNP) techniques and their 15N chemical shifts were found to be highly sensitive to pH. These probes displayed sharp 15N resonances and large differences in chemical shifts (Δδ >90 ppm) between their free base and protonated forms. These favorable features make these agents highly suitable candidates for the detection of small changes in tissue pH near physiological values. PMID:25774436

High-sensitivity temperature sensor based on highly-birefringent microfiber

NASA Astrophysics Data System (ADS)

Sun, Li-Peng; Li, Jie; Jin, Long; Gao, Shuai; Tian, Zhuang; Ran, Yang; Guan, Bai-Ou

2013-09-01

We demonstrate an ultrasensitive temperature sensor by sealing a highly-birefringent microfiber into an alcoholinfiltrated copper capillary. With a Sagnac loop configuration, the interferometric spectrum is strongly dependent on the external refractive index (RI) with sensitivity of 36800nm/RIU around RI=1.356. As mainly derived from the ultrahigh RI sensitivity, the temperature response can reach as high as -14.72 nm/°C in the range of 30.9-36.9 °C. The measured response time is ~8s, as determined by the heat-conducting characteristic of the device and the diameter of the copper capillary. Our sensor is featured with low cost, easy fabrication and robustness.

Rough sets and Laplacian score based cost-sensitive feature selection

PubMed Central

Yu, Shenglong

2018-01-01

Cost-sensitive feature selection learning is an important preprocessing step in machine learning and data mining. Recently, most existing cost-sensitive feature selection algorithms are heuristic algorithms, which evaluate the importance of each feature individually and select features one by one. Obviously, these algorithms do not consider the relationship among features. In this paper, we propose a new algorithm for minimal cost feature selection called the rough sets and Laplacian score based cost-sensitive feature selection. The importance of each feature is evaluated by both rough sets and Laplacian score. Compared with heuristic algorithms, the proposed algorithm takes into consideration the relationship among features with locality preservation of Laplacian score. We select a feature subset with maximal feature importance and minimal cost when cost is undertaken in parallel, where the cost is given by three different distributions to simulate different applications. Different from existing cost-sensitive feature selection algorithms, our algorithm simultaneously selects out a predetermined number of “good” features. Extensive experimental results show that the approach is efficient and able to effectively obtain the minimum cost subset. In addition, the results of our method are more promising than the results of other cost-sensitive feature selection algorithms. PMID:29912884

Rough sets and Laplacian score based cost-sensitive feature selection.

PubMed

Yu, Shenglong; Zhao, Hong

2018-01-01

Cost-sensitive feature selection learning is an important preprocessing step in machine learning and data mining. Recently, most existing cost-sensitive feature selection algorithms are heuristic algorithms, which evaluate the importance of each feature individually and select features one by one. Obviously, these algorithms do not consider the relationship among features. In this paper, we propose a new algorithm for minimal cost feature selection called the rough sets and Laplacian score based cost-sensitive feature selection. The importance of each feature is evaluated by both rough sets and Laplacian score. Compared with heuristic algorithms, the proposed algorithm takes into consideration the relationship among features with locality preservation of Laplacian score. We select a feature subset with maximal feature importance and minimal cost when cost is undertaken in parallel, where the cost is given by three different distributions to simulate different applications. Different from existing cost-sensitive feature selection algorithms, our algorithm simultaneously selects out a predetermined number of "good" features. Extensive experimental results show that the approach is efficient and able to effectively obtain the minimum cost subset. In addition, the results of our method are more promising than the results of other cost-sensitive feature selection algorithms.

[Clinical features of Enterococcus faecium meningitis in children].

PubMed

Wang, Li-Yuan; Cai, Xiao-Tang; Wang, Zhi-Ling; Liu, Shun-Li; Xie, Yong-Mei; Zhou, Hui

2018-03-01

To summarize the clinical features of Enterococcus faecium meningitis in children. The clinical data of nine children with Enterococcus faecium meningitis were analyzed. In all the nine children, Enterococcus faecium was isolated from blood, cerebrospinal fluid, or peripherally inserted central catheters; 6 (67%) patients were neonates, 2 (22%) patients were younger than 6 months, and 1 (11%) patient was three years and four months of age. In those patients, 56% had high-risk factors before onset, which included intestinal infection, resettlement of drainage tube after surgery for hydrocephalus, skull fracture, perinatal maternal infection history, and catheter-related infection. The main symptoms were fever and poor response. In those patients, 22% had seizures; no child had meningeal irritation sign or disturbance of consciousness. The white blood cell count and level of C-reactive protein were normal or increased; the nucleated cell count in cerebrospinal fluid was normal or mildly elevated; the protein level was substantially elevated; the glucose level was decreased. The drug sensitivity test showed that bacteria were all sensitive to vancomycin and the vancomycin treatment was effective. Only one child had the complication of hydrocephalus. Enterococcus faecium meningitis occurs mainly in neonates and infants. The patients have atypical clinical features. A high proportion of patients with Enterococcus faecium meningitis have high-risk factors. Enterococcus faecium is sensitive to vancomycin.

Textural kinetics: a novel dynamic contrast-enhanced (DCE)-MRI feature for breast lesion classification.

PubMed

Agner, Shannon C; Soman, Salil; Libfeld, Edward; McDonald, Margie; Thomas, Kathleen; Englander, Sarah; Rosen, Mark A; Chin, Deanna; Nosher, John; Madabhushi, Anant

2011-06-01

Dynamic contrast-enhanced (DCE)-magnetic resonance imaging (MRI) of the breast has emerged as an adjunct imaging tool to conventional X-ray mammography due to its high detection sensitivity. Despite the increasing use of breast DCE-MRI, specificity in distinguishing malignant from benign breast lesions is low, and interobserver variability in lesion classification is high. The novel contribution of this paper is in the definition of a new DCE-MRI descriptor that we call textural kinetics, which attempts to capture spatiotemporal changes in breast lesion texture in order to distinguish malignant from benign lesions. We qualitatively and quantitatively demonstrated on 41 breast DCE-MRI studies that textural kinetic features outperform signal intensity kinetics and lesion morphology features in distinguishing benign from malignant lesions. A probabilistic boosting tree (PBT) classifier in conjunction with textural kinetic descriptors yielded an accuracy of 90%, sensitivity of 95%, specificity of 82%, and an area under the curve (AUC) of 0.92. Graph embedding, used for qualitative visualization of a low-dimensional representation of the data, showed the best separation between benign and malignant lesions when using textural kinetic features. The PBT classifier results and trends were also corroborated via a support vector machine classifier which showed that textural kinetic features outperformed the morphological, static texture, and signal intensity kinetics descriptors. When textural kinetic attributes were combined with morphologic descriptors, the resulting PBT classifier yielded 89% accuracy, 99% sensitivity, 76% specificity, and an AUC of 0.91.

Multi-test cervical cancer diagnosis with missing data estimation

NASA Astrophysics Data System (ADS)

Xu, Tao; Huang, Xiaolei; Kim, Edward; Long, L. Rodney; Antani, Sameer

2015-03-01

Cervical cancer is a leading most common type of cancer for women worldwide. Existing screening programs for cervical cancer suffer from low sensitivity. Using images of the cervix (cervigrams) as an aid in detecting pre-cancerous changes to the cervix has good potential to improve sensitivity and help reduce the number of cervical cancer cases. In this paper, we present a method that utilizes multi-modality information extracted from multiple tests of a patient's visit to classify the patient visit to be either low-risk or high-risk. Our algorithm integrates image features and text features to make a diagnosis. We also present two strategies to estimate the missing values in text features: Image Classifier Supervised Mean Imputation (ICSMI) and Image Classifier Supervised Linear Interpolation (ICSLI). We evaluate our method on a large medical dataset and compare it with several alternative approaches. The results show that the proposed method with ICSLI strategy achieves the best result of 83.03% specificity and 76.36% sensitivity. When higher specificity is desired, our method can achieve 90% specificity with 62.12% sensitivity.

Testing for new physics: neutrinos and the primordial power spectrum

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

Canac, Nicolas; Abazajian, Kevork N.; Aslanyan, Grigor

2016-09-01

We test the sensitivity of neutrino parameter constraints from combinations of CMB and LSS data sets to the assumed form of the primordial power spectrum (PPS) using Bayesian model selection. Significantly, none of the tested combinations, including recent high-precision local measurements of H{sub 0} and cluster abundances, indicate a signal for massive neutrinos or extra relativistic degrees of freedom. For PPS models with a large, but fixed number of degrees of freedom, neutrino parameter constraints do not change significantly if the location of any features in the PPS are allowed to vary, although neutrino constraints are more sensitive to PPSmore » features if they are known a priori to exist at fixed intervals in log k . Although there is no support for a non-standard neutrino sector from constraints on both neutrino mass and relativistic energy density, we see surprisingly strong evidence for features in the PPS when it is constrained with data from Planck 2015, SZ cluster counts, and recent high-precision local measurements of H{sub 0}. Conversely combining Planck with matter power spectrum and BAO measurements yields a much weaker constraint. Given that this result is sensitive to the choice of data this tension between SZ cluster counts, Planck and H{sub 0} measurements is likely an indication of unmodeled systematic bias that mimics PPS features, rather than new physics in the PPS or neutrino sector.« less

A multilevel-ROI-features-based machine learning method for detection of morphometric biomarkers in Parkinson's disease.

PubMed

Peng, Bo; Wang, Suhong; Zhou, Zhiyong; Liu, Yan; Tong, Baotong; Zhang, Tao; Dai, Yakang

2017-06-09

Machine learning methods have been widely used in recent years for detection of neuroimaging biomarkers in regions of interest (ROIs) and assisting diagnosis of neurodegenerative diseases. The innovation of this study is to use multilevel-ROI-features-based machine learning method to detect sensitive morphometric biomarkers in Parkinson's disease (PD). Specifically, the low-level ROI features (gray matter volume, cortical thickness, etc.) and high-level correlative features (connectivity between ROIs) are integrated to construct the multilevel ROI features. Filter- and wrapper- based feature selection method and multi-kernel support vector machine (SVM) are used in the classification algorithm. T1-weighted brain magnetic resonance (MR) images of 69 PD patients and 103 normal controls from the Parkinson's Progression Markers Initiative (PPMI) dataset are included in the study. The machine learning method performs well in classification between PD patients and normal controls with an accuracy of 85.78%, a specificity of 87.79%, and a sensitivity of 87.64%. The most sensitive biomarkers between PD patients and normal controls are mainly distributed in frontal lobe, parental lobe, limbic lobe, temporal lobe, and central region. The classification performance of our method with multilevel ROI features is significantly improved comparing with other classification methods using single-level features. The proposed method shows promising identification ability for detecting morphometric biomarkers in PD, thus confirming the potentiality of our method in assisting diagnosis of the disease. Copyright © 2017 Elsevier B.V. All rights reserved.

Evaluation and construction of diagnostic criteria for inclusion body myositis

PubMed Central

Mammen, Andrew L.; Amato, Anthony A.; Weiss, Michael D.; Needham, Merrilee

2014-01-01

Objective: To use patient data to evaluate and construct diagnostic criteria for inclusion body myositis (IBM), a progressive disease of skeletal muscle. Methods: The literature was reviewed to identify all previously proposed IBM diagnostic criteria. These criteria were applied through medical records review to 200 patients diagnosed as having IBM and 171 patients diagnosed as having a muscle disease other than IBM by neuromuscular specialists at 2 institutions, and to a validating set of 66 additional patients with IBM from 2 other institutions. Machine learning techniques were used for unbiased construction of diagnostic criteria. Results: Twenty-four previously proposed IBM diagnostic categories were identified. Twelve categories all performed with high (≥97%) specificity but varied substantially in their sensitivities (11%–84%). The best performing category was European Neuromuscular Centre 2013 probable (sensitivity of 84%). Specialized pathologic features and newly introduced strength criteria (comparative knee extension/hip flexion strength) performed poorly. Unbiased data-directed analysis of 20 features in 371 patients resulted in construction of higher-performing data-derived diagnostic criteria (90% sensitivity and 96% specificity). Conclusions: Published expert consensus–derived IBM diagnostic categories have uniformly high specificity but wide-ranging sensitivities. High-performing IBM diagnostic category criteria can be developed directly from principled unbiased analysis of patient data. Classification of evidence: This study provides Class II evidence that published expert consensus–derived IBM diagnostic categories accurately distinguish IBM from other muscle disease with high specificity but wide-ranging sensitivities. PMID:24975859

A hybrid cost-sensitive ensemble for imbalanced breast thermogram classification.

PubMed

Krawczyk, Bartosz; Schaefer, Gerald; Woźniak, Michał

2015-11-01

Early recognition of breast cancer, the most commonly diagnosed form of cancer in women, is of crucial importance, given that it leads to significantly improved chances of survival. Medical thermography, which uses an infrared camera for thermal imaging, has been demonstrated as a particularly useful technique for early diagnosis, because it detects smaller tumors than the standard modality of mammography. In this paper, we analyse breast thermograms by extracting features describing bilateral symmetries between the two breast areas, and present a classification system for decision making. Clearly, the costs associated with missing a cancer case are much higher than those for mislabelling a benign case. At the same time, datasets contain significantly fewer malignant cases than benign ones. Standard classification approaches fail to consider either of these aspects. In this paper, we introduce a hybrid cost-sensitive classifier ensemble to address this challenging problem. Our approach entails a pool of cost-sensitive decision trees which assign a higher misclassification cost to the malignant class, thereby boosting its recognition rate. A genetic algorithm is employed for simultaneous feature selection and classifier fusion. As an optimisation criterion, we use a combination of misclassification cost and diversity to achieve both a high sensitivity and a heterogeneous ensemble. Furthermore, we prune our ensemble by discarding classifiers that contribute minimally to the decision making. For a challenging dataset of about 150 thermograms, our approach achieves an excellent sensitivity of 83.10%, while maintaining a high specificity of 89.44%. This not only signifies improved recognition of malignant cases, it also statistically outperforms other state-of-the-art algorithms designed for imbalanced classification, and hence provides an effective approach for analysing breast thermograms. Our proposed hybrid cost-sensitive ensemble can facilitate a highly accurate early diagnostic of breast cancer based on thermogram features. It overcomes the difficulties posed by the imbalanced distribution of patients in the two analysed groups. Copyright © 2015 Elsevier B.V. All rights reserved.

Sensitivity and specificity of ultrasonographic features of gout in intercritical and chronic phase.

PubMed

Das, Shyamashis; Ghosh, Alakendu; Ghosh, Parasar; Lahiri, Debasish; Sinhamahapatra, Pradyot; Basu, Kaushik

2017-07-01

This study aimed to assess the sensitivity and specificity of ultrasonographic features of gout in intercritical and chronic stages and compared ultrasonographic features of gout between patients with persistent high serum uric acid (SUA) and patients with low SUA. Adult patients with gout confirmed by demonstration of monosodium urate crystals were recruited, if they were in intercritical or chronic stage clinically. Ultrasonographic examination of the first metatarsophalangeal joints (MTPJs) and the knee joints of both sides were done by a blinded rheumatologist trained in musculoskeletal ultrasound. Sixty-two patients with gout and 30 control subjects were examined. The double contour sign (DCS) was found in 71 (57.3%) first MTPJs and tophi were found in 54 (43.5%) first MTPJs. DCS was present in 43 (69.4%) gout patients but none in the control group (P < 0.001). Sensitivity and specificity (95% CI) of DCS in gout patients were 69.4% (56.4-80.4%) and 100% (88.3-100%), respectively, while of tophi they were 66.1% (53-77.7%) and 100% (88.3-100%), respectively. The sensitivity of DCS increased to 100% in high the SUA subgroup (SUA ≥ 7 mg/dL). The low SUA (SUA < 7 mg/dL) gout subgroup showed significantly higher occurrence of erosions (40%) and tophi (50%) in first MTP joints than the control group. MSUS is useful for diagnosis of gout in intercritical or chronic stages, especially in patients with persistently high SUA level. © 2016 Asia Pacific League of Associations for Rheumatology and John Wiley & Sons Australia, Ltd.

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

Harmon, S; Jeraj, R; Galavis, P

Purpose: Sensitivity of PET-derived texture features to reconstruction methods has been reported for features extracted from axial planes; however, studies often utilize three dimensional techniques. This work aims to quantify the impact of multi-plane (3D) vs. single-plane (2D) feature extraction on radiomics-based analysis, including sensitivity to reconstruction parameters and potential loss of spatial information. Methods: Twenty-three patients with solid tumors underwent [{sup 18}F]FDG PET/CT scans under identical protocols. PET data were reconstructed using five sets of reconstruction parameters. Tumors were segmented using an automatic, in-house algorithm robust to reconstruction variations. 50 texture features were extracted using two Methods: 2D patchesmore » along axial planes and 3D patches. For each method, sensitivity of features to reconstruction parameters was calculated as percent difference relative to the average value across reconstructions. Correlations between feature values were compared when using 2D and 3D extraction. Results: 21/50 features showed significantly different sensitivity to reconstruction parameters when extracted in 2D vs 3D (wilcoxon α<0.05), assessed by overall range of variation, Rangevar(%). Eleven showed greater sensitivity to reconstruction in 2D extraction, primarily first-order and co-occurrence features (average Rangevar increase 83%). The remaining ten showed higher variation in 3D extraction (average Range{sub var}increase 27%), mainly co-occurence and greylevel run-length features. Correlation of feature value extracted in 2D and feature value extracted in 3D was poor (R<0.5) in 12/50 features, including eight co-occurrence features. Feature-to-feature correlations in 2D were marginally higher than 3D, ∣R∣>0.8 in 16% and 13% of all feature combinations, respectively. Larger sensitivity to reconstruction parameters were seen for inter-feature correlation in 2D(σ=6%) than 3D (σ<1%) extraction. Conclusion: Sensitivity and correlation of various texture features were shown to significantly differ between 2D and 3D extraction. Additionally, inter-feature correlations were more sensitive to reconstruction variation using single-plane extraction. This work highlights a need for standardized feature extraction/selection techniques in radiomics.« less

High-efficiency K-band tracking antenna feed

NASA Technical Reports Server (NTRS)

Beavin, R. L.; Simanyi, A. I.

1975-01-01

Antenna feed features high aperture efficiency of multimode near-field horn and develops tracking signals without conventional monopulse bridge. Feed assembly is relatively simple and very compact. However, feed is sensitive to cross-polarized energy which couples into orthogonal error channel.

Multiplexed Simultaneous High Sensitivity Sensors with High-Order Mode Based on the Integration of Photonic Crystal 1 × 3 Beam Splitter and Three Different Single-Slot PCNCs.

PubMed

Zhou, Jian; Huang, Lijun; Fu, Zhongyuan; Sun, Fujun; Tian, Huiping

2016-07-07

We simulated an efficient method for the sensor array of high-sensitivity single-slot photonic crystal nanobeam cavities (PCNCs) on a silicon platform. With the combination of a well-designed photonic crystal waveguide (PhCW) filter and an elaborate single-slot PCNC, a specific high-order resonant mode was filtered for sensing. A 1 × 3 beam splitter carefully established was implemented to split channels and integrate three sensors to realize microarrays. By applying the three-dimensional finite-difference-time-domain (3D-FDTD) method, the sensitivities calculated were S₁ = 492 nm/RIU, S₂ = 244 nm/RIU, and S₃ = 552 nm/RIU, respectively. To the best of our knowledge, this is the first multiplexing design in which each sensor cite features such a high sensitivity simultaneously.

Multiplexed Simultaneous High Sensitivity Sensors with High-Order Mode Based on the Integration of Photonic Crystal 1 × 3 Beam Splitter and Three Different Single-Slot PCNCs

PubMed Central

Zhou, Jian; Huang, Lijun; Fu, Zhongyuan; Sun, Fujun; Tian, Huiping

2016-01-01

We simulated an efficient method for the sensor array of high-sensitivity single-slot photonic crystal nanobeam cavities (PCNCs) on a silicon platform. With the combination of a well-designed photonic crystal waveguide (PhCW) filter and an elaborate single-slot PCNC, a specific high-order resonant mode was filtered for sensing. A 1 × 3 beam splitter carefully established was implemented to split channels and integrate three sensors to realize microarrays. By applying the three-dimensional finite-difference-time-domain (3D-FDTD) method, the sensitivities calculated were S1 = 492 nm/RIU, S2 = 244 nm/RIU, and S3 = 552 nm/RIU, respectively. To the best of our knowledge, this is the first multiplexing design in which each sensor cite features such a high sensitivity simultaneously. PMID:27399712

Self-Assembled ZnO Nanosheet-Based Spherical Structure as Photoanode in Dye-Sensitized Solar Cells

NASA Astrophysics Data System (ADS)

Ameri, Mohsen; Raoufi, Meysam; Zamani-Meymian, M.-R.; Samavat, Feridoun; Fathollahi, M.-R.; Mohajerani, Ezeddin

2018-03-01

High surface area and enhanced light scattering of ZnO nanosheet aggregates have made them a promising active layer candidate material for fabrication of nanostructure dye-sensitized solar cells. Here, we propose a facile preparation method of such ZnO nanosheet structures, and in order to verify their applicability as photoanode material for dye-sensitized solar cells, we employ morphological, optical, structural and electrical measurements. The results reveal the high surface area available for dye molecules for enhancing adsorption, high light scattering and competitive power conversion efficiencies compared to the works in literature. Finally, the device is optimized with respect to the photoanode thickness. The favorable features shown here can extend the application of the structure to other types of sensitization-based perovskite and quantum dot solar cells.

A Small Mission Featuring an Imaging X-ray Polarimeter with High Sensitivity

NASA Technical Reports Server (NTRS)

Weisskopf, Martin C.; Baldini, Luca; Bellazini, Ronaldo; Brez, Alessandro; Costa, Enrico; Dissley, Richard; Elsner, Ronald; Fabiani, Sergio; Matt, Giorgio; Minuti, Massimo;

A highly sensitive and flexible pressure sensor with electrodes and elastomeric interlayer containing silver nanowires.

PubMed

Wang, Jun; Jiu, Jinting; Nogi, Masaya; Sugahara, Tohru; Nagao, Shijo; Koga, Hirotaka; He, Peng; Suganuma, Katsuaki

2015-02-21

The next-generation application of pressure sensors is gradually being extended to include electronic artificial skin (e-skin), wearable devices, humanoid robotics and smart prosthetics. In these advanced applications, high sensing capability is an essential feature for high performance. Although surface patterning treatments and some special elastomeric interlayers have been applied to improve sensitivity, the process is complex and this inevitably raises the cost and is an obstacle to large-scale production. In the present study a simple printing process without complex patterning has been used for constructing the sensor, and an interlayer is employed comprising elastomeric composites filled with silver nanowires. By increasing the relative permittivity, εr, of the composite interlayer induced by compression at high nanowire concentration, it has been possible to achieve a maximum sensitivity of 5.54 kPa(-1). The improvement in sensitivity did not sacrifice or undermine the other features of the sensor. Thanks to the silver nanowire electrodes, the sensor is flexible and stable after 200 cycles at a bending radius of 2 mm, and exhibits outstanding reproducibility without hysteresis under similar pressure pulses. The sensor has been readily integrated onto an adhesive bandage and has been successful in detecting human movements. In addition to measuring pressure in direct contact, non-contact pressures such as air flow can also be detected.

Ion mobility mass spectrometry of proteins in a modified commercial mass spectrometer

NASA Astrophysics Data System (ADS)

Thalassinos, K.; Slade, S. E.; Jennings, K. R.; Scrivens, J. H.; Giles, K.; Wildgoose, J.; Hoyes, J.; Bateman, R. H.; Bowers, M. T.

2004-08-01

Ion mobility has emerged as an important technique for determining biopolymer conformations in solvent free environments. These experiments have been nearly exclusively performed on home built systems. In this paper we describe modifications to a commercial high performance mass spectrometer, the Waters UK "Ultima" Q-Tof, that allows high sensitivity measurement of peptide and protein cross sections. Arrival time distributions are obtained for a series of peptides (bradykinin, LHRH, substance P, bombesin) and proteins (bovine and equine cytochrome c, myoglobin, [alpha]-lactalbumin) with good agreement found with literature cross sections where available. In complex ATD's, mass spectra can be obtained for each feature confirming assignments. The increased sensitivity of the commercial instrument is retained along with the convenience of the data system, crucial features for analysis of protein misfolding systems.

[Sensitivity and specificity of optical coherence tomography in diagnosing polypoidal choroidal vasculopathy].

PubMed

Zhang, Yi; Yao, Jing; Wang, Xiao-Hua; Zhao, Lin; Wang, Li-Jun; Wang, Jian-Ming; Zhou, Ai-Yi

2016-02-20

To establish the diagnostic criteria for polypoidal choroidal vasculopathy (PCV) based on spectral-domain optical coherence tomography (SD OCT) by evaluating the sensitivity and specificity of SD OCT in differentiating PCV from wet age-related macular degeneration (wAMD). The clinical data were reviewed for 62 patients (63 eyes) with the initial diagnosis of PCV or wAMD between August, 2012 and June, 2016. Twenty-four patients (25 eyes) were diagnosed to have PCV and 38 (38 eyes) had wAMD based on findings by fundus photography, fluorescein angiography (FFA) and indocyanine green angiography (ICGA). Among the 6 features of SD OCT, namely a sharp RPED peak, double-layer sign, multiple RPED, an RPED notch, a hyporeflective lumen representing polyps, and hyperreflective intraretinal hard exudates, findings of the first two features and at least one of the other features sufficed the diagnosis of PCV; in the absence of the first two features, the diagnosis of PCV was also made when at least 3 of the other features were present simultaneously. The sensitivity and specificity of SD OCT-based diagnosis were estimated by comparison with the gold standard ICGA-based diagnosis. In the 25 eyes with an established diagnosis of PCV, 23 eyes (92.0%) met the diagnostic criteria based on SD OCT findings; in the 38 eyes with the diagnosis of wAMD, only 4 eyes (10.5%) met the criteria. The sensitivity and specificity of SD OCT-based diagnosis of PCV was 92.0% and 89.5%, respectively. s We established the diagnostic criteria for PCV based on SD OCT findings with a high sensitivity and specificity. SD OCT shows a strong capacity for differentiating PCV from wAMD.

Automated detection of diabetic retinopathy on digital fundus images.

PubMed

Sinthanayothin, C; Boyce, J F; Williamson, T H; Cook, H L; Mensah, E; Lal, S; Usher, D

2002-02-01

The aim was to develop an automated screening system to analyse digital colour retinal images for important features of non-proliferative diabetic retinopathy (NPDR). High performance pre-processing of the colour images was performed. Previously described automated image analysis systems were used to detect major landmarks of the retinal image (optic disc, blood vessels and fovea). Recursive region growing segmentation algorithms combined with the use of a new technique, termed a 'Moat Operator', were used to automatically detect features of NPDR. These features included haemorrhages and microaneurysms (HMA), which were treated as one group, and hard exudates as another group. Sensitivity and specificity data were calculated by comparison with an experienced fundoscopist. The algorithm for exudate recognition was applied to 30 retinal images of which 21 contained exudates and nine were without pathology. The sensitivity and specificity for exudate detection were 88.5% and 99.7%, respectively, when compared with the ophthalmologist. HMA were present in 14 retinal images. The algorithm achieved a sensitivity of 77.5% and specificity of 88.7% for detection of HMA. Fully automated computer algorithms were able to detect hard exudates and HMA. This paper presents encouraging results in automatic identification of important features of NPDR.

Partial dependence of breast tumor malignancy on ultrasound image features derived from boosted trees

NASA Astrophysics Data System (ADS)

Yang, Wei; Zhang, Su; Li, Wenying; Chen, Yaqing; Lu, Hongtao; Chen, Wufan; Chen, Yazhu

2010-04-01

Various computerized features extracted from breast ultrasound images are useful in assessing the malignancy of breast tumors. However, the underlying relationship between the computerized features and tumor malignancy may not be linear in nature. We use the decision tree ensemble trained by the cost-sensitive boosting algorithm to approximate the target function for malignancy assessment and to reflect this relationship qualitatively. Partial dependence plots are employed to explore and visualize the effect of features on the output of the decision tree ensemble. In the experiments, 31 image features are extracted to quantify the sonographic characteristics of breast tumors. Patient age is used as an external feature because of its high clinical importance. The area under the receiver-operating characteristic curve of the tree ensembles can reach 0.95 with sensitivity of 0.95 (61/64) at the associated specificity 0.74 (77/104). The partial dependence plots of the four most important features are demonstrated to show the influence of the features on malignancy, and they are in accord with the empirical observations. The results can provide visual and qualitative references on the computerized image features for physicians, and can be useful for enhancing the interpretability of computer-aided diagnosis systems for breast ultrasound.

Encoding properties of haltere neurons enable motion feature detection in a biological gyroscope

PubMed Central

Fox, Jessica L.; Fairhall, Adrienne L.; Daniel, Thomas L.

2010-01-01

The halteres of dipteran insects are essential sensory organs for flight control. They are believed to detect Coriolis and other inertial forces associated with body rotation during flight. Flies use this information for rapid flight control. We show that the primary afferent neurons of the haltere’s mechanoreceptors respond selectively with high temporal precision to multiple stimulus features. Although we are able to identify many stimulus features contributing to the response using principal component analysis, predictive models using only two features, common across the cell population, capture most of the cells’ encoding activity. However, different sensitivity to these two features permits each cell to respond to sinusoidal stimuli with a different preferred phase. This feature similarity, combined with diverse phase encoding, allows the haltere to transmit information at a high rate about numerous inertial forces, including Coriolis forces. PMID:20133721

Improved scintimammography using a high-resolution camera mounted on an upright mammography gantry

NASA Astrophysics Data System (ADS)

Itti, Emmanuel; Patt, Bradley E.; Diggles, Linda E.; MacDonald, Lawrence; Iwanczyk, Jan S.; Mishkin, Fred S.; Khalkhali, Iraj

2003-01-01

99mTc-sestamibi scintimammography (SMM) is a useful adjunct to conventional X-ray mammography (XMM) for the assessment of breast cancer. An increasing number of studies has emphasized fair sensitivity values for the detection of tumors >1 cm, compared to XMM, particularly in situations where high glandular breast densities make mammographic interpretation difficult. In addition, SMM has demonstrated high specificity for cancer, compared to various functional and anatomic imaging modalities. However, large field-of-view (FOV) gamma cameras are difficult to position close to the breasts, which decreases spatial resolution and subsequently, the sensitivity of detection for tumors <1 cm. New dedicated detectors featuring small FOV and increased spatial resolution have recently been developed. In this setting, improvement in tumor detection sensitivity, particularly with regard to small cancers is expected. At Division of Nuclear Medicine, Harbor-UCLA Medical Center, we have performed over 2000 SMM within the last 9 years. We have recently used a dedicated breast camera (LumaGEM™) featuring a 12.8×12.8 cm 2 FOV and an array of 2×2×6 mm 3 discrete crystals coupled to a photon-sensitive photomultiplier tube readout. This camera is mounted on a mammography gantry allowing upright imaging, medial positioning and use of breast compression. Preliminary data indicates significant enhancement of spatial resolution by comparison with standard imaging in the first 10 patients. Larger series will be needed to conclude on sensitivity/specificity issues.

Effects of Presurgical Treatment for Prostate Cancer

Cancer.gov

In this study, men diagnosed with androgen-sensitive prostate cancer with intermediate- or high-risk features will be examined with mpMRI, undergo targeted biopsies, and be treated with neoadjuvant androgen deprivation therapy.

Preparation and thermoluminescent dosimetry features of high sensitivity LiF:Mg,Ce phosphor

NASA Astrophysics Data System (ADS)

Shoushtari, M. K.; Zahedifar, M.; Sadeghi, E.

2018-04-01

Thermoluminescence (TL) kinetics and dosimetry features of newly produced LiF doped with Mg and Ce were investigated. Different contents of Mg (0-1 mol%) and Ce (0-2 mol%) were introduced in host material by melting method. The most TL sensitivity of the fabricated phosphor was obtained at 0.7 and 0.05 mol% concentrations of Mg and Ce impurities, respectively. The optimum pre-irradiation annealing regime of the synthesized LiF-based material was found at 350 °C for 10 min. Kinetic parameters of LiF:Mg,Ce dosimeter were obtained using different methods of computerized glow curve deconvolution (CGCD), initial rise (IR) and isothermal decay (ID). A good conformity are observed between the results obtained from different kinetic analysis methods. Other TL features such as fading, dose response and reusability were also examined.

Quantification of confocal fluorescence microscopy for the detection of cervical intraepithelial neoplasia.

PubMed

Sheikhzadeh, Fahime; Ward, Rabab K; Carraro, Anita; Chen, Zhao Yang; van Niekerk, Dirk; Miller, Dianne; Ehlen, Tom; MacAulay, Calum E; Follen, Michele; Lane, Pierre M; Guillaud, Martial

2015-10-24

Cervical cancer remains a major health problem, especially in developing countries. Colposcopic examination is used to detect high-grade lesions in patients with a history of abnormal pap smears. New technologies are needed to improve the sensitivity and specificity of this technique. We propose to test the potential of fluorescence confocal microscopy to identify high-grade lesions. We examined the quantification of ex vivo confocal fluorescence microscopy to differentiate among normal cervical tissue, low-grade Cervical Intraepithelial Neoplasia (CIN), and high-grade CIN. We sought to (1) quantify nuclear morphology and tissue architecture features by analyzing images of cervical biopsies; and (2) determine the accuracy of high-grade CIN detection via confocal microscopy relative to the accuracy of detection by colposcopic impression. Forty-six biopsies obtained from colposcopically normal and abnormal cervical sites were evaluated. Confocal images were acquired at different depths from the epithelial surface and histological images were analyzed using in-house software. The features calculated from the confocal images compared well with those features obtained from the histological images and histopathological reviews of the specimens (obtained by a gynecologic pathologist). The correlations between two of these features (the nuclear-cytoplasmic ratio and the average of three nearest Delaunay-neighbors distance) and the grade of dysplasia were higher than that of colposcopic impression. The sensitivity of detecting high-grade dysplasia by analysing images collected at the surface of the epithelium, and at 15 and 30 μm below the epithelial surface were respectively 100, 100, and 92 %. Quantitative analysis of confocal fluorescence images showed its capacity for discriminating high-grade CIN lesions vs. low-grade CIN lesions and normal tissues, at different depth of imaging. This approach could be used to help clinicians identify high-grade CIN in clinical settings.

Coupled multiview autoencoders with locality sensitivity for three-dimensional human pose estimation

NASA Astrophysics Data System (ADS)

Yu, Jialin; Sun, Jifeng; Luo, Shasha; Duan, Bichao

2017-09-01

Estimating three-dimensional (3D) human poses from a single camera is usually implemented by searching pose candidates with image descriptors. Existing methods usually suppose that the mapping from feature space to pose space is linear, but in fact, their mapping relationship is highly nonlinear, which heavily degrades the performance of 3D pose estimation. We propose a method to recover 3D pose from a silhouette image. It is based on the multiview feature embedding (MFE) and the locality-sensitive autoencoders (LSAEs). On the one hand, we first depict the manifold regularized sparse low-rank approximation for MFE and then the input image is characterized by a fused feature descriptor. On the other hand, both the fused feature and its corresponding 3D pose are separately encoded by LSAEs. A two-layer back-propagation neural network is trained by parameter fine-tuning and then used to map the encoded 2D features to encoded 3D poses. Our LSAE ensures a good preservation of the local topology of data points. Experimental results demonstrate the effectiveness of our proposed method.

Flexible hemispheric microarrays of highly pressure-sensitive sensors based on breath figure method.

PubMed

Wang, Zhihui; Zhang, Ling; Liu, Jin; Jiang, Hao; Li, Chunzhong

2018-05-30

Recently, flexible pressure sensors featuring high sensitivity, broad sensing range and real-time detection have aroused great attention owing to their crucial role in the development of artificial intelligent devices and healthcare systems. Herein, highly sensitive pressure sensors based on hemisphere-microarray flexible substrates are fabricated via inversely templating honeycomb structures deriving from a facile and static breath figure process. The interlocked and subtle microstructures greatly improve the sensing characteristics and compressibility of the as-prepared pressure sensor, endowing it a sensitivity as high as 196 kPa-1 and a wide pressure sensing range (0-100 kPa), as well as other superior performance, including a lower detection limit of 0.5 Pa, fast response time (<26 ms) and high reversibility (>10 000 cycles). Based on the outstanding sensing performance, the potential capability of our pressure sensor in capturing physiological information and recognizing speech signals has been demonstrated, indicating promising application in wearable and intelligent electronics.

Personality disorders among patients with panic disorder and individuals with high anxiety sensitivity.

PubMed

Osma, Jorge; García-Palacios, Azucena; Botella, Cristina; Barrada, Juan Ramón

2014-05-01

No studies have been found that compared the psychopathology features, including personality disorders, of Panic Disorder (PD) and Panic Disorder with Agoraphobia (PDA), and a nonclinical sample with anxiety vulnerability. The total sample included 152 participants, 52 in the PD/PDA, 45 in the high anxiety sensitivity (AS) sample, and 55 in the nonclinical sample. The participants in PD/PDA sample were evaluated with the structured interview ADIS-IV. The Brief Symptom Inventory and the MCMI-III were used in all three samples. Statistically significant differences were found between the PD/PDA and the nonclinical sample in all MCMI-III scales except for antisocial and compulsive. No significant differences were found between PD/PDA and the sample with high scores in AS. Phobic Anxiety and Paranoid Ideation were the only scales where there were significant differences between the PD/PDA sample and the high AS sample. Our findings showed that people who scored high on AS, despite not having a diagnosis of PD/PDA, were similar in regard to psychopathology features and personality to individuals with PD/PDA.

Breast cancer Ki67 expression preoperative discrimination by DCE-MRI radiomics features

NASA Astrophysics Data System (ADS)

Ma, Wenjuan; Ji, Yu; Qin, Zhuanping; Guo, Xinpeng; Jian, Xiqi; Liu, Peifang

2018-02-01

To investigate whether quantitative radiomics features extracted from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) are associated with Ki67 expression of breast cancer. In this institutional review board approved retrospective study, we collected 377 cases Chinese women who were diagnosed with invasive breast cancer in 2015. This cohort included 53 low-Ki67 expression (Ki67 proliferation index less than 14%) and 324 cases with high-Ki67 expression (Ki67 proliferation index more than 14%). A binary-classification of low- vs. high- Ki67 expression was performed. A set of 52 quantitative radiomics features, including morphological, gray scale statistic, and texture features, were extracted from the segmented lesion area. Three most common machine learning classification methods, including Naive Bayes, k-Nearest Neighbor and support vector machine with Gaussian kernel, were employed for the classification and the least absolute shrink age and selection operator (LASSO) method was used to select most predictive features set for the classifiers. Classification performance was evaluated by the area under receiver operating characteristic curve (AUC), accuracy, sensitivity and specificity. The model that used Naive Bayes classification method achieved the best performance than the other two methods, yielding 0.773 AUC value, 0.757 accuracy, 0.777 sensitivity and 0.769 specificity. Our study showed that quantitative radiomics imaging features of breast tumor extracted from DCE-MRI are associated with breast cancer Ki67 expression. Future larger studies are needed in order to further evaluate the findings.

Deep-UV-sensitive high-frame-rate backside-illuminated CCD camera developments

NASA Astrophysics Data System (ADS)

Dawson, Robin M.; Andreas, Robert; Andrews, James T.; Bhaskaran, Mahalingham; Farkas, Robert; Furst, David; Gershstein, Sergey; Grygon, Mark S.; Levine, Peter A.; Meray, Grazyna M.; O'Neal, Michael; Perna, Steve N.; Proefrock, Donald; Reale, Michael; Soydan, Ramazan; Sudol, Thomas M.; Swain, Pradyumna K.; Tower, John R.; Zanzucchi, Pete

2002-04-01

New applications for ultra-violet imaging are emerging in the fields of drug discovery and industrial inspection. High throughput is critical for these applications where millions of drug combinations are analyzed in secondary screenings or high rate inspection of small feature sizes over large areas is required. Sarnoff demonstrated in1990 a back illuminated, 1024 X 1024, 18 um pixel, split-frame-transfer device running at > 150 frames per second with high sensitivity in the visible spectrum. Sarnoff designed, fabricated and delivered cameras based on these CCDs and is now extending this technology to devices with higher pixel counts and higher frame rates through CCD architectural enhancements. The high sensitivities obtained in the visible spectrum are being pushed into the deep UV to support these new medical and industrial inspection applications. Sarnoff has achieved measured quantum efficiencies > 55% at 193 nm, rising to 65% at 300 nm, and remaining almost constant out to 750 nm. Optimization of the sensitivity is being pursued to tailor the quantum efficiency for particular wavelengths. Characteristics of these high frame rate CCDs and cameras will be described and results will be presented demonstrating high UV sensitivity down to 150 nm.

A compact, high temperature nuclear magnetic resonance probe for use in a narrow-bore superconducting magnet

NASA Astrophysics Data System (ADS)

Adler, Stuart B.; Michaels, James N.; Reimer, Jeffrey A.

1990-11-01

The design of a nuclear magnetic resonance (NMR) probe is reported, that can be used in narrow-bore superconducting solenoids for the observation of nuclear induction at high temperatures. The probe is compact, highly sensitive, and stable in continuous operation at temperatures up to 1050 C. The essential feature of the probe is a water-cooled NMR coil that contains the sample-furnace; this design maximizes sensitivity and circuit stability by maintaining the probe electronics at ambient temperature. The design is demonstrated by showing high temperature O-17 NMR spectra and relaxation measurements in solid barium bismuth oxide and yttria-stabilized zirconia.

The role of histopathology in establishing the diagnosis of tuberculous pericardial effusions in the presence of HIV.

PubMed

Reuter, H; Burgess, L J; Schneider, J; Van Vuuren, W; Doubell, A F

2006-02-01

To establish the influence of human immunodeficiency virus (HIV) infection on the histopathological features of patients presenting with tuberculous pericarditis. A prospective study was carried out at Tygerberg Academic Hospital, South Africa; 36 patients with large pericardial effusions had open pericardial biopsies under general anaesthesia and were included in the study. Patients underwent pericardiocentesis, followed by daily intermittent catheter drainage; a comprehensive diagnostic work-up (including histopathology of the pericardial tissue) was also performed. Histological tuberculous pericarditis was diagnosed according to predetermined criteria. Tuberculous pericarditis was identified in 25 patients, five of whom were HIV+. The presence of granulomatous inflammation (with or without necrosis) and/or Ziehl-Neelsen positivity yielded the best test results (sensitivity 64%, specificity 100% and diagnostic efficiency 75%). Co-infection with HIV impacts on the histopathological features of pericardial tuberculosis and leads to a decrease in the sensitivity of the test. In areas which have a high prevalence of tuberculosis, the combination of a sensitive test such as adenosine deaminase, chest X-ray and clinical features has a higher diagnostic efficiency than pericardial biopsy in diagnosing tuberculous pericarditis.

Thyroid Nodule Classification in Ultrasound Images by Fine-Tuning Deep Convolutional Neural Network.

PubMed

Chi, Jianning; Walia, Ekta; Babyn, Paul; Wang, Jimmy; Groot, Gary; Eramian, Mark

2017-08-01

With many thyroid nodules being incidentally detected, it is important to identify as many malignant nodules as possible while excluding those that are highly likely to be benign from fine needle aspiration (FNA) biopsies or surgeries. This paper presents a computer-aided diagnosis (CAD) system for classifying thyroid nodules in ultrasound images. We use deep learning approach to extract features from thyroid ultrasound images. Ultrasound images are pre-processed to calibrate their scale and remove the artifacts. A pre-trained GoogLeNet model is then fine-tuned using the pre-processed image samples which leads to superior feature extraction. The extracted features of the thyroid ultrasound images are sent to a Cost-sensitive Random Forest classifier to classify the images into "malignant" and "benign" cases. The experimental results show the proposed fine-tuned GoogLeNet model achieves excellent classification performance, attaining 98.29% classification accuracy, 99.10% sensitivity and 93.90% specificity for the images in an open access database (Pedraza et al. 16), while 96.34% classification accuracy, 86% sensitivity and 99% specificity for the images in our local health region database.

Improving the performance of lesion-based computer-aided detection schemes of breast masses using a case-based adaptive cueing method

NASA Astrophysics Data System (ADS)

Tan, Maxine; Aghaei, Faranak; Wang, Yunzhi; Qian, Wei; Zheng, Bin

2016-03-01

Current commercialized CAD schemes have high false-positive (FP) detection rates and also have high correlations in positive lesion detection with radiologists. Thus, we recently investigated a new approach to improve the efficacy of applying CAD to assist radiologists in reading and interpreting screening mammograms. Namely, we developed a new global feature based CAD approach/scheme that can cue the warning sign on the cases with high risk of being positive. In this study, we investigate the possibility of fusing global feature or case-based scores with the local or lesion-based CAD scores using an adaptive cueing method. We hypothesize that the information from the global feature extraction (features extracted from the whole breast regions) are different from and can provide supplementary information to the locally-extracted features (computed from the segmented lesion regions only). On a large and diverse full-field digital mammography (FFDM) testing dataset with 785 cases (347 negative and 438 cancer cases with masses only), we ran our lesion-based and case-based CAD schemes "as is" on the whole dataset. To assess the supplementary information provided by the global features, we used an adaptive cueing method to adaptively adjust the original CAD-generated detection scores (Sorg) of a detected suspicious mass region based on the computed case-based score (Scase) of the case associated with this detected region. Using the adaptive cueing method, better sensitivity results were obtained at lower FP rates (<= 1 FP per image). Namely, increases of sensitivities (in the FROC curves) of up to 6.7% and 8.2% were obtained for the ROI and Case-based results, respectively.

A nano ultra-performance liquid chromatography-high resolution mass spectrometry approach for global metabolomic profiling and case study on drug-resistant multiple myeloma.

PubMed

Jones, Drew R; Wu, Zhiping; Chauhan, Dharminder; Anderson, Kenneth C; Peng, Junmin

2014-04-01

Global metabolomics relies on highly reproducible and sensitive detection of a wide range of metabolites in biological samples. Here we report the optimization of metabolome analysis by nanoflow ultraperformance liquid chromatography coupled to high-resolution orbitrap mass spectrometry. Reliable peak features were extracted from the LC-MS runs based on mandatory detection in duplicates and additional noise filtering according to blank injections. The run-to-run variation in peak area showed a median of 14%, and the false discovery rate during a mock comparison was evaluated. To maximize the number of peak features identified, we systematically characterized the effect of sample loading amount, gradient length, and MS resolution. The number of features initially rose and later reached a plateau as a function of sample amount, fitting a hyperbolic curve. Longer gradients improved unique feature detection in part by time-resolving isobaric species. Increasing the MS resolution up to 120000 also aided in the differentiation of near isobaric metabolites, but higher MS resolution reduced the data acquisition rate and conferred no benefits, as predicted from a theoretical simulation of possible metabolites. Moreover, a biphasic LC gradient allowed even distribution of peak features across the elution, yielding markedly more peak features than the linear gradient. Using this robust nUPLC-HRMS platform, we were able to consistently analyze ~6500 metabolite features in a single 60 min gradient from 2 mg of yeast, equivalent to ~50 million cells. We applied this optimized method in a case study of drug (bortezomib) resistant and drug-sensitive multiple myeloma cells. Overall, 18% of metabolite features were matched to KEGG identifiers, enabling pathway enrichment analysis. Principal component analysis and heat map data correctly clustered isogenic phenotypes, highlighting the potential for hundreds of small molecule biomarkers of cancer drug resistance.

Exploring the impacts of physics and resolution on aqua-planet simulations from a nonhydrostatic global variable-resolution modeling framework: IMPACTS OF PHYSICS AND RESOLUTION

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

Zhao, Chun; Leung, L. Ruby; Park, Sang-Hun

Advances in computing resources are gradually moving regional and global numerical forecasting simulations towards sub-10 km resolution, but global high resolution climate simulations remain a challenge. The non-hydrostatic Model for Prediction Across Scales (MPAS) provides a global framework to achieve very high resolution using regional mesh refinement. Previous studies using the hydrostatic version of MPAS (H-MPAS) with the physics parameterizations of Community Atmosphere Model version 4 (CAM4) found notable resolution dependent behaviors. This study revisits the resolution sensitivity using the non-hydrostatic version of MPAS (NH-MPAS) with both CAM4 and CAM5 physics. A series of aqua-planet simulations at global quasi-uniform resolutionsmore » ranging from 240 km to 30 km and global variable resolution simulations with a regional mesh refinement of 30 km resolution over the tropics are analyzed, with a primary focus on the distinct characteristics of NH-MPAS in simulating precipitation, clouds, and large-scale circulation features compared to H-MPAS-CAM4. The resolution sensitivity of total precipitation and column integrated moisture in NH-MPAS is smaller than that in H-MPAS-CAM4. This contributes importantly to the reduced resolution sensitivity of large-scale circulation features such as the inter-tropical convergence zone and Hadley circulation in NH-MPAS compared to H-MPAS. In addition, NH-MPAS shows almost no resolution sensitivity in the simulated westerly jet, in contrast to the obvious poleward shift in H-MPAS with increasing resolution, which is partly explained by differences in the hyperdiffusion coefficients used in the two models that influence wave activity. With the reduced resolution sensitivity, simulations in the refined region of the NH-MPAS global variable resolution configuration exhibit zonally symmetric features that are more comparable to the quasi-uniform high-resolution simulations than those from H-MPAS that displays zonal asymmetry in simulations inside the refined region. Overall, NH-MPAS with CAM5 physics shows less resolution sensitivity compared to CAM4. These results provide a reference for future studies to further explore the use of NH-MPAS for high-resolution climate simulations in idealized and realistic configurations.« less

Probabilistic hazard assessment for skin sensitization potency by dose–response modeling using feature elimination instead of quantitative structure–activity relationships

PubMed Central

McKim, James M.; Hartung, Thomas; Kleensang, Andre; Sá-Rocha, Vanessa

2016-01-01

Supervised learning methods promise to improve integrated testing strategies (ITS), but must be adjusted to handle high dimensionality and dose–response data. ITS approaches are currently fueled by the increasing mechanistic understanding of adverse outcome pathways (AOP) and the development of tests reflecting these mechanisms. Simple approaches to combine skin sensitization data sets, such as weight of evidence, fail due to problems in information redundancy and high dimension-ality. The problem is further amplified when potency information (dose/response) of hazards would be estimated. Skin sensitization currently serves as the foster child for AOP and ITS development, as legislative pressures combined with a very good mechanistic understanding of contact dermatitis have led to test development and relatively large high-quality data sets. We curated such a data set and combined a recursive variable selection algorithm to evaluate the information available through in silico, in chemico and in vitro assays. Chemical similarity alone could not cluster chemicals’ potency, and in vitro models consistently ranked high in recursive feature elimination. This allows reducing the number of tests included in an ITS. Next, we analyzed with a hidden Markov model that takes advantage of an intrinsic inter-relationship among the local lymph node assay classes, i.e. the monotonous connection between local lymph node assay and dose. The dose-informed random forest/hidden Markov model was superior to the dose-naive random forest model on all data sets. Although balanced accuracy improvement may seem small, this obscures the actual improvement in misclassifications as the dose-informed hidden Markov model strongly reduced "false-negatives" (i.e. extreme sensitizers as non-sensitizer) on all data sets. PMID:26046447

Probabilistic hazard assessment for skin sensitization potency by dose-response modeling using feature elimination instead of quantitative structure-activity relationships.

PubMed

Luechtefeld, Thomas; Maertens, Alexandra; McKim, James M; Hartung, Thomas; Kleensang, Andre; Sá-Rocha, Vanessa

2015-11-01

Supervised learning methods promise to improve integrated testing strategies (ITS), but must be adjusted to handle high dimensionality and dose-response data. ITS approaches are currently fueled by the increasing mechanistic understanding of adverse outcome pathways (AOP) and the development of tests reflecting these mechanisms. Simple approaches to combine skin sensitization data sets, such as weight of evidence, fail due to problems in information redundancy and high dimensionality. The problem is further amplified when potency information (dose/response) of hazards would be estimated. Skin sensitization currently serves as the foster child for AOP and ITS development, as legislative pressures combined with a very good mechanistic understanding of contact dermatitis have led to test development and relatively large high-quality data sets. We curated such a data set and combined a recursive variable selection algorithm to evaluate the information available through in silico, in chemico and in vitro assays. Chemical similarity alone could not cluster chemicals' potency, and in vitro models consistently ranked high in recursive feature elimination. This allows reducing the number of tests included in an ITS. Next, we analyzed with a hidden Markov model that takes advantage of an intrinsic inter-relationship among the local lymph node assay classes, i.e. the monotonous connection between local lymph node assay and dose. The dose-informed random forest/hidden Markov model was superior to the dose-naive random forest model on all data sets. Although balanced accuracy improvement may seem small, this obscures the actual improvement in misclassifications as the dose-informed hidden Markov model strongly reduced " false-negatives" (i.e. extreme sensitizers as non-sensitizer) on all data sets. Copyright © 2015 John Wiley & Sons, Ltd.

Noninvasive Dissection of Mouse Sleep Using a Piezoelectric Motion Sensor

PubMed Central

Yaghouby, Farid; Donohue, Kevin D.; O’Hara, Bruce F.; Sunderam, Sridhar

2015-01-01

Background Changes in autonomic control cause regular breathing during NREM sleep to fluctuate during REM. Piezoelectric cage-floor sensors have been used to successfully discriminate sleep and wake states in mice based on signal features related to respiration and other movements. This study presents a classifier for noninvasively classifying REM and NREM using a piezoelectric sensor. New Method Vigilance state was scored manually in 4-second epochs for 24-hour EEG/EMG recordings in twenty mice. An unsupervised classifier clustered piezoelectric signal features quantifying movement and respiration into three states: one active; and two inactive with regular and irregular breathing respectively. These states were hypothesized to correspond to Wake, NREM, and REM respectively. States predicted by the classifier were compared against manual EEG/EMG scores to test this hypothesis. Results Using only piezoelectric signal features, an unsupervised classifier distinguished Wake with high (89% sensitivity, 96% specificity) and REM with moderate (73% sensitivity, 75% specificity) accuracy, but NREM with poor sensitivity (51%) and high specificity (96%). The classifier sometimes confused light NREM sleep—characterized by irregular breathing and moderate delta EEG power—with REM. A supervised classifier improved sensitivities to 90, 81, and 67% and all specificities to over 90% for Wake, NREM, and REM respectively. Comparison with Existing Methods Unlike most actigraphic techniques, which only differentiate sleep from wake, the proposed piezoelectric method further dissects sleep based on breathing regularity into states strongly correlated with REM and NREM. Conclusions This approach could facilitate large-sample screening for genes influencing different sleep traits, besides drug studies or other manipulations. PMID:26582569

A cross-sectional study of pain sensitivity, disease-activity assessment, mental health, and fibromyalgia status in rheumatoid arthritis.

PubMed

Joharatnam, Nalinie; McWilliams, Daniel F; Wilson, Deborah; Wheeler, Maggie; Pande, Ira; Walsh, David A

2015-01-20

Pain remains the most important problem for people with rheumatoid arthritis (RA). Active inflammatory disease contributes to pain, but pain due to non-inflammatory mechanisms can confound the assessment of disease activity. We hypothesize that augmented pain processing, fibromyalgic features, poorer mental health, and patient-reported 28-joint disease activity score (DAS28) components are associated in RA. In total, 50 people with stable, long-standing RA recruited from a rheumatology outpatient clinic were assessed for pain-pressure thresholds (PPTs) at three separate sites (knee, tibia, and sternum), DAS28, fibromyalgia, and mental health status. Multivariable analysis was performed to assess the association between PPT and DAS28 components, DAS28-P (the proportion of DAS28 derived from the patient-reported components of visual analogue score and tender joint count), or fibromyalgia status. More-sensitive PPTs at sites over or distant from joints were each associated with greater reported pain, higher patient-reported DAS28 components, and poorer mental health. A high proportion of participants (48%) satisfied classification criteria for fibromyalgia, and fibromyalgia classification or characteristics were each associated with more sensitive PPTs, higher patient-reported DAS28 components, and poorer mental health. Widespread sensitivity to pressure-induced pain, a high prevalence of fibromyalgic features, higher patient-reported DAS28 components, and poorer mental health are all linked in established RA. The increased sensitivity at nonjoint sites (sternum and anterior tibia), as well as over joints, indicates that central mechanisms may contribute to pain sensitivity in RA. The contribution of patient-reported components to high DAS28 should inform decisions on disease-modifying or pain-management approaches in the treatment of RA when inflammation may be well controlled.

Freezing of Gait Detection in Parkinson's Disease: A Subject-Independent Detector Using Anomaly Scores.

PubMed

Pham, Thuy T; Moore, Steven T; Lewis, Simon John Geoffrey; Nguyen, Diep N; Dutkiewicz, Eryk; Fuglevand, Andrew J; McEwan, Alistair L; Leong, Philip H W

2017-11-01

Freezing of gait (FoG) is common in Parkinsonian gait and strongly relates to falls. Current clinical FoG assessments are patients' self-report diaries and experts' manual video analysis. Both are subjective and yield moderate reliability. Existing detection algorithms have been predominantly designed in subject-dependent settings. In this paper, we aim to develop an automated FoG detector for subject independent. After extracting highly relevant features, we apply anomaly detection techniques to detect FoG events. Specifically, feature selection is performed using correlation and clusterability metrics. From a list of 244 feature candidates, 36 candidates were selected using saliency and robustness criteria. We develop an anomaly score detector with adaptive thresholding to identify FoG events. Then, using accuracy metrics, we reduce the feature list to seven candidates. Our novel multichannel freezing index was the most selective across all window sizes, achieving sensitivity (specificity) of (). On the other hand, freezing index from the vertical axis was the best choice for a single input, achieving sensitivity (specificity) of () for ankle and () for back sensors. Our subject-independent method is not only significantly more accurate than those previously reported, but also uses a much smaller window (e.g., versus ) and/or lower tolerance (e.g., versus ).Freezing of gait (FoG) is common in Parkinsonian gait and strongly relates to falls. Current clinical FoG assessments are patients' self-report diaries and experts' manual video analysis. Both are subjective and yield moderate reliability. Existing detection algorithms have been predominantly designed in subject-dependent settings. In this paper, we aim to develop an automated FoG detector for subject independent. After extracting highly relevant features, we apply anomaly detection techniques to detect FoG events. Specifically, feature selection is performed using correlation and clusterability metrics. From a list of 244 feature candidates, 36 candidates were selected using saliency and robustness criteria. We develop an anomaly score detector with adaptive thresholding to identify FoG events. Then, using accuracy metrics, we reduce the feature list to seven candidates. Our novel multichannel freezing index was the most selective across all window sizes, achieving sensitivity (specificity) of (). On the other hand, freezing index from the vertical axis was the best choice for a single input, achieving sensitivity (specificity) of () for ankle and () for back sensors. Our subject-independent method is not only significantly more accurate than those previously reported, but also uses a much smaller window (e.g., versus ) and/or lower tolerance (e.g., versus ).

Continuously Tunable, Polarization Controlled, Colour Palette Produced from Nanoscale Plasmonic Pixels.

PubMed

Balaur, Eugeniu; Sadatnajafi, Catherine; Kou, Shan Shan; Lin, Jiao; Abbey, Brian

2016-06-17

Colour filters based on nano-apertures in thin metallic films have been widely studied due to their extraordinary optical transmission and small size. These properties make them prime candidates for use in high-resolution colour displays and high accuracy bio-sensors. The inclusion of polarization sensitive plasmonic features in such devices allow additional control over the electromagnetic field distribution, critical for investigations of polarization induced phenomena. Here we demonstrate that cross-shaped nano-apertures can be used for polarization controlled color tuning in the visible range and apply fundamental theoretical models to interpret key features of the transmitted spectrum. Full color transmission was achieved by fine-tuning the periodicity of the apertures, whilst keeping the geometry of individual apertures constant. We demonstrate this effect for both transverse electric and magnetic fields. Furthermore we have been able to demonstrate the same polarization sensitivity even for nano-size, sub-wavelength sets of arrays, which is paramount for ultra-high resolution compact colour displays.

Continuously Tunable, Polarization Controlled, Colour Palette Produced from Nanoscale Plasmonic Pixels

PubMed Central

Balaur, Eugeniu; Sadatnajafi, Catherine; Kou, Shan Shan; Lin, Jiao; Abbey, Brian

2016-01-01

Colour filters based on nano-apertures in thin metallic films have been widely studied due to their extraordinary optical transmission and small size. These properties make them prime candidates for use in high-resolution colour displays and high accuracy bio-sensors. The inclusion of polarization sensitive plasmonic features in such devices allow additional control over the electromagnetic field distribution, critical for investigations of polarization induced phenomena. Here we demonstrate that cross-shaped nano-apertures can be used for polarization controlled color tuning in the visible range and apply fundamental theoretical models to interpret key features of the transmitted spectrum. Full color transmission was achieved by fine-tuning the periodicity of the apertures, whilst keeping the geometry of individual apertures constant. We demonstrate this effect for both transverse electric and magnetic fields. Furthermore we have been able to demonstrate the same polarization sensitivity even for nano-size, sub-wavelength sets of arrays, which is paramount for ultra-high resolution compact colour displays. PMID:27312072

Optimizing defect inspection strategy through the use of design-aware database control layers

NASA Astrophysics Data System (ADS)

Stoler, Dvori; Ruch, Wayne; Ma, Weimin; Chakravarty, Swapnajit; Liu, Steven; Morgan, Ray; Valadez, John; Moore, Bill; Burns, John

2007-10-01

Resolution limitations in the mask making process can cause differences between the features that appear in a database and those printed to a reticle. These differences may result from intentional or unintentional features in the database exceeding the resolution limit of the mask making process such as small gaps or lines in the data, line end shortening on small sub-resolution assist features etc creating challenges to both mask writing and mask inspection. Areas with high variance from design to mask, often referred to as high MEEF areas (mask error enhancement factor), become highly problematic and can directly impact mask and device yield, mask manufacturing cycle time and ultimately mask costs. Specific to mask inspection it may be desirable to inspect certain non-critical or non-relevant features at reduced sensitivity so as not to detect real, but less significant process defects. In contrast there may also be times where increased sensitivity is required for critical mask features or areas. Until recently, this process was extremely manual, creating added time and cost to the mask inspection cycle. Shifting to more intelligent and automated inspection flows is the key focus of this paper. A novel approach to importing design data directly into the mask inspection to include both MDP generated MRC errors files and LRC generated MEEF files. The results of recently developed inspection and review capability based upon controlling defect inspection using design aware data base control layers on a pixel basis are discussed. Typical mask shop applications and implementations will be shown.

High-throughput molecular identification of Staphylococcus spp. isolated from a clean room facility in an environmental monitoring program

PubMed Central

2010-01-01

Background The staphylococci are one of the most common environmental isolates found in clean room facility. Consequently, isolation followed by comprehensive and accurate identification is an essential step in any environmental monitoring program. Findings We have used the API Staph identification kit (bioMérieux, France) which depends on the expression of metabolic activities and or morphological features to identify the Staphylococcus isolates. The API staphylococci showed low sensitivity in the identification of some species, so we performed molecular methods based on PCR based fingerprinting of glyceraldehyde-3-phosphate dehydrogenase encoding gene as useful taxonomic tool for examining Staphylococcus isolates. Conclusions Our results showed that PCR protocol used in this study which depends on genotypic features was relatively accurate, rapid, sensitive and superior in the identification of at least 7 species of Staphylococcus than API Staph which depends on phenotypic features. PMID:21047438

High-throughput molecular identification of Staphylococcus spp. isolated from a clean room facility in an environmental monitoring program.

PubMed

Sheraba, Norhan S; Yassin, Aymen S; Amin, Magdy A

2010-11-04

The staphylococci are one of the most common environmental isolates found in clean room facility. Consequently, isolation followed by comprehensive and accurate identification is an essential step in any environmental monitoring program. We have used the API Staph identification kit (bioMérieux, France) which depends on the expression of metabolic activities and or morphological features to identify the Staphylococcus isolates. The API staphylococci showed low sensitivity in the identification of some species, so we performed molecular methods based on PCR based fingerprinting of glyceraldehyde-3-phosphate dehydrogenase encoding gene as useful taxonomic tool for examining Staphylococcus isolates. Our results showed that PCR protocol used in this study which depends on genotypic features was relatively accurate, rapid, sensitive and superior in the identification of at least 7 species of Staphylococcus than API Staph which depends on phenotypic features.

Safer energetic materials by a nanotechnological approach

NASA Astrophysics Data System (ADS)

Siegert, Benny; Comet, Marc; Spitzer, Denis

2011-09-01

Energetic materials - explosives, thermites, populsive powders - are used in a variety of military and civilian applications. Their mechanical and electrostatic sensitivity is high in many cases, which can lead to accidents during handling and transport. These considerations limit the practical use of some energetic materials despite their good performance. For industrial applications, safety is one of the main criteria for selecting energetic materials. The sensitivity has been regarded as an intrinsic property of a substance for a long time. However, in recent years, several approaches to lower the sensitivity of a given substance, using nanotechnology and materials engineering, have been described. This feature article gives an overview over ways to prepare energetic (nano-)materials with a lower sensitivity.Energetic materials - explosives, thermites, populsive powders - are used in a variety of military and civilian applications. Their mechanical and electrostatic sensitivity is high in many cases, which can lead to accidents during handling and transport. These considerations limit the practical use of some energetic materials despite their good performance. For industrial applications, safety is one of the main criteria for selecting energetic materials. The sensitivity has been regarded as an intrinsic property of a substance for a long time. However, in recent years, several approaches to lower the sensitivity of a given substance, using nanotechnology and materials engineering, have been described. This feature article gives an overview over ways to prepare energetic (nano-)materials with a lower sensitivity. Electronic supplementary information (ESI) available: Experimental details for the preparation of the V2O5@CNF/Al nanothermite; X-ray diffractogram of the V2O5@CNF/Al combustion residue; installation instructions and source code for the nt-timeline program. See DOI: 10.1039/c1nr10292c

Sensitivity-Enhanced Wearable Active Voiceprint Sensor Based on Cellular Polypropylene Piezoelectret.

PubMed

Li, Wenbo; Zhao, Sheng; Wu, Nan; Zhong, Junwen; Wang, Bo; Lin, Shizhe; Chen, Shuwen; Yuan, Fang; Jiang, Hulin; Xiao, Yongjun; Hu, Bin; Zhou, Jun

2017-07-19

Wearable active sensors have extensive applications in mobile biosensing and human-machine interaction but require good flexibility, high sensitivity, excellent stability, and self-powered feature. In this work, cellular polypropylene (PP) piezoelectret was chosen as the core material of a sensitivity-enhanced wearable active voiceprint sensor (SWAVS) to realize voiceprint recognition. By virtue of the dipole orientation control method, the air layers in the piezoelectret were efficiently utilized, and the current sensitivity was enhanced (from 1.98 pA/Hz to 5.81 pA/Hz at 115 dB). The SWAVS exhibited the superiorities of high sensitivity, accurate frequency response, and excellent stability. The voiceprint recognition system could make correct reactions to human voices by judging both the password and speaker. This study presented a voiceprint sensor with potential applications in noncontact biometric recognition and safety guarantee systems, promoting the progress of wearable sensor networks.

CMOS Amperometric ADC With High Sensitivity, Dynamic Range and Power Efficiency for Air Quality Monitoring.

PubMed

Li, Haitao; Boling, C Sam; Mason, Andrew J

2016-08-01

Airborne pollutants are a leading cause of illness and mortality globally. Electrochemical gas sensors show great promise for personal air quality monitoring to address this worldwide health crisis. However, implementing miniaturized arrays of such sensors demands high performance instrumentation circuits that simultaneously meet challenging power, area, sensitivity, noise and dynamic range goals. This paper presents a new multi-channel CMOS amperometric ADC featuring pixel-level architecture for gas sensor arrays. The circuit combines digital modulation of input currents and an incremental Σ∆ ADC to achieve wide dynamic range and high sensitivity with very high power efficiency and compact size. Fabricated in 0.5 [Formula: see text] CMOS, the circuit was measured to have 164 dB cross-scale dynamic range, 100 fA sensitivity while consuming only 241 [Formula: see text] and 0.157 [Formula: see text] active area per channel. Electrochemical experiments with liquid and gas targets demonstrate the circuit's real-time response to a wide range of analyte concentrations.

Why 8-Year-Olds Cannot Tell the Difference between Steve Martin and Paul Newman: Factors Contributing to the Slow Development of Sensitivity to the Spacing of Facial Features

ERIC Educational Resources Information Center

Mondloch, Catherine J.; Dobson, Kate S.; Parsons, Julie; Maurer, Daphne

2004-01-01

Children are nearly as sensitive as adults to some cues to facial identity (e.g., differences in the shape of internal features and the external contour), but children are much less sensitive to small differences in the spacing of facial features. To identify factors that contribute to this pattern, we compared 8-year-olds' sensitivity to spacing…

Automatic detection of anomalies in screening mammograms

PubMed Central

2013-01-01

Background Diagnostic performance in breast screening programs may be influenced by the prior probability of disease. Since breast cancer incidence is roughly half a percent in the general population there is a large probability that the screening exam will be normal. That factor may contribute to false negatives. Screening programs typically exhibit about 83% sensitivity and 91% specificity. This investigation was undertaken to determine if a system could be developed to pre-sort screening-images into normal and suspicious bins based on their likelihood to contain disease. Wavelets were investigated as a method to parse the image data, potentially removing confounding information. The development of a classification system based on features extracted from wavelet transformed mammograms is reported. Methods In the multi-step procedure images were processed using 2D discrete wavelet transforms to create a set of maps at different size scales. Next, statistical features were computed from each map, and a subset of these features was the input for a concerted-effort set of naïve Bayesian classifiers. The classifier network was constructed to calculate the probability that the parent mammography image contained an abnormality. The abnormalities were not identified, nor were they regionalized. The algorithm was tested on two publicly available databases: the Digital Database for Screening Mammography (DDSM) and the Mammographic Images Analysis Society’s database (MIAS). These databases contain radiologist-verified images and feature common abnormalities including: spiculations, masses, geometric deformations and fibroid tissues. Results The classifier-network designs tested achieved sensitivities and specificities sufficient to be potentially useful in a clinical setting. This first series of tests identified networks with 100% sensitivity and up to 79% specificity for abnormalities. This performance significantly exceeds the mean sensitivity reported in literature for the unaided human expert. Conclusions Classifiers based on wavelet-derived features proved to be highly sensitive to a range of pathologies, as a result Type II errors were nearly eliminated. Pre-sorting the images changed the prior probability in the sorted database from 37% to 74%. PMID:24330643

High Sensitivity Combined with Extended Structural Coverage of Labile Compounds via Nanoelectrospray Ionization at Subambient Pressures

DOE PAGES

Cox, Jonathan T.; Kronewitter, Scott R.; Shukla, Anil K.; ...

2014-09-15

Subambient pressure ionization with nanoelectrospray (SPIN) has proven to be effective in producing ions with high efficiency and transmitting them to low pressures for high sensitivity mass spectrometry (MS) analysis. Here we present evidence that not only does the SPIN source improve MS sensitivity but also allows for gentler ionization conditions. The gentleness of a conventional heated capillary electrospray ionization (ESI) source and the SPIN source was compared by the liquid chromatography mass spectrometry (LC-MS) analysis of colominic acid. Colominic acid is a mixture of sialic acid polymers of different lengths containing labile glycosidic linkages between monomer units necessitating amore » gentle ion source. By coupling the SPIN source with high resolution mass spectrometry and using advanced data processing tools, we demonstrate much extended coverage of sialic acid polymer chains as compared to using the conventional ESI source. Additionally we show that SPIN-LC-MS is effective in elucidating polymer features with high efficiency and high sensitivity previously unattainable by the conventional ESI-LC-MS methods.« less

Reverse engineering the face space: Discovering the critical features for face identification.

PubMed

Abudarham, Naphtali; Yovel, Galit

2016-01-01

How do we identify people? What are the critical facial features that define an identity and determine whether two faces belong to the same person or different people? To answer these questions, we applied the face space framework, according to which faces are represented as points in a multidimensional feature space, such that face space distances are correlated with perceptual similarities between faces. In particular, we developed a novel method that allowed us to reveal the critical dimensions (i.e., critical features) of the face space. To that end, we constructed a concrete face space, which included 20 facial features of natural face images, and asked human observers to evaluate feature values (e.g., how thick are the lips). Next, we systematically and quantitatively changed facial features, and measured the perceptual effects of these manipulations. We found that critical features were those for which participants have high perceptual sensitivity (PS) for detecting differences across identities (e.g., which of two faces has thicker lips). Furthermore, these high PS features vary minimally across different views of the same identity, suggesting high PS features support face recognition across different images of the same face. The methods described here set an infrastructure for discovering the critical features of other face categories not studied here (e.g., Asians, familiar) as well as other aspects of face processing, such as attractiveness or trait inferences.

Histopathological Identification of Colon Cancer with Microsatellite Instability

PubMed Central

Alexander, Julian; Watanabe, Toshiaki; Wu, Tsung-Teh; Rashid, Asif; Li, Shuan; Hamilton, Stanley R.

2001-01-01

Cancer with high levels of microsatellite instability (MSI-H) is the hallmark of hereditary nonpolyposis colorectal cancer syndrome, and MSI-H occurs in ∼15% of sporadic colorectal carcinomas that have improved prognosis. We examined the utility of histopathology for the identification of MSI-H cancers by evaluating the features of 323 sporadic carcinomas using specified criteria and comparing the results to MSI-H status. Coded hematoxylin and eosin sections were evaluated for tumor features (signet ring cells; mucinous histology; cribriforming, poor differentiation, and medullary-type pattern; sponge-like mucinous growth; pushing invasive margin) and features of host immune response (Crohn’s-like lymphoid reaction, intratumoral lymphocytic infiltrate, and intraepithelial T cells by immunohistochemistry for CD3 with morphometry). Interobserver variation among five pathologists was determined. Subjective interpretation of histopathology as an indication for MSI testing was recorded. We found that medullary carcinoma, intraepithelial lymphocytosis, and poor differentiation were the best discriminators between MSI-H and microsatellite-stable cancers (odds ratio: 37.8, 9.8, and 4.0, respectively; P = 0.000003 to <0.000001) with high specificity (99 to 87%). The sensitivities, however, were very low (14 to 38%), and interobserver agreement was good only for evaluation of poor differentiation (kappa, 0.69). Mucinous histopathological type and presence of signet ring cells had low odds ratios of 3.3 and 2.7 (P = 0.005 and P = 0.02) with specificities of 95% but sensitivities of only 15 and 13%. Subjective interpretation of the overall histopathology as suggesting MSI-H performed better than any individual feature; the odds ratio was 7.5 (P < 0.000001) with sensitivity of 49%, specificity of 89%, and moderate interobserver agreement (kappa, 0.52). Forty intraepithelial CD3-positive lymphocytes/0.94 mm2, as established by receiver operating characteristic curve analysis, resulted in an odds ratio of 6.0 (P < 0.000001) with sensitivity of 75% and specificity of 67%. Our findings indicate that histopathological evaluation can be used to prioritize sporadic colon cancers for MSI studies, but morphological prediction of MSI-H has low sensitivity, requiring molecular analysis for therapeutic decisions. PMID:11159189

Individual classification of ADHD patients by integrating multiscale neuroimaging markers and advanced pattern recognition techniques

PubMed Central

Cheng, Wei; Ji, Xiaoxi; Zhang, Jie; Feng, Jianfeng

2012-01-01

Accurate classification or prediction of the brain state across individual subject, i.e., healthy, or with brain disorders, is generally a more difficult task than merely finding group differences. The former must be approached with highly informative and sensitive biomarkers as well as effective pattern classification/feature selection approaches. In this paper, we propose a systematic methodology to discriminate attention deficit hyperactivity disorder (ADHD) patients from healthy controls on the individual level. Multiple neuroimaging markers that are proved to be sensitive features are identified, which include multiscale characteristics extracted from blood oxygenation level dependent (BOLD) signals, such as regional homogeneity (ReHo) and amplitude of low-frequency fluctuations. Functional connectivity derived from Pearson, partial, and spatial correlation is also utilized to reflect the abnormal patterns of functional integration, or, dysconnectivity syndromes in the brain. These neuroimaging markers are calculated on either voxel or regional level. Advanced feature selection approach is then designed, including a brain-wise association study (BWAS). Using identified features and proper feature integration, a support vector machine (SVM) classifier can achieve a cross-validated classification accuracy of 76.15% across individuals from a large dataset consisting of 141 healthy controls and 98 ADHD patients, with the sensitivity being 63.27% and the specificity being 85.11%. Our results show that the most discriminative features for classification are primarily associated with the frontal and cerebellar regions. The proposed methodology is expected to improve clinical diagnosis and evaluation of treatment for ADHD patient, and to have wider applications in diagnosis of general neuropsychiatric disorders. PMID:22888314

Amygdala and auditory cortex exhibit distinct sensitivity to relevant acoustic features of auditory emotions.

PubMed

Pannese, Alessia; Grandjean, Didier; Frühholz, Sascha

2016-12-01

Discriminating between auditory signals of different affective value is critical to successful social interaction. It is commonly held that acoustic decoding of such signals occurs in the auditory system, whereas affective decoding occurs in the amygdala. However, given that the amygdala receives direct subcortical projections that bypass the auditory cortex, it is possible that some acoustic decoding occurs in the amygdala as well, when the acoustic features are relevant for affective discrimination. We tested this hypothesis by combining functional neuroimaging with the neurophysiological phenomena of repetition suppression (RS) and repetition enhancement (RE) in human listeners. Our results show that both amygdala and auditory cortex responded differentially to physical voice features, suggesting that the amygdala and auditory cortex decode the affective quality of the voice not only by processing the emotional content from previously processed acoustic features, but also by processing the acoustic features themselves, when these are relevant to the identification of the voice's affective value. Specifically, we found that the auditory cortex is sensitive to spectral high-frequency voice cues when discriminating vocal anger from vocal fear and joy, whereas the amygdala is sensitive to vocal pitch when discriminating between negative vocal emotions (i.e., anger and fear). Vocal pitch is an instantaneously recognized voice feature, which is potentially transferred to the amygdala by direct subcortical projections. These results together provide evidence that, besides the auditory cortex, the amygdala too processes acoustic information, when this is relevant to the discrimination of auditory emotions. Copyright © 2016 Elsevier Ltd. All rights reserved.

CA resist with high sensitivity and sub-100-nm resolution for advanced mask making

NASA Astrophysics Data System (ADS)

Huang, Wu-Song; Kwong, Ranee W.; Hartley, John G.; Moreau, Wayne M.; Angelopoulos, Marie; Magg, Christopher; Lawliss, Mark

2000-07-01

Recently, there is significant interest in using CA resist for electron beam (E-beam) applications including mask making, direct write, and projection printing. CA resists provide superior lithographic performance in comparison to traditional non-CA E-beam resist in particular high contrast, resolution, and sensitivity. However, most of the commercially available CA resist have the concern of airborne base contaminants and sensitivity to PAB and/or PEB temperatures. In this presentation, we will discuss a new improved ketal resists system referred to as KRS-XE which exhibits excellent lithography, is robust toward airborne base, compatible with 0.263N TMAH aqueous developer and exhibits excellent lithography, is robust toward airborne base, compatible with 0.263N TMAH aqueous developer and exhibits a large PAB/PEB latitude. With the combination of a high performance mask making E-beam exposure tool, high kV shaped beam system EL4+ and the KRS-XE resist, we have printed 75nm lines/space feature with excellent profile control at a dose of 13(mu) C/cm2 at 75kV. The shaped beam vector scan system used here provides a unique property in resolving small features in lithography and throughput. Overhead in EL4+$ limits the systems ability to fully exploit the sensitivity of the new resist for throughput. The EL5 system has sufficiently low overhead that it is projected to print a 4X, 16G DRAM mask with OPC in under 3 hours with the CA resist. We will discuss the throughput advantages of the next generation EL5 system over the existing EL4+.

Patient characteristics associated with improved outcomes with use of an inhaled corticosteroid in preschool children at risk for asthma.

PubMed

Bacharier, Leonard B; Guilbert, Theresa W; Zeiger, Robert S; Strunk, Robert C; Morgan, Wayne J; Lemanske, Robert F; Moss, Mark; Szefler, Stanley J; Krawiec, Marzena; Boehmer, Susan; Mauger, David; Taussig, Lynn M; Martinez, Fernando D

2009-05-01

Maintenance inhaled corticosteroid (ICS) therapy in preschool children with recurrent wheezing at high-risk for development of asthma produces multiple clinical benefits. However, determination of baseline features associated with ICS responsiveness may identify children most likely to benefit from ICS treatment. To determine if demographic and atopic features predict response to ICS in preschool children at high risk for asthma. Two years of treatment with an ICS, fluticasone propionate (88 microg twice daily), was compared with matching placebo in a double-masked, randomized, multicenter study of 285 children 2 and 3 years old at high risk for asthma development. Baseline demographic and atopic features were related to clinical outcomes in a post hoc subgroup analysis. Multivariate analysis demonstrated significantly greater improvement with fluticasone than placebo in terms of episode-free days among boys, white subjects, participants with an emergency department (ED) visit or hospitalization within the past year, and those who experienced more symptomatic days at baseline. Children with aeroallergen sensitization experienced greater benefits in terms of oral corticosteroid use, urgent care and ED visits, and use of supplemental controller medications. More favorable responses to ICS than placebo in high-risk preschool children over a 2-year period were more likely in those with a ED visit or hospitalization for asthma within the past year, children with aeroallergen sensitization, boys, and white subjects.

Analysis and amelioration about the cross-sensitivity of a high resolution MOEMS accelerometer based on diffraction grating

NASA Astrophysics Data System (ADS)

Lu, Qianbo; Bai, Jian; Wang, Kaiwei; Lou, Shuqi; Jiao, Xufen; Han, Dandan

2016-10-01

Cross-sensitivity is a crucial parameter since it detrimentally affect the performance of an accelerometer, especially for a high resolution accelerometer. In this paper, a suite of analytical and finite-elements-method (FEM) models for characterizing the mechanism and features of the cross-sensitivity of a single-axis MOEMS accelerometer composed of a diffraction grating and a micromachined mechanical sensing chip are presented, which have not been systematically investigated yet. The mechanism and phenomena of the cross-sensitivity of this type MOEMS accelerometer based on diffraction grating differ quite a lot from the traditional ones owing to the identical sensing principle. By analyzing the models, some ameliorations and the modified design are put forward to suppress the cross-sensitivity. The modified design, achieved by double sides etching on a specific double-substrate-layer silicon-on-insulator (SOI) wafer, is validated to have a far smaller cross-sensitivity compared with the design previously reported in the literature. Moreover, this design can suppress the cross-sensitivity dramatically without compromising the acceleration sensitivity and resolution.

A Monolithic CMOS Magnetic Hall Sensor with High Sensitivity and Linearity Characteristics

PubMed Central

Huang, Haiyun; Wang, Dejun; Xu, Yue

2015-01-01

This paper presents a fully integrated linear Hall sensor by means of 0.8 μm high voltage complementary metal-oxide semiconductor (CMOS) technology. This monolithic Hall sensor chip features a highly sensitive horizontal switched Hall plate and an efficient signal conditioner using dynamic offset cancellation technique. An improved cross-like Hall plate achieves high magnetic sensitivity and low offset. A new spinning current modulator stabilizes the quiescent output voltage and improves the reliability of the signal conditioner. The tested results show that at the 5 V supply voltage, the maximum Hall output voltage of the monolithic Hall sensor microsystem, is up to ±2.1 V and the linearity of Hall output voltage is higher than 99% in the magnetic flux density range from ±5 mT to ±175 mT. The output equivalent residual offset is 0.48 mT and the static power consumption is 20 mW. PMID:26516864

A Monolithic CMOS Magnetic Hall Sensor with High Sensitivity and Linearity Characteristics.

PubMed

Huang, Haiyun; Wang, Dejun; Xu, Yue

2015-10-27

This paper presents a fully integrated linear Hall sensor by means of 0.8 μm high voltage complementary metal-oxide semiconductor (CMOS) technology. This monolithic Hall sensor chip features a highly sensitive horizontal switched Hall plate and an efficient signal conditioner using dynamic offset cancellation technique. An improved cross-like Hall plate achieves high magnetic sensitivity and low offset. A new spinning current modulator stabilizes the quiescent output voltage and improves the reliability of the signal conditioner. The tested results show that at the 5 V supply voltage, the maximum Hall output voltage of the monolithic Hall sensor microsystem, is up to ±2.1 V and the linearity of Hall output voltage is higher than 99% in the magnetic flux density range from ±5 mT to ±175 mT. The output equivalent residual offset is 0.48 mT and the static power consumption is 20 mW.

G Protein-Coupled Receptor Rhodopsin: A Prospectus

PubMed Central

Filipek, Sławomir; Stenkamp, Ronald E.; Teller, David C.; Palczewski, Krzysztof

2006-01-01

Rhodopsin is a retinal photoreceptor protein of bipartite structure consisting of the transmembrane protein opsin and a light-sensitive chromophore 11-cis-retinal, linked to opsin via a protonated Schiff base. Studies on rhodopsin have unveiled many structural and functional features that are common to a large and pharmacologically important group of proteins from the G protein-coupled receptor (GPCR) superfamily, of which rhodopsin is the best-studied member. In this work, we focus on structural features of rhodopsin as revealed by many biochemical and structural investigations. In particular, the high-resolution structure of bovine rhodopsin provides a template for understanding how GPCRs work. We describe the sensitivity and complexity of rhodopsin that lead to its important role in vision. PMID:12471166

Classification of CT examinations for COPD visual severity analysis

NASA Astrophysics Data System (ADS)

Tan, Jun; Zheng, Bin; Wang, Xingwei; Pu, Jiantao; Gur, David; Sciurba, Frank C.; Leader, J. Ken

2012-03-01

In this study we present a computational method of CT examination classification into visual assessed emphysema severity. The visual severity categories ranged from 0 to 5 and were rated by an experienced radiologist. The six categories were none, trace, mild, moderate, severe and very severe. Lung segmentation was performed for every input image and all image features are extracted from the segmented lung only. We adopted a two-level feature representation method for the classification. Five gray level distribution statistics, six gray level co-occurrence matrix (GLCM), and eleven gray level run-length (GLRL) features were computed for each CT image depicted segment lung. Then we used wavelets decomposition to obtain the low- and high-frequency components of the input image, and again extract from the lung region six GLCM features and eleven GLRL features. Therefore our feature vector length is 56. The CT examinations were classified using the support vector machine (SVM) and k-nearest neighbors (KNN) and the traditional threshold (density mask) approach. The SVM classifier had the highest classification performance of all the methods with an overall sensitivity of 54.4% and a 69.6% sensitivity to discriminate "no" and "trace visually assessed emphysema. We believe this work may lead to an automated, objective method to categorically classify emphysema severity on CT exam.

The performance improvement of automatic classification among obstructive lung diseases on the basis of the features of shape analysis, in addition to texture analysis at HRCT

NASA Astrophysics Data System (ADS)

Lee, Youngjoo; Kim, Namkug; Seo, Joon Beom; Lee, JuneGoo; Kang, Suk Ho

2007-03-01

In this paper, we proposed novel shape features to improve classification performance of differentiating obstructive lung diseases, based on HRCT (High Resolution Computerized Tomography) images. The images were selected from HRCT images, obtained from 82 subjects. For each image, two experienced radiologists selected rectangular ROIs with various sizes (16x16, 32x32, and 64x64 pixels), representing each disease or normal lung parenchyma. Besides thirteen textural features, we employed additional seven shape features; cluster shape features, and Top-hat transform features. To evaluate the contribution of shape features for differentiation of obstructive lung diseases, several experiments were conducted with two different types of classifiers and various ROI sizes. For automated classification, the Bayesian classifier and support vector machine (SVM) were implemented. To assess the performance and cross-validation of the system, 5-folding method was used. In comparison to employing only textural features, adding shape features yields significant enhancement of overall sensitivity(5.9, 5.4, 4.4% in the Bayesian and 9.0, 7.3, 5.3% in the SVM), in the order of ROI size 16x16, 32x32, 64x64 pixels, respectively (t-test, p<0.01). Moreover, this enhancement was largely due to the improvement on class-specific sensitivity of mild centrilobular emphysema and bronchiolitis obliterans which are most hard to differentiate for radiologists. According to these experimental results, adding shape features to conventional texture features is much useful to improve classification performance of obstructive lung diseases in both Bayesian and SVM classifiers.

Distinguishing early and late brain aging from the Alzheimer's disease spectrum: consistent morphological patterns across independent samples.

PubMed

Doan, Nhat Trung; Engvig, Andreas; Zaske, Krystal; Persson, Karin; Lund, Martina Jonette; Kaufmann, Tobias; Cordova-Palomera, Aldo; Alnæs, Dag; Moberget, Torgeir; Brækhus, Anne; Barca, Maria Lage; Nordvik, Jan Egil; Engedal, Knut; Agartz, Ingrid; Selbæk, Geir; Andreassen, Ole A; Westlye, Lars T

2017-09-01

Alzheimer's disease (AD) is a debilitating age-related neurodegenerative disorder. Accurate identification of individuals at risk is complicated as AD shares cognitive and brain features with aging. We applied linked independent component analysis (LICA) on three complementary measures of gray matter structure: cortical thickness, area and gray matter density of 137 AD, 78 mild (MCI) and 38 subjective cognitive impairment patients, and 355 healthy adults aged 18-78 years to identify dissociable multivariate morphological patterns sensitive to age and diagnosis. Using the lasso classifier, we performed group classification and prediction of cognition and age at different age ranges to assess the sensitivity and diagnostic accuracy of the LICA patterns in relation to AD, as well as early and late healthy aging. Three components showed high sensitivity to the diagnosis and cognitive status of AD, with different relationships with age: one reflected an anterior-posterior gradient in thickness and gray matter density and was uniquely related to diagnosis, whereas the other two, reflecting widespread cortical thickness and medial temporal lobe volume, respectively, also correlated significantly with age. Repeating the LICA decomposition and between-subject analysis on ADNI data, including 186 AD, 395 MCI and 220 age-matched healthy controls, revealed largely consistent brain patterns and clinical associations across samples. Classification results showed that multivariate LICA-derived brain characteristics could be used to predict AD and age with high accuracy (area under ROC curve up to 0.93 for classification of AD from controls). Comparison between classifiers based on feature ranking and feature selection suggests both common and unique feature sets implicated in AD and aging, and provides evidence of distinct age-related differences in early compared to late aging. Copyright © 2017 Elsevier Inc. All rights reserved.

Feature saliency and feedback information interactively impact visual category learning

PubMed Central

Hammer, Rubi; Sloutsky, Vladimir; Grill-Spector, Kalanit

2015-01-01

Visual category learning (VCL) involves detecting which features are most relevant for categorization. VCL relies on attentional learning, which enables effectively redirecting attention to object’s features most relevant for categorization, while ‘filtering out’ irrelevant features. When features relevant for categorization are not salient, VCL relies also on perceptual learning, which enables becoming more sensitive to subtle yet important differences between objects. Little is known about how attentional learning and perceptual learning interact when VCL relies on both processes at the same time. Here we tested this interaction. Participants performed VCL tasks in which they learned to categorize novel stimuli by detecting the feature dimension relevant for categorization. Tasks varied both in feature saliency (low-saliency tasks that required perceptual learning vs. high-saliency tasks), and in feedback information (tasks with mid-information, moderately ambiguous feedback that increased attentional load, vs. tasks with high-information non-ambiguous feedback). We found that mid-information and high-information feedback were similarly effective for VCL in high-saliency tasks. This suggests that an increased attentional load, associated with the processing of moderately ambiguous feedback, has little effect on VCL when features are salient. In low-saliency tasks, VCL relied on slower perceptual learning; but when the feedback was highly informative participants were able to ultimately attain the same performance as during the high-saliency VCL tasks. However, VCL was significantly compromised in the low-saliency mid-information feedback task. We suggest that such low-saliency mid-information learning scenarios are characterized by a ‘cognitive loop paradox’ where two interdependent learning processes have to take place simultaneously. PMID:25745404

A novel feature ranking method for prediction of cancer stages using proteomics data

PubMed Central

Saghapour, Ehsan; Sehhati, Mohammadreza

2017-01-01

Proteomic analysis of cancers' stages has provided new opportunities for the development of novel, highly sensitive diagnostic tools which helps early detection of cancer. This paper introduces a new feature ranking approach called FRMT. FRMT is based on the Technique for Order of Preference by Similarity to Ideal Solution method (TOPSIS) which select the most discriminative proteins from proteomics data for cancer staging. In this approach, outcomes of 10 feature selection techniques were combined by TOPSIS method, to select the final discriminative proteins from seven different proteomic databases of protein expression profiles. In the proposed workflow, feature selection methods and protein expressions have been considered as criteria and alternatives in TOPSIS, respectively. The proposed method is tested on seven various classifier models in a 10-fold cross validation procedure that repeated 30 times on the seven cancer datasets. The obtained results proved the higher stability and superior classification performance of method in comparison with other methods, and it is less sensitive to the applied classifier. Moreover, the final introduced proteins are informative and have the potential for application in the real medical practice. PMID:28934234

Combining targeted drugs to overcome and prevent resistance of solid cancers with some stem-like cell features

PubMed Central

Koivunen, Peppi; Koivunen, Jussi P.

2014-01-01

Treatment resistance significantly inhibits the efficiency of targeted cancer therapies in drug-sensitive genotypes. In the current work, we studied mechanisms for rapidly occurring, adaptive resistance in targeted therapy-sensitive lung, breast, and melanoma cancer cell lines. The results show that in ALK translocated lung cancer lines H3122 and H2228, cells with cancer stem-like cell features characterized by high expression of cancer stem cell markers and/or in vivo tumorigenesis can mediate adaptive resistance to oncogene ablative therapy. When pharmacological ablation of ALK oncogene was accompanied with PI3K inhibitor or salinomycin therapy, cancer stem-like cell features were reversed which was accompanied with decreased colony formation. Furthermore, co-targeting was able to block the formation of acquired resistance in H3122 line. The results suggest that cells with cancer stem-like cell features can mediate adaptive resistance to targeted therapies. Since these cells follow the stochastic model, concurrent therapy with an oncogene ablating agent and a stem-like cell-targeting drug is needed for maximal therapeutic efficiency. PMID:25238228

Tongue Images Classification Based on Constrained High Dispersal Network.

PubMed

Meng, Dan; Cao, Guitao; Duan, Ye; Zhu, Minghua; Tu, Liping; Xu, Dong; Xu, Jiatuo

2017-01-01

Computer aided tongue diagnosis has a great potential to play important roles in traditional Chinese medicine (TCM). However, the majority of the existing tongue image analyses and classification methods are based on the low-level features, which may not provide a holistic view of the tongue. Inspired by deep convolutional neural network (CNN), we propose a novel feature extraction framework called constrained high dispersal neural networks (CHDNet) to extract unbiased features and reduce human labor for tongue diagnosis in TCM. Previous CNN models have mostly focused on learning convolutional filters and adapting weights between them, but these models have two major issues: redundancy and insufficient capability in handling unbalanced sample distribution. We introduce high dispersal and local response normalization operation to address the issue of redundancy. We also add multiscale feature analysis to avoid the problem of sensitivity to deformation. Our proposed CHDNet learns high-level features and provides more classification information during training time, which may result in higher accuracy when predicting testing samples. We tested the proposed method on a set of 267 gastritis patients and a control group of 48 healthy volunteers. Test results show that CHDNet is a promising method in tongue image classification for the TCM study.

Automated quantification of surface water inundation in wetlands using optical satellite imagery

USGS Publications Warehouse

DeVries, Ben; Huang, Chengquan; Lang, Megan W.; Jones, John W.; Huang, Wenli; Creed, Irena F.; Carroll, Mark L.

2017-01-01

We present a fully automated and scalable algorithm for quantifying surface water inundation in wetlands. Requiring no external training data, our algorithm estimates sub-pixel water fraction (SWF) over large areas and long time periods using Landsat data. We tested our SWF algorithm over three wetland sites across North America, including the Prairie Pothole Region, the Delmarva Peninsula and the Everglades, representing a gradient of inundation and vegetation conditions. We estimated SWF at 30-m resolution with accuracies ranging from a normalized root-mean-square-error of 0.11 to 0.19 when compared with various high-resolution ground and airborne datasets. SWF estimates were more sensitive to subtle inundated features compared to previously published surface water datasets, accurately depicting water bodies, large heterogeneously inundated surfaces, narrow water courses and canopy-covered water features. Despite this enhanced sensitivity, several sources of errors affected SWF estimates, including emergent or floating vegetation and forest canopies, shadows from topographic features, urban structures and unmasked clouds. The automated algorithm described in this article allows for the production of high temporal resolution wetland inundation data products to support a broad range of applications.

The reliability of continuous brain responses during naturalistic listening to music.

PubMed

Burunat, Iballa; Toiviainen, Petri; Alluri, Vinoo; Bogert, Brigitte; Ristaniemi, Tapani; Sams, Mikko; Brattico, Elvira

2016-01-01

Low-level (timbral) and high-level (tonal and rhythmical) musical features during continuous listening to music, studied by functional magnetic resonance imaging (fMRI), have been shown to elicit large-scale responses in cognitive, motor, and limbic brain networks. Using a similar methodological approach and a similar group of participants, we aimed to study the replicability of previous findings. Participants' fMRI responses during continuous listening of a tango Nuevo piece were correlated voxelwise against the time series of a set of perceptually validated musical features computationally extracted from the music. The replicability of previous results and the present study was assessed by two approaches: (a) correlating the respective activation maps, and (b) computing the overlap of active voxels between datasets at variable levels of ranked significance. Activity elicited by timbral features was better replicable than activity elicited by tonal and rhythmical ones. These results indicate more reliable processing mechanisms for low-level musical features as compared to more high-level features. The processing of such high-level features is probably more sensitive to the state and traits of the listeners, as well as of their background in music. Copyright © 2015 Elsevier Inc. All rights reserved.

PH-sensitive dispersion of carbon nanotubes by myoglobin

NASA Astrophysics Data System (ADS)

Nie, Haiyu; Shen, Ganni; Sun, Junlin; Zhang, Tao

2017-03-01

A facile and effective method of dispersion of double-walled carbon nanotubes (DWNTs) was developed. At appropriate pH value and sonication, myoglobin helps the solubilization of DWNTs. The product is a pH-sensitive dispersion, which remains in a highly dispersed state at pH<3.0 and pH>10.0. This approach can be used to disperse DWNTs in scale. A reversible conversion of the highly dispersed state to the aggregated state could be observed by changing the pH value. This feature holds great promise for the development of pH sensors.

Developments in Scanning Hall Probe Microscopy

NASA Astrophysics Data System (ADS)

Chouinard, Taras; Chu, Ricky; David, Nigel; Broun, David

2009-05-01

Low temperature scanning Hall probe microscopy is a sensitive means of imaging magnetic structures with high spatial resolution and magnetic flux sensitivity approaching that of a Superconducting Quantum Interference Device. We have developed a scanning Hall probe microscope with novel features, including highly reliable coarse positioning, in situ optimization of sensor-sample alignment and capacitive transducers for linear, long range positioning measurement. This has been motivated by the need to reposition accurately above fabricated nanostructures such as small superconducting rings. Details of the design and performance will be presented as well as recent progress towards time-resolved measurements with sub nanosecond resolution.

Noise sensitivity and loudness derivative index for urban road traffic noise annoyance computation.

PubMed

Gille, Laure-Anne; Marquis-Favre, Catherine; Weber, Reinhard

2016-12-01

Urban road traffic composed of powered-two-wheelers (PTWs), buses, heavy, and light vehicles is a major source of noise annoyance. In order to assess annoyance models considering different acoustical and non-acoustical factors, a laboratory experiment on short-term annoyance due to urban road traffic noise was conducted. At the end of the experiment, participants were asked to rate their noise sensitivity and to describe the noise sequences they heard. This verbalization task highlights that annoyance ratings are highly influenced by the presence of PTWs and by different acoustical features: noise intensity, irregular temporal amplitude variation, regular amplitude modulation, and spectral content. These features, except irregular temporal amplitude variation, are satisfactorily characterized by the loudness, the total energy of tonal components and the sputtering and nasal indices. Introduction of the temporal derivative of loudness allows successful modeling of perceived amplitude variations. Its contribution to the tested annoyance models is high and seems to be higher than the contribution of mean loudness index. A multilevel regression is performed to assess annoyance models using selected acoustical indices and noise sensitivity. Three models are found to be promising for further studies that aim to enhance current annoyance models.

Direct Growth of Graphene Films on 3D Grating Structural Quartz Substrates for High-Performance Pressure-Sensitive Sensors.

PubMed

Song, Xuefen; Sun, Tai; Yang, Jun; Yu, Leyong; Wei, Dacheng; Fang, Liang; Lu, Bin; Du, Chunlei; Wei, Dapeng

2016-07-06

Conformal graphene films have directly been synthesized on the surface of grating microstructured quartz substrates by a simple chemical vapor deposition process. The wonderful conformality and relatively high quality of the as-prepared graphene on the three-dimensional substrate have been verified by scanning electron microscopy and Raman spectra. This conformal graphene film possesses excellent electrical and optical properties with a sheet resistance of <2000 Ω·sq(-1) and a transmittance of >80% (at 550 nm), which can be attached with a flat graphene film on a poly(dimethylsiloxane) substrate, and then could work as a pressure-sensitive sensor. This device possesses a high-pressure sensitivity of -6.524 kPa(-1) in a low-pressure range of 0-200 Pa. Meanwhile, this pressure-sensitive sensor exhibits super-reliability (≥5000 cycles) and an ultrafast response time (≤4 ms). Owing to these features, this pressure-sensitive sensor based on 3D conformal graphene is adequately introduced to test wind pressure, expressing higher accuracy and a lower background noise level than a market anemometer.

Diagnostic features of Alzheimer's disease extracted from PET sinograms

NASA Astrophysics Data System (ADS)

Sayeed, A.; Petrou, M.; Spyrou, N.; Kadyrov, A.; Spinks, T.

2002-01-01

Texture analysis of positron emission tomography (PET) images of the brain is a very difficult task, due to the poor signal to noise ratio. As a consequence, very few techniques can be implemented successfully. We use a new global analysis technique known as the Trace transform triple features. This technique can be applied directly to the raw sinograms to distinguish patients with Alzheimer's disease (AD) from normal volunteers. FDG-PET images of 18 AD and 10 normal controls obtained from the same CTI ECAT-953 scanner were used in this study. The Trace transform triple feature technique was used to extract features that were invariant to scaling, translation and rotation, referred to as invariant features, as well as features that were sensitive to rotation but invariant to scaling and translation, referred to as sensitive features in this study. The features were used to classify the groups using discriminant function analysis. Cross-validation tests using stepwise discriminant function analysis showed that combining both sensitive and invariant features produced the best results, when compared with the clinical diagnosis. Selecting the five best features produces an overall accuracy of 93% with sensitivity of 94% and specificity of 90%. This is comparable with the classification accuracy achieved by Kippenhan et al (1992), using regional metabolic activity.

Performance of a time-resolved fluorescence immunoassay for measuring varicella-zoster virus immunoglobulin G levels in adults and comparison with commercial enzyme immunoassays and Merck glycoprotein enzyme immunoassay.

PubMed

Maple, P A C; Gray, J; Breuer, J; Kafatos, G; Parker, S; Brown, D

2006-02-01

Highly sensitive and specific, quantitative assays are needed to detect varicella-zoster virus (VZV) immunoglobulin G in human sera, particularly for determining immune status and response following vaccination. A time-resolved fluorescence immunoassay (TRFIA) has been developed, and its performance was compared to that of two commercial enzyme immunoassays (EIAs) and Merck glycoprotein EIA (gpEIA). The TRFIA had equivalent sensitivity (97.8%) and high specificity (93.5%) in relation to gpEIA. A commercial (Behring) EIA compared favorably with TRFIA in terms of sensitivity (98.4%) but had lower specificity (80.7%). Another commercial EIA (Diamedix) had high specificity (97.1%) but low sensitivity (76.4%) compared to TRFIA if equivocal test results were treated as negative for VZV antibody. A novel feature of the TRFIA was that the cutoff was generated using population mixture modeling and was expressed in mIU/ml, as the assay was calibrated using the British standard VZV antibody.

Single-feature polymorphism discovery in the barley transcriptome

PubMed Central

Rostoks, Nils; Borevitz, Justin O; Hedley, Peter E; Russell, Joanne; Mudie, Sharon; Morris, Jenny; Cardle, Linda; Marshall, David F; Waugh, Robbie

2005-01-01

A probe-level model for analysis of GeneChip gene-expression data is presented which identified more than 10,000 single-feature polymorphisms (SFP) between two barley genotypes. The method has good sensitivity, as 67% of known single-nucleotide polymorphisms (SNP) were called as SFPs. This method is applicable to all oligonucleotide microarray data, accounts for SNP effects in gene-expression data and represents an efficient and versatile approach for highly parallel marker identification in large genomes. PMID:15960806

A fuzzy feature fusion method for auto-segmentation of gliomas with multi-modality diffusion and perfusion magnetic resonance images in radiotherapy.

PubMed

Guo, Lu; Wang, Ping; Sun, Ranran; Yang, Chengwen; Zhang, Ning; Guo, Yu; Feng, Yuanming

2018-02-19

The diffusion and perfusion magnetic resonance (MR) images can provide functional information about tumour and enable more sensitive detection of the tumour extent. We aimed to develop a fuzzy feature fusion method for auto-segmentation of gliomas in radiotherapy planning using multi-parametric functional MR images including apparent diffusion coefficient (ADC), fractional anisotropy (FA) and relative cerebral blood volume (rCBV). For each functional modality, one histogram-based fuzzy model was created to transform image volume into a fuzzy feature space. Based on the fuzzy fusion result of the three fuzzy feature spaces, regions with high possibility belonging to tumour were generated automatically. The auto-segmentations of tumour in structural MR images were added in final auto-segmented gross tumour volume (GTV). For evaluation, one radiation oncologist delineated GTVs for nine patients with all modalities. Comparisons between manually delineated and auto-segmented GTVs showed that, the mean volume difference was 8.69% (±5.62%); the mean Dice's similarity coefficient (DSC) was 0.88 (±0.02); the mean sensitivity and specificity of auto-segmentation was 0.87 (±0.04) and 0.98 (±0.01) respectively. High accuracy and efficiency can be achieved with the new method, which shows potential of utilizing functional multi-parametric MR images for target definition in precision radiation treatment planning for patients with gliomas.

Chromatic information and feature detection in fast visual analysis

DOE PAGES

Del Viva, Maria M.; Punzi, Giovanni; Shevell, Steven K.; ...

2016-08-01

The visual system is able to recognize a scene based on a sketch made of very simple features. This ability is likely crucial for survival, when fast image recognition is necessary, and it is believed that a primal sketch is extracted very early in the visual processing. Such highly simplified representations can be sufficient for accurate object discrimination, but an open question is the role played by color in this process. Rich color information is available in natural scenes, yet artist's sketches are usually monochromatic; and, black-andwhite movies provide compelling representations of real world scenes. Also, the contrast sensitivity ofmore » color is low at fine spatial scales. We approach the question from the perspective of optimal information processing by a system endowed with limited computational resources. We show that when such limitations are taken into account, the intrinsic statistical properties of natural scenes imply that the most effective strategy is to ignore fine-scale color features and devote most of the bandwidth to gray-scale information. We find confirmation of these information-based predictions from psychophysics measurements of fast-viewing discrimination of natural scenes. As a result, we conclude that the lack of colored features in our visual representation, and our overall low sensitivity to high-frequency color components, are a consequence of an adaptation process, optimizing the size and power consumption of our brain for the visual world we live in.« less

Chromatic information and feature detection in fast visual analysis

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

Del Viva, Maria M.; Punzi, Giovanni; Shevell, Steven K.

The visual system is able to recognize a scene based on a sketch made of very simple features. This ability is likely crucial for survival, when fast image recognition is necessary, and it is believed that a primal sketch is extracted very early in the visual processing. Such highly simplified representations can be sufficient for accurate object discrimination, but an open question is the role played by color in this process. Rich color information is available in natural scenes, yet artist's sketches are usually monochromatic; and, black-andwhite movies provide compelling representations of real world scenes. Also, the contrast sensitivity ofmore » color is low at fine spatial scales. We approach the question from the perspective of optimal information processing by a system endowed with limited computational resources. We show that when such limitations are taken into account, the intrinsic statistical properties of natural scenes imply that the most effective strategy is to ignore fine-scale color features and devote most of the bandwidth to gray-scale information. We find confirmation of these information-based predictions from psychophysics measurements of fast-viewing discrimination of natural scenes. As a result, we conclude that the lack of colored features in our visual representation, and our overall low sensitivity to high-frequency color components, are a consequence of an adaptation process, optimizing the size and power consumption of our brain for the visual world we live in.« less

Sonographic features of thyroid nodules that may help distinguish clinically atypical subacute thyroiditis from thyroid malignancy.

PubMed

Pan, Fu-shun; Wang, Wei; Wang, Yan; Xu, Ming; Liang, Jin-yu; Zheng, Yan-ling; Xie, Xiao-yan; Li, Xiao-xi

2015-04-01

The purpose of this study was to evaluate sonographic features for distinguishing clinically atypical subacute thyroiditis from malignant thyroid nodules. A total of 165 hypoechoic thyroid nodules without calcification in 135 patients with histologic diagnosis were included in this study. These nodules were classified into 2 groups: a thyroiditis group (55 nodules in 36 patients) and a malignancy group (110 nodules in 99 patients). The sonographic features of the groups were retrospectively reviewed. No significant differences were detected for the variables of marked echogenicity, a taller-than-wide shape, and mixed vascularity. However, a poorly defined margin was detected more frequently in the thyroiditis group than the malignancy group (P < .05); it yielded a high capability for differential diagnosis of atypical subacute thyroiditis, with sensitivity and specificity of 87.3% and 80.9%, respectively. Centripetal reduction echogenicity was observed exclusively in the thyroiditis group, with high specificity (100%) but low sensitivity (21.8%) for atypical subacute thyroiditis diagnosis. All of the thyroiditis nodules with a positive color signal showed noninternal vascularity (negative predictive value, 100%). There is a considerable overlap between the sonographic features of atypical subacute thyroiditis and thyroid malignancy. However, the margin, echogenicity, and vascularity type are helpful indicators for differential diagnosis of atypical subacute thyroiditis. © 2015 by the American Institute of Ultrasound in Medicine.

TADIR-production version: El-Op's high-resolution 480x4 TDI thermal imaging system

NASA Astrophysics Data System (ADS)

Sarusi, Gabby; Ziv, Natan; Zioni, O.; Gaber, J.; Shechterman, Mark S.; Lerner, M.

1999-07-01

Efforts invested at El-Op during the last four years have led to the development of TADIR - engineering model thermal imager, demonstrated in 1998, and eventually to the final production version of TADIR to be demonstrated in full operation during 1999. Both versions take advantage of the high resolution and high sensitivity obtained by the 480 X 4 TDI MCT detector as well as many more features implemented in the system to obtain a state of the art high- end thermal imager. The production version of TADIR uses a 480 X 6 TDI HgCdTe detector made by the SCD Israeli company. In this paper, we will present the main features of the production version of TADIR.

Artificial Neural Network for Probabilistic Feature Recognition in Liquid Chromatography Coupled to High-Resolution Mass Spectrometry.

PubMed

Woldegebriel, Michael; Derks, Eduard

2017-01-17

In this work, a novel probabilistic untargeted feature detection algorithm for liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) using artificial neural network (ANN) is presented. The feature detection process is approached as a pattern recognition problem, and thus, ANN was utilized as an efficient feature recognition tool. Unlike most existing feature detection algorithms, with this approach, any suspected chromatographic profile (i.e., shape of a peak) can easily be incorporated by training the network, avoiding the need to perform computationally expensive regression methods with specific mathematical models. In addition, with this method, we have shown that the high-resolution raw data can be fully utilized without applying any arbitrary thresholds or data reduction, therefore improving the sensitivity of the method for compound identification purposes. Furthermore, opposed to existing deterministic (binary) approaches, this method rather estimates the probability of a feature being present/absent at a given point of interest, thus giving chance for all data points to be propagated down the data analysis pipeline, weighed with their probability. The algorithm was tested with data sets generated from spiked samples in forensic and food safety context and has shown promising results by detecting features for all compounds in a computationally reasonable time.

First Images from HERO: A Hard-X-Ray Focusing Telescope

NASA Technical Reports Server (NTRS)

Ramsey, Brian D.; Alexander, Cheryl D.; Apple, Jeff A.; Benson, Carl M.; Dietz, Kurtis L.; Elsner, Ronald F.; Engelhaupt, Darell E.; Ghosh, Kajal K.; Kolodziejczak, Jeffery J.; ODell, Stephen L.;

Temperature-dependent THz vibrational spectra of clenbuterol hydrochloride

NASA Astrophysics Data System (ADS)

Yang, YuPing; Lei, XiangYun; Yue, Ai; Zhang, Zhenwei

2013-04-01

Using the high-resolution Terahertz Time-domain spectroscopy (THz-TDS) and the standard sample pellet technique, the far-infrared vibrational spectra of clenbuterol hydrochloride (CH), a β 2-adrenergic agonist for decreasing fat deposition and enhancing protein accretion, were measured in temperature range of 77-295 K. Between 0.2 and 3.6 THz (6.6-120.0 cm-1), seven highly resolved spectral features, strong line-narrowing and a frequency blue-shift were observed with cooling. However, ractopamine hydrochloride, with some structural and pharmacological similarities to clenbuterol hydrochloride, showed no spectral features, indicating high sensitivity and strong specificity of THz-TDS. These results could be used for the rapid and nondestructive CH residual detection in food safety control.

Atropos: specific, sensitive, and speedy trimming of sequencing reads.

PubMed

Didion, John P; Martin, Marcel; Collins, Francis S

2017-01-01

A key step in the transformation of raw sequencing reads into biological insights is the trimming of adapter sequences and low-quality bases. Read trimming has been shown to increase the quality and reliability while decreasing the computational requirements of downstream analyses. Many read trimming software tools are available; however, no tool simultaneously provides the accuracy, computational efficiency, and feature set required to handle the types and volumes of data generated in modern sequencing-based experiments. Here we introduce Atropos and show that it trims reads with high sensitivity and specificity while maintaining leading-edge speed. Compared to other state-of-the-art read trimming tools, Atropos achieves significant increases in trimming accuracy while remaining competitive in execution times. Furthermore, Atropos maintains high accuracy even when trimming data with elevated rates of sequencing errors. The accuracy, high performance, and broad feature set offered by Atropos makes it an appropriate choice for the pre-processing of Illumina, ABI SOLiD, and other current-generation short-read sequencing datasets. Atropos is open source and free software written in Python (3.3+) and available at https://github.com/jdidion/atropos.

Atropos: specific, sensitive, and speedy trimming of sequencing reads

PubMed Central

Collins, Francis S.

2017-01-01

A key step in the transformation of raw sequencing reads into biological insights is the trimming of adapter sequences and low-quality bases. Read trimming has been shown to increase the quality and reliability while decreasing the computational requirements of downstream analyses. Many read trimming software tools are available; however, no tool simultaneously provides the accuracy, computational efficiency, and feature set required to handle the types and volumes of data generated in modern sequencing-based experiments. Here we introduce Atropos and show that it trims reads with high sensitivity and specificity while maintaining leading-edge speed. Compared to other state-of-the-art read trimming tools, Atropos achieves significant increases in trimming accuracy while remaining competitive in execution times. Furthermore, Atropos maintains high accuracy even when trimming data with elevated rates of sequencing errors. The accuracy, high performance, and broad feature set offered by Atropos makes it an appropriate choice for the pre-processing of Illumina, ABI SOLiD, and other current-generation short-read sequencing datasets. Atropos is open source and free software written in Python (3.3+) and available at https://github.com/jdidion/atropos. PMID:28875074

Dual-band plasmonic resonator based on Jerusalem cross-shaped nanoapertures

NASA Astrophysics Data System (ADS)

Cetin, Arif E.; Kaya, Sabri; Mertiri, Alket; Aslan, Ekin; Erramilli, Shyamsunder; Altug, Hatice; Turkmen, Mustafa

2015-06-01

In this paper, we both experimentally and numerically introduce a dual-resonant metamaterial based on subwavelength Jerusalem cross-shaped apertures. We numerically investigate the physical origin of the dual-resonant behavior, originating from the constituting aperture elements, through finite difference time domain calculations. Our numerical calculations show that at the dual-resonances, the aperture system supports large and easily accessible local electromagnetic fields. In order to experimentally realize the aperture system, we utilize a high-precision and lift-off free fabrication method based on electron-beam lithography. We also introduce a fine-tuning mechanism for controlling the dual-resonant spectral response through geometrical device parameters. Finally, we show the aperture system's highly advantageous far- and near-field characteristics through numerical calculations on refractive index sensitivity. The quantitative analyses on the availability of the local fields supported by the aperture system are employed to explain the grounds behind the sensitivity of each spectral feature within the dual-resonant behavior. Possessing dual-resonances with large and accessible electromagnetic fields, Jerusalem cross-shaped apertures can be highly advantageous for wide range of applications demanding multiple spectral features with strong nearfield characteristics.

Clinical Effectiveness of Prospectively Reported Sonographic Twinkling Artifact for the Diagnosis of Renal Calculus in Patients Without Known Urolithiasis.

PubMed

Masch, William R; Cohan, Richard H; Ellis, James H; Dillman, Jonathan R; Rubin, Jonathan M; Davenport, Matthew S

2016-02-01

The purpose of this study was to determine the clinical effectiveness of prospectively reported sonographic twinkling artifact for the diagnosis of renal calculus in patients without known urolithiasis. All ultrasound reports finalized in one health system from June 15, 2011, to June 14, 2014, that contained the words "twinkle" or "twinkling" in reference to suspected renal calculus were identified. Patients with known urolithiasis or lack of a suitable reference standard (unenhanced abdominal CT with ≤ 2.5-mm slice thickness performed ≤ 30 days after ultrasound) were excluded. The sensitivity, specificity, and positive likelihood ratio of sonographic twinkling artifact for the diagnosis of renal calculus were calculated by renal unit and stratified by two additional diagnostic features for calcification (echogenic focus, posterior acoustic shadowing). Eighty-five patients formed the study population. Isolated sonographic twinkling artifact had sensitivity of 0.78 (82/105), specificity of 0.40 (26/65), and a positive likelihood ratio of 1.30 for the diagnosis of renal calculus. Specificity and positive likelihood ratio improved and sensitivity declined when the following additional diagnostic features were present: sonographic twinkling artifact and echogenic focus (sensitivity, 0.61 [64/105]; specificity, 0.65 [42/65]; positive likelihood ratio, 1.72); sonographic twinkling artifact and posterior acoustic shadowing (sensitivity, 0.31 [33/105]; specificity, 0.95 [62/65]; positive likelihood ratio, 6.81); all three features (sensitivity, 0.31 [33/105]; specificity, 0.95 [62/65]; positive likelihood ratio, 6.81). Isolated sonographic twinkling artifact has a high false-positive rate (60%) for the diagnosis of renal calculus in patients without known urolithiasis.

Highly efficient monolithic dye-sensitized solar cells.

PubMed

Kwon, Jeong; Park, Nam-Gyu; Lee, Jun Young; Ko, Min Jae; Park, Jong Hyeok

2013-03-01

Monolithic dye-sensitized solar cells (M-DSSCs) provide an effective way to reduce the fabrication cost of general DSSCs since they do not require transparent conducting oxide substrates for the counter electrode. However, conventional monolithic devices have low efficiency because of the impediments resulting from counter electrode materials and spacer layers. Here, we demonstrate highly efficient M-DSSCs featuring a highly conductive polymer combined with macroporous polymer spacer layers. With M-DSSCs based on a PEDOT/polymer spacer layer, a power conversion efficiency of 7.73% was achieved, which is, to the best of our knowledge, the highest efficiency for M-DSSCs to date. Further, PEDOT/polymer spacer layers were applied to flexible DSSCs and their cell performance was investigated.

Diamond X-ray Photodiode for White and Monochromatic SR beams

PubMed Central

Keister, Jeffrey W.; Smedley, John; Muller, Erik M.; Bohon, Jen; Héroux, Annie

2011-01-01

High purity, single crystal CVD diamond plates are screened for quality and instrumented into a sensor assembly for quantitative characterization of flux and position sensitivity. Initial investigations have yielded encouraging results and have led to further development. Several limiting complications are observed and discussed, as well as mitigations thereof. For example, diamond quality requirements for x-ray diodes include low nitrogen impurity and crystallographic defectivity. Thin electrode windows and electronic readout performance are ultimately also critical to device performance. Promising features observed so far from prototype devices include calculable responsivity, flux linearity, position sensitivity and timing performance. Recent results from testing in high flux and high speed applications are described. PMID:21822344

Graphene-Based Long-Period Fiber Grating Surface Plasmon Resonance Sensor for High-Sensitivity Gas Sensing

PubMed Central

Wei, Wei; Nong, Jinpeng; Zhang, Guiwen; Tang, Linlong; Jiang, Xiao; Chen, Na; Luo, Suqin; Lan, Guilian; Zhu, Yong

2016-01-01

A graphene-based long-period fiber grating (LPFG) surface plasmon resonance (SPR) sensor is proposed. A monolayer of graphene is coated onto the Ag film surface of the LPFG SPR sensor, which increases the intensity of the evanescent field on the surface of the fiber and thereby enhances the interaction between the SPR wave and molecules. Such features significantly improve the sensitivity of the sensor. The experimental results demonstrate that the sensitivity of the graphene-based LPFG SPR sensor can reach 0.344 nm%−1 for methane, which is improved 2.96 and 1.31 times with respect to the traditional LPFG sensor and Ag-coated LPFG SPR sensor, respectively. Meanwhile, the graphene-based LPFG SPR sensor exhibits excellent response characteristics and repeatability. Such a SPR sensing scheme offers a promising platform to achieve high sensitivity for gas-sensing applications. PMID:28025483

MOF-Bacteriophage Biosensor for Highly Sensitive and Specific Detection of Staphylococcus aureus.

PubMed

Bhardwaj, Neha; Bhardwaj, Sanjeev K; Mehta, Jyotsana; Kim, Ki-Hyun; Deep, Akash

2017-10-04

To produce a sensitive and specific biosensor for Staphylococcus aureus, bacteriophages have been interfaced with a water-dispersible and environmentally stable metal-organic framework (MOF), NH 2 -MIL-53(Fe). The conjugation of the MOF with bacteriophages has been achieved through the use of glutaraldehyde as cross-linker. Highly sensitive detection of S. aureus in both synthetic and real samples was realized by the proposed MOF-bacteriophage biosensor based on the photoluminescence quenching phenomena: limit of detection (31 CFU/mL) and range of detection (40 to 4 × 10 8 CFU/mL). This is the first report exploiting the use of an MOF-bacteriophage complex for the biosensing of S. aureus. The results of our study highlight that the proposed biosensor is more sensitive than most of the previous methods while exhibiting some advanced features like specificity, regenerability, extended range of linear detection, and stability for long-term storage (even at room temperature).

Safer energetic materials by a nanotechnological approach.

PubMed

Siegert, Benny; Comet, Marc; Spitzer, Denis

2011-09-01

Energetic materials - explosives, thermites, populsive powders - are used in a variety of military and civilian applications. Their mechanical and electrostatic sensitivity is high in many cases, which can lead to accidents during handling and transport. These considerations limit the practical use of some energetic materials despite their good performance. For industrial applications, safety is one of the main criteria for selecting energetic materials. The sensitivity has been regarded as an intrinsic property of a substance for a long time. However, in recent years, several approaches to lower the sensitivity of a given substance, using nanotechnology and materials engineering, have been described. This feature article gives an overview over ways to prepare energetic (nano-)materials with a lower sensitivity.

Cost-Sensitive Local Binary Feature Learning for Facial Age Estimation.

PubMed

Lu, Jiwen; Liong, Venice Erin; Zhou, Jie

2015-12-01

In this paper, we propose a cost-sensitive local binary feature learning (CS-LBFL) method for facial age estimation. Unlike the conventional facial age estimation methods that employ hand-crafted descriptors or holistically learned descriptors for feature representation, our CS-LBFL method learns discriminative local features directly from raw pixels for face representation. Motivated by the fact that facial age estimation is a cost-sensitive computer vision problem and local binary features are more robust to illumination and expression variations than holistic features, we learn a series of hashing functions to project raw pixel values extracted from face patches into low-dimensional binary codes, where binary codes with similar chronological ages are projected as close as possible, and those with dissimilar chronological ages are projected as far as possible. Then, we pool and encode these local binary codes within each face image as a real-valued histogram feature for face representation. Moreover, we propose a cost-sensitive local binary multi-feature learning method to jointly learn multiple sets of hashing functions using face patches extracted from different scales to exploit complementary information. Our methods achieve competitive performance on four widely used face aging data sets.

Genetic Particle Swarm Optimization-Based Feature Selection for Very-High-Resolution Remotely Sensed Imagery Object Change Detection.

PubMed

Chen, Qiang; Chen, Yunhao; Jiang, Weiguo

2016-07-30

In the field of multiple features Object-Based Change Detection (OBCD) for very-high-resolution remotely sensed images, image objects have abundant features and feature selection affects the precision and efficiency of OBCD. Through object-based image analysis, this paper proposes a Genetic Particle Swarm Optimization (GPSO)-based feature selection algorithm to solve the optimization problem of feature selection in multiple features OBCD. We select the Ratio of Mean to Variance (RMV) as the fitness function of GPSO, and apply the proposed algorithm to the object-based hybrid multivariate alternative detection model. Two experiment cases on Worldview-2/3 images confirm that GPSO can significantly improve the speed of convergence, and effectively avoid the problem of premature convergence, relative to other feature selection algorithms. According to the accuracy evaluation of OBCD, GPSO is superior at overall accuracy (84.17% and 83.59%) and Kappa coefficient (0.6771 and 0.6314) than other algorithms. Moreover, the sensitivity analysis results show that the proposed algorithm is not easily influenced by the initial parameters, but the number of features to be selected and the size of the particle swarm would affect the algorithm. The comparison experiment results reveal that RMV is more suitable than other functions as the fitness function of GPSO-based feature selection algorithm.

[MRI semiotics features of experimental acute intracerebral hematomas].

PubMed

Burenchev, D V; Skvortsova, V I; Tvorogova, T V; Guseva, O I; Gubskiĭ, L V; Kupriianov, D A; Pirogov, Iu A

2009-01-01

The aim of this study was to assess the possibility of revealing intracerebral hematomas (ICH), using MRI, within the first hours after onset and to determine their MRI semiotics features. Thirty animals with experimental ICH were studied. A method of two-stage introduction of autologous blood was used to develop ICH as human spontaneous intracranial hematomas. Within 3-5h after blood introduction to the rat brain. The control MRI was performed in the 3rd and 7th days after blood injections. ICH were definitely identified in the first MRI scans. The MRI semiotics features of acute ICH and their transformations were assessed. The high sensitivity of MRI to ICH as well as the uniform manifestations in all animals were shown. In conclusion, the method has high specificity for acute ICH detection.

Jet-images — deep learning edition

DOE PAGES

de Oliveira, Luke; Kagan, Michael; Mackey, Lester; ...

2016-07-13

Building on the notion of a particle physics detector as a camera and the collimated streams of high energy particles, or jets, it measures as an image, we investigate the potential of machine learning techniques based on deep learning architectures to identify highly boosted W bosons. Modern deep learning algorithms trained on jet images can out-perform standard physically-motivated feature driven approaches to jet tagging. We develop techniques for visualizing how these features are learned by the network and what additional information is used to improve performance. Finally, this interplay between physically-motivated feature driven tools and supervised learning algorithms is generalmore » and can be used to significantly increase the sensitivity to discover new particles and new forces, and gain a deeper understanding of the physics within jets.« less

Jet-images — deep learning edition

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

de Oliveira, Luke; Kagan, Michael; Mackey, Lester

Building on the notion of a particle physics detector as a camera and the collimated streams of high energy particles, or jets, it measures as an image, we investigate the potential of machine learning techniques based on deep learning architectures to identify highly boosted W bosons. Modern deep learning algorithms trained on jet images can out-perform standard physically-motivated feature driven approaches to jet tagging. We develop techniques for visualizing how these features are learned by the network and what additional information is used to improve performance. Finally, this interplay between physically-motivated feature driven tools and supervised learning algorithms is generalmore » and can be used to significantly increase the sensitivity to discover new particles and new forces, and gain a deeper understanding of the physics within jets.« less

CA resist with high sensitivity and sub-100-nm resolution for advanced mask and device making

NASA Astrophysics Data System (ADS)

Kwong, Ranee W.; Huang, Wu-Song; Hartley, John G.; Moreau, Wayne M.; Robinson, Christopher F.; Angelopoulos, Marie; Magg, Christopher; Lawliss, Mark

2000-07-01

Recently, there is significant interest in using CA resists for electron beam (E-Beam) applications including mask making, direct write, and projection printing. CA resists provide superior lithographic performance in comparison to traditional non CA E-beam resists in particular high contrast, resolution, and sensitivity. However, most of the commercially available CA resists have the concern of airborne base contaminants and sensitivity to PAB and/or PEB temperatures. In this presentation, we will discuss a new improved ketal resist system referred to as KRS-XE which exhibits excellent lithography, is robust toward airborne base, compatible with 0.263 N TMAH aqueous developer and exhibits a large PAB/PEB latitude. With the combination of a high performance mask making E-beam exposure tool, high kV (75 kV) shaped beam system EL4+ and the KRS-XE resist, we have printed 75 nm lines/space features with excellent profile control at a dose of 13 (mu) C/cm2 at 75 kV. The shaped beam vector scan system used here provides an unique property in resolving small features in lithography and throughput. Overhead in EL4+ limits the systems ability to fully exploit the sensitivity of the new resist for throughput. The EL5 system, currently in the build phase, has sufficiently low overhead that it is projected to print a 4X, 16G, DRAM mask with OPC in under 3 hours with the CA resist. We will discuss the throughput advantages of the next generation EL5 system over the existing EL4+. In addition we will show the resolution of KRS-XE down to 70 nm using the PREVAIL projection printing system.

Sarcoidosis diagnostic score (SDS): a systematic evaluation to enhance the diagnosis of sarcoidosis.

PubMed

Bickett, Alexandra N; Lower, Elyse E; Baughman, Robert P

2018-05-17

The diagnosis of sarcoidosis is made by the combination of clinical features and biopsy results. The clinical features of sarcoidosis can be quite variable. We developed a Sarcoidosis Diagnostic Score (SDS) to summarize the clinical features of possible sarcoidosis patients. Biopsy confirmed sarcoidosis patients seen during a seven-month time period at the University of Cincinnati Sarcoidosis clinic were prospectively identified. Non-sarcoidosis patients seen at the same clinic were used as controls. Using a modified WASOG organ assessment instrument, we scored all patients for presence of biopsy, one or more highly probable symptom, and one or more at least probable symptom for each area. Two sarcoidosis scores were generated: SDS biopsy (with biopsy) and SDS clinical (without biopsy). The 980 evaluable patients were divided into two cohorts: an initial 600 patients (450 biopsy confirmed sarcoidosis, 150 controls) to establish cut-off values for SDS biopsy and SDS clinical and a validation cohort of 380 patients (103 biopsy confirmed sarcoidosis patients and 277 controls). The best cutoff value for SDS biopsy was > 6 (sensitivity =99.3%; specificity=100%). For the total the 980 patients, an SDS clinical > 3 had a sensitivity of 94.2%, specificity of 88.8%, and a likelihood ratio of 7.9. An SDS clinical score > 4 had a lower sensitivity of (76.9%) but higher specificity (98.6%). For sarcoidosis, the presence of specific clinical features, especially multi-organ involvement, can enhance the diagnostic certainty. The SDS scoring system quantitated the clinical features consistent with sarcoidosis. Copyright © 2018. Published by Elsevier Inc.

Inference of physical/biological dynamics from synthetic ocean colour images

NASA Technical Reports Server (NTRS)

Eert, J.; Holloway, G.; Gower, J. F. R.; Denman, K.; Abbott, M.

1987-01-01

High resolution numerical experiments with well resolved eddies are performed including advection of a biologically active plankton field. Shelf wave propagation and bottom topographic features are included. The resulting synthetic ocean color fields are examined for sensitivity to the (known) underlying physical dynamics.

Computer-aided Classification of Mammographic Masses Using Visually Sensitive Image Features

PubMed Central

Wang, Yunzhi; Aghaei, Faranak; Zarafshani, Ali; Qiu, Yuchen; Qian, Wei; Zheng, Bin

2017-01-01

Purpose To develop a new computer-aided diagnosis (CAD) scheme that computes visually sensitive image features routinely used by radiologists to develop a machine learning classifier and distinguish between the malignant and benign breast masses detected from digital mammograms. Methods An image dataset including 301 breast masses was retrospectively selected. From each segmented mass region, we computed image features that mimic five categories of visually sensitive features routinely used by radiologists in reading mammograms. We then selected five optimal features in the five feature categories and applied logistic regression models for classification. A new CAD interface was also designed to show lesion segmentation, computed feature values and classification score. Results Areas under ROC curves (AUC) were 0.786±0.026 and 0.758±0.027 when to classify mass regions depicting on two view images, respectively. By fusing classification scores computed from two regions, AUC increased to 0.806±0.025. Conclusion This study demonstrated a new approach to develop CAD scheme based on 5 visually sensitive image features. Combining with a “visual aid” interface, CAD results may be much more easily explainable to the observers and increase their confidence to consider CAD generated classification results than using other conventional CAD approaches, which involve many complicated and visually insensitive texture features. PMID:27911353

Boundary Layer Remote Sensing with Combined Active and Passive Techniques: GPS Radio Occultation and High-Resolution Stereo Imaging (WindCam) Small Satellite Concept

NASA Technical Reports Server (NTRS)

Mannucci, A.J.; Wu, D.L.; Teixeira, J.; Ao, C.O.; Xie, F.; Diner, D.J.; Wood, R.; Turk, Joe

2012-01-01

Objective: significant progress in understanding low-cloud boundary layer processes. This is the Single largest uncertainty in climate projections. Radio occultation has unique features suited to boundary layer remote sensing (1) Cloud penetrating (2) Very high vertical resolution (approximately 50m-100m) (3) Sensitivity to thermodynamic variables

Incorporation of beams into bossed diaphragm for a high sensitivity and overload micro pressure sensor

NASA Astrophysics Data System (ADS)

Yu, Zhongliang; Zhao, Yulong; Sun, Lu; Tian, Bian; Jiang, Zhuangde

2013-01-01

The paper presents a piezoresistive absolute micro pressure sensor, which is of great benefits for altitude location. In this investigation, the design, fabrication, and test of the sensor are involved. By analyzing the stress distribution of sensitive elements using finite element method, a novel structure through the introduction of sensitive beams into traditional bossed diaphragm is built up. The proposed configuration presents its advantages in terms of high sensitivity and high overload resistance compared with the conventional bossed diaphragm and flat diaphragm structures. Curve fittings of surface stress and deflection based on ANSYS simulation results are performed to establish the equations about the sensor. Nonlinear optimization by MATLAB is carried out to determine the structure dimensions. The output signals in both static and dynamic environments are evaluated. Silicon bulk micromachining technology is utilized to fabricate the sensor prototype, and the fabrication process is discussed. Experimental results demonstrate the sensor features a high sensitivity of 11.098 μV/V/Pa in the operating range of 500 Pa at room temperature, and a high overload resistance of 200 times overpressure to promise its survival under atmosphere. Due to the excellent performance above, the sensor can be applied in measuring the absolute micro pressure lower than 500 Pa.

Transparent, Flexible, Conformal Capacitive Pressure Sensors with Nanoparticles.

PubMed

Kim, Hyeohn; Kim, Gwangmook; Kim, Taehoon; Lee, Sangwoo; Kang, Donyoung; Hwang, Min-Soo; Chae, Youngcheol; Kang, Shinill; Lee, Hyungsuk; Park, Hong-Gyu; Shim, Wooyoung

2018-02-01

The fundamental challenge in designing transparent pressure sensors is the ideal combination of high optical transparency and high pressure sensitivity. Satisfying these competing demands is commonly achieved by a compromise between the transparency and usage of a patterned dielectric surface, which increases pressure sensitivity, but decreases transparency. Herein, a design strategy for fabricating high-transparency and high-sensitivity capacitive pressure sensors is proposed, which relies on the multiple states of nanoparticle dispersity resulting in enhanced surface roughness and light transmittance. We utilize two nanoparticle dispersion states on a surface: (i) homogeneous dispersion, where each nanoparticle (≈500 nm) with a size comparable to the visible light wavelength has low light scattering; and (ii) heterogeneous dispersion, where aggregated nanoparticles form a micrometer-sized feature, increasing pressure sensitivity. This approach is experimentally verified using a nanoparticle-dispersed polymer composite, which has high pressure sensitivity (1.0 kPa -1 ), and demonstrates excellent transparency (>95%). We demonstrate that the integration of nanoparticle-dispersed capacitor elements into an array readily yields a real-time pressure monitoring application and a fully functional touch device capable of acting as a pressure sensor-based input device, thereby opening up new avenues to establish processing techniques that are effective on the nanoscale yet applicable to macroscopic processing. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Effect of commensals and probiotics on visceral sensitivity and pain in irritable bowel syndrome

PubMed Central

Theodorou, Vassilia; Belgnaoui, Afifa Ait; Agostini, Simona; Eutamene, Helene

2014-01-01

The last ten years’ wide progress in the gut microbiota phylogenetic and functional characterization has been made evidencing dysbiosis in several gastrointestinal diseases including inflammatory bowel diseases and irritable bowel syndrome (IBS). IBS is a functional gut disease with high prevalence and negative impact on patient’s quality of life characterized mainly by visceral pain and/or discomfort, representing a good paradigm of chronic gut hypersensitivity. The IBS features are strongly regulated by bidirectional gut-brain interactions and there is increasing evidence for the involvement of gut bacteria and/or their metabolites in these features, including visceral pain. Further, gut microbiota modulation by antibiotics or probiotics has been promising in IBS. Mechanistic data provided mainly by animal studies highlight that commensals or probiotics may exert a direct action through bacterial metabolites on sensitive nerve endings in the gut mucosa, or indirect pathways targeting the intestinal epithelial barrier, the mucosal and/or systemic immune activation, and subsequent neuronal sensitization and/or activation. PMID:25184834

High-Performance Piezoresistive MEMS Strain Sensor with Low Thermal Sensitivity

PubMed Central

Mohammed, Ahmed A. S.; Moussa, Walied A.; Lou, Edmond

2011-01-01

This paper presents the experimental evaluation of a new piezoresistive MEMS strain sensor. Geometric characteristics of the sensor silicon carrier have been employed to improve the sensor sensitivity. Surface features or trenches have been introduced in the vicinity of the sensing elements. These features create stress concentration regions (SCRs) and as a result, the strain/stress field was altered. The improved sensing sensitivity compensated for the signal loss. The feasibility of this methodology was proved in a previous work using Finite Element Analysis (FEA). This paper provides the experimental part of the previous study. The experiments covered a temperature range from −50 °C to +50 °C. The MEMS sensors are fabricated using five different doping concentrations. FEA is also utilized to investigate the effect of material properties and layer thickness of the bonding adhesive on the sensor response. The experimental findings are compared to the simulation results to guide selection of bonding adhesive and installation procedure. Finally, FEA was used to analyze the effect of rotational/alignment errors. PMID:22319384

High-sensitivity acoustic sensors from nanofibre webs.

PubMed

Lang, Chenhong; Fang, Jian; Shao, Hao; Ding, Xin; Lin, Tong

2016-03-23

Considerable interest has been devoted to converting mechanical energy into electricity using polymer nanofibres. In particular, piezoelectric nanofibres produced by electrospinning have shown remarkable mechanical energy-to-electricity conversion ability. However, there is little data for the acoustic-to-electric conversion of electrospun nanofibres. Here we show that electrospun piezoelectric nanofibre webs have a strong acoustic-to-electric conversion ability. Using poly(vinylidene fluoride) as a model polymer and a sensor device that transfers sound directly to the nanofibre layer, we show that the sensor devices can detect low-frequency sound with a sensitivity as high as 266 mV Pa(-1). They can precisely distinguish sound waves in low to middle frequency region. These features make them especially suitable for noise detection. Our nanofibre device has more than five times higher sensitivity than a commercial piezoelectric poly(vinylidene fluoride) film device. Electrospun piezoelectric nanofibres may be useful for developing high-performance acoustic sensors.

High-sensitivity acoustic sensors from nanofibre webs

PubMed Central

Lang, Chenhong; Fang, Jian; Shao, Hao; Ding, Xin; Lin, Tong

2016-01-01

Considerable interest has been devoted to converting mechanical energy into electricity using polymer nanofibres. In particular, piezoelectric nanofibres produced by electrospinning have shown remarkable mechanical energy-to-electricity conversion ability. However, there is little data for the acoustic-to-electric conversion of electrospun nanofibres. Here we show that electrospun piezoelectric nanofibre webs have a strong acoustic-to-electric conversion ability. Using poly(vinylidene fluoride) as a model polymer and a sensor device that transfers sound directly to the nanofibre layer, we show that the sensor devices can detect low-frequency sound with a sensitivity as high as 266 mV Pa−1. They can precisely distinguish sound waves in low to middle frequency region. These features make them especially suitable for noise detection. Our nanofibre device has more than five times higher sensitivity than a commercial piezoelectric poly(vinylidene fluoride) film device. Electrospun piezoelectric nanofibres may be useful for developing high-performance acoustic sensors. PMID:27005010

Near Infrared Emission of Highly Electronically Excited CO: A Sensitive Probe to Study the Interstellar Medium??

NASA Technical Reports Server (NTRS)

Gudipati, Murthy S.

2002-01-01

Among the various spectroscopic features of the second most abundant molecule in the space, CO, "the triplet - triplet transitions involving the lowest triplet state a(sup 3)II and the higher-lying a(sup 1)3 SIGMA (sup +), d(sup 3) (DELTA), e (sup 3) SIGMA (sup -) states spanning near-UV to mid-IR spectral range" have so far not been explored in astrophysical observations. The energies of these transitions are highly sensitive to the surroundings in which CO exists, i.e. gas-phase, polar or non-polar condensed phase. It is proposed here that these triplet-triplet emission/absorption bands can be used as a sensitive probe to investigate the local environments of CO, whether in the planetary atmosphere, stellar atmosphere or interstellar medium.

Accuracy of computed tomographic features in differentiating intestinal tuberculosis from Crohn's disease: a systematic review with meta-analysis.

PubMed

Kedia, Saurabh; Sharma, Raju; Sreenivas, Vishnubhatla; Madhusudhan, Kumble Seetharama; Sharma, Vishal; Bopanna, Sawan; Pratap Mouli, Venigalla; Dhingra, Rajan; Yadav, Dawesh Prakash; Makharia, Govind; Ahuja, Vineet

2017-04-01

Abdominal computed tomography (CT) can noninvasively image the entire gastrointestinal tract and assess extraintestinal features that are important in differentiating Crohn's disease (CD) and intestinal tuberculosis (ITB). The present meta-analysis pooled the results of all studies on the role of CT abdomen in differentiating between CD and ITB. We searched PubMed and Embase for all publications in English that analyzed the features differentiating between CD and ITB on abdominal CT. The features included comb sign, necrotic lymph nodes, asymmetric bowel wall thickening, skip lesions, fibrofatty proliferation, mural stratification, ileocaecal area, long segment, and left colonic involvements. Sensitivity, specificity, positive and negative likelihood ratios, and diagnostic odds ratio (DOR) were calculated for all the features. Symmetric receiver operating characteristic curve was plotted for features present in >3 studies. Heterogeneity and publication bias was assessed and sensitivity analysis was performed by excluding studies that compared features on conventional abdominal CT instead of CT enterography (CTE). We included 6 studies (4 CTE, 1 conventional abdominal CT, and 1 CTE+conventional abdominal CT) involving 417 and 195 patients with CD and ITB, respectively. Necrotic lymph nodes had the highest diagnostic accuracy (sensitivity, 23%; specificity, 100%; DOR, 30.2) for ITB diagnosis, and comb sign (sensitivity, 82%; specificity, 81%; DOR, 21.5) followed by skip lesions (sensitivity, 86%; specificity, 74%; DOR, 16.5) had the highest diagnostic accuracy for CD diagnosis. On sensitivity analysis, the diagnostic accuracy of other features excluding asymmetric bowel wall thickening remained similar. Necrotic lymph nodes and comb sign on abdominal CT had the best diagnostic accuracy in differentiating CD and ITB.

Differential diagnosis of neurodegenerative diseases using structural MRI data

PubMed Central

Koikkalainen, Juha; Rhodius-Meester, Hanneke; Tolonen, Antti; Barkhof, Frederik; Tijms, Betty; Lemstra, Afina W.; Tong, Tong; Guerrero, Ricardo; Schuh, Andreas; Ledig, Christian; Rueckert, Daniel; Soininen, Hilkka; Remes, Anne M.; Waldemar, Gunhild; Hasselbalch, Steen; Mecocci, Patrizia; van der Flier, Wiesje; Lötjönen, Jyrki

2016-01-01

Different neurodegenerative diseases can cause memory disorders and other cognitive impairments. The early detection and the stratification of patients according to the underlying disease are essential for an efficient approach to this healthcare challenge. This emphasizes the importance of differential diagnostics. Most studies compare patients and controls, or Alzheimer's disease with one other type of dementia. Such a bilateral comparison does not resemble clinical practice, where a clinician is faced with a number of different possible types of dementia. Here we studied which features in structural magnetic resonance imaging (MRI) scans could best distinguish four types of dementia, Alzheimer's disease, frontotemporal dementia, vascular dementia, and dementia with Lewy bodies, and control subjects. We extracted an extensive set of features quantifying volumetric and morphometric characteristics from T1 images, and vascular characteristics from FLAIR images. Classification was performed using a multi-class classifier based on Disease State Index methodology. The classifier provided continuous probability indices for each disease to support clinical decision making. A dataset of 504 individuals was used for evaluation. The cross-validated classification accuracy was 70.6% and balanced accuracy was 69.1% for the five disease groups using only automatically determined MRI features. Vascular dementia patients could be detected with high sensitivity (96%) using features from FLAIR images. Controls (sensitivity 82%) and Alzheimer's disease patients (sensitivity 74%) could be accurately classified using T1-based features, whereas the most difficult group was the dementia with Lewy bodies (sensitivity 32%). These results were notable better than the classification accuracies obtained with visual MRI ratings (accuracy 44.6%, balanced accuracy 51.6%). Different quantification methods provided complementary information, and consequently, the best results were obtained by utilizing several quantification methods. The results prove that automatic quantification methods and computerized decision support methods are feasible for clinical practice and provide comprehensive information that may help clinicians in the diagnosis making. PMID:27104138

High sensitivity detection of NO2 employing cavity ringdown spectroscopy and an external cavity continuously tunable quantum cascade laser.

PubMed

Rao, Gottipaty N; Karpf, Andreas

2010-09-10

A trace gas sensor for the detection of nitrogen dioxide based on cavity ringdown spectroscopy (CRDS) and a continuous wave external cavity tunable quantum cascade laser operating at room temperature has been designed, and its features and performance characteristics are reported. By measuring the ringdown times of the cavity at different concentrations of NO(2), we report a sensitivity of 1.2 ppb for the detection of NO(2) in Zero Air.

Prediction of redox-sensitive cysteines using sequential distance and other sequence-based features.

PubMed

Sun, Ming-An; Zhang, Qing; Wang, Yejun; Ge, Wei; Guo, Dianjing

2016-08-24

Reactive oxygen species can modify the structure and function of proteins and may also act as important signaling molecules in various cellular processes. Cysteine thiol groups of proteins are particularly susceptible to oxidation. Meanwhile, their reversible oxidation is of critical roles for redox regulation and signaling. Recently, several computational tools have been developed for predicting redox-sensitive cysteines; however, those methods either only focus on catalytic redox-sensitive cysteines in thiol oxidoreductases, or heavily depend on protein structural data, thus cannot be widely used. In this study, we analyzed various sequence-based features potentially related to cysteine redox-sensitivity, and identified three types of features for efficient computational prediction of redox-sensitive cysteines. These features are: sequential distance to the nearby cysteines, PSSM profile and predicted secondary structure of flanking residues. After further feature selection using SVM-RFE, we developed Redox-Sensitive Cysteine Predictor (RSCP), a SVM based classifier for redox-sensitive cysteine prediction using primary sequence only. Using 10-fold cross-validation on RSC758 dataset, the accuracy, sensitivity, specificity, MCC and AUC were estimated as 0.679, 0.602, 0.756, 0.362 and 0.727, respectively. When evaluated using 10-fold cross-validation with BALOSCTdb dataset which has structure information, the model achieved performance comparable to current structure-based method. Further validation using an independent dataset indicates it is robust and of relatively better accuracy for predicting redox-sensitive cysteines from non-enzyme proteins. In this study, we developed a sequence-based classifier for predicting redox-sensitive cysteines. The major advantage of this method is that it does not rely on protein structure data, which ensures more extensive application compared to other current implementations. Accurate prediction of redox-sensitive cysteines not only enhances our understanding about the redox sensitivity of cysteine, it may also complement the proteomics approach and facilitate further experimental investigation of important redox-sensitive cysteines.

Pain Sensitization Associated with Non-Response Following Physiotherapy in People with Knee Osteoarthritis.

PubMed

O'Leary, Helen; Smart, Keith M; Moloney, Niamh A; Blake, Catherine; Doody, Catherine M

2018-05-22

In knee osteoarthritis (OA) pain sensitization has been linked to a more severe symptomatology, but the prognostic implications of pain sensitivity in people undergoing conservative treatment such as physiotherapy are not established. This study aimed to prospectively investigate the association between features of pain sensitization and clinical outcome (non-response) following guideline-based physiotherapy in people with knee OA. Participants (n=156) with moderate/severe knee OA were recruited from secondary care. All participants completed self-administered questionnaires and underwent quantitative sensory testing (QST) at baseline, thereby establishing subjective and objective measures of pain sensitization. Participants (n=134) were later classified following a physiotherapy intervention, using treatment responder criteria (responder/non-responder). QST data was reduced to a core set of latent variables using principal component analysis. A hierarchical logistic regression model was constructed to investigate if features related to pain sensitization predicted non-response after controlling for other known predictors of poor outcome in knee OA. Higher temporal summation (TS) (OR 2.00, 95% CI 1.23 to 3.27) and lower pressure pain thresholds (PPT) (OR 0.48, 95% CI 0.29 to 0.81) emerged as robust predictors of non-response following physiotherapy, along with a higher comorbidity score. The model demonstrated high sensitivity (87.8%) but modest specificity (52.3%). The independent relationship between pain sensitization and non-response may indicate an underlying explanatory association between neuroplastic changes in nociceptive processing and the maintenance of on-going pain and disability in knee OA pain. These preliminary results suggest interventions targeting pain sensitization may warrant future investigation in this population.

Portable SERS sensor for malachite green and other small dye molecules

NASA Astrophysics Data System (ADS)

Qiu, Suyan; Zhao, Fusheng; Li, Jingting; Shih, Wei-Chuan

2017-02-01

Sensitive detection of specific chemicals on site can be extremely powerful in many fields. Owing to its molecular fingerprinting capability, surface-enhanced Raman scattering has been one of the technological contenders. In this paper, we describe the novel use of DNA topological nanostructure on nanoporous gold nanoparticle (NPG-NP) array chip for chemical sensing. NPG-NP features large surface area and high-density plasmonic field enhancement known as "hotspots". Hence, NPG-NP array chip has found many applications in nanoplasmonic sensor development. This technique can provide novel label-free molecular sensing capability and enables high sensitivity and specificity detection using a portable Raman spectrometer.

High sensitivity, wide coverage, and high-resolution NIR non-cryogenic spectrograph, WINERED

NASA Astrophysics Data System (ADS)

Ikeda, Yuji; Kobayashi, Naoto; Kondo, Sohei; Otsubo, Shogo; Hamano, Satoshi; Sameshima, Hiroaki; Yoshikawa, Tomoshiro; Fukue, Kei; Nakanishi, Kenshi; Kawanishi, Takafumi; Nakaoka, Tetsuya; Kinoshita, Masaomi; Kitano, Ayaka; Asano, Akira; Takenaka, Keiichi; Watase, Ayaka; Mito, Hiroyuki; Yasui, Chikako; Minami, Atsushi; Izumu, Natsuko; Yamamoto, Ryo; Mizumoto, Misaki; Arasaki, Takayuki; Arai, Akira; Matsunaga, Noriyuki; Kawakita, Hideyo

2016-08-01

Near-infrared (NIR) high-resolution spectroscopy is a fundamental observational method in astronomy. It provides significant information on the kinematics, the magnetic fields, and the chemical abundances, of astronomical objects embedded in or behind the highly extinctive clouds or at the cosmological distances. Scientific requirements have accelerated the development of the technology required for NIR high resolution spectrographs using 10 m telescopes. WINERED is a near-infrared (NIR) high-resolution spectrograph that is currently mounted on the 1.3 m Araki telescope of the Koyama Astronomical Observatory in Kyoto-Sangyo University, Japan, and has been successfully operated for three years. It covers a wide wavelength range from 0.90 to 1.35 μm (the z-, Y-, and J-bands) with a spectral resolution of R = 28,000 (Wide-mode) and R = 80,000 (Hires-Y and Hires-J modes). WINERED has three distinctive features: (i) optics with no cold stop, (ii) wide spectral coverage, and (iii) high sensitivity. The first feature, originating from the Joyce proposal, was first achieved by WINERED, with a short cutoff infrared array, cold baffles, and custom-made thermal blocking filters, and resulted in reducing the time for development, alignment, and maintenance, as well as the total cost. The second feature is realized with the spectral coverage of Δλ/λ 1/6 in a single exposure. This wide coverage is realized by a combination of a decent optical design with a cross-dispersed echelle and a large format array (2k x 2k HAWAII- 2RG). The Third feature, high sensitivity, is achieved via the high-throughput optics (>60 %) and the very low noise of the system. The major factors affecting the high throughput are the echelle grating and the VPH cross-disperser with high diffraction efficiencies of 83 % and 86 %, respectively, and the high QE of HAWAII-2RG (83 % at 1.23 μm). The readout noise of the electronics and the ambient thermal background radiation at longer wavelengths could be major noise sources. The readout noise is 5.3 e- for NDR = 32, and the ambient thermal background is significantly reduced to 0.05 e- pix-1 sec-1 at 273 K. As a result, the limiting magnitudes of WINERED are estimated to be mJ = 13.8 mag for the 1.3 m telescope, mJ = 16.9 mag for the 3.6 m telescope, and mJ = 19.2 mag for 10 m telescope with adoptive optics, respectively. Finally, we introduce some scientific highlights provided by WINERED for both emission and absorption line objects in the fields of stars, the interstellar medium, and the solar system.

Learning to Detect Vandalism in Social Content Systems: A Study on Wikipedia

NASA Astrophysics Data System (ADS)

Javanmardi, Sara; McDonald, David W.; Caruana, Rich; Forouzan, Sholeh; Lopes, Cristina V.

A challenge facing user generated content systems is vandalism, i.e. edits that damage content quality. The high visibility and easy access to social networks makes them popular targets for vandals. Detecting and removing vandalism is critical for these user generated content systems. Because vandalism can take many forms, there are many different kinds of features that are potentially useful for detecting it. The complex nature of vandalism, and the large number of potential features, make vandalism detection difficult and time consuming for human editors. Machine learning techniques hold promise for developing accurate, tunable, and maintainable models that can be incorporated into vandalism detection tools. We describe a method for training classifiers for vandalism detection that yields classifiers that are more accurate on the PAN 2010 corpus than others previously developed. Because of the high turnaround in social network systems, it is important for vandalism detection tools to run in real-time. To this aim, we use feature selection to find the minimal set of features consistent with high accuracy. In addition, because some features are more costly to compute than others, we use cost-sensitive feature selection to reduce the total computational cost of executing our models. In addition to the features previously used for spam detection, we introduce new features based on user action histories. The user history features contribute significantly to classifier performance. The approach we use is general and can easily be applied to other user generated content systems.

A new scoring model for characterization of adnexal masses based on two-dimensional gray-scale and colour Doppler sonographic features

PubMed Central

Abbas, A.M.; Zahran, K.M.; Nasr, A.; Kamel, H.S.

2014-01-01

Objective: To determine the most discriminating two-dimensional gray-scale and colour Doppler sonographic features that allow differentiation between malignant and benign adnexal masses, and to develop a scoring model that would enable more accurate diagnosis with those features. Methods: A cross sectional prospective study was conducted on patients scheduled for surgery due to presence of adnexal masses at Woman’s Health Center, Assiut University, Egypt between October 2012 and October 2013. All patients were evaluated by 2D ultrasound for morphological features of the masses combined with colour Doppler examination of their vessels. The final diagnosis, based on histopathological analysis, was used as a gold standard. Results: One hundred forty-six patients were recruited, 104 with benign masses, 42 with malignant masses. Features that allowed statistically significant discrimination of benignity from malignancy were; volume of mass, type of mass, presence and thickness of septae, presence and length of papillary projections, location of vessels at colour Doppler and colour score. A scoring model was formulated combining these features together; Assiut Scoring Model (ASM). The cut-off level with the highest accuracy in detection of malignancy, was ≥6, had a sensitivity of 93.5% and specificity of 92.2%. Conclusion: Our Scoring Model; a multiparameter scoring using four gray-scale ultrasound and two colour Doppler features, had shown a high sensitivity and specificity for prediction of malignancy in adnexal masses compared with previous scoring systems. PMID:25009729

Infants' Developing Sensitivity to Object Function: Attention to Features and Feature Correlations

ERIC Educational Resources Information Center

Baumgartner, Heidi A.; Oakes, Lisa M.

2011-01-01

When learning object function, infants must detect relations among features--for example, that squeezing is associated with squeaking or that objects with wheels roll. Previously, Perone and Oakes (2006) found 10-month-old infants were sensitive to relations between object appearances and actions, but not to relations between appearances and…

Computer-aided detection of renal calculi from noncontrast CT images using TV-flow and MSER features.

PubMed

Liu, Jianfei; Wang, Shijun; Turkbey, Evrim B; Linguraru, Marius George; Yao, Jianhua; Summers, Ronald M

2015-01-01

Renal calculi are common extracolonic incidental findings on computed tomographic colonography (CTC). This work aims to develop a fully automated computer-aided diagnosis system to accurately detect renal calculi on CTC images. The authors developed a total variation (TV) flow method to reduce image noise within the kidneys while maintaining the characteristic appearance of renal calculi. Maximally stable extremal region (MSER) features were then calculated to robustly identify calculi candidates. Finally, the authors computed texture and shape features that were imported to support vector machines for calculus classification. The method was validated on a dataset of 192 patients and compared to a baseline approach that detects calculi by thresholding. The authors also compared their method with the detection approaches using anisotropic diffusion and nonsmoothing. At a false positive rate of 8 per patient, the sensitivities of the new method and the baseline thresholding approach were 69% and 35% (p < 1e - 3) on all calculi from 1 to 433 mm(3) in the testing dataset. The sensitivities of the detection methods using anisotropic diffusion and nonsmoothing were 36% and 0%, respectively. The sensitivity of the new method increased to 90% if only larger and more clinically relevant calculi were considered. Experimental results demonstrated that TV-flow and MSER features are efficient means to robustly and accurately detect renal calculi on low-dose, high noise CTC images. Thus, the proposed method can potentially improve diagnosis.

Computer-aided detection of renal calculi from noncontrast CT images using TV-flow and MSER features

PubMed Central

Liu, Jianfei; Wang, Shijun; Turkbey, Evrim B.; Linguraru, Marius George; Yao, Jianhua; Summers, Ronald M.

2015-01-01

Purpose: Renal calculi are common extracolonic incidental findings on computed tomographic colonography (CTC). This work aims to develop a fully automated computer-aided diagnosis system to accurately detect renal calculi on CTC images. Methods: The authors developed a total variation (TV) flow method to reduce image noise within the kidneys while maintaining the characteristic appearance of renal calculi. Maximally stable extremal region (MSER) features were then calculated to robustly identify calculi candidates. Finally, the authors computed texture and shape features that were imported to support vector machines for calculus classification. The method was validated on a dataset of 192 patients and compared to a baseline approach that detects calculi by thresholding. The authors also compared their method with the detection approaches using anisotropic diffusion and nonsmoothing. Results: At a false positive rate of 8 per patient, the sensitivities of the new method and the baseline thresholding approach were 69% and 35% (p < 1e − 3) on all calculi from 1 to 433 mm3 in the testing dataset. The sensitivities of the detection methods using anisotropic diffusion and nonsmoothing were 36% and 0%, respectively. The sensitivity of the new method increased to 90% if only larger and more clinically relevant calculi were considered. Conclusions: Experimental results demonstrated that TV-flow and MSER features are efficient means to robustly and accurately detect renal calculi on low-dose, high noise CTC images. Thus, the proposed method can potentially improve diagnosis. PMID:25563255

Musical ability and non-native speech-sound processing are linked through sensitivity to pitch and spectral information.

PubMed

Kempe, Vera; Bublitz, Dennis; Brooks, Patricia J

2015-05-01

Is the observed link between musical ability and non-native speech-sound processing due to enhanced sensitivity to acoustic features underlying both musical and linguistic processing? To address this question, native English speakers (N = 118) discriminated Norwegian tonal contrasts and Norwegian vowels. Short tones differing in temporal, pitch, and spectral characteristics were used to measure sensitivity to the various acoustic features implicated in musical and speech processing. Musical ability was measured using Gordon's Advanced Measures of Musical Audiation. Results showed that sensitivity to specific acoustic features played a role in non-native speech-sound processing: Controlling for non-verbal intelligence, prior foreign language-learning experience, and sex, sensitivity to pitch and spectral information partially mediated the link between musical ability and discrimination of non-native vowels and lexical tones. The findings suggest that while sensitivity to certain acoustic features partially mediates the relationship between musical ability and non-native speech-sound processing, complex tests of musical ability also tap into other shared mechanisms. © 2014 The British Psychological Society.

Aqueous Black Colloids of Reticular Nanostructured Gold

NASA Astrophysics Data System (ADS)

Stanca, S. E.; Fritzsche, W.; Dellith, J.; Froehlich, F.; Undisz, A.; Deckert, V.; Krafft, C.; Popp, J.

2015-01-01

Since ancient times, noble gold has continuously contributed to several aspects of life from medicine to electronics. It perpetually reveals its new features. We report the finding of a unique form of gold, reticular nanostructured gold (RNG), as an aqueous black colloid, for which we present a one-step synthesis. The reticules consist of gold crystals that interconnect to form compact strands. RNG exhibits high conductivity and low reflection, and these features, coupled with the high specific surface area of the material, could prove valuable for applications in electronics and catalysis. Due to high absorption throughout the visible and infrared domain, RNG has the potential to be applied in the construction of sensitive solar cells or as a substrate for Raman spectroscopy.

Detection of breast cancer in automated 3D breast ultrasound

NASA Astrophysics Data System (ADS)

Tan, Tao; Platel, Bram; Mus, Roel; Karssemeijer, Nico

2012-03-01

Automated 3D breast ultrasound (ABUS) is a novel imaging modality, in which motorized scans of the breasts are made with a wide transducer through a membrane under modest compression. The technology has gained high interest and may become widely used in screening of dense breasts, where sensitivity of mammography is poor. ABUS has a high sensitivity for detecting solid breast lesions. However, reading ABUS images is time consuming, and subtle abnormalities may be missed. Therefore, we are developing a computer aided detection (CAD) system to help reduce reading time and errors. In the multi-stage system we propose, segmentations of the breast and nipple are performed, providing landmarks for the detection algorithm. Subsequently, voxel features characterizing coronal spiculation patterns, blobness, contrast, and locations with respect to landmarks are extracted. Using an ensemble of classifiers, a likelihood map indicating potential malignancies is computed. Local maxima in the likelihood map are determined using a local maxima detector and form a set of candidate lesions in each view. These candidates are further processed in a second detection stage, which includes region segmentation, feature extraction and a final classification. Region segmentation is performed using a 3D spiral-scanning dynamic programming method. Region features include descriptors of shape, acoustic behavior and texture. Performance was determined using a 78-patient dataset with 93 images, including 50 malignant lesions. We used 10-fold cross-validation. Using FROC analysis we found that the system obtains a lesion sensitivity of 60% and 70% at 2 and 4 false positives per image respectively.

Polarimetric imaging of retinal disease by polarization sensitive SLO

NASA Astrophysics Data System (ADS)

Miura, Masahiro; Elsner, Ann E.; Iwasaki, Takuya; Goto, Hiroshi

2015-03-01

Polarimetry imaging is used to evaluate different features of the macular disease. Polarimetry images were recorded using a commercially- available polarization-sensitive scanning laser opthalmoscope at 780 nm (PS-SLO, GDx-N). From data sets of PS-SLO, we computed average reflectance image, depolarized light images, and ratio-depolarized light images. The average reflectance image is the grand mean of all input polarization states. The depolarized light image is the minimum of crossed channel. The ratio-depolarized light image is a ratio between the average reflectance image and depolarized light image, and was used to compensate for variation of brightness. Each polarimetry image is compared with the autofluorescence image at 800 nm (NIR-AF) and autofluorescence image at 500 nm (SW-AF). We evaluated four eyes with geographic atrophy in age related macular degeneration, one eye with retinal pigment epithelium hyperplasia, and two eyes with chronic central serous chorioretinopathy. Polarization analysis could selectively emphasize different features of the retina. Findings in ratio depolarized light image had similarities and differences with NIR-AF images. Area of hyper-AF in NIR-AF images showed high intensity areas in the ratio depolarized light image, representing melanin accumulation. Areas of hypo-AF in NIR-AF images showed low intensity areas in the ratio depolarized light images, representing melanin loss. Drusen were high-intensity areas in the ratio depolarized light image, but NIR-AF images was insensitive to the presence of drusen. Unlike NIR-AF images, SW-AF images showed completely different features from the ratio depolarized images. Polarization sensitive imaging is an effective tool as a non-invasive assessment of macular disease.

Tracking Electroencephalographic Changes Using Distributions of Linear Models: Application to Propofol-Based Depth of Anesthesia Monitoring.

PubMed

Kuhlmann, Levin; Manton, Jonathan H; Heyse, Bjorn; Vereecke, Hugo E M; Lipping, Tarmo; Struys, Michel M R F; Liley, David T J

2017-04-01

Tracking brain states with electrophysiological measurements often relies on short-term averages of extracted features and this may not adequately capture the variability of brain dynamics. The objective is to assess the hypotheses that this can be overcome by tracking distributions of linear models using anesthesia data, and that anesthetic brain state tracking performance of linear models is comparable to that of a high performing depth of anesthesia monitoring feature. Individuals' brain states are classified by comparing the distribution of linear (auto-regressive moving average-ARMA) model parameters estimated from electroencephalographic (EEG) data obtained with a sliding window to distributions of linear model parameters for each brain state. The method is applied to frontal EEG data from 15 subjects undergoing propofol anesthesia and classified by the observers assessment of alertness/sedation (OAA/S) scale. Classification of the OAA/S score was performed using distributions of either ARMA parameters or the benchmark feature, Higuchi fractal dimension. The highest average testing sensitivity of 59% (chance sensitivity: 17%) was found for ARMA (2,1) models and Higuchi fractal dimension achieved 52%, however, no statistical difference was observed. For the same ARMA case, there was no statistical difference if medians are used instead of distributions (sensitivity: 56%). The model-based distribution approach is not necessarily more effective than a median/short-term average approach, however, it performs well compared with a distribution approach based on a high performing anesthesia monitoring measure. These techniques hold potential for anesthesia monitoring and may be generally applicable for tracking brain states.

Comparison of Texture Features Used for Classification of Life Stages of Malaria Parasite.

PubMed

Bairagi, Vinayak K; Charpe, Kshipra C

2016-01-01

Malaria is a vector borne disease widely occurring at equatorial region. Even after decades of campaigning of malaria control, still today it is high mortality causing disease due to improper and late diagnosis. To prevent number of people getting affected by malaria, the diagnosis should be in early stage and accurate. This paper presents an automatic method for diagnosis of malaria parasite in the blood images. Image processing techniques are used for diagnosis of malaria parasite and to detect their stages. The diagnosis of parasite stages is done using features like statistical features and textural features of malaria parasite in blood images. This paper gives a comparison of the textural based features individually used and used in group together. The comparison is made by considering the accuracy, sensitivity, and specificity of the features for the same images in database.

Advanced materials for improving biosensing performances of propagating and localized plasmonic transducers

NASA Astrophysics Data System (ADS)

Manera, M. G.; Colombelli, A.; Convertino, A.; Rella, S.; De Lorenzis, E.; Taurino, A.; Malitesta, C.; Rella, R.

2015-05-01

Among all transduction methodologies reported in the field of solid state optical chemical sensors, the attention has been focused onto the optical sensing characterization by using propagating and localized surface plasmon resonance (SPR) techniques. The research in this field is always oriented in the improvement of the sensing features in terms of sensitivity and limits of detection. To this purpose different strategies have been proposed to realize advanced materials for high sensitive plasmonic devices. In this work nanostructured silica nanowires decorated by gold nanoparticles and active magneto-plasmonic transductors are considered as new biosensing transductors useful to increase the performance of sensitive devices.

Optical security features for plastic card documents

NASA Astrophysics Data System (ADS)

Hossick Schott, Joachim

1998-04-01

Print-on-demand is currently a major trend in the production of paper based documents. This fully digital production philosophy will likely have ramifications also for the secure identification document market. Here, plastic cards increasingly replace traditionally paper based security sensitive documents such as drivers licenses and passports. The information content of plastic cards can be made highly secure by using chip cards. However, printed and other optical security features will continue to play an important role, both for machine readable and visual inspection. Therefore, on-demand high resolution print technologies, laser engraving, luminescent pigments and laminated features such as holograms, kinegrams or phase gratings will have to be considered for the production of secure identification documents. Very important are also basic optical, surface and material durability properties of the laminates as well as the strength and nature of the adhesion between the layers. This presentation will address some of the specific problems encountered when optical security features such as high resolution printing and laser engraving are to be integrated in the on-demand production of secure plastic card identification documents.

Mining Context-Aware Association Rules Using Grammar-Based Genetic Programming.

PubMed

Luna, Jose Maria; Pechenizkiy, Mykola; Del Jesus, Maria Jose; Ventura, Sebastian

2017-09-25

Real-world data usually comprise features whose interpretation depends on some contextual information. Such contextual-sensitive features and patterns are of high interest to be discovered and analyzed in order to obtain the right meaning. This paper formulates the problem of mining context-aware association rules, which refers to the search for associations between itemsets such that the strength of their implication depends on a contextual feature. For the discovery of this type of associations, a model that restricts the search space and includes syntax constraints by means of a grammar-based genetic programming methodology is proposed. Grammars can be considered as a useful way of introducing subjective knowledge to the pattern mining process as they are highly related to the background knowledge of the user. The performance and usefulness of the proposed approach is examined by considering synthetically generated datasets. A posteriori analysis on different domains is also carried out to demonstrate the utility of this kind of associations. For example, in educational domains, it is essential to identify and understand contextual and context-sensitive factors that affect overall and individual student behavior and performance. The results of the experiments suggest that the approach is feasible and it automatically identifies interesting context-aware associations from real-world datasets.

MO-DE-207B-04: Impact of Reconstruction Field of View On Radiomics Features in Computed Tomography (CT) Using a Texture Phantom

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

Shafiq ul Hassan, M; Zhang, G; Oliver, J

Purpose: To investigate the impact of reconstruction Field of View on Radiomics features in computed tomography (CT) using a texture phantom. Methods: A rectangular Credence Cartridge Radiomics (CCR) phantom, composed of 10 different cartridges, was scanned on four different CT scanners from two manufacturers. A pre-defined scanning protocol was adopted for consistency. The slice thickness and reconstruction interval of 1.5 mm was used on all scanners. The reconstruction FOV was varied to result a voxel size ranging from 0.38 to 0.98 mm. A spherical region of interest (ROI) was contoured on the shredded rubber cartridge from CCR phantom CT scans.more » Ninety three Radiomics features were extracted from ROI using an in-house program. These include 10 shape, 22 intensity, 26 GLCM, 11 GLZSM, 11 RLM, 5 NGTDM and 8 fractal dimensional features. To evaluate the Interscanner variability across three scanners, a coefficient of variation (COV) was calculated for each feature group. Each group was further classified according to the COV by calculating the percentage of features in each of the following categories: COV≤ 5%, between 5 and 10% and ≥ 10%. Results: Shape features were the most robust, as expected, because of the spherical contouring of ROI. Intensity features were the second most robust with 54.5 to 64% of features with COV < 5%. GLCM features ranged from 31 to 35% for the same category. RLM features were sensitive to specific scanner and 5% variability was 9 to 54%. Almost all GLZM and NGTDM features showed COV ≥10% among the scanners. The dependence of fractal dimensions features on FOV was not consistent across different scanners. Conclusion: We concluded that reconstruction FOV greatly influence Radiomics features. The GLZSM and NGTDM are highly sensitive to FOV. funded in part by Grant NIH/NCI R01CA190105-01.« less

Adsorption properties of thermally sputtered calcein film

NASA Astrophysics Data System (ADS)

Kruglenko, I.; Burlachenko, J.; Kravchenko, S.; Savchenko, A.; Slabkovska, M.; Shirshov, Yu.

2014-05-01

High humidity environments are often found in such areas as biotechnology, food chemistry, plant physiology etc. The controlling of parameters of such ambiences is vitally important. Thermally deposited calcein films have extremely high adsorptivity at exposure to water vapor of high concentration. This feature makes calcein a promising material for humidity sensing applications. The aim of this work is to explain high sensitivity and selectivity of calcein film to high humidity. Quartz crystal microbalance sensor, AFM and ellipsometry were used for calcein film characterization and adsorption properties investigation. The proposed model takes into account both the molecular properties of calcein (the presence of several functional groups capable of forming hydrogen bonds, and their arrangement) and the features of structure of thermally deposited calcein film (film restructuring due to the switching of bonds "calcein-calcein" to "calcein-water" in the course of water adsorption).

Greater perceptual sensitivity to happy facial expression.

PubMed

Maher, Stephen; Ekstrom, Tor; Chen, Yue

2014-01-01

Perception of subtle facial expressions is essential for social functioning; yet it is unclear if human perceptual sensitivities differ in detecting varying types of facial emotions. Evidence diverges as to whether salient negative versus positive emotions (such as sadness versus happiness) are preferentially processed. Here, we measured perceptual thresholds for the detection of four types of emotion in faces--happiness, fear, anger, and sadness--using psychophysical methods. We also evaluated the association of the perceptual performances with facial morphological changes between neutral and respective emotion types. Human observers were highly sensitive to happiness compared with the other emotional expressions. Further, this heightened perceptual sensitivity to happy expressions can be attributed largely to the emotion-induced morphological change of a particular facial feature (end-lip raise).

Structural transformation and enhanced gas sensing characteristics of TiO2 nanostructures induced by annealing

NASA Astrophysics Data System (ADS)

Tshabalala, Zamaswazi P.; Motaung, David E.; Swart, Hendrik C.

2018-04-01

The improved sensitivity and selectivity, and admirable stability are fundamental features required for the current age gas sensing devices to appease future humanity and environmental requirements. Therefore, herein, we report on the room temperature gas sensing behaviour of TiO2 nanotubes with significance response and sensitivity towards 60 ppm NO2 gas. Improved sensitivity of 29.44 ppm-1 and admirable selectivity towards NO2, among other gases ensuring adequate safety in monitoring NO2 in automobile and food industries. The improved sensitivity of TiO2 nanotubes was attributed to larger surface area provided by the hollow nanotubes resulting to improved gas adsorption and the relatively high concentration of oxygen vacancies.

Chromium picolinate does not improve key features of metabolic syndrome in obese nondiabetic adults.

PubMed

Iqbal, Nayyar; Cardillo, Serena; Volger, Sheri; Bloedon, LeAnne T; Anderson, Richard A; Boston, Raymond; Szapary, Philippe O

2009-04-01

The use of chromium-containing dietary supplements is widespread among patients with type 2 diabetes. Chromium's effects in patients at high risk for developing diabetes, especially those with metabolic syndrome, is unknown. The objective of this study was to determine the effects of chromium picolinate (CrPic) on glucose metabolism in patients with metabolic syndrome. A double-blind, placebo-controlled, randomized trial was conducted at a U.S. academic medical center. Sixty three patients with National Cholesterol Education Program (NCEP) Adult Treatment Panel III (ATP III)-defined metabolic syndrome were included. The primary end point was a change in the insulin sensitivity index derived from a frequently sampled intravenous glucose tolerance test. Prespecified secondary end points included changes in other measurements of glucose metabolism, oxidative stress, fasting serum lipids, and high sensitivity C-reactive protein. After 16 weeks of CrPic treatment, there was no significant change in insulin sensitivity index between groups (P = 0.14). However, CrPic increased acute insulin response to glucose (P 0.02). CrPic had no significant effect on other measures of glucose metabolism, body weight, serum lipids, or measures of inflammation and oxidative stress. CrPic at 1000 microg/day does not improve key features of the metabolic syndrome in obese nondiabetic patients.

Evaluation of quantitative image analysis criteria for the high-resolution microendoscopic detection of neoplasia in Barrett's esophagus

NASA Astrophysics Data System (ADS)

Muldoon, Timothy J.; Thekkek, Nadhi; Roblyer, Darren; Maru, Dipen; Harpaz, Noam; Potack, Jonathan; Anandasabapathy, Sharmila; Richards-Kortum, Rebecca

2010-03-01

Early detection of neoplasia in patients with Barrett's esophagus is essential to improve outcomes. The aim of this ex vivo study was to evaluate the ability of high-resolution microendoscopic imaging and quantitative image analysis to identify neoplastic lesions in patients with Barrett's esophagus. Nine patients with pathologically confirmed Barrett's esophagus underwent endoscopic examination with biopsies or endoscopic mucosal resection. Resected fresh tissue was imaged with fiber bundle microendoscopy; images were analyzed by visual interpretation or by quantitative image analysis to predict whether the imaged sites were non-neoplastic or neoplastic. The best performing pair of quantitative features were chosen based on their ability to correctly classify the data into the two groups. Predictions were compared to the gold standard of histopathology. Subjective analysis of the images by expert clinicians achieved average sensitivity and specificity of 87% and 61%, respectively. The best performing quantitative classification algorithm relied on two image textural features and achieved a sensitivity and specificity of 87% and 85%, respectively. This ex vivo pilot trial demonstrates that quantitative analysis of images obtained with a simple microendoscope system can distinguish neoplasia in Barrett's esophagus with good sensitivity and specificity when compared to histopathology and to subjective image interpretation.

Combined empirical mode decomposition and texture features for skin lesion classification using quadratic support vector machine.

PubMed

Wahba, Maram A; Ashour, Amira S; Napoleon, Sameh A; Abd Elnaby, Mustafa M; Guo, Yanhui

2017-12-01

Basal cell carcinoma is one of the most common malignant skin lesions. Automated lesion identification and classification using image processing techniques is highly required to reduce the diagnosis errors. In this study, a novel technique is applied to classify skin lesion images into two classes, namely the malignant Basal cell carcinoma and the benign nevus. A hybrid combination of bi-dimensional empirical mode decomposition and gray-level difference method features is proposed after hair removal. The combined features are further classified using quadratic support vector machine (Q-SVM). The proposed system has achieved outstanding performance of 100% accuracy, sensitivity and specificity compared to other support vector machine procedures as well as with different extracted features. Basal Cell Carcinoma is effectively classified using Q-SVM with the proposed combined features.

Fabrication of Pt nanowires with a diffraction-unlimited feature size by high-threshold lithography

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

Li, Li, E-mail: lil@cust.edu.cn, E-mail: wangz@cust.edu.cn, E-mail: kq-peng@bnu.edu.cn; Zhang, Ziang; Yu, Miao

2015-09-28

Although the nanoscale world can already be observed at a diffraction-unlimited resolution using far-field optical microscopy, to make the step from microscopy to lithography still requires a suitable photoresist material system. In this letter, we consider the threshold to be a region with a width characterized by the extreme feature size obtained using a Gaussian beam spot. By narrowing such a region through improvement of the threshold sensitization to intensity in a high-threshold material system, the minimal feature size becomes smaller. By using platinum as the negative photoresist, we demonstrate that high-threshold lithography can be used to fabricate nanowire arraysmore » with a scalable resolution along the axial direction of the linewidth from the micro- to the nanoscale using a nanosecond-pulsed laser source with a wavelength λ{sub 0} = 1064 nm. The minimal feature size is only several nanometers (sub λ{sub 0}/100). Compared with conventional polymer resist lithography, the advantages of high-threshold lithography are sharper pinpoints of laser intensity triggering the threshold response and also higher robustness allowing for large area exposure by a less-expensive nanosecond-pulsed laser.« less

Genetic Particle Swarm Optimization–Based Feature Selection for Very-High-Resolution Remotely Sensed Imagery Object Change Detection

PubMed Central

Chen, Qiang; Chen, Yunhao; Jiang, Weiguo

2016-01-01

In the field of multiple features Object-Based Change Detection (OBCD) for very-high-resolution remotely sensed images, image objects have abundant features and feature selection affects the precision and efficiency of OBCD. Through object-based image analysis, this paper proposes a Genetic Particle Swarm Optimization (GPSO)-based feature selection algorithm to solve the optimization problem of feature selection in multiple features OBCD. We select the Ratio of Mean to Variance (RMV) as the fitness function of GPSO, and apply the proposed algorithm to the object-based hybrid multivariate alternative detection model. Two experiment cases on Worldview-2/3 images confirm that GPSO can significantly improve the speed of convergence, and effectively avoid the problem of premature convergence, relative to other feature selection algorithms. According to the accuracy evaluation of OBCD, GPSO is superior at overall accuracy (84.17% and 83.59%) and Kappa coefficient (0.6771 and 0.6314) than other algorithms. Moreover, the sensitivity analysis results show that the proposed algorithm is not easily influenced by the initial parameters, but the number of features to be selected and the size of the particle swarm would affect the algorithm. The comparison experiment results reveal that RMV is more suitable than other functions as the fitness function of GPSO-based feature selection algorithm. PMID:27483285

Interpersonal sensitivity and persistent attenuated psychotic symptoms in adolescence.

PubMed

Masillo, Alice; Brandizzi, M; Valmaggia, L R; Saba, R; Lo Cascio, N; Lindau, J F; Telesforo, L; Venturini, P; Montanaro, D; Di Pietro, D; D'Alema, M; Girardi, P; Fiori Nastro, P

2018-03-01

Interpersonal sensitivity defines feelings of inner-fragility in the presence of others due to the expectation of criticism or rejection. Interpersonal sensitivity was found to be related to attenuated positive psychotic symptom during the prodromal phase of psychosis. The aims of this study were to examine if high level of interpersonal sensitivity at baseline are associated with the persistence of attenuated positive psychotic symptoms and general psychopathology at 18-month follow-up. A sample of 85 help-seeking individuals (mean age = 16.6, SD = 5.05) referred an Italian early detection project, completed the interpersonal sensitivity measure and the structured interview for prodromal symptoms (SIPS) at baseline and were assessed at 18-month follow-up using the SIPS. Results showed that individuals with high level of interpersonal sensitivity at baseline reported high level of attenuated positive psychotic symptoms (i.e., unusual thought content) and general symptoms (i.e., depression, irritability and low tolerance to daily stress) at follow-up. This study suggests that being "hypersensitive" to interpersonal interactions is a psychological feature associated with attenuated positive psychotic symptoms and general symptoms, such as depression and irritability, at 18-month follow-up. Assessing and treating inner-self fragilities may be an important step of early detection program to avoid the persistence of subtle but very distressing long-terms symptoms.

Is recurrence in major depressive disorder related to bipolarity and mixed features? Results from the BRIDGE-II-Mix study.

PubMed

Mazzarini, Lorenzo; Kotzalidis, Georgios D; Piacentino, Daria; Rizzato, Salvatore; Angst, Jules; Azorin, Jean-Michel; Bowden, Charles L; Mosolov, Sergey; Young, Allan H; Vieta, Eduard; Girardi, Paolo; Perugi, Giulio

2018-03-15

Current classifications separate Bipolar (BD) from Major Depressive Disorder (MDD) based on polarity rather than recurrence. We aimed to determine bipolar/mixed feature frequency in a large MDD multinational sample with (High-Rec) and without (Low-Rec) >3 recurrences, comparing the two subsamples. We measured frequency of bipolarity/hypomanic features during current depressive episodes (MDEs) in 2347 MDD patients from the BRIDGE-II-mix database, comparing High-Rec with Low-Rec. We used Bonferroni-corrected Student's t-test for continuous, and chi-squared test, for categorical variables. Logistic regression estimated the size of the association between clinical characteristics and High-Rec MDD. Compared to Low-Rec (n = 1084, 46.2%), High-Rec patients (n = 1263, 53.8%) were older, with earlier depressive onset, had more family history of BD, more atypical features, suicide attempts, hospitalisations, and treatment resistance and (hypo)manic switches when treated with antidepressants, higher comorbidity with borderline personality disorder, and more hypomanic symptoms during current MDE, resulting in higher rates of mixed depression according to both DSM-5 and research-based diagnostic (RBDC) criteria. Logistic regression showed age at first symptoms < 30 years, current MDE duration ≤ 1 month, hypomania/mania among first-degree relatives, past suicide attempts, treatment-resistance, antidepressant-induced swings, and atypical, mixed, or psychotic features during MDE to associate with High-Rec. Number of MDEs for defining recurrence was arbitrary; cross-sectionality did not allow assessment of conversion from MDD to BD. High-Rec MDD differed from Low-Rec group for several clinical/epidemiological variables, including bipolar/mixed features. Bipolarity specifier and RBDC were more sensitive than DSM-5 criteria in detecting bipolar and mixed features in MDD. Copyright © 2017. Published by Elsevier B.V.

Simultaneous determination of indoor ammonia pollution and its biological metabolite in the human body with a recyclable nanocrystalline lanthanide-functionalized MOF

NASA Astrophysics Data System (ADS)

Hao, Ji-Na; Yan, Bing

2016-01-01

A Eu3+ post-functionalized metal-organic framework of nanosized Ga(OH)bpydc(Eu3+@Ga(OH)bpydc, 1a) with intense luminescence is synthesized and characterized. Luminescence measurements reveal that 1a can detect ammonia gas selectively and sensitively among various indoor air pollutants. 1a can simultaneously determine a biological ammonia metabolite (urinary urea) in the human body, which is a rare example of a luminescent sensor that can monitor pollutants in the environment and also detect their biological markers. Furthermore, 1a exhibits appealing features including high selectivity and sensitivity, fast response, simple and quick regeneration, and excellent recyclability.A Eu3+ post-functionalized metal-organic framework of nanosized Ga(OH)bpydc(Eu3+@Ga(OH)bpydc, 1a) with intense luminescence is synthesized and characterized. Luminescence measurements reveal that 1a can detect ammonia gas selectively and sensitively among various indoor air pollutants. 1a can simultaneously determine a biological ammonia metabolite (urinary urea) in the human body, which is a rare example of a luminescent sensor that can monitor pollutants in the environment and also detect their biological markers. Furthermore, 1a exhibits appealing features including high selectivity and sensitivity, fast response, simple and quick regeneration, and excellent recyclability. Electronic supplementary information (ESI) available: Experimental section; XPS spectra; N2 adsorption-desorption isotherms; ICP data; SEM image; PXRD patterns and other luminescence data. See DOI: 10.1039/c5nr06066d

Manx: Close air support aircraft preliminary design

NASA Technical Reports Server (NTRS)

Amy, Annie; Crone, David; Hendrickson, Heidi; Willis, Randy; Silva, Vince

1991-01-01

The Manx is a twin engine, twin tailed, single seat close air support design proposal for the 1991 Team Student Design Competition. It blends advanced technologies into a lightweight, high performance design with the following features: High sensitivity (rugged, easily maintained, with night/adverse weather capability); Highly maneuverable (negative static margin, forward swept wing, canard, and advanced avionics result in enhanced aircraft agility); and Highly versatile (design flexibility allows the Manx to contribute to a truly integrated ground team capable of rapid deployment from forward sites).

IGF-1 contributes to the expansion of melanoma-initiating cells through an epithelial-mesenchymal transition process.

PubMed

Le Coz, Vincent; Zhu, Chaobin; Devocelle, Aurore; Vazquez, Aimé; Boucheix, Claude; Azzi, Sandy; Gallerne, Cindy; Eid, Pierre; Lecourt, Séverine; Giron-Michel, Julien

2016-12-13

Melanoma is a particularly virulent human cancer, due to its resistance to conventional treatments and high frequency of metastasis. Melanomas contain a fraction of cells, the melanoma-initiating cells (MICs), responsible for tumor propagation and relapse. Identification of the molecular pathways supporting MICs is, therefore, vital for the development of targeted treatments. One factor produced by melanoma cells and their microenvironment, insulin-like growth factor-1 (IGF- 1), is linked to epithelial-mesenchymal transition (EMT) and stemness features in several cancers.We evaluated the effect of IGF-1 on the phenotype and chemoresistance of B16-F10 cells. IGF-1 inhibition in these cells prevented malignant cell proliferation, migration and invasion, and lung colony formation in immunodeficient mice. IGF-1 downregulation also markedly inhibited EMT, with low levels of ZEB1 and mesenchymal markers (N-cadherin, CD44, CD29, CD105) associated with high levels of E-cadherin and MITF, the major regulator of melanocyte differentiation. IGF-1 inhibition greatly reduced stemness features, including the expression of key stem markers (SOX2, Oct-3/4, CD24 and CD133), and the functional characteristics of MICs (melanosphere formation, aldehyde dehydrogenase activity, side population). These features were associated with a high degree of sensitivity to mitoxantrone treatment.In this study, we deciphered new connections between IGF-1 and stemness features and identified IGF-1 as instrumental for maintaining the MIC phenotype. The IGF1/IGF1-R nexus could be targeted for the development of more efficient anti-melanoma treatments. Blocking the IGF-1 pathway would improve the immune response, decrease the metastatic potential of tumor cells and sensitize melanoma cells to conventional treatments.

Towards semantically sensitive text clustering: a feature space modeling technology based on dimension extension.

PubMed

Liu, Yuanchao; Liu, Ming; Wang, Xin

2015-01-01

The objective of text clustering is to divide document collections into clusters based on the similarity between documents. In this paper, an extension-based feature modeling approach towards semantically sensitive text clustering is proposed along with the corresponding feature space construction and similarity computation method. By combining the similarity in traditional feature space and that in extension space, the adverse effects of the complexity and diversity of natural language can be addressed and clustering semantic sensitivity can be improved correspondingly. The generated clusters can be organized using different granularities. The experimental evaluations on well-known clustering algorithms and datasets have verified the effectiveness of our approach.

Towards Semantically Sensitive Text Clustering: A Feature Space Modeling Technology Based on Dimension Extension

PubMed Central

Liu, Yuanchao; Liu, Ming; Wang, Xin

2015-01-01

The objective of text clustering is to divide document collections into clusters based on the similarity between documents. In this paper, an extension-based feature modeling approach towards semantically sensitive text clustering is proposed along with the corresponding feature space construction and similarity computation method. By combining the similarity in traditional feature space and that in extension space, the adverse effects of the complexity and diversity of natural language can be addressed and clustering semantic sensitivity can be improved correspondingly. The generated clusters can be organized using different granularities. The experimental evaluations on well-known clustering algorithms and datasets have verified the effectiveness of our approach. PMID:25794172

Automatic detection of ECG cable interchange by analyzing both morphology and interlead relations.

PubMed

Han, Chengzong; Gregg, Richard E; Feild, Dirk Q; Babaeizadeh, Saeed

2014-01-01

ECG cable interchange can generate erroneous diagnoses. For algorithms detecting ECG cable interchange, high specificity is required to maintain a low total false positive rate because the prevalence of interchange is low. In this study, we propose and evaluate an improved algorithm for automatic detection and classification of ECG cable interchange. The algorithm was developed by using both ECG morphology information and redundancy information. ECG morphology features included QRS-T and P-wave amplitude, frontal axis and clockwise vector loop rotation. The redundancy features were derived based on the EASI™ lead system transformation. The classification was implemented using linear support vector machine. The development database came from multiple sources including both normal subjects and cardiac patients. An independent database was used to test the algorithm performance. Common cable interchanges were simulated by swapping either limb cables or precordial cables. For the whole validation database, the overall sensitivity and specificity for detecting precordial cable interchange were 56.5% and 99.9%, and the sensitivity and specificity for detecting limb cable interchange (excluding left arm-left leg interchange) were 93.8% and 99.9%. Defining precordial cable interchange or limb cable interchange as a single positive event, the total false positive rate was 0.7%. When the algorithm was designed for higher sensitivity, the sensitivity for detecting precordial cable interchange increased to 74.6% and the total false positive rate increased to 2.7%, while the sensitivity for detecting limb cable interchange was maintained at 93.8%. The low total false positive rate was maintained at 0.6% for the more abnormal subset of the validation database including only hypertrophy and infarction patients. The proposed algorithm can detect and classify ECG cable interchanges with high specificity and low total false positive rate, at the cost of decreased sensitivity for certain precordial cable interchanges. The algorithm could also be configured for higher sensitivity for different applications where a lower specificity can be tolerated. Copyright © 2014 Elsevier Inc. All rights reserved.

Bowel obstruction complicated by ischemia: analysis of CT findings.

PubMed

Cox, Veronica L; Tahvildari, Ali M; Johnson, Benjamin; Wei, Wei; Jeffrey, R Brooke

2018-06-01

To analyze CT signs of bowel ischemia in patients with surgical bowel obstruction, and thereby improve CT diagnosis in this common clinical scenario. Surgical and histopathological findings were used as the reference standard. We retrospectively analyzed CT findings in patients brought to surgery for bowel obstruction over 13 years. Etiology of obstruction (adhesion, hernia, etc.) was recorded. Specific CT features of acute mesenteric ischemia (AMI) were analyzed, including bowel wall thickening, mucosal hypoenhancement, and others. 173 cases were eligible for analysis. 21% of cases were positive for bowel ischemia. Volvulus, internal hernia, and closed-loop obstructions showed ischemia rates of 60%, 43%, and 43%; ischemia rate in obstruction from simple adhesion was 21%. Patients with bowel obstruction related to malignancy were never ischemic. Sensitivities and specificities for CT features predicting ischemia were calculated, with wall thickening, hypoenhancement, and pneumatosis showing high specificity for ischemia (86%-100%). Wall thickening, hypoenhancement, and pneumatosis are highly specific CT signs of ischemia in the setting of obstruction. None of the evaluated CT signs were found to be highly sensitive. Overall frequency of ischemia in surgical bowel obstruction is 21%, and 2-3 times that for complex obstructions (volvulus, closed loop, etc.). Obstructions related to malignancy virtually never become ischemic.

Performance of Ultrasound in the Diagnosis of Gout in a Multicenter Study: Comparison With Monosodium Urate Monohydrate Crystal Analysis as the Gold Standard.

PubMed

Ogdie, Alexis; Taylor, William J; Neogi, Tuhina; Fransen, Jaap; Jansen, Tim L; Schumacher, H Ralph; Louthrenoo, Worawit; Vazquez-Mellado, Janitzia; Eliseev, Maxim; McCarthy, Geraldine; Stamp, Lisa K; Perez-Ruiz, Fernando; Sivera, Francisca; Ea, Hang-Korng; Gerritsen, Martijn; Cagnotto, Giovanni; Cavagna, Lorenzo; Lin, Chingtsai; Chou, Yin-Yi; Tausche, Anne-Kathrin; Lima Gomes Ochtrop, Manuella; Janssen, Matthijs; Chen, Jiunn-Horng; Slot, Ole; Lazovskis, Juris; White, Douglas; Cimmino, Marco A; Uhlig, Till; Dalbeth, Nicola

2017-02-01

To examine the performance of ultrasound (US) for the diagnosis of gout using the presence of monosodium urate monohydrate (MSU) crystals as the gold standard. We analyzed data from the Study for Updated Gout Classification Criteria (SUGAR), a large, multicenter observational cross-sectional study of consecutive subjects with at least 1 swollen joint who conceivably may have gout. All subjects underwent arthrocentesis; cases were subjects with confirmed MSU crystals. Rheumatologists or radiologists who were blinded with regard to the results of the MSU crystal analysis performed US on 1 or more clinically affected joints. US findings of interest were double contour sign, tophus, and snowstorm appearance. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. Multivariable logistic regression models were used to examine factors associated with positive US results among subjects with gout. US was performed in 824 subjects (416 cases and 408 controls). The sensitivity, specificity, PPV, and NPV for the presence of any 1 of the features were 76.9%, 84.3%, 83.3%, and 78.2%, respectively. Sensitivity was higher among subjects with a disease duration of ≥2 years and among subjects with subcutaneous nodules on examination (suspected tophus). Associations with a positive US finding included suspected clinical tophus (odds ratio [OR] 4.77 [95% confidence interval (95% CI) 2.23-10.21]), any abnormality on plain radiography (OR 4.68 [95% CI 2.68-8.17]), and serum urate level (OR 1.31 [95% CI 1.06-1.62]). US features of MSU crystal deposition had high specificity and high PPV but more limited sensitivity for early gout. The specificity remained high in subjects with early disease and without clinical signs of tophi. © 2016, American College of Rheumatology.

Performance of Ultrasound in the Diagnosis of Gout in a Multi-Center Study: Comparison with Monosodium Urate Crystal Analysis as the Gold Standard

PubMed Central

Ogdie, Alexis; Taylor, William J; Neogi, Tuhina; Fransen, Jaap; Jansen, Tim L; Schumacher, H. Ralph; Louthrenoo, Worawit; Vazquez-Mellado, Janitzia; Eliseev, Maxim; McCarthy, Geraldine; Stamp, Lisa K.; Perez-Ruiz, Fernando; Sivera, Francisca; Ea, Hang-Korng; Gerritsen, Martijn; Cagnotto, Giovanni; Cavagna, Lorenzo; Lin, Chingtsai; Chou, Yin-Yi; Tausche, Anne-Kathrin; Ochtrop, Manuella Lima Gomes; Janssen, Matthijs; Chen, Jiunn-Horng; Slot, Ole; Lazovskis, Juris; White, Douglas; Cimmino, Marco A.; Uhlig, Till; Dalbeth, Nicola

2017-01-01

Objectives To examine the performance of ultrasound for the diagnosis of gout using presence of monosodium urate (MSU) crystals as the gold standard. Methods We analyzed data from the Study for Updated Gout Classification Criteria (SUGAR), a large, multi-center observational cross-sectional study of consecutive subjects with at least one swollen joint who conceivably may have gout. All subjects underwent arthrocentesis; cases were subjects with MSU crystal confirmation. Rheumatologists or radiologists, blinded to the results of the MSU crystal analysis, performed ultrasound on one or more clinically affected joints. Ultrasound findings of interest were: double contour sign (DCS), tophus, and ‘snowstorm’ appearance. Sensitivity, specificity, positive and negative predictive values (PPV and NPV) were calculated. Multivariable logistic regression models were used to examine factors associated with positive ultrasound results among subjects with gout. Results Ultrasound was performed in 824 subjects (416 cases and 408 controls). The sensitivity, specificity, PPV and NPV for the presence of any one of the features were 76.9%, 84.3%, 83.3% and 78.1% respectively. Sensitivity was higher among subjects with disease ≥2 years duration and among subjects with subcutaneous nodules on exam (suspected tophus). Associations with a positive ultrasound finding included suspected clinical tophus (odds ratio 4.77; 95% CI 2.23–10.21), any abnormal plain film radiograph (4.68; 2.68–8.17) and serum urate (1.31; 1.06–1.62). Conclusions Ultrasound features of MSU crystal deposition had high specificity and high positive predictive value but more limited sensitivity for early gout. The specificity remained high in subjects with early disease and without clinical signs of tophi. PMID:27748084

Stream ecosystems change with urban development

USGS Publications Warehouse

Bell, Amanda H.; James, F. Coles; McMahon, Gerard

2012-01-01

The healthy condition of the physical living space in a natural stream—defined by unaltered hydrology (streamflow), high diversity of habitat features, and natural water chemistry—supports diverse biological communities with aquatic species that are sensitive to disturbances. In a highly degraded urban stream, the poor condition of the physical living space—streambank and tree root damage from altered hydrology, low diversity of habitat, and inputs of chemical contaminants—contributes to biological communities with low diversity and high tolerance to disturbance.

WND-CHARM: Multi-purpose image classification using compound image transforms

PubMed Central

Orlov, Nikita; Shamir, Lior; Macura, Tomasz; Johnston, Josiah; Eckley, D. Mark; Goldberg, Ilya G.

2008-01-01

We describe a multi-purpose image classifier that can be applied to a wide variety of image classification tasks without modifications or fine-tuning, and yet provide classification accuracy comparable to state-of-the-art task-specific image classifiers. The proposed image classifier first extracts a large set of 1025 image features including polynomial decompositions, high contrast features, pixel statistics, and textures. These features are computed on the raw image, transforms of the image, and transforms of transforms of the image. The feature values are then used to classify test images into a set of pre-defined image classes. This classifier was tested on several different problems including biological image classification and face recognition. Although we cannot make a claim of universality, our experimental results show that this classifier performs as well or better than classifiers developed specifically for these image classification tasks. Our classifier’s high performance on a variety of classification problems is attributed to (i) a large set of features extracted from images; and (ii) an effective feature selection and weighting algorithm sensitive to specific image classification problems. The algorithms are available for free download from openmicroscopy.org. PMID:18958301

Automatic seizure detection in SEEG using high frequency activities in wavelet domain.

PubMed

Ayoubian, L; Lacoma, H; Gotman, J

2013-03-01

Existing automatic detection techniques show high sensitivity and moderate specificity, and detect seizures a relatively long time after onset. High frequency (80-500 Hz) activity has recently been shown to be prominent in the intracranial EEG of epileptic patients but has not been used in seizure detection. The purpose of this study is to investigate if these frequencies can contribute to seizure detection. The system was designed using 30 h of intracranial EEG, including 15 seizures in 15 patients. Wavelet decomposition, feature extraction, adaptive thresholding and artifact removal were employed in training data. An EMG removal algorithm was developed based on two features: Lack of correlation between frequency bands and energy-spread in frequency. Results based on the analysis of testing data (36 h of intracranial EEG, including 18 seizures) show a sensitivity of 72%, a false detection of 0.7/h and a median delay of 5.7 s. Missed seizures originated mainly from seizures with subtle or absent high frequencies or from EMG removal procedures. False detections were mainly due to weak EMG or interictal high frequency activities. The system performed sufficiently well to be considered for clinical use, despite the exclusive use of frequencies not usually considered in clinical interpretation. High frequencies have the potential to contribute significantly to the detection of epileptic seizures. Crown Copyright © 2012. Published by Elsevier Ltd. All rights reserved.

Automatic seizure detection in SEEG using high frequency activities in wavelet domain

PubMed Central

Ayoubian, L.; Lacoma, H.; Gotman, J.

2015-01-01

Existing automatic detection techniques show high sensitivity and moderate specificity, and detect seizures a relatively long time after onset. High frequency (80–500 Hz) activity has recently been shown to be prominent in the intracranial EEG of epileptic patients but has not been used in seizure detection. The purpose of this study is to investigate if these frequencies can contribute to seizure detection. The system was designed using 30 h of intracranial EEG, including 15 seizures in 15 patients. Wavelet decomposition, feature extraction, adaptive thresholding and artifact removal were employed in training data. An EMG removal algorithm was developed based on two features: Lack of correlation between frequency bands and energy-spread in frequency. Results based on the analysis of testing data (36 h of intracranial EEG, including 18 seizures) show a sensitivity of 72%, a false detection of 0.7/h and a median delay of 5.7 s. Missed seizures originated mainly from seizures with subtle or absent high frequencies or from EMG removal procedures. False detections were mainly due to weak EMG or interictal high frequency activities. The system performed sufficiently well to be considered for clinical use, despite the exclusive use of frequencies not usually considered in clinical interpretation. High frequencies have the potential to contribute significantly to the detection of epileptic seizures. PMID:22647836

Automated detection of retinal whitening in malarial retinopathy

NASA Astrophysics Data System (ADS)

Joshi, V.; Agurto, C.; Barriga, S.; Nemeth, S.; Soliz, P.; MacCormick, I.; Taylor, T.; Lewallen, S.; Harding, S.

2016-03-01

Cerebral malaria (CM) is a severe neurological complication associated with malarial infection. Malaria affects approximately 200 million people worldwide, and claims 600,000 lives annually, 75% of whom are African children under five years of age. Because most of these mortalities are caused by the high incidence of CM misdiagnosis, there is a need for an accurate diagnostic to confirm the presence of CM. The retinal lesions associated with malarial retinopathy (MR) such as retinal whitening, vessel discoloration, and hemorrhages, are highly specific to CM, and their detection can improve the accuracy of CM diagnosis. This paper will focus on development of an automated method for the detection of retinal whitening which is a unique sign of MR that manifests due to retinal ischemia resulting from CM. We propose to detect the whitening region in retinal color images based on multiple color and textural features. First, we preprocess the image using color and textural features of the CMYK and CIE-XYZ color spaces to minimize camera reflex. Next, we utilize color features of the HSL, CMYK, and CIE-XYZ channels, along with the structural features of difference of Gaussians. A watershed segmentation algorithm is used to assign each image region a probability of being inside the whitening, based on extracted features. The algorithm was applied to a dataset of 54 images (40 with whitening and 14 controls) that resulted in an image-based (binary) classification with an AUC of 0.80. This provides 88% sensitivity at a specificity of 65%. For a clinical application that requires a high specificity setting, the algorithm can be tuned to a specificity of 89% at a sensitivity of 82%. This is the first published method for retinal whitening detection and combining it with the detection methods for vessel discoloration and hemorrhages can further improve the detection accuracy for malarial retinopathy.

Bacterial chemoreceptors: high-performance signaling in networked arrays.

PubMed

Hazelbauer, Gerald L; Falke, Joseph J; Parkinson, John S

2008-01-01

Chemoreceptors are crucial components in the bacterial sensory systems that mediate chemotaxis. Chemotactic responses exhibit exquisite sensitivity, extensive dynamic range and precise adaptation. The mechanisms that mediate these high-performance functions involve not only actions of individual proteins but also interactions among clusters of components, localized in extensive patches of thousands of molecules. Recently, these patches have been imaged in native cells, important features of chemoreceptor structure and on-off switching have been identified, and new insights have been gained into the structural basis and functional consequences of higher order interactions among sensory components. These new data suggest multiple levels of molecular interactions, each of which contribute specific functional features and together create a sophisticated signaling device.

Bacterial chemoreceptors: high-performance signaling in networked arrays

PubMed Central

Hazelbauer, Gerald L.; Falke, Joseph J.; Parkinson, John S.

2010-01-01

Chemoreceptors are crucial components in the bacterial sensory systems that mediate chemotaxis. Chemotactic responses exhibit exquisite sensitivity, extensive dynamic range and precise adaptation. The mechanisms that mediate these high-performance functions involve not only actions of individual proteins but also interactions among clusters of components, localized in extensive patches of thousands of molecules. Recently, these patches have been imaged in native cells, important features of chemoreceptor structure and on–off switching have been identified, and new insights have been gained into the structural basis and functional consequences of higher order interactions among sensory components. These new data suggest multiple levels of molecular interactions, each of which contribute specific functional features and together create a sophisticated signaling device. PMID:18165013

Electromagnetic perception and individual features of human beings.

PubMed

Lebedeva, N N; Kotrovskaya, T I

2001-01-01

An investigation was made of the individual reactions of human subjects exposed to electromagnetic fields. We performed the study on 86 volunteers separated into two groups. The first group was exposed to the electromagnetic field of infralow frequencies, whereas the second group was exposed to the electromagnetic field of extremely high frequencies. We found that the electromagnetic perception of human beings correlated with their individual features, such as EEG parameters, the critical frequency of flash merging, and the electric current sensitivity. Human subjects who had a high-quality perception of electromagnetic waves showed an optimal balance of cerebral processes, an excellent functional state of the central nervous system, and a good decision criterion.

Design Considerations and Performance of MEMS Acoustoelectric Ultrasound Detectors

PubMed Central

Wang, Zhaohui; Ingram, Pier; Greenlee, Charles L.; Olafsson, Ragnar; Norwood, Robert A.; Witte, Russell S.

2014-01-01

Most single-element hydrophones depend on a piezoelectric material that converts pressure changes to electricity. These devices, however, can be expensive, susceptible to damage at high pressure, and/or have limited bandwidth and sensitivity. We have previously described the acoustoelectric (AE) hydrophone as an inexpensive alternative for mapping an ultrasound beam and monitoring acoustic exposure. The device exploits the AE effect, an interaction between electrical current flowing through a material and a propagating pressure wave. Previous designs required imprecise fabrication methods using common laboratory supplies, making it difficult to control basic features such as shape and size. This study describes a different approach based on microelectromechanical systems (MEMS) processing that allows for much finer control of several design features. In an effort to improve the performance of the AE hydrophone, we combine simulations with bench-top testing to evaluate key design features, such as thickness, shape, and conductivity of the active and passive elements. The devices were evaluated in terms of sensitivity, frequency response, and accuracy for reproducing the beam pattern. Our simulations and experimental results both indicated that designs using a combination of indium tin oxide (ITO) for the active element and gold for the passive electrodes (conductivity ratio = ~20) produced the best result for mapping the beam of a 2.25-MHz ultrasound transducer. Also, the AE hydrophone with a rectangular dumbbell configuration achieved a better beam pattern than other shape configurations. Lateral and axial resolutions were consistent with images generated from a commercial capsule hydrophone. Sensitivity of the best-performing device was 1.52 nV/Pa at 500 kPa using a bias voltage of 20 V. We expect a thicker AE hydrophone closer to half the acoustic wavelength to produce even better sensitivity, while maintaining high spectral bandwidth for characterizing medical ultrasound transducers. AE ultrasound detectors may also be useful for monitoring acoustic exposure during therapy or as receivers for photoacoustic imaging. PMID:24658721

Spatial-time-state fusion algorithm for defect detection through eddy current pulsed thermography

NASA Astrophysics Data System (ADS)

Xiao, Xiang; Gao, Bin; Woo, Wai Lok; Tian, Gui Yun; Xiao, Xiao Ting

2018-05-01

Eddy Current Pulsed Thermography (ECPT) has received extensive attention due to its high sensitive of detectability on surface and subsurface cracks. However, it remains as a difficult challenge in unsupervised detection as to identify defects without knowing any prior knowledge. This paper presents a spatial-time-state features fusion algorithm to obtain fully profile of the defects by directional scanning. The proposed method is intended to conduct features extraction by using independent component analysis (ICA) and automatic features selection embedding genetic algorithm. Finally, the optimal feature of each step is fused to obtain defects reconstruction by applying common orthogonal basis extraction (COBE) method. Experiments have been conducted to validate the study and verify the efficacy of the proposed method on blind defect detection.

Limitations in 4-Year-Old Children's Sensitivity to the Spacing among Facial Features

ERIC Educational Resources Information Center

Mondloch, Catherine J.; Thomson, Kendra

2008-01-01

Four-year-olds' sensitivity to differences among faces in the spacing of features was tested under 4 task conditions: judging distinctiveness when the external contour was visible and when it was occluded, simultaneous match-to-sample, and recognizing the face of a friend. In each task, the foil differed only in the spacing of features, and…

African American English and Spelling: How Do Second Graders Spell Dialect-Sensitive Features of Words?

ERIC Educational Resources Information Center

Patton-Terry, Nicole; Connor, Carol

2010-01-01

This study explored the spelling skills of African American second graders who produced African American English (AAE) features in speech. The children (N = 92), who varied in spoken AAE use and word reading skills, were asked to spell words that contained phonological and morphological dialect-sensitive (DS) features that can vary between AAE and…

Trusted Computing Technologies, Intel Trusted Execution Technology.

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

Guise, Max Joseph; Wendt, Jeremy Daniel

2011-01-01

We describe the current state-of-the-art in Trusted Computing Technologies - focusing mainly on Intel's Trusted Execution Technology (TXT). This document is based on existing documentation and tests of two existing TXT-based systems: Intel's Trusted Boot and Invisible Things Lab's Qubes OS. We describe what features are lacking in current implementations, describe what a mature system could provide, and present a list of developments to watch. Critical systems perform operation-critical computations on high importance data. In such systems, the inputs, computation steps, and outputs may be highly sensitive. Sensitive components must be protected from both unauthorized release, and unauthorized alteration: Unauthorizedmore » users should not access the sensitive input and sensitive output data, nor be able to alter them; the computation contains intermediate data with the same requirements, and executes algorithms that the unauthorized should not be able to know or alter. Due to various system requirements, such critical systems are frequently built from commercial hardware, employ commercial software, and require network access. These hardware, software, and network system components increase the risk that sensitive input data, computation, and output data may be compromised.« less

A Wearable and Highly Sensitive Graphene Strain Sensor for Precise Home-Based Pulse Wave Monitoring.

PubMed

Yang, Tingting; Jiang, Xin; Zhong, Yujia; Zhao, Xuanliang; Lin, Shuyuan; Li, Jing; Li, Xinming; Xu, Jianlong; Li, Zhihong; Zhu, Hongwei

2017-07-28

Profuse medical information about cardiovascular properties can be gathered from pulse waveforms. Therefore, it is desirable to design a smart pulse monitoring device to achieve noninvasive and real-time acquisition of cardiovascular parameters. The majority of current pulse sensors are usually bulky or insufficient in sensitivity. In this work, a graphene-based skin-like sensor is explored for pulse wave sensing with features of easy use and wearing comfort. Moreover, the adjustment of the substrate stiffness and interfacial bonding accomplish the optimal balance between sensor linearity and signal sensitivity, as well as measurement of the beat-to-beat radial arterial pulse. Compared with the existing bulky and nonportable clinical instruments, this highly sensitive and soft sensing patch not only provides primary sensor interface to human skin, but also can objectively and accurately detect the subtle pulse signal variations in a real-time fashion, such as pulse waveforms with different ages, pre- and post-exercise, thus presenting a promising solution to home-based pulse monitoring.

Low-Energy Proton Testing Methodology

NASA Technical Reports Server (NTRS)

Pellish, Jonathan A.; Marshall, Paul W.; Heidel, David F.; Schwank, James R.; Shaneyfelt, Marty R.; Xapsos, M.A.; Ladbury, Raymond L.; LaBel, Kenneth A.; Berg, Melanie; Kim, Hak S.;

Hydrogen peroxide biosensor based on hemoglobin immobilized at graphene, flower-like zinc oxide, and gold nanoparticles nanocomposite modified glassy carbon electrode.

PubMed

Xie, Lingling; Xu, Yuandong; Cao, Xiaoyu

2013-07-01

In this work, a highly sensitive hydrogen peroxide (H2O2) biosensor based on immobilization of hemoglobin (Hb) at Au nanoparticles (AuNPs)/flower-like zinc oxide/graphene (AuNPs/ZnO/Gr) composite modified glassy carbon electrode (GCE) was constructed, where ZnO and Au nanoparticles were modified through layer-by-layer onto Gr/GCE. Flower-like ZnO nanoparticles could be easily prepared by adding ethanol to the precursor solution having higher concentration of hydroxide ions. The Hb/AuNPs/ZnO/Gr composite film showed a pair of well-defined, quasi-reversible redox peaks with a formal potential (E(0)) of -0.367 V, characteristic features of heme redox couple of Hb. The electron transfer rate constant (k(s)) of immobilized Hb was 1.3 s(-1). The developed biosensor showed a very fast response (<2 s) toward H2O2 with good sensitivity, wide linear range, and low detection limit of 0.8 μM. The fabricated biosensor showed interesting features, including high selectivity, acceptable stability, good reproducibility, and repeatability along with excellent conductivity, facile electron mobility of Gr, and good biocompatibility of ZnO and AuNPs. The fabrication method of this biosensor was simple and effective for determination of H2O2 in real samples with quick response, good sensitivity, high selectivity, and acceptable recovery. Copyright © 2013 Elsevier B.V. All rights reserved.

Method of assessing the state of a rolling bearing based on the relative compensation distance of multiple-domain features and locally linear embedding

NASA Astrophysics Data System (ADS)

Kang, Shouqiang; Ma, Danyang; Wang, Yujing; Lan, Chaofeng; Chen, Qingguo; Mikulovich, V. I.

2017-03-01

To effectively assess different fault locations and different degrees of performance degradation of a rolling bearing with a unified assessment index, a novel state assessment method based on the relative compensation distance of multiple-domain features and locally linear embedding is proposed. First, for a single-sample signal, time-domain and frequency-domain indexes can be calculated for the original vibration signal and each sensitive intrinsic mode function obtained by improved ensemble empirical mode decomposition, and the singular values of the sensitive intrinsic mode function matrix can be extracted by singular value decomposition to construct a high-dimensional hybrid-domain feature vector. Second, a feature matrix can be constructed by arranging each feature vector of multiple samples, the dimensions of each row vector of the feature matrix can be reduced by the locally linear embedding algorithm, and the compensation distance of each fault state of the rolling bearing can be calculated using the support vector machine. Finally, the relative distance between different fault locations and different degrees of performance degradation and the normal-state optimal classification surface can be compensated, and on the basis of the proposed relative compensation distance, the assessment model can be constructed and an assessment curve drawn. Experimental results show that the proposed method can effectively assess different fault locations and different degrees of performance degradation of the rolling bearing under certain conditions.

Optimizing classification performance in an object-based very-high-resolution land use-land cover urban application

NASA Astrophysics Data System (ADS)

Georganos, Stefanos; Grippa, Tais; Vanhuysse, Sabine; Lennert, Moritz; Shimoni, Michal; Wolff, Eléonore

2017-10-01

This study evaluates the impact of three Feature Selection (FS) algorithms in an Object Based Image Analysis (OBIA) framework for Very-High-Resolution (VHR) Land Use-Land Cover (LULC) classification. The three selected FS algorithms, Correlation Based Selection (CFS), Mean Decrease in Accuracy (MDA) and Random Forest (RF) based Recursive Feature Elimination (RFE), were tested on Support Vector Machine (SVM), K-Nearest Neighbor, and Random Forest (RF) classifiers. The results demonstrate that the accuracy of SVM and KNN classifiers are the most sensitive to FS. The RF appeared to be more robust to high dimensionality, although a significant increase in accuracy was found by using the RFE method. In terms of classification accuracy, SVM performed the best using FS, followed by RF and KNN. Finally, only a small number of features is needed to achieve the highest performance using each classifier. This study emphasizes the benefits of rigorous FS for maximizing performance, as well as for minimizing model complexity and interpretation.

Modular, Antibody-free Time-Resolved LRET Kinase Assay Enabled by Quantum Dots and Tb3+-sensitizing Peptides

NASA Astrophysics Data System (ADS)

Cui, Wei; Parker, Laurie L.

2016-07-01

Fluorescent drug screening assays are essential for tyrosine kinase inhibitor discovery. Here we demonstrate a flexible, antibody-free TR-LRET kinase assay strategy that is enabled by the combination of streptavidin-coated quantum dot (QD) acceptors and biotinylated, Tb3+ sensitizing peptide donors. By exploiting the spectral features of Tb3+ and QD, and the high binding affinity of the streptavidin-biotin interaction, we achieved multiplexed detection of kinase activity in a modular fashion without requiring additional covalent labeling of each peptide substrate. This strategy is compatible with high-throughput screening, and should be adaptable to the rapidly changing workflows and targets involved in kinase inhibitor discovery.

Molecular Genetic Characterization of Mutagenesis Using a Highly Sensitive Single-Stranded DNA Reporter System in Budding Yeast.

PubMed

Chan, Kin

2018-01-01

Mutations are permanent alterations to the coding content of DNA. They are starting material for the Darwinian evolution of species by natural selection, which has yielded an amazing diversity of life on Earth. Mutations can also be the fundamental basis of serious human maladies, most notably cancers. In this chapter, I describe a highly sensitive reporter system for the molecular genetic analysis of mutagenesis, featuring controlled generation of long stretches of single-stranded DNA in budding yeast cells. This system is ~100- to ~1000-fold more susceptible to mutation than conventional double-stranded DNA reporters, and is well suited for generating large mutational datasets to investigate the properties of mutagens.

Analytical improvements of hybrid LC-MS/MS techniques for the efficient evaluation of emerging contaminants in river waters: a case study of the Henares River (Madrid, Spain).

PubMed

Pérez-Parada, Andrés; Gómez-Ramos, María del Mar; Martínez Bueno, María Jesús; Uclés, Samanta; Uclés, Ana; Fernández-Alba, Amadeo R

2012-02-01

Instrumental capabilities and software tools of modern hybrid mass spectrometry (MS) instruments such as high-resolution mass spectrometry (HRMS), quadrupole time-of-flight (QTOF), and quadrupole linear ion trap (QLIT) were experimentally investigated for the study of emerging contaminants in Henares River water samples. Automated screening and confirmatory capabilities of QTOF working in full-scan MS and tandem MS (MS/MS) were explored when dealing with real samples. Investigations on the effect of sensitivity and resolution power influence on mass accuracy were studied for the correct assignment of the amoxicillin transformation product 5(R) amoxicillin-diketopiperazine-2',5' as an example of a nontarget compound. On the other hand, a comparison of quantitative and qualitative strategies based on direct injection analysis and off-line solid-phase extraction sample treatment were assayed using two different QLIT instruments for a selected group of emerging contaminants when operating in selected reaction monitoring (SRM) and information-dependent acquisition (IDA) modes. Software-aided screening usually needs a further confirmatory step. Resolving power and MS/MS feature of QTOF showed to confirm/reject most findings in river water, although sensitivity-related limitations are usually found. Superior sensitivity of modern QLIT-MS/MS offered the possibility of direct injection analysis for proper quantitative study of a variety of contaminants, while it simultaneously reduced the matrix effect and increased the reliability of the results. Confirmation of ethylamphetamine, which lacks on a second SRM transition, was accomplished by using the IDA feature. Hybrid MS instruments equipped with high resolution and high sensitivity contributes to enlarge the scope of targeted analytes in river waters. However, in the tested instruments, there is a margin of improvement principally in required sensitivity and data treatment software tools devoted to reliable confirmation and improved automated data processing.

Latent class analysis reveals clinically relevant atopy phenotypes in 2 birth cohorts.

PubMed

Hose, Alexander J; Depner, Martin; Illi, Sabina; Lau, Susanne; Keil, Thomas; Wahn, Ulrich; Fuchs, Oliver; Pfefferle, Petra Ina; Schmaußer-Hechfellner, Elisabeth; Genuneit, Jon; Lauener, Roger; Karvonen, Anne M; Roduit, Caroline; Dalphin, Jean-Charles; Riedler, Josef; Pekkanen, Juha; von Mutius, Erika; Ege, Markus J

2017-06-01

Phenotypes of childhood-onset asthma are characterized by distinct trajectories and functional features. For atopy, definition of phenotypes during childhood is less clear. We sought to define phenotypes of atopic sensitization over the first 6 years of life using a latent class analysis (LCA) integrating 3 dimensions of atopy: allergen specificity, time course, and levels of specific IgE (sIgE). Phenotypes were defined by means of LCA in 680 children of the Multizentrische Allergiestudie (MAS) and 766 children of the Protection against allergy: Study in Rural Environments (PASTURE) birth cohorts and compared with classical nondisjunctive definitions of seasonal, perennial, and food sensitization with respect to atopic diseases and lung function. Cytokine levels were measured in the PASTURE cohort. The LCA classified predominantly by type and multiplicity of sensitization (food vs inhalant), allergen combinations, and sIgE levels. Latent classes were related to atopic disease manifestations with higher sensitivity and specificity than the classical definitions. LCA detected consistently in both cohorts a distinct group of children with severe atopy characterized by high seasonal sIgE levels and a strong propensity for asthma; hay fever; eczema; and impaired lung function, also in children without an established asthma diagnosis. Severe atopy was associated with an increased IL-5/IFN-γ ratio. A path analysis among sensitized children revealed that among all features of severe atopy, only excessive sIgE production early in life affected asthma risk. LCA revealed a set of benign, symptomatic, and severe atopy phenotypes. The severe phenotype emerged as a latent condition with signs of a dysbalanced immune response. It determined high asthma risk through excessive sIgE production and directly affected impaired lung function. Copyright © 2016 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

A cascaded QSAR model for efficient prediction of overall power conversion efficiency of all-organic dye-sensitized solar cells.

PubMed

Li, Hongzhi; Zhong, Ziyan; Li, Lin; Gao, Rui; Cui, Jingxia; Gao, Ting; Hu, Li Hong; Lu, Yinghua; Su, Zhong-Min; Li, Hui

2015-05-30

A cascaded model is proposed to establish the quantitative structure-activity relationship (QSAR) between the overall power conversion efficiency (PCE) and quantum chemical molecular descriptors of all-organic dye sensitizers. The cascaded model is a two-level network in which the outputs of the first level (JSC, VOC, and FF) are the inputs of the second level, and the ultimate end-point is the overall PCE of dye-sensitized solar cells (DSSCs). The model combines quantum chemical methods and machine learning methods, further including quantum chemical calculations, data division, feature selection, regression, and validation steps. To improve the efficiency of the model and reduce the redundancy and noise of the molecular descriptors, six feature selection methods (multiple linear regression, genetic algorithms, mean impact value, forward selection, backward elimination, and +n-m algorithm) are used with the support vector machine. The best established cascaded model predicts the PCE values of DSSCs with a MAE of 0.57 (%), which is about 10% of the mean value PCE (5.62%). The validation parameters according to the OECD principles are R(2) (0.75), Q(2) (0.77), and Qcv2 (0.76), which demonstrate the great goodness-of-fit, predictivity, and robustness of the model. Additionally, the applicability domain of the cascaded QSAR model is defined for further application. This study demonstrates that the established cascaded model is able to effectively predict the PCE for organic dye sensitizers with very low cost and relatively high accuracy, providing a useful tool for the design of dye sensitizers with high PCE. © 2015 Wiley Periodicals, Inc.

Development of nanosensors in nuclear technology

NASA Astrophysics Data System (ADS)

Hassan, Thamir A. A.

2017-01-01

Selectivity, sensitivity, and stability (three S parameters) are developed as a new range of sensor this provided instruments for harsh, radioactive waste polluted environment monitoring. Isotope effect is very effective for nuclear radiation sensors preparation.in this presentation are reviewed of the development of Nanosensors in nuclear technology, such as high temperature boron and its compounds with suitable physical and chemical features as sensitive element for temperature and nuclear sensor, Boron isotopes based semiconductor nanosensors and studies of the mechanism of the removal uranium from radioactive wastewater with graphene oxide (GO).

Real-time UNIX in HEP data acquisition

NASA Astrophysics Data System (ADS)

Buono, S.; Gaponenko, I.; Jones, R.; Mapelli, L.; Mornacchi, G.; Prigent, D.; Sanchez-Corral, E.; Skiadelli, M.; Toppers, A.; Duval, P. Y.; Ferrato, D.; Le Van Suu, A.; Qian, Z.; Rondot, C.; Ambrosini, G.; Fumagalli, G.; Aguer, M.; Huet, M.

1994-12-01

Today's experimentation in high energy physics is characterized by an increasing need for sensitivity to rare phenomena and complex physics signatures, which require the use of huge and sophisticated detectors and consequently a high performance readout and data acquisition. Multi-level triggering, hierarchical data collection and an always increasing amount of processing power, distributed throughout the data acquisition layers, will impose a number of features on the software environment, especially the need for a high level of standardization. Real-time UNIX seems, today, the best solution for the platform independence, operating system interface standards and real-time features necessary for data acquisition in HEP experiments. We present the results of the evaluation, in a realistic application environment, of a Real-Time UNIX operating system: the EP/LX real-time UNIX system.

Fabrication of a novel transparent SERS substrate comprised of Ag-nanoparticle arrays and its application in rapid detection of ractopamine on meat

USDA-ARS?s Scientific Manuscript database

Surface-enhanced Raman spectroscopy (SERS) is an emerging analytical tool that boasts the feature of high detection sensitivity and molecular fingerprint specificity attracting increased attention and showing promise in applications including detecting residues of veterinary drugs. In practice, spec...

Experiments with Charge Indicator Based on Bipolar Transistors

ERIC Educational Resources Information Center

Dvorak, Leos; Planinsic, Gorazd

2012-01-01

A simple charge indicator with bipolar transistors described recently enables us to perform a number of experiments suitable for high-school physics. Several such experiments are presented and discussed in this paper as well as some features of the indicator important for its use in schools, namely its sensitivity and robustness, i.e. the…

Quantitative evaluation of skeletal muscle defects in second harmonic generation images.

PubMed

Liu, Wenhua; Raben, Nina; Ralston, Evelyn

2013-02-01

Skeletal muscle pathologies cause irregularities in the normally periodic organization of the myofibrils. Objective grading of muscle morphology is necessary to assess muscle health, compare biopsies, and evaluate treatments and the evolution of disease. To facilitate such quantitation, we have developed a fast, sensitive, automatic imaging analysis software. It detects major and minor morphological changes by combining texture features and Fourier transform (FT) techniques. We apply this tool to second harmonic generation (SHG) images of muscle fibers which visualize the repeating myosin bands. Texture features are then calculated by using a Haralick gray-level cooccurrence matrix in MATLAB. Two scores are retrieved from the texture correlation plot by using FT and curve-fitting methods. The sensitivity of the technique was tested on SHG images of human adult and infant muscle biopsies and of mouse muscle samples. The scores are strongly correlated to muscle fiber condition. We named the software MARS (muscle assessment and rating scores). It is executed automatically and is highly sensitive even to subtle defects. We propose MARS as a powerful and unbiased tool to assess muscle health.

Quantitative evaluation of skeletal muscle defects in second harmonic generation images

NASA Astrophysics Data System (ADS)

Liu, Wenhua; Raben, Nina; Ralston, Evelyn

2013-02-01

Skeletal muscle pathologies cause irregularities in the normally periodic organization of the myofibrils. Objective grading of muscle morphology is necessary to assess muscle health, compare biopsies, and evaluate treatments and the evolution of disease. To facilitate such quantitation, we have developed a fast, sensitive, automatic imaging analysis software. It detects major and minor morphological changes by combining texture features and Fourier transform (FT) techniques. We apply this tool to second harmonic generation (SHG) images of muscle fibers which visualize the repeating myosin bands. Texture features are then calculated by using a Haralick gray-level cooccurrence matrix in MATLAB. Two scores are retrieved from the texture correlation plot by using FT and curve-fitting methods. The sensitivity of the technique was tested on SHG images of human adult and infant muscle biopsies and of mouse muscle samples. The scores are strongly correlated to muscle fiber condition. We named the software MARS (muscle assessment and rating scores). It is executed automatically and is highly sensitive even to subtle defects. We propose MARS as a powerful and unbiased tool to assess muscle health.

Sensor fusion to enable next generation low cost Night Vision systems

NASA Astrophysics Data System (ADS)

Schweiger, R.; Franz, S.; Löhlein, O.; Ritter, W.; Källhammer, J.-E.; Franks, J.; Krekels, T.

2010-04-01

The next generation of automotive Night Vision Enhancement systems offers automatic pedestrian recognition with a performance beyond current Night Vision systems at a lower cost. This will allow high market penetration, covering the luxury as well as compact car segments. Improved performance can be achieved by fusing a Far Infrared (FIR) sensor with a Near Infrared (NIR) sensor. However, fusing with today's FIR systems will be too costly to get a high market penetration. The main cost drivers of the FIR system are its resolution and its sensitivity. Sensor cost is largely determined by sensor die size. Fewer and smaller pixels will reduce die size but also resolution and sensitivity. Sensitivity limits are mainly determined by inclement weather performance. Sensitivity requirements should be matched to the possibilities of low cost FIR optics, especially implications of molding of highly complex optical surfaces. As a FIR sensor specified for fusion can have lower resolution as well as lower sensitivity, fusing FIR and NIR can solve performance and cost problems. To allow compensation of FIR-sensor degradation on the pedestrian detection capabilities, a fusion approach called MultiSensorBoosting is presented that produces a classifier holding highly discriminative sub-pixel features from both sensors at once. The algorithm is applied on data with different resolution and on data obtained from cameras with varying optics to incorporate various sensor sensitivities. As it is not feasible to record representative data with all different sensor configurations, transformation routines on existing high resolution data recorded with high sensitivity cameras are investigated in order to determine the effects of lower resolution and lower sensitivity to the overall detection performance. This paper also gives an overview of the first results showing that a reduction of FIR sensor resolution can be compensated using fusion techniques and a reduction of sensitivity can be compensated.

High-Energy Density science at the Linac Coherent Light Source

NASA Astrophysics Data System (ADS)

Glenzer, S. H.; Fletcher, L. B.; Hastings, J. B.

2016-03-01

The Matter in Extreme Conditions end station at the Linac Coherent Light Source holds great promise for novel pump-probe experiments to make new discoveries in high- energy density science. In recent experiments we have demonstrated the first spectrally- resolved measurements of plasmons using a seeded 8-keV x-ray laser beam. Forward x-ray Thomson scattering spectra from isochorically heated solid aluminum show a well-resolved plasmon feature that is down-shifted in energy by 19 eV from the incident 8 keV elastic scattering feature. In this spectral range, the simultaneously measured backscatter spectrum shows no spectral features indicating observation of collective plasmon oscillations on a scattering length comparable to the screening length. This technique is a prerequisite for Thomson scattering measurements in compressed matter where the plasmon shift is a sensitive function of the free electron density and where the plasmon intensity provides information on temperature.

High-Energy Density science at the Linac Coherent Light Source

DOE PAGES

Glenzer, S. H.; Fletcher, L. B.; Hastings, J. B.

2016-04-01

The Matter in Extreme Conditions end station at the Linac Coherent Light Source holds great promise for novel pump-probe experiments to make new discoveries in high- energy density science. Recently, our experiments have demonstrated the first spectrally- resolved measurements of plasmons using a seeded 8-keV x-ray laser beam. Forward x-ray Thomson scattering spectra from isochorically heated solid aluminum show a well-resolved plasmon feature that is down-shifted in energy by 19 eV from the incident 8 keV elastic scattering feature. In this spectral range, the simultaneously measured backscatter spectrum shows no spectral features indicating observation of collective plasmon oscillations on amore » scattering length comparable to the screening length. Moreover, this technique is a prerequisite for Thomson scattering measurements in compressed matter where the plasmon shift is a sensitive function of the free electron density and where the plasmon intensity provides information on temperature.« less

Microstructural effects on ignition sensitivity in Ni/Al systems subjected to high strain rate impacts

NASA Astrophysics Data System (ADS)

Reeves, Robert; Mukasyan, Alexander; Son, Steven

2011-06-01

The effect of microstructural refinement on the sensitivity of the Ni/Al (1:1 at%) system to ignition via high strain rate impacts is investigated. The tested microstructures include compacts of irregularly convoluted lamellar structures with nanometric features created through high-energy ball milling (HEBM) of micron size Ni/Al powders and compacts of nanometric Ni and Al powders. The test materials were subjected to high strain rate impacts through Asay shear experiments powered by a light gas gun. Muzzle velocities up to 1.1 km/s were used. It was found that the nanometric powder exhibited a greater sensitivity to ignition via impact than the HEBM material, despite greater thermal sensitivity of the HEBM. A previously unseen fast reaction mode where the reaction front traveled at the speed of the input stress wave was also observed in the nanometric mixtures at high muzzle energies. This fast mode is considered to be a mechanically induced thermal explosion mode dependent on the magnitude of the traveling stress wave, rather than a self-propagating detonation, since its propagation rate decreases rapidly across the sample. A similar mode is not exhibited by HEBM samples, although local, nonpropagating reaction zones occur in shear bands formed during the impact event.

Microstructural effects on ignition sensitivity in Ni/Al systems subjected to high strain rate impacts

NASA Astrophysics Data System (ADS)

Reeves, Robert V.; Mukasyan, Alexander S.; Son, Steven

2012-03-01

The effect of microstructural refinement on the sensitivity of the Ni/Al (1:1 mol%) system to ignition via high strain rate impacts is investigated. The tested microstructures include compacts of irregularly convoluted lamellar structures with nanometric features created through high-energy ball milling (HEBM) of micron size Ni/Al powders and compacts of nanometric Ni and Al powders. The test materials were subjected to high strain rate impacts through Asay shear experiments powered by a light gas gun. Muzzle velocities up to 1.1 km/s were used. It was found that the nanometric powder exhibited a greater sensitivity to ignition via impact than the HEBM material, despite greater thermal sensitivity of the HEBM. A previously unseen fast reaction mode where the reaction front traveled at the speed of the input stress wave was also observed in the nanometric mixtures at high muzzle energies. This fast mode is considered to be a mechanically induced thermal explosion mode dependent on the magnitude of the traveling stress wave, rather than a self-propagating detonation, since its propagation rate decreases rapidly across the sample. A similar mode is not exhibited by HEBM samples, although local, nonpropagating reaction zones shear bands formed during the impact event are observed.

A case of high noise sensitivity

NASA Astrophysics Data System (ADS)

Murata, M.; Sakamoto, H.

1995-10-01

A case of noise sensitivity with a five-year follow-up period is reported. The patient was a 34-year-old single man who was diagnosed as having psychosomatic disorder triggered by two stressful life events in rapid succession with secondary hypersensitivity to noise. Hypersensitivity to light and cold also developed later in the clinical course. The auditory threshold was within the normal range. The discomfort threshold as a measure of the noise sensitivity secondary to mental illness was measured repeatedly using test tone of audiometry. The discomfort threshold varied depending upon his mental status, ranging from 40-50 dB in the comparatively poorer mental state to 70-95 dB in the relatively good mental state. The features of noise sensitivity, including that secondary to mental illness, are discussed.

Comparison of hand-craft feature based SVM and CNN based deep learning framework for automatic polyp classification.

PubMed

Younghak Shin; Balasingham, Ilangko

2017-07-01

Colonoscopy is a standard method for screening polyps by highly trained physicians. Miss-detected polyps in colonoscopy are potential risk factor for colorectal cancer. In this study, we investigate an automatic polyp classification framework. We aim to compare two different approaches named hand-craft feature method and convolutional neural network (CNN) based deep learning method. Combined shape and color features are used for hand craft feature extraction and support vector machine (SVM) method is adopted for classification. For CNN approach, three convolution and pooling based deep learning framework is used for classification purpose. The proposed framework is evaluated using three public polyp databases. From the experimental results, we have shown that the CNN based deep learning framework shows better classification performance than the hand-craft feature based methods. It achieves over 90% of classification accuracy, sensitivity, specificity and precision.

Angle-selective optical filter for highly sensitive reflection photoplethysmogram

PubMed Central

Hwang, Chan-Sol; Yang, Sung-Pyo; Jang, Kyung-Won; Park, Jung-Woo; Jeong, Ki-Hun

2017-01-01

We report an angle-selective optical filter (ASOF) for highly sensitive reflection photoplethysmography (PPG) sensors. The ASOF features slanted aluminum (Al) micromirror arrays embedded in transparent polymer resin, which effectively block scattered light under human tissue. The device microfabrication was done by using geometry-guided resist reflow of polymer micropatterns, polydimethylsiloxane replica molding, and oblique angle deposition of thin Al film. The angular transmittance through the ASOF is precisely controlled by the angle of micromirrors. For the mirror angle of 30 degrees, the ASOF accepts an incident light between - 90 to + 50 degrees and the maximum transmittance at - 55 degrees. The ASOF exhibits the substantial reduction of both the in-band noise of PPG signals over a factor of two and the low-frequency noise by three times. Consequently, this filter allows distinguishing the diastolic peak that allows miscellaneous parameters with diverse vascular information. This optical filter provides a new opportunity for highly sensitive PPG monitoring or miscellaneous optical tomography. PMID:29082070

COS and WFC3 Observations of I Zwicky 18 Part 2

NASA Astrophysics Data System (ADS)

Green, James

2010-09-01

This program is a continuation of 11523, in which we took advantage of COS' high sensitivity to study both the stellar and gaseous component of the very-low-metallicity galaxy, I Zwicky 18 {IZw18}. Here, we repeat observations of I Zw 18 with G130M and G160M to increase the S/N of weak {or apparently absent} stellar and nebular features in order to improve our abundance estimates. For example, we wish to confirm the VERY low stellar abundance of nitrogen through spectral observations of the N V 1240 resonance doublet and the N IV 1718 line. We will also take advantage of WFC3's high-QE IR sensitivity to search for high-redshift galaxies via the Lyman-Break method.

Sensitivity enhancement of the high-resolution xMT multi-trigger resist for EUV lithography

NASA Astrophysics Data System (ADS)

Popescu, Carmen; Frommhold, Andreas; McClelland, Alexandra; Roth, John; Ekinci, Yasin; Robinson, Alex P. G.

2017-03-01

Irresistible Materials is developing a new molecular resist system that demonstrates high-resolution capability based on the multi-trigger concept. A series of studies such as resist purification, developer choice,and enhanced resist crosslinking were conducted in order to optimize the performance of this material. The optimized conditions allowed patterning 14 nm half-pitch (hp) lines with a line width roughness (LWR) of 2.7 nm at the XIL beamline of the Swiss Light source. Furthermore it was possible to pattern 14 nm hp features with dose of 14 mJ/cm2 with an LWR of 4.9 nm. We have also begun to investigate the addition of high-Z additives to EUV photoresist as a means to increase sensitivity and modify secondary electron blur.

Identification of molecular subtypes of gastric cancer with different responses to PI3-kinase inhibitors and 5-fluorouracil.

PubMed

Lei, Zhengdeng; Tan, Iain Beehuat; Das, Kakoli; Deng, Niantao; Zouridis, Hermioni; Pattison, Sharon; Chua, Clarinda; Feng, Zhu; Guan, Yeoh Khay; Ooi, Chia Huey; Ivanova, Tatiana; Zhang, Shenli; Lee, Minghui; Wu, Jeanie; Ngo, Anna; Manesh, Sravanthy; Tan, Elisabeth; Teh, Bin Tean; So, Jimmy Bok Yan; Goh, Liang Kee; Boussioutas, Alex; Lim, Tony Kiat Hon; Flotow, Horst; Tan, Patrick; Rozen, Steven G

2013-09-01

Almost all gastric cancers are adenocarcinomas, which have considerable heterogeneity among patients. We sought to identify subtypes of gastric adenocarcinomas with particular biological properties and responses to chemotherapy and targeted agents. We compared gene expression patterns among 248 gastric tumors; using a robust method of unsupervised clustering, consensus hierarchical clustering with iterative feature selection, we identified 3 major subtypes. We developed a classifier for these subtypes and validated it in 70 tumors from a different population. We identified distinct genomic and epigenomic properties of the subtypes. We determined drug sensitivities of the subtypes in primary tumors using clinical survival data, and in cell lines through high-throughput drug screening. We identified 3 subtypes of gastric adenocarcinoma: proliferative, metabolic, and mesenchymal. Tumors of the proliferative subtype had high levels of genomic instability, TP53 mutations, and DNA hypomethylation. Cancer cells of the metabolic subtype were more sensitive to 5-fluorouracil than the other subtypes. Furthermore, in 2 independent groups of patients, those with tumors of the metabolic subtype appeared to have greater benefits with 5-fluorouracil treatment. Tumors of the mesenchymal subtype contain cells with features of cancer stem cells, and cell lines of this subtype are particularly sensitive to phosphatidylinositol 3-kinase-AKT-mTOR inhibitors in vitro. Based on gene expression patterns, we classified gastric cancers into 3 subtypes, and validated these in an independent set of tumors. The subgroups have differences in molecular and genetic features and response to therapy; this information might be used to select specific treatment approaches for patients with gastric cancer. Copyright © 2013 AGA Institute. Published by Elsevier Inc. All rights reserved.

GIS coupled Multiple Criteria based Decision Support for Classification of Urban Coastal Areas in India

NASA Astrophysics Data System (ADS)

Dhiman, R.; Kalbar, P.; Inamdar, A. B.

2017-12-01

Coastal area classification in India is a challenge for federal and state government agencies due to fragile institutional framework, unclear directions in implementation of costal regulations and violations happening at private and government level. This work is an attempt to improvise the objectivity of existing classification methods to synergies the ecological systems and socioeconomic development in coastal cities. We developed a Geographic information system coupled Multi-criteria Decision Making (GIS-MCDM) approach to classify urban coastal areas where utility functions are used to transform the costal features into quantitative membership values after assessing the sensitivity of urban coastal ecosystem. Furthermore, these membership values for costal features are applied in different weighting schemes to derive Coastal Area Index (CAI) which classifies the coastal areas in four distinct categories viz. 1) No Development Zone, 2) Highly Sensitive Zone, 3) Moderately Sensitive Zone and 4) Low Sensitive Zone based on the sensitivity of urban coastal ecosystem. Mumbai, a coastal megacity in India is used as case study for demonstration of proposed method. Finally, uncertainty analysis using Monte Carlo approach to validate the sensitivity of CAI under specific multiple scenarios is carried out. Results of CAI method shows the clear demarcation of coastal areas in GIS environment based on the ecological sensitivity. CAI provides better decision support for federal and state level agencies to classify urban coastal areas according to the regional requirement of coastal resources considering resilience and sustainable development. CAI method will strengthen the existing institutional framework for decision making in classification of urban coastal areas where most effective coastal management options can be proposed.

Evaluation of Feature Extraction and Recognition for Activity Monitoring and Fall Detection Based on Wearable sEMG Sensors.

PubMed

Xi, Xugang; Tang, Minyan; Miran, Seyed M; Luo, Zhizeng

2017-05-27

As an essential subfield of context awareness, activity awareness, especially daily activity monitoring and fall detection, plays a significant role for elderly or frail people who need assistance in their daily activities. This study investigates the feature extraction and pattern recognition of surface electromyography (sEMG), with the purpose of determining the best features and classifiers of sEMG for daily living activities monitoring and fall detection. This is done by a serial of experiments. In the experiments, four channels of sEMG signal from wireless, wearable sensors located on lower limbs are recorded from three subjects while they perform seven activities of daily living (ADL). A simulated trip fall scenario is also considered with a custom-made device attached to the ankle. With this experimental setting, 15 feature extraction methods of sEMG, including time, frequency, time/frequency domain and entropy, are analyzed based on class separability and calculation complexity, and five classification methods, each with 15 features, are estimated with respect to the accuracy rate of recognition and calculation complexity for activity monitoring and fall detection. It is shown that a high accuracy rate of recognition and a minimal calculation time for daily activity monitoring and fall detection can be achieved in the current experimental setting. Specifically, the Wilson Amplitude (WAMP) feature performs the best, and the classifier Gaussian Kernel Support Vector Machine (GK-SVM) with Permutation Entropy (PE) or WAMP results in the highest accuracy for activity monitoring with recognition rates of 97.35% and 96.43%. For fall detection, the classifier Fuzzy Min-Max Neural Network (FMMNN) has the best sensitivity and specificity at the cost of the longest calculation time, while the classifier Gaussian Kernel Fisher Linear Discriminant Analysis (GK-FDA) with the feature WAMP guarantees a high sensitivity (98.70%) and specificity (98.59%) with a short calculation time (65.586 ms), making it a possible choice for pre-impact fall detection. The thorough quantitative comparison of the features and classifiers in this study supports the feasibility of a wireless, wearable sEMG sensor system for automatic activity monitoring and fall detection.

Evaluation of Feature Extraction and Recognition for Activity Monitoring and Fall Detection Based on Wearable sEMG Sensors

PubMed Central

Xi, Xugang; Tang, Minyan; Miran, Seyed M.; Luo, Zhizeng

2017-01-01

As an essential subfield of context awareness, activity awareness, especially daily activity monitoring and fall detection, plays a significant role for elderly or frail people who need assistance in their daily activities. This study investigates the feature extraction and pattern recognition of surface electromyography (sEMG), with the purpose of determining the best features and classifiers of sEMG for daily living activities monitoring and fall detection. This is done by a serial of experiments. In the experiments, four channels of sEMG signal from wireless, wearable sensors located on lower limbs are recorded from three subjects while they perform seven activities of daily living (ADL). A simulated trip fall scenario is also considered with a custom-made device attached to the ankle. With this experimental setting, 15 feature extraction methods of sEMG, including time, frequency, time/frequency domain and entropy, are analyzed based on class separability and calculation complexity, and five classification methods, each with 15 features, are estimated with respect to the accuracy rate of recognition and calculation complexity for activity monitoring and fall detection. It is shown that a high accuracy rate of recognition and a minimal calculation time for daily activity monitoring and fall detection can be achieved in the current experimental setting. Specifically, the Wilson Amplitude (WAMP) feature performs the best, and the classifier Gaussian Kernel Support Vector Machine (GK-SVM) with Permutation Entropy (PE) or WAMP results in the highest accuracy for activity monitoring with recognition rates of 97.35% and 96.43%. For fall detection, the classifier Fuzzy Min-Max Neural Network (FMMNN) has the best sensitivity and specificity at the cost of the longest calculation time, while the classifier Gaussian Kernel Fisher Linear Discriminant Analysis (GK-FDA) with the feature WAMP guarantees a high sensitivity (98.70%) and specificity (98.59%) with a short calculation time (65.586 ms), making it a possible choice for pre-impact fall detection. The thorough quantitative comparison of the features and classifiers in this study supports the feasibility of a wireless, wearable sEMG sensor system for automatic activity monitoring and fall detection. PMID:28555016

Art Expertise Reduces Influence of Visual Salience on Fixation in Viewing Abstract-Paintings

PubMed Central

Koide, Naoko; Kubo, Takatomi; Nishida, Satoshi; Shibata, Tomohiro; Ikeda, Kazushi

2015-01-01

When viewing a painting, artists perceive more information from the painting on the basis of their experience and knowledge than art novices do. This difference can be reflected in eye scan paths during viewing of paintings. Distributions of scan paths of artists are different from those of novices even when the paintings contain no figurative object (i.e. abstract paintings). There are two possible explanations for this difference of scan paths. One is that artists have high sensitivity to high-level features such as textures and composition of colors and therefore their fixations are more driven by such features compared with novices. The other is that fixations of artists are more attracted by salient features than those of novices and the fixations are driven by low-level features. To test these, we measured eye fixations of artists and novices during the free viewing of various abstract paintings and compared the distribution of their fixations for each painting with a topological attentional map that quantifies the conspicuity of low-level features in the painting (i.e. saliency map). We found that the fixation distribution of artists was more distinguishable from the saliency map than that of novices. This difference indicates that fixations of artists are less driven by low-level features than those of novices. Our result suggests that artists may extract visual information from paintings based on high-level features. This ability of artists may be associated with artists’ deep aesthetic appreciation of paintings. PMID:25658327

Multi-stream LSTM-HMM decoding and histogram equalization for noise robust keyword spotting.

PubMed

Wöllmer, Martin; Marchi, Erik; Squartini, Stefano; Schuller, Björn

2011-09-01

Highly spontaneous, conversational, and potentially emotional and noisy speech is known to be a challenge for today's automatic speech recognition (ASR) systems, which highlights the need for advanced algorithms that improve speech features and models. Histogram Equalization is an efficient method to reduce the mismatch between clean and noisy conditions by normalizing all moments of the probability distribution of the feature vector components. In this article, we propose to combine histogram equalization and multi-condition training for robust keyword detection in noisy speech. To better cope with conversational speaking styles, we show how contextual information can be effectively exploited in a multi-stream ASR framework that dynamically models context-sensitive phoneme estimates generated by a long short-term memory neural network. The proposed techniques are evaluated on the SEMAINE database-a corpus containing emotionally colored conversations with a cognitive system for "Sensitive Artificial Listening".

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

Liu, Jianfei; Wang, Shijun; Turkbey, Evrim B.

Purpose: Renal calculi are common extracolonic incidental findings on computed tomographic colonography (CTC). This work aims to develop a fully automated computer-aided diagnosis system to accurately detect renal calculi on CTC images. Methods: The authors developed a total variation (TV) flow method to reduce image noise within the kidneys while maintaining the characteristic appearance of renal calculi. Maximally stable extremal region (MSER) features were then calculated to robustly identify calculi candidates. Finally, the authors computed texture and shape features that were imported to support vector machines for calculus classification. The method was validated on a dataset of 192 patients andmore » compared to a baseline approach that detects calculi by thresholding. The authors also compared their method with the detection approaches using anisotropic diffusion and nonsmoothing. Results: At a false positive rate of 8 per patient, the sensitivities of the new method and the baseline thresholding approach were 69% and 35% (p < 1e − 3) on all calculi from 1 to 433 mm{sup 3} in the testing dataset. The sensitivities of the detection methods using anisotropic diffusion and nonsmoothing were 36% and 0%, respectively. The sensitivity of the new method increased to 90% if only larger and more clinically relevant calculi were considered. Conclusions: Experimental results demonstrated that TV-flow and MSER features are efficient means to robustly and accurately detect renal calculi on low-dose, high noise CTC images. Thus, the proposed method can potentially improve diagnosis.« less

Epileptic Seizure Prediction Using Diffusion Distance and Bayesian Linear Discriminate Analysis on Intracranial EEG.

PubMed

Yuan, Shasha; Zhou, Weidong; Chen, Liyan

2018-02-01

Epilepsy is a chronic neurological disorder characterized by sudden and apparently unpredictable seizures. A system capable of forecasting the occurrence of seizures is crucial and could open new therapeutic possibilities for human health. This paper addresses an algorithm for seizure prediction using a novel feature - diffusion distance (DD) in intracranial Electroencephalograph (iEEG) recordings. Wavelet decomposition is conducted on segmented electroencephalograph (EEG) epochs and subband signals at scales 3, 4 and 5 are utilized to extract the diffusion distance. The features of all channels composing a feature vector are then fed into a Bayesian Linear Discriminant Analysis (BLDA) classifier. Finally, postprocessing procedure is applied to reduce false prediction alarms. The prediction method is evaluated on the public intracranial EEG dataset, which consists of 577.67[Formula: see text]h of intracranial EEG recordings from 21 patients with 87 seizures. We achieved a sensitivity of 85.11% for a seizure occurrence period of 30[Formula: see text]min and a sensitivity of 93.62% for a seizure occurrence period of 50[Formula: see text]min, both with the seizure prediction horizon of 10[Formula: see text]s. Our false prediction rate was 0.08/h. The proposed method yields a high sensitivity as well as a low false prediction rate, which demonstrates its potential for real-time prediction of seizures.

Research on the high-precision non-contact optical detection technology for banknotes

NASA Astrophysics Data System (ADS)

Jin, Xiaofeng; Liang, Tiancai; Luo, Pengfeng; Sun, Jianfeng

2015-09-01

The technology of high-precision laser interferometry was introduced for optical measurement of the banknotes in this paper. Taking advantage of laser short wavelength and high sensitivity, information of adhesive tape and cavity about the banknotes could be checked efficiently. Compared with current measurement devices, including mechanical wheel measurement device, Infrared measurement device, ultrasonic measurement device, the laser interferometry measurement has higher precision and reliability. This will improve the ability of banknotes feature information in financial electronic equipment.

Stimuli-Responsive NO Release for On-Demand Gas-Sensitized Synergistic Cancer Therapy.

PubMed

Fan, Wenpei; Yung, Bryant C; Chen, Xiaoyuan

2018-03-08

Featuring high biocompatibility, the emerging field of gas therapy has attracted extensive attention in the medical and scientific communities. Currently, considerable research has focused on the gasotransmitter nitric oxide (NO) owing to its unparalleled dual roles in directly killing cancer cells at high concentrations and cooperatively sensitizing cancer cells to other treatments for synergistic therapy. Of particular note, recent state-of-the-art studies have turned our attention to the chemical design of various endogenous/exogenous stimuli-responsive NO-releasing nanomedicines and their biomedical applications for on-demand NO-sensitized synergistic cancer therapy, which are discussed in this Minireview. Moreover, the potential challenges regarding NO gas therapy are also described, aiming to advance the development of NO nanomedicines as well as usher in new frontiers in this fertile research area. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

High-performance gas sensors with temperature measurement

PubMed Central

Zhang, Yong; Li, Shengtao; Zhang, Jingyuan; Pan, Zhigang; Min, Daomin; Li, Xin; Song, Xiaoping; Liu, Junhua

2013-01-01

There are a number of gas ionization sensors using carbon nanotubes as cathode or anode. Unfortunately, their applications are greatly limited by their multi-valued sensitivity, one output value corresponding to several measured concentration values. Here we describe a triple-electrode structure featuring two electric fields with opposite directions, which enable us to overcome the multi-valued sensitivity problem at 1 atm in a wide range of gas concentrations. We used a carbon nanotube array as the first electrode, and the two electric fields between the upper and the lower interelectrode gaps were designed to extract positive ions generated in the upper gap, hence significantly reduced positive ion bombardment on the nanotube electrode, which allowed us to maintain a high electric field near the nanotube tips, leading to a single-valued sensitivity and a long nanotube life. We have demonstrated detection of various gases and simultaneously monitoring temperature, and a potential for applications. PMID:23405281

Development of low-cost high-performance multispectral camera system at Banpil

NASA Astrophysics Data System (ADS)

Oduor, Patrick; Mizuno, Genki; Olah, Robert; Dutta, Achyut K.

2014-05-01

Banpil Photonics (Banpil) has developed a low-cost high-performance multispectral camera system for Visible to Short- Wave Infrared (VIS-SWIR) imaging for the most demanding high-sensitivity and high-speed military, commercial and industrial applications. The 640x512 pixel InGaAs uncooled camera system is designed to provide a compact, smallform factor to within a cubic inch, high sensitivity needing less than 100 electrons, high dynamic range exceeding 190 dB, high-frame rates greater than 1000 frames per second (FPS) at full resolution, and low power consumption below 1W. This is practically all the feature benefits highly desirable in military imaging applications to expand deployment to every warfighter, while also maintaining a low-cost structure demanded for scaling into commercial markets. This paper describes Banpil's development of the camera system including the features of the image sensor with an innovation integrating advanced digital electronics functionality, which has made the confluence of high-performance capabilities on the same imaging platform practical at low cost. It discusses the strategies employed including innovations of the key components (e.g. focal plane array (FPA) and Read-Out Integrated Circuitry (ROIC)) within our control while maintaining a fabless model, and strategic collaboration with partners to attain additional cost reductions on optics, electronics, and packaging. We highlight the challenges and potential opportunities for further cost reductions to achieve a goal of a sub-$1000 uncooled high-performance camera system. Finally, a brief overview of emerging military, commercial and industrial applications that will benefit from this high performance imaging system and their forecast cost structure is presented.

Dynamic Encoding of Speech Sequence Probability in Human Temporal Cortex

PubMed Central

Leonard, Matthew K.; Bouchard, Kristofer E.; Tang, Claire

2015-01-01

Sensory processing involves identification of stimulus features, but also integration with the surrounding sensory and cognitive context. Previous work in animals and humans has shown fine-scale sensitivity to context in the form of learned knowledge about the statistics of the sensory environment, including relative probabilities of discrete units in a stream of sequential auditory input. These statistics are a defining characteristic of one of the most important sequential signals humans encounter: speech. For speech, extensive exposure to a language tunes listeners to the statistics of sound sequences. To address how speech sequence statistics are neurally encoded, we used high-resolution direct cortical recordings from human lateral superior temporal cortex as subjects listened to words and nonwords with varying transition probabilities between sound segments. In addition to their sensitivity to acoustic features (including contextual features, such as coarticulation), we found that neural responses dynamically encoded the language-level probability of both preceding and upcoming speech sounds. Transition probability first negatively modulated neural responses, followed by positive modulation of neural responses, consistent with coordinated predictive and retrospective recognition processes, respectively. Furthermore, transition probability encoding was different for real English words compared with nonwords, providing evidence for online interactions with high-order linguistic knowledge. These results demonstrate that sensory processing of deeply learned stimuli involves integrating physical stimulus features with their contextual sequential structure. Despite not being consciously aware of phoneme sequence statistics, listeners use this information to process spoken input and to link low-level acoustic representations with linguistic information about word identity and meaning. PMID:25948269

Folded concave penalized learning in identifying multimodal MRI marker for Parkinson’s disease

PubMed Central

Liu, Hongcheng; Du, Guangwei; Zhang, Lijun; Lewis, Mechelle M.; Wang, Xue; Yao, Tao; Li, Runze; Huang, Xuemei

2016-01-01

Background Brain MRI holds promise to gauge different aspects of Parkinson’s disease (PD)-related pathological changes. Its analysis, however, is hindered by the high-dimensional nature of the data. New method This study introduces folded concave penalized (FCP) sparse logistic regression to identify biomarkers for PD from a large number of potential factors. The proposed statistical procedures target the challenges of high-dimensionality with limited data samples acquired. The maximization problem associated with the sparse logistic regression model is solved by local linear approximation. The proposed procedures then are applied to the empirical analysis of multimodal MRI data. Results From 45 features, the proposed approach identified 15 MRI markers and the UPSIT, which are known to be clinically relevant to PD. By combining the MRI and clinical markers, we can enhance substantially the specificity and sensitivity of the model, as indicated by the ROC curves. Comparison to existing methods We compare the folded concave penalized learning scheme with both the Lasso penalized scheme and the principle component analysis-based feature selection (PCA) in the Parkinson’s biomarker identification problem that takes into account both the clinical features and MRI markers. The folded concave penalty method demonstrates a substantially better clinical potential than both the Lasso and PCA in terms of specificity and sensitivity. Conclusions For the first time, we applied the FCP learning method to MRI biomarker discovery in PD. The proposed approach successfully identified MRI markers that are clinically relevant. Combining these biomarkers with clinical features can substantially enhance performance. PMID:27102045

Mammogram classification scheme using 2D-discrete wavelet and local binary pattern for detection of breast cancer

NASA Astrophysics Data System (ADS)

Adi Putra, Januar

2018-04-01

In this paper, we propose a new mammogram classification scheme to classify the breast tissues as normal or abnormal. Feature matrix is generated using Local Binary Pattern to all the detailed coefficients from 2D-DWT of the region of interest (ROI) of a mammogram. Feature selection is done by selecting the relevant features that affect the classification. Feature selection is used to reduce the dimensionality of data and features that are not relevant, in this paper the F-test and Ttest will be performed to the results of the feature extraction dataset to reduce and select the relevant feature. The best features are used in a Neural Network classifier for classification. In this research we use MIAS and DDSM database. In addition to the suggested scheme, the competent schemes are also simulated for comparative analysis. It is observed that the proposed scheme has a better say with respect to accuracy, specificity and sensitivity. Based on experiments, the performance of the proposed scheme can produce high accuracy that is 92.71%, while the lowest accuracy obtained is 77.08%.

Highly stretchable resistive pressure sensors using a conductive elastomeric composite on a micropyramid array.

PubMed

Choong, Chwee-Lin; Shim, Mun-Bo; Lee, Byoung-Sun; Jeon, Sanghun; Ko, Dong-Su; Kang, Tae-Hyung; Bae, Jihyun; Lee, Sung Hoon; Byun, Kyung-Eun; Im, Jungkyun; Jeong, Yong Jin; Park, Chan Eon; Park, Jong-Jin; Chung, U-In

2014-06-04

A stretchable resistive pressure sensor is achieved by coating a compressible substrate with a highly stretchable electrode. The substrate contains an array of microscale pyramidal features, and the electrode comprises a polymer composite. When the pressure-induced geometrical change experienced by the electrode is maximized at 40% elongation, a sensitivity of 10.3 kPa(-1) is achieved. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Analysis of high-speed digital phonoscopy pediatric images

NASA Astrophysics Data System (ADS)

Unnikrishnan, Harikrishnan; Donohue, Kevin D.; Patel, Rita R.

2012-02-01

The quantitative characterization of vocal fold (VF) motion can greatly enhance the diagnosis and treatment of speech pathologies. The recent availability of high-speed systems has created new opportunities to understand VF dynamics. This paper presents quantitative methods for analyzing VF dynamics with high-speed digital phonoscopy, with a focus on expected VF changes during childhood. A robust method for automatic VF edge tracking during phonation is introduced and evaluated against 4 expert human observers. Results from 100 test frames show a subpixel difference between the VF edges selected by algorithm and expert observers. Waveforms created from the VF edge displacement are used to created motion features with limited sensitivity to variations of camera resolution on the imaging plane. New features are introduced based on acceleration ratios of critical points over each phonation cycle, which have the potential for studying issues related to impact stress. A novel denoising and hybrid interpolation/extrapolation scheme is also introduced to reduce the impact of quantization errors and large sampling intervals relative to the phonation cycle. Features extracted from groups of 4 adults and 5 children show large differences for features related to asymmetry between the right and left fold and consistent differences for impact acceleration ratio.

Anatomical evidence for low frequency sensitivity in an archaeocete whale: comparison of the inner ear of Zygorhiza kochii with that of crown Mysticeti.

PubMed

Ekdale, Eric G; Racicot, Rachel A

2015-01-01

The evolution of hearing in cetaceans is a matter of current interest given that odontocetes (toothed whales) are sensitive to high frequency sounds and mysticetes (baleen whales) are sensitive to low and potentially infrasonic noises. Earlier diverging stem cetaceans (archaeocetes) were hypothesized to have had either low or high frequency sensitivity. Through CT scanning, the morphology of the bony labyrinth of the basilosaurid archaeocete Zygorhiza kochii is described and compared to novel information from the inner ears of mysticetes, which are less known than the inner ears of odontocetes. Further comparisons are made with published information for other cetaceans. The anatomy of the cochlea of Zygorhiza is in line with mysticetes and supports the hypothesis that Zygorhiza was sensitive to low frequency noises. Morphological features that support the low frequency hypothesis and are shared by Zygorhiza and mysticetes include a long cochlear canal with a high number of turns, steeply graded curvature of the cochlear spiral in which the apical turn is coiled tighter than the basal turn, thin walls separating successive turns that overlap in vestibular view, and reduction of the secondary bony lamina. Additional morphology of the vestibular system indicates that Zygorhiza was more sensitive to head rotations than extant mysticetes are, which likely indicates higher agility in the ancestral taxon. © 2014 Anatomical Society.

Anatomical evidence for low frequency sensitivity in an archaeocete whale: comparison of the inner ear of Zygorhiza kochii with that of crown Mysticeti

PubMed Central

Ekdale, Eric G; Racicot, Rachel A

2015-01-01

The evolution of hearing in cetaceans is a matter of current interest given that odontocetes (toothed whales) are sensitive to high frequency sounds and mysticetes (baleen whales) are sensitive to low and potentially infrasonic noises. Earlier diverging stem cetaceans (archaeocetes) were hypothesized to have had either low or high frequency sensitivity. Through CT scanning, the morphology of the bony labyrinth of the basilosaurid archaeocete Zygorhiza kochii is described and compared to novel information from the inner ears of mysticetes, which are less known than the inner ears of odontocetes. Further comparisons are made with published information for other cetaceans. The anatomy of the cochlea of Zygorhiza is in line with mysticetes and supports the hypothesis that Zygorhiza was sensitive to low frequency noises. Morphological features that support the low frequency hypothesis and are shared by Zygorhiza and mysticetes include a long cochlear canal with a high number of turns, steeply graded curvature of the cochlear spiral in which the apical turn is coiled tighter than the basal turn, thin walls separating successive turns that overlap in vestibular view, and reduction of the secondary bony lamina. Additional morphology of the vestibular system indicates that Zygorhiza was more sensitive to head rotations than extant mysticetes are, which likely indicates higher agility in the ancestral taxon. PMID:25400023

An EEG-based machine learning method to screen alcohol use disorder.

PubMed

Mumtaz, Wajid; Vuong, Pham Lam; Xia, Likun; Malik, Aamir Saeed; Rashid, Rusdi Bin Abd

2017-04-01

Screening alcohol use disorder (AUD) patients has been challenging due to the subjectivity involved in the process. Hence, robust and objective methods are needed to automate the screening of AUD patients. In this paper, a machine learning method is proposed that utilized resting-state electroencephalography (EEG)-derived features as input data to classify the AUD patients and healthy controls and to perform automatic screening of AUD patients. In this context, the EEG data were recorded during 5 min of eyes closed and 5 min of eyes open conditions. For this purpose, 30 AUD patients and 15 aged-matched healthy controls were recruited. After preprocessing the EEG data, EEG features such as inter-hemispheric coherences and spectral power for EEG delta, theta, alpha, beta and gamma bands were computed involving 19 scalp locations. The selection of most discriminant features was performed with a rank-based feature selection method assigning a weight value to each feature according to a criterion, i.e., receiver operating characteristics curve. For example, a feature with large weight was considered more relevant to the target labels than a feature with less weight. Therefore, a reduced set of most discriminant features was identified and further be utilized during classification of AUD patients and healthy controls. As results, the inter-hemispheric coherences between the brain regions were found significantly different between the study groups and provided high classification efficiency ( Accuracy  = 80.8, sensitivity  = 82.5, and specificity  = 80, F - Measure  = 0.78). In addition, the power computed in different EEG bands were found significant and provided an overall classification efficiency as ( Accuracy  = 86.6, sensitivity  = 95, specificity  = 82.5, and F - Measure  = 0.88). Further, the integration of these EEG feature resulted into even higher results ( Accuracy  = 89.3 %, sensitivity  = 88.5 %, specificity  = 91 %, and F - Measure  = 0.90). Based on the results, it is concluded that the EEG data (integration of the theta, beta, and gamma power and inter-hemispheric coherence) could be utilized as objective markers to screen the AUD patients and healthy controls.

Chromium Picolinate Does Not Improve Key Features of Metabolic Syndrome in Obese Nondiabetic Adults

PubMed Central

Iqbal, Nayyar; Cardillo, Serena; Volger, Sheri; Bloedon, LeAnne T.; Anderson, Richard A.; Boston, Raymond

2009-01-01

Abstract Background The use of chromium-containing dietary supplements is widespread among patients with type 2 diabetes. Chromium's effects in patients at high risk for developing diabetes, especially those with metabolic syndrome, is unknown. The objective of this study was to determine the effects of chromium picolinate (CrPic) on glucose metabolism in patients with metabolic syndrome. Method A double-blind, placebo-controlled, randomized trial was conducted at a U.S. academic medical center. Sixty three patients with National Cholesterol Education Program (NCEP) Adult Treatment Panel III (ATP III)-defined metabolic syndrome were included. The primary end point was a change in the insulin sensitivity index derived from a frequently sampled intravenous glucose tolerance test. Prespecified secondary end points included changes in other measurements of glucose metabolism, oxidative stress, fasting serum lipids, and high sensitivity C-reactive protein. Results After 16 weeks of CrPic treatment, there was no significant change in insulin sensitivity index between groups (P = 0.14). However, CrPic increased acute insulin response to glucose (P = 0.02). CrPic had no significant effect on other measures of glucose metabolism, body weight, serum lipids, or measures of inflammation and oxidative stress. Conclusion CrPic at 1000 μg/day does not improve key features of the metabolic syndrome in obese nondiabetic patients. PMID:19422140

The effect of category learning on attentional modulation of visual cortex.

PubMed

Folstein, Jonathan R; Fuller, Kelly; Howard, Dorothy; DePatie, Thomas

2017-09-01

Learning about visual object categories causes changes in the way we perceive those objects. One likely mechanism by which this occurs is the application of attention to potentially relevant objects. Here we test the hypothesis that category membership influences the allocation of attention, allowing attention to be applied not only to object features, but to entire categories. Participants briefly learned to categorize a set of novel cartoon animals after which EEG was recorded while participants distinguished between a target and non-target category. A second identical EEG session was conducted after two sessions of categorization practice. The category structure and task design allowed parametric manipulation of number of target features while holding feature frequency and category membership constant. We found no evidence that category membership influenced attentional selection: a postero-lateral negative component, labeled the selection negativity/N250, increased over time and was sensitive to number of target features, not target categories. In contrast, the right hemisphere N170 was not sensitive to target features. The P300 appeared sensitive to category in the first session, but showed a graded sensitivity to number of target features in the second session, possibly suggesting a transition from rule-based to similarity based categorization. Copyright © 2017. Published by Elsevier Ltd.

Integrating High-Reliability Principles to Transform Access and Throughput by Creating a Centralized Operations Center.

PubMed

Davenport, Paul B; Carter, Kimberly F; Echternach, Jeffrey M; Tuck, Christopher R

2018-02-01

High-reliability organizations (HROs) demonstrate unique and consistent characteristics, including operational sensitivity and control, situational awareness, hyperacute use of technology and data, and actionable process transformation. System complexity and reliance on information-based processes challenge healthcare organizations to replicate HRO processes. This article describes a healthcare organization's 3-year journey to achieve key HRO features to deliver high-quality, patient-centric care via an operations center powered by the principles of high-reliability data and software to impact patient throughput and flow.

Development of Sensitivity to Spacing Versus Feature Changes in Pictures of Houses: Evidence for Slow Development of a General Spacing Detection Mechanism?

ERIC Educational Resources Information Center

Robbins, Rachel A.; Shergill, Yaadwinder; Maurer, Daphne; Lewis, Terri L.

2011-01-01

Adults are expert at recognizing faces, in part because of exquisite sensitivity to the spacing of facial features. Children are poorer than adults at recognizing facial identity and less sensitive to spacing differences. Here we examined the specificity of the immaturity by comparing the ability of 8-year-olds, 14-year-olds, and adults to…

High-resolution angle-resolved photoemission study of electronic structure and charge-density wave formation in HoTe3

NASA Astrophysics Data System (ADS)

Liu, Guodong; Wang, Chenlu; Zhang, Yan; Hu, Bingfeng; Mou, Daixiang; Yu, Li; Zhao, Lin; Zhou, Xingjiang; Wang, Nanlin; Chen, Chuangtian; Xu, Zuyan

We performed high-resolution angle-resolved photoemission spectroscopy (ARPES) measurement on high quality crystal of HoTe3, an intriguing quasi-two-dimensional rare-earth-element tritelluride charge-density-wave (CDW) compound. The main features of the electronic structure in this compound are established by employing a quasi-CW laser (7eV) and a helium discharging lamp (21.22 eV) as excitation light sources. It reveals many bands back folded according to the CDW periodicity and two incommensurate CDW gaps created by perpendicular Fermi surface (FS) nesting vectors. A large gap is found to open in well nested regions of the Fermi surface sheets, whereas other Fermi surface sections with poor nesting remain ungapped. In particular, some peculiar features are identified by using our ultra-high resolution and bulk sensitive laser-ARPES.

Using environmental features to model highway crossing behavior of Canada lynx in the Southern Rocky Mountains

Treesearch

Phillip E. Baigas; John R. Squires; Lucretia E. Olson; Jacob S. Ivan; Elizabeth. K. Roberts

2017-01-01

Carnivores are particularly sensitive to reductions in population connectivity caused by human disturbance and habitat fragmentation. Permeability of transportation corridors to carnivore movements is central to species conservation given the large spatial extent of transportation networks and the high mobility of many carnivore species. We investigated the degree to...

Objective quantification of perturbations produced with a piecewise PV inversion technique

NASA Astrophysics Data System (ADS)

Fita, L.; Romero, R.; Ramis, C.

2007-11-01

PV inversion techniques have been widely used in numerical studies of severe weather cases. These techniques can be applied as a way to study the sensitivity of the responsible meteorological system to changes in the initial conditions of the simulations. Dynamical effects of a collection of atmospheric features involved in the evolution of the system can be isolated. However, aspects, such as the definition of the atmospheric features or the amount of change in the initial conditions, are largely case-dependent and/or subjectively defined. An objective way to calculate the modification of the initial fields is proposed to alleviate this problem. The perturbations are quantified as the mean absolute variations of the total energy between the original and modified fields, and an unique energy variation value is fixed for all the perturbations derived from different PV anomalies. Thus, PV features of different dimensions and characteristics introduce the same net modification of the initial conditions from an energetic point of view. The devised quantification method is applied to study the high impact weather case of 9-11 November 2001 in the Western Mediterranean basin, when a deep and strong cyclone was formed. On the Balearic Islands 4 people died, and sustained winds of 30 ms-1 and precipitation higher than 200 mm/24 h were recorded. Moreover, 700 people died in Algiers during the first phase of the event. The sensitivities to perturbations in the initial conditions of a deep upper level trough, the anticyclonic system related to the North Atlantic high and the surface thermal anomaly related to the baroclinicity of the environment are determined. Results reveal a high influence of the upper level trough and the surface thermal anomaly and a minor role of the North Atlantic high during the genesis of the cyclone.

Sensitivity and specificity of radiographic methods for predicting insertion torque of dental implants.

PubMed

Cortes, Arthur Rodriguez Gonzalez; Eimar, Hazem; Barbosa, Jorge de Sá; Costa, Claudio; Arita, Emiko Saito; Tamimi, Faleh

2015-05-01

Subjective radiographic classifications of alveolar bone have been proposed and correlated with implant insertion torque (IT). The present diagnostic study aims to identify quantitative bone features influencing IT and to use these findings to develop an objective radiographic classification for predicting IT. Demographics, panoramic radiographs (taken at the beginning of dental treatment), and cone-beam computed tomographic scans (taken for implant surgical planning) of 25 patients receiving 31 implants were analyzed. Bone samples retrieved from implant sites were assessed with dual x-ray absorptiometry, microcomputed tomography, and histology. Odds ratio, sensitivity, and specificity of all variables to predict high peak IT were assessed. A ridge cortical thickness >0.75 mm and a normal appearance of the inferior mandibular cortex were the most sensitive variables for predicting high peak IT (87.5% and 75%, respectively). A classification based on the combination of both variables presented high sensitivity (90.9%) and specificity (100%) for predicting IT. Within the limitations of this study, the results suggest that it is possible to predict IT accurately based on radiographic findings of the patient. This could be useful in the treatment plan of immediate loading cases.

Engineering the bioelectrochemical interface using functional nanomaterials and microchip technique toward sensitive and portable electrochemical biosensors.

PubMed

Jia, Xiaofang; Dong, Shaojun; Wang, Erkang

2016-02-15

Electrochemical biosensors have played active roles at the forefront of bioanalysis because they have the potential to achieve sensitive, specific and low-cost detection of biomolecules and many others. Engineering the electrochemical sensing interface with functional nanomaterials leads to novel electrochemical biosensors with improved performances in terms of sensitivity, selectivity, stability and simplicity. Functional nanomaterials possess good conductivity, catalytic activity, biocompatibility and high surface area. Coupled with bio-recognition elements, these features can amplify signal transduction and biorecognition events, resulting in highly sensitive biosensing. Additionally, microfluidic electrochemical biosensors have attracted considerable attention on account of their miniature, portable and low-cost systems as well as high fabrication throughput and ease of scaleup. For example, electrochemical enzymetic biosensors and aptamer biosensors (aptasensors) based on the integrated microchip can be used for portable point-of-care diagnostics and environmental monitoring. This review is a summary of our recent progress in the field of electrochemical biosensors, including aptasensors, cytosensors, enzymatic biosensors and self-powered biosensors based on biofuel cells. We presented the advantages that functional nanomaterials and microfluidic chip technology bring to the electrochemical biosensors, together with future prospects and possible challenges. Copyright © 2015 Elsevier B.V. All rights reserved.

Reversal of apomorphine locomotor sensitization by a single post-conditioning trial treatment with a low autoreceptor dose of apomorphine: a memory re-consolidation approach.

PubMed

Carrera, Marinete Pinheiro; Carey, Robert J; Dias, Flávia Regina Cruz; de Matos, Liana Wermelinger

2011-07-01

Sensitization is a common feature of psychostimulants and sensitization effects are generally considered to be linked to the addictive properties of these drugs. We used a conventional paired/unpaired Pavlovian protocol to induce a context specific sensitization to the locomotor stimulant effect of a high dose of apomorphine (2.0mg/kg). Two days following a 5 session sensitization induction phase, a brief 5min non-drug test for conditioning was conducted. Only the paired groups exhibited locomotor stimulant conditioned response effects. Immediately following this brief test for conditioning, the paired and the unpaired groups received injections of 0.05mg/kg apomorphine, 2.0mg/kg apomorphine or vehicle designed to differentially impact memory re-consolidation of the conditioning. Two days later, all groups received a sensitization challenge test with 2.0mg/kg apomorphine. The 2.0mg/kg apomorphine post-trial treatment potentiated sensitization while the 0.05mg/kg eliminated sensitization. These effects were only observed in the paired groups. The activation of dopaminergic systems by the high dose of apomorphine strengthened the drug/environment association whereas the inhibition of dopamine activity by the low auto-receptor dose eliminated this association. The results point to the importance of conditioning to context specific sensitization and targeting memory re-consolidation of conditioning as a paradigm to modify sensitization. Copyright © 2011 Elsevier Inc. All rights reserved.

Infra-red photoresponse of mesoscopic NiO-based solar cells sensitized with PbS quantum dot

PubMed Central

Raissi, Mahfoudh; Pellegrin, Yann; Jobic, Stéphane; Boujtita, Mohammed; Odobel, Fabrice

2016-01-01

Sensitized NiO based photocathode is a new field of investigation with increasing scientific interest in relation with the development of tandem dye-sensitized solar cells (photovoltaic) and dye-sensitized photoelectrosynthetic cells (solar fuel). We demonstrate herein that PbS quantum dots (QDs) represent promising inorganic sensitizers for NiO-based quantum dot-sensitized solar cells (QDSSCs). The solar cell sensitized with PbS quantum dot exhibits significantly higher photoconversion efficiency than solar cells sensitized with a classical and efficient molecular sensitizer (P1 dye = 4-(Bis-{4-[5-(2,2-dicyano-vinyl)-thiophene-2-yl]-phenyl}-amino)-benzoic acid). Furthermore, the system features an IPCE (Incident Photon-to-Current Efficiency) spectrum that spreads into the infra-red region, reaching operating wavelengths of 950 nm. The QDSSC photoelectrochemical device works with the complexes tris(4,4′-ditert-butyl-2,2′-bipyridine)cobalt(III/II) redox mediators, underscoring the formation of a long-lived charge-separated state. The electrochemical impedance spectrocopy measurements are consistent with a high packing of the QDs upon the NiO surface, the high density of which limits the access of the electrolyte and results in favorable light absorption cross-sections and a significant hole lifetime. These notable results highlight the potential of NiO-based photocathodes sensitized with quantum dots for accessing and exploiting the low-energy part of the solar spectrum in photovoltaic and photocatalysis applications. PMID:27125454

Beyond the resolution limit: subpixel resolution in animals and now in silicon

NASA Astrophysics Data System (ADS)

Wilcox, M. J.

2007-09-01

Automatic acquisition of aerial threats at thousands of kilometers distance requires high sensitivity to small differences in contrast and high optical quality for subpixel resolution, since targets occupy much less surface area than a single pixel. Targets travel at high speed and break up in the re-entry phase. Target/decoy discrimination at the earliest possible time is imperative. Real time performance requires a multifaceted approach with hyperspectral imaging and analog processing allowing feature extraction in real time. Hyperacuity Systems has developed a prototype chip capable of nonlinear increase in resolution or subpixel resolution far beyond either pixel size or spacing. Performance increase is due to a biomimetic implementation of animal retinas. Photosensitivity is not homogeneous across the sensor surface, allowing pixel parsing. It is remarkably simple to provide this profile to detectors and we showed at least three ways to do so. Individual photoreceptors have a Gaussian sensitivity profile and this nonlinear profile can be exploited to extract high-resolution. Adaptive, analog circuitry provides contrast enhancement, dynamic range setting with offset and gain control. Pixels are processed in parallel within modular elements called cartridges like photo-receptor inputs in fly eyes. These modular elements are connected by a novel function for a cell matrix known as L4. The system is exquisitely sensitive to small target motion and operates with a robust signal under degraded viewing conditions, allowing detection of targets smaller than a single pixel or at greater distance. Therefore, not only is instantaneous feature extraction possible but also subpixel resolution. Analog circuitry increases processing speed with more accurate motion specification for target tracking and identification.

Improved phase sensitivity in spectral domain phase microscopy using line-field illumination and self phase-referencing

PubMed Central

Yaqoob, Zahid; Choi, Wonshik; Oh, Seungeun; Lue, Niyom; Park, Yongkeun; Fang-Yen, Christopher; Dasari, Ramachandra R.; Badizadegan, Kamran; Feld, Michael S.

2010-01-01

We report a quantitative phase microscope based on spectral domain optical coherence tomography and line-field illumination. The line illumination allows self phase-referencing method to reject common-mode phase noise. The quantitative phase microscope also features a separate reference arm, permitting the use of high numerical aperture (NA > 1) microscope objectives for high resolution phase measurement at multiple points along the line of illumination. We demonstrate that the path-length sensitivity of the instrument can be as good as 41 pm/Hz, which makes it suitable for nanometer scale study of cell motility. We present the detection of natural motions of cell surface and two-dimensional surface profiling of a HeLa cell. PMID:19550464

Hyperbranched quasi-1D nanostructures for solid-state dye-sensitized solar cells.

PubMed

Passoni, Luca; Ghods, Farbod; Docampo, Pablo; Abrusci, Agnese; Martí-Rujas, Javier; Ghidelli, Matteo; Divitini, Giorgio; Ducati, Caterina; Binda, Maddalena; Guarnera, Simone; Li Bassi, Andrea; Casari, Carlo Spartaco; Snaith, Henry J; Petrozza, Annamaria; Di Fonzo, Fabio

2013-11-26

In this work we demonstrate hyperbranched nanostructures, grown by pulsed laser deposition, composed of one-dimensional anatase single crystals assembled in arrays of high aspect ratio hierarchical mesostructures. The proposed growth mechanism relies on a two-step process: self-assembly from the gas phase of amorphous TiO2 clusters in a forest of tree-shaped hierarchical mesostructures with high aspect ratio; oriented crystallization of the branches upon thermal treatment. Structural and morphological characteristics can be optimized to achieve both high specific surface area for optimal dye uptake and broadband light scattering thanks to the microscopic feature size. Solid-state dye sensitized solar cells fabricated with arrays of hyperbranched TiO2 nanostructures on FTO-glass sensitized with D102 dye showed a significant 66% increase in efficiency with respect to a reference mesoporous photoanode and reached a maximum efficiency of 3.96% (among the highest reported for this system). This result was achieved mainly thanks to an increase in photogenerated current directly resulting from improved light harvesting efficiency of the hierarchical photoanode. The proposed photoanode overcomes typical limitations of 1D TiO2 nanostructures applied to ss-DSC and emerges as a promising foundation for next-generation high-efficiency solid-state devices comprosed of dyes, polymers, or quantum dots as sensitizers.

Brittle materials at high-loading rates: an open area of research

NASA Astrophysics Data System (ADS)

Forquin, Pascal

2017-01-01

Brittle materials are extensively used in many civil and military applications involving high-strain-rate loadings such as: blasting or percussive drilling of rocks, ballistic impact against ceramic armour or transparent windshields, plastic explosives used to damage or destroy concrete structures, soft or hard impacts against concrete structures and so on. With all of these applications, brittle materials are subjected to intense loadings characterized by medium to extremely high strain rates (few tens to several tens of thousands per second) leading to extreme and/or specific damage modes such as multiple fragmentation, dynamic cracking, pore collapse, shearing, mode II fracturing and/or microplasticity mechanisms in the material. Additionally, brittle materials exhibit complex features such as a strong strain-rate sensitivity and confining pressure sensitivity that justify expending greater research efforts to understand these complex features. Currently, the most popular dynamic testing techniques used for this are based on the use of split Hopkinson pressure bar methodologies and/or plate-impact testing methods. However, these methods do have some critical limitations and drawbacks when used to investigate the behaviour of brittle materials at high loading rates. The present theme issue of Philosophical Transactions A provides an overview of the latest experimental methods and numerical tools that are currently being developed to investigate the behaviour of brittle materials at high loading rates. This article is part of the themed issue 'Experimental testing and modelling of brittle materials at high strain rates'.

Brittle materials at high-loading rates: an open area of research

PubMed Central

2017-01-01

Brittle materials are extensively used in many civil and military applications involving high-strain-rate loadings such as: blasting or percussive drilling of rocks, ballistic impact against ceramic armour or transparent windshields, plastic explosives used to damage or destroy concrete structures, soft or hard impacts against concrete structures and so on. With all of these applications, brittle materials are subjected to intense loadings characterized by medium to extremely high strain rates (few tens to several tens of thousands per second) leading to extreme and/or specific damage modes such as multiple fragmentation, dynamic cracking, pore collapse, shearing, mode II fracturing and/or microplasticity mechanisms in the material. Additionally, brittle materials exhibit complex features such as a strong strain-rate sensitivity and confining pressure sensitivity that justify expending greater research efforts to understand these complex features. Currently, the most popular dynamic testing techniques used for this are based on the use of split Hopkinson pressure bar methodologies and/or plate-impact testing methods. However, these methods do have some critical limitations and drawbacks when used to investigate the behaviour of brittle materials at high loading rates. The present theme issue of Philosophical Transactions A provides an overview of the latest experimental methods and numerical tools that are currently being developed to investigate the behaviour of brittle materials at high loading rates. This article is part of the themed issue ‘Experimental testing and modelling of brittle materials at high strain rates’. PMID:27956517

Brittle materials at high-loading rates: an open area of research.

PubMed

Forquin, Pascal

2017-01-28

Brittle materials are extensively used in many civil and military applications involving high-strain-rate loadings such as: blasting or percussive drilling of rocks, ballistic impact against ceramic armour or transparent windshields, plastic explosives used to damage or destroy concrete structures, soft or hard impacts against concrete structures and so on. With all of these applications, brittle materials are subjected to intense loadings characterized by medium to extremely high strain rates (few tens to several tens of thousands per second) leading to extreme and/or specific damage modes such as multiple fragmentation, dynamic cracking, pore collapse, shearing, mode II fracturing and/or microplasticity mechanisms in the material. Additionally, brittle materials exhibit complex features such as a strong strain-rate sensitivity and confining pressure sensitivity that justify expending greater research efforts to understand these complex features. Currently, the most popular dynamic testing techniques used for this are based on the use of split Hopkinson pressure bar methodologies and/or plate-impact testing methods. However, these methods do have some critical limitations and drawbacks when used to investigate the behaviour of brittle materials at high loading rates. The present theme issue of Philosophical Transactions A provides an overview of the latest experimental methods and numerical tools that are currently being developed to investigate the behaviour of brittle materials at high loading rates.This article is part of the themed issue 'Experimental testing and modelling of brittle materials at high strain rates'. © 2016 The Author(s).

Identifying significant environmental features using feature recognition.

DOT National Transportation Integrated Search

2015-10-01

The Department of Environmental Analysis at the Kentucky Transportation Cabinet has expressed an interest in feature-recognition capability because it may help analysts identify environmentally sensitive features in the landscape, : including those r...

Bombykol receptors in the silkworm moth and the fruit fly

PubMed Central

Syed, Zainulabeuddin; Kopp, Artyom; Kimbrell, Deborah A.; Leal, Walter S.

2010-01-01

Male moths are endowed with odorant receptors (ORs) to detect species-specific sex pheromones with remarkable sensitivity and selectivity. We serendipitously discovered that an endogenous OR in the fruit fly, Drosophila melanogaster, is highly sensitive to the sex pheromone of the silkworm moth, bombykol. Intriguingly, the fruit fly detectors are more sensitive than the receptors of the silkworm moth, although its ecological significance is unknown. By expression in the “empty neuron” system, we identified the fruit fly bombykol-sensitive OR as DmelOR7a (= DmOR7a). The profiles of this receptor in response to bombykol in the native sensilla (ab4) or expressed in the empty neuron system (ab3 sensilla) are indistinguishable. Both WT and transgenic flies responded with high sensitivity, in a dose-dependent manner, and with rapid signal termination. In contrast, the same empty neuron expressing the moth bombykol receptor, BmorOR1, demonstrated low sensitivity and slow signal inactivation. When expressed in the trichoid sensilla T1 of the fruit fly, the neuron housing BmorOR1 responded with sensitivity comparable to that of the native trichoid sensilla in the silkworm moth. By challenging the native bombykol receptor in the fruit fly with high doses of another odorant to which the receptor responds with the highest sensitivity, we demonstrate that slow signal termination is induced by overdose of a stimulus. As opposed to the empty neuron system in the basiconic sensilla, the structural, biochemical, and/or biophysical features of the sensilla make the T1 trichoid system of the fly a better surrogate for the moth receptor. PMID:20439725

Computer-assisted diagnosis of melanoma.

PubMed

Fuller, Collin; Cellura, A Paul; Hibler, Brian P; Burris, Katy

2016-03-01

The computer-assisted diagnosis of melanoma is an exciting area of research where imaging techniques are combined with diagnostic algorithms in an attempt to improve detection and outcomes for patients with skin lesions suspicious for malignancy. Once an image has been acquired, it undergoes a processing pathway which includes preprocessing, enhancement, segmentation, feature extraction, feature selection, change detection, and ultimately classification. Practicality for everyday clinical use remains a vital question. A successful model must obtain results that are on par or outperform experienced dermatologists, keep costs at a minimum, be user-friendly, and be time efficient with high sensitivity and specificity. ©2015 Frontline Medical Communications.

TU-AB-BRA-04: Quantitative Radiomics: Sensitivity of PET Textural Features to Image Acquisition and Reconstruction Parameters Implies the Need for Standards

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

Nyflot, MJ; Yang, F; Byrd, D

Purpose: Despite increased use of heterogeneity metrics for PET imaging, standards for metrics such as textural features have yet to be developed. We evaluated the quantitative variability caused by image acquisition and reconstruction parameters on PET textural features. Methods: PET images of the NEMA IQ phantom were simulated with realistic image acquisition noise. 35 features based on intensity histograms (IH), co-occurrence matrices (COM), neighborhood-difference matrices (NDM), and zone-size matrices (ZSM) were evaluated within lesions (13, 17, 22, 28, 33 mm diameter). Variability in metrics across 50 independent images was evaluated as percent difference from mean for three phantom girths (850,more » 1030, 1200 mm) and two OSEM reconstructions (2 iterations, 28 subsets, 5 mm FWHM filtration vs 6 iterations, 28 subsets, 8.6 mm FWHM filtration). Also, patient sample size to detect a clinical effect of 30% with Bonferroni-corrected α=0.001 and 95% power was estimated. Results: As a class, NDM features demonstrated greatest sensitivity in means (5–50% difference for medium girth and reconstruction comparisons and 10–100% for large girth comparisons). Some IH features (standard deviation, energy, entropy) had variability below 10% for all sensitivity studies, while others (kurtosis, skewness) had variability above 30%. COM and ZSM features had complex sensitivities; correlation, energy, entropy (COM) and zone percentage, short-zone emphasis, zone-size non-uniformity (ZSM) had variability less than 5% while other metrics had differences up to 30%. Trends were similar for sample size estimation; for example, coarseness, contrast, and strength required 12, 38, and 52 patients to detect a 30% effect for the small girth case but 38, 88, and 128 patients in the large girth case. Conclusion: The sensitivity of PET textural features to image acquisition and reconstruction parameters is large and feature-dependent. Standards are needed to ensure that prospective trials which incorporate textural features are properly designed to detect clinical endpoints. Supported by NIH grants R01 CA169072, U01 CA148131, NCI Contract (SAIC-Frederick) 24XS036-004, and a research contract from GE Healthcare.« less

In-Vivo Imaging of Cell Migration Using Contrast Enhanced MRI and SVM Based Post-Processing.

PubMed

Weis, Christian; Hess, Andreas; Budinsky, Lubos; Fabry, Ben

2015-01-01

The migration of cells within a living organism can be observed with magnetic resonance imaging (MRI) in combination with iron oxide nanoparticles as an intracellular contrast agent. This method, however, suffers from low sensitivity and specificty. Here, we developed a quantitative non-invasive in-vivo cell localization method using contrast enhanced multiparametric MRI and support vector machines (SVM) based post-processing. Imaging phantoms consisting of agarose with compartments containing different concentrations of cancer cells labeled with iron oxide nanoparticles were used to train and evaluate the SVM for cell localization. From the magnitude and phase data acquired with a series of T2*-weighted gradient-echo scans at different echo-times, we extracted features that are characteristic for the presence of superparamagnetic nanoparticles, in particular hyper- and hypointensities, relaxation rates, short-range phase perturbations, and perturbation dynamics. High detection quality was achieved by SVM analysis of the multiparametric feature-space. The in-vivo applicability was validated in animal studies. The SVM detected the presence of iron oxide nanoparticles in the imaging phantoms with high specificity and sensitivity with a detection limit of 30 labeled cells per mm3, corresponding to 19 μM of iron oxide. As proof-of-concept, we applied the method to follow the migration of labeled cancer cells injected in rats. The combination of iron oxide labeled cells, multiparametric MRI and a SVM based post processing provides high spatial resolution, specificity, and sensitivity, and is therefore suitable for non-invasive in-vivo cell detection and cell migration studies over prolonged time periods.

New Target for Cosmic Axion Searches.

PubMed

Baumann, Daniel; Green, Daniel; Wallisch, Benjamin

2016-10-21

Future cosmic microwave background experiments have the potential to probe the density of relativistic species at the subpercent level. This sensitivity allows light thermal relics to be detected up to arbitrarily high decoupling temperatures. Conversely, the absence of a detection would require extra light species never to have been in equilibrium with the Standard Model. In this Letter, we exploit this feature to demonstrate the sensitivity of future cosmological observations to the couplings of axions to photons, gluons, and charged fermions. In many cases, the constraints achievable from cosmology will surpass existing bounds from laboratory experiments and astrophysical observations by orders of magnitude.

The Effect of Experimental Variables on Industrial X-Ray Micro-Computed Sensitivity

NASA Technical Reports Server (NTRS)

Roth, Don J.; Rauser, Richard W.

2014-01-01

A study was performed on the effect of experimental variables on radiographic sensitivity (image quality) in x-ray micro-computed tomography images for a high density thin wall metallic cylinder containing micro-EDM holes. Image quality was evaluated in terms of signal-to-noise ratio, flaw detectability, and feature sharpness. The variables included: day-to-day reproducibility, current, integration time, voltage, filtering, number of frame averages, number of projection views, beam width, effective object radius, binning, orientation of sample, acquisition angle range (180deg to 360deg), and directional versus transmission tube.

Frequency organization and responses to complex sounds in the medial geniculate body of the mustached bat.

PubMed

Wenstrup, J J

1999-11-01

The auditory cortex of the mustached bat (Pteronotus parnellii) displays some of the most highly developed physiological and organizational features described in mammalian auditory cortex. This study examines response properties and organization in the medial geniculate body (MGB) that may contribute to these features of auditory cortex. About 25% of 427 auditory responses had simple frequency tuning with single excitatory tuning curves. The remainder displayed more complex frequency tuning using two-tone or noise stimuli. Most of these were combination-sensitive, responsive to combinations of different frequency bands within sonar or social vocalizations. They included FM-FM neurons, responsive to different harmonic elements of the frequency modulated (FM) sweep in the sonar signal, and H1-CF neurons, responsive to combinations of the bat's first sonar harmonic (H1) and a higher harmonic of the constant frequency (CF) sonar signal. Most combination-sensitive neurons (86%) showed facilitatory interactions. Neurons tuned to frequencies outside the biosonar range also displayed combination-sensitive responses, perhaps related to analyses of social vocalizations. Complex spectral responses were distributed throughout dorsal and ventral divisions of the MGB, forming a major feature of this bat's analysis of complex sounds. The auditory sector of the thalamic reticular nucleus also was dominated by complex spectral responses to sounds. The ventral division was organized tonotopically, based on best frequencies of singly tuned neurons and higher best frequencies of combination-sensitive neurons. Best frequencies were lowest ventrolaterally, increasing dorsally and then ventromedially. However, representations of frequencies associated with higher harmonics of the FM sonar signal were reduced greatly. Frequency organization in the dorsal division was not tonotopic; within the middle one-third of MGB, combination-sensitive responses to second and third harmonic CF sonar signals (60-63 and 90-94 kHz) occurred in adjacent regions. In the rostral one-third, combination-sensitive responses to second, third, and fourth harmonic FM frequency bands predominated. These FM-FM neurons, thought to be selective for delay between an emitted pulse and echo, showed some organization of delay selectivity. The organization of frequency sensitivity in the MGB suggests a major rewiring of the output of the central nucleus of the inferior colliculus, by which collicular neurons tuned to the bat's FM sonar signals mostly project to the dorsal, not the ventral, division. Because physiological differences between collicular and MGB neurons are minor, a major role of the tecto-thalamic projection in the mustached bat may be the reorganization of responses to provide for cortical representations of sonar target features.

East Europe Report, Economic and Industrial Affairs, No. 2410.

DTIC Science & Technology

1983-06-13

high culture. Spring wheat of the Jara variety was developed at CSRS. Its features are: a very high grain production, low sensitivity to powdery ... mildew and rust, it can be harvested sooner than any presently grown varieties of Spring wheats in our country. It is adaptable for cultivation in wheat ...has great hope for the Polon variety. Its char- acteristics are: good yield, good resistance to powdery mildew and mottle disease, and what is also

Crescent shaped Fabry-Perot fiber cavity for ultra-sensitive strain measurement.

PubMed

Liu, Ye; Wang, D N; Chen, W P

2016-12-02

Optical Fabry-Perot interferometer sensors based on inner air-cavity is featured with compact size, good robustness and high strain sensitivity, especially when an ultra-thin air-cavity is adopted. The typical shape of Fabry-Perot inner air-cavity with reflection mode of operation is elliptic, with minor axis along with and major axis perpendicular to the fiber length. The first reflection surface is diverging whereas the second one is converging. To increase the visibility of the output interference pattern, the length of major axis should be large for a given cavity length. However, the largest value of the major axis is limited by the optical fiber diameter. If the major axis length reaches the fiber diameter, the robustness of the Fabry-Perot cavity device would be decreased. Here we demonstrate an ultra-thin crescent shaped Fabry-Perot cavity for strain sensing with ultra-high sensitivity and low temperature cross-sensitivity. The crescent-shape cavity consists of two converging reflection surfaces, which provide the advantages of enhanced strain sensitivity when compared with elliptic or D-shaped FP cavity. The device is fabricated by fusion splicing an etched multimode fiber with a single mode fiber, and hence is simple in structure and economic in cost.

Crescent shaped Fabry-Perot fiber cavity for ultra-sensitive strain measurement

NASA Astrophysics Data System (ADS)

Liu, Ye; Wang, D. N.; Chen, W. P.

2016-12-01

Optical Fabry-Perot interferometer sensors based on inner air-cavity is featured with compact size, good robustness and high strain sensitivity, especially when an ultra-thin air-cavity is adopted. The typical shape of Fabry-Perot inner air-cavity with reflection mode of operation is elliptic, with minor axis along with and major axis perpendicular to the fiber length. The first reflection surface is diverging whereas the second one is converging. To increase the visibility of the output interference pattern, the length of major axis should be large for a given cavity length. However, the largest value of the major axis is limited by the optical fiber diameter. If the major axis length reaches the fiber diameter, the robustness of the Fabry-Perot cavity device would be decreased. Here we demonstrate an ultra-thin crescent shaped Fabry-Perot cavity for strain sensing with ultra-high sensitivity and low temperature cross-sensitivity. The crescent-shape cavity consists of two converging reflection surfaces, which provide the advantages of enhanced strain sensitivity when compared with elliptic or D-shaped FP cavity. The device is fabricated by fusion splicing an etched multimode fiber with a single mode fiber, and hence is simple in structure and economic in cost.

Likelihood ratio-based differentiation of nodular Hashimoto thyroiditis and papillary thyroid carcinoma in patients with sonographically evident diffuse hashimoto thyroiditis: preliminary study.

PubMed

Wang, Liang; Xia, Yu; Jiang, Yu-Xin; Dai, Qing; Li, Xiao-Yi

2012-11-01

To assess the efficacy of sonography for discriminating nodular Hashimoto thyroiditis from papillary thyroid carcinoma in patients with sonographically evident diffuse Hashimoto thyroiditis. This study included 20 patients with 24 surgically confirmed Hashimoto thyroiditis nodules and 40 patients with 40 papillary thyroid carcinoma nodules; all had sonographically evident diffuse Hashimoto thyroiditis. A retrospective review of the sonograms was performed, and significant benign and malignant sonographic features were selected by univariate and multivariate analyses. The combined likelihood ratio was calculated as the product of each feature's likelihood ratio for papillary thyroid carcinoma. We compared the abilities of the original sonographic features and combined likelihood ratios in diagnosing nodular Hashimoto thyroiditis and papillary thyroid carcinoma by their sensitivity, specificity, and Youden index. The diagnostic capabilities of the sonographic features varied greatly, with Youden indices ranging from 0.175 to 0.700. Compared with single features, combinations of features were unable to improve the Youden indices effectively because the sensitivity and specificity usually changed in opposite directions. For combined likelihood ratios, however, the sensitivity improved greatly without an obvious reduction in specificity, which resulted in the maximum Youden index (0.825). With a combined likelihood ratio greater than 7.00 as the diagnostic criterion for papillary thyroid carcinoma, sensitivity reached 82.5%, whereas specificity remained at 100.0%. With a combined likelihood ratio less than 1.00 for nodular Hashimoto thyroiditis, sensitivity and specificity were 90.0% and 92.5%, respectively. Several sonographic features of nodular Hashimoto thyroiditis and papillary thyroid carcinoma in a background of diffuse Hashimoto thyroiditis were significantly different. The combined likelihood ratio may be superior to original sonographic features for discrimination of nodular Hashimoto thyroiditis from papillary thyroid carcinoma; therefore, it is a promising risk index for thyroid nodules and warrants further investigation.

Feature construction can improve diagnostic criteria for high-dimensional metabolic data in newborn screening for medium-chain acyl-CoA dehydrogenase deficiency.

PubMed

Ho, Sirikit; Lukacs, Zoltan; Hoffmann, Georg F; Lindner, Martin; Wetter, Thomas

2007-07-01

In newborn screening with tandem mass spectrometry, multiple intermediary metabolites are quantified in a single analytical run for the diagnosis of fatty-acid oxidation disorders, organic acidurias, and aminoacidurias. Published diagnostic criteria for these disorders normally incorporate a primary metabolic marker combined with secondary markers, often analyte ratios, for which the markers have been chosen to reflect metabolic pathway deviations. We applied a procedure to extract new markers and diagnostic criteria for newborn screening to the data of newborns with confirmed medium-chain acyl-CoA dehydrogenase deficiency (MCADD) and a control group from the newborn screening program, Heidelberg, Germany. We validated the results with external data of the screening center in Hamburg, Germany. We extracted new markers by performing a systematic search for analyte combinations (features) with high discriminatory performance for MCADD. To select feature thresholds, we applied automated procedures to separate controls and cases on the basis of the feature values. Finally, we built classifiers from these new markers to serve as diagnostic criteria in screening for MCADD. On the basis of chi(2) scores, we identified approximately 800 of >628,000 new analyte combinations with superior discriminatory performance compared with the best published combinations. Classifiers built with the new features achieved diagnostic sensitivities and specificities approaching 100%. Feature construction methods provide ways to disclose information hidden in the set of measured analytes. Other diagnostic tasks based on high-dimensional metabolic data might also profit from this approach.

Improving EEG-Based Driver Fatigue Classification Using Sparse-Deep Belief Networks.

PubMed

Chai, Rifai; Ling, Sai Ho; San, Phyo Phyo; Naik, Ganesh R; Nguyen, Tuan N; Tran, Yvonne; Craig, Ashley; Nguyen, Hung T

2017-01-01

This paper presents an improvement of classification performance for electroencephalography (EEG)-based driver fatigue classification between fatigue and alert states with the data collected from 43 participants. The system employs autoregressive (AR) modeling as the features extraction algorithm, and sparse-deep belief networks (sparse-DBN) as the classification algorithm. Compared to other classifiers, sparse-DBN is a semi supervised learning method which combines unsupervised learning for modeling features in the pre-training layer and supervised learning for classification in the following layer. The sparsity in sparse-DBN is achieved with a regularization term that penalizes a deviation of the expected activation of hidden units from a fixed low-level prevents the network from overfitting and is able to learn low-level structures as well as high-level structures. For comparison, the artificial neural networks (ANN), Bayesian neural networks (BNN), and original deep belief networks (DBN) classifiers are used. The classification results show that using AR feature extractor and DBN classifiers, the classification performance achieves an improved classification performance with a of sensitivity of 90.8%, a specificity of 90.4%, an accuracy of 90.6%, and an area under the receiver operating curve (AUROC) of 0.94 compared to ANN (sensitivity at 80.8%, specificity at 77.8%, accuracy at 79.3% with AUC-ROC of 0.83) and BNN classifiers (sensitivity at 84.3%, specificity at 83%, accuracy at 83.6% with AUROC of 0.87). Using the sparse-DBN classifier, the classification performance improved further with sensitivity of 93.9%, a specificity of 92.3%, and an accuracy of 93.1% with AUROC of 0.96. Overall, the sparse-DBN classifier improved accuracy by 13.8, 9.5, and 2.5% over ANN, BNN, and DBN classifiers, respectively.

Improving EEG-Based Driver Fatigue Classification Using Sparse-Deep Belief Networks

PubMed Central

Chai, Rifai; Ling, Sai Ho; San, Phyo Phyo; Naik, Ganesh R.; Nguyen, Tuan N.; Tran, Yvonne; Craig, Ashley; Nguyen, Hung T.

2017-01-01

This paper presents an improvement of classification performance for electroencephalography (EEG)-based driver fatigue classification between fatigue and alert states with the data collected from 43 participants. The system employs autoregressive (AR) modeling as the features extraction algorithm, and sparse-deep belief networks (sparse-DBN) as the classification algorithm. Compared to other classifiers, sparse-DBN is a semi supervised learning method which combines unsupervised learning for modeling features in the pre-training layer and supervised learning for classification in the following layer. The sparsity in sparse-DBN is achieved with a regularization term that penalizes a deviation of the expected activation of hidden units from a fixed low-level prevents the network from overfitting and is able to learn low-level structures as well as high-level structures. For comparison, the artificial neural networks (ANN), Bayesian neural networks (BNN), and original deep belief networks (DBN) classifiers are used. The classification results show that using AR feature extractor and DBN classifiers, the classification performance achieves an improved classification performance with a of sensitivity of 90.8%, a specificity of 90.4%, an accuracy of 90.6%, and an area under the receiver operating curve (AUROC) of 0.94 compared to ANN (sensitivity at 80.8%, specificity at 77.8%, accuracy at 79.3% with AUC-ROC of 0.83) and BNN classifiers (sensitivity at 84.3%, specificity at 83%, accuracy at 83.6% with AUROC of 0.87). Using the sparse-DBN classifier, the classification performance improved further with sensitivity of 93.9%, a specificity of 92.3%, and an accuracy of 93.1% with AUROC of 0.96. Overall, the sparse-DBN classifier improved accuracy by 13.8, 9.5, and 2.5% over ANN, BNN, and DBN classifiers, respectively. PMID:28326009

Temporal voice areas exist in autism spectrum disorder but are dysfunctional for voice identity recognition

PubMed Central

Borowiak, Kamila; von Kriegstein, Katharina

2016-01-01

The ability to recognise the identity of others is a key requirement for successful communication. Brain regions that respond selectively to voices exist in humans from early infancy on. Currently, it is unclear whether dysfunction of these voice-sensitive regions can explain voice identity recognition impairments. Here, we used two independent functional magnetic resonance imaging studies to investigate voice processing in a population that has been reported to have no voice-sensitive regions: autism spectrum disorder (ASD). Our results refute the earlier report that individuals with ASD have no responses in voice-sensitive regions: Passive listening to vocal, compared to non-vocal, sounds elicited typical responses in voice-sensitive regions in the high-functioning ASD group and controls. In contrast, the ASD group had a dysfunction in voice-sensitive regions during voice identity but not speech recognition in the right posterior superior temporal sulcus/gyrus (STS/STG)—a region implicated in processing complex spectrotemporal voice features and unfamiliar voices. The right anterior STS/STG correlated with voice identity recognition performance in controls but not in the ASD group. The findings suggest that right STS/STG dysfunction is critical for explaining voice recognition impairments in high-functioning ASD and show that ASD is not characterised by a general lack of voice-sensitive responses. PMID:27369067

Mapping feature-sensitivity and attentional modulation in human auditory cortex with functional magnetic resonance imaging

PubMed Central

Paltoglou, Aspasia E; Sumner, Christian J; Hall, Deborah A

2011-01-01

Feature-specific enhancement refers to the process by which selectively attending to a particular stimulus feature specifically increases the response in the same region of the brain that codes that stimulus property. Whereas there are many demonstrations of this mechanism in the visual system, the evidence is less clear in the auditory system. The present functional magnetic resonance imaging (fMRI) study examined this process for two complex sound features, namely frequency modulation (FM) and spatial motion. The experimental design enabled us to investigate whether selectively attending to FM and spatial motion enhanced activity in those auditory cortical areas that were sensitive to the two features. To control for attentional effort, the difficulty of the target-detection tasks was matched as closely as possible within listeners. Locations of FM-related and motion-related activation were broadly compatible with previous research. The results also confirmed a general enhancement across the auditory cortex when either feature was being attended to, as compared with passive listening. The feature-specific effects of selective attention revealed the novel finding of enhancement for the nonspatial (FM) feature, but not for the spatial (motion) feature. However, attention to spatial features also recruited several areas outside the auditory cortex. Further analyses led us to conclude that feature-specific effects of selective attention are not statistically robust, and appear to be sensitive to the choice of fMRI experimental design and localizer contrast. PMID:21447093

Sigmoid stenosis caused by diverticulitis vs. carcinoma: usefulness of sonographic features for their differentiation in the emergency setting.

PubMed

Ripollés, Tomás; Martínez-Pérez, María Jesús; Gómez Valencia, Diana Patricia; Vizuete, José; Martín, Gregorio

2015-10-01

To retrospectively evaluate the accuracy of ultrasound as a diagnostic method for differentiating acute diverticulitis from colon cancer in patients with sigmoid colon stenosis. Ultrasound examinations of 91 consecutive patients with sigmoid stenosis (50 diverticulitis and 41 colon cancers) were reviewed by two trained radiologists. Sixty-five (71%) patients presented with acute abdominal symptoms. Thirteen sonographic criteria retrieved from the literature were evaluated to differentiate benign from malignant strictures. A score including all parameters which showed significant differences between benign vs. malignant was built. Sensitivity, specificity, accuracy, and positive or negative predictive values of each sonographic sign, the overall diagnosis, and sonographic score were calculated. Loss of the bowel wall stratification was the most reliable criteria for the diagnosis of malignancy (92% and 94% of sensitivity and specificity, respectively), and the best inter-radiologist agreement (κ = 0.848). Adjacent lymph nodes were the most specific feature (98%) for colon cancer, but its sensitivity was low. Global assessment could differentiate both diseases with high sensitivity (92-94.9%) and specificity (98-100%). Sonographic score >3 enabled differentiation of carcinoma from diverticulitis with 95% sensitivity and 92-94% specificity, with an area under the ROC curve of 0.98-0.987. There were no significant differences in the results between patients with acute and nonacute abdominal symptoms. The combination of several morphological sonographic findings using a score can differentiate most cases of diverticulitis from colon carcinoma in sigmoid strictures.

Difference in EUV photoresist design towards reduction of LWR and LCDU

NASA Astrophysics Data System (ADS)

Jiang, Jing; De Simone, Danilo; Vandenberghe, Geert

2017-03-01

Pattern fidelity of EUV lithography is crucial for high resolution features, since small variation can affect device performance and even cause short or open circuit. For 1D features, dense lines and contact holes are the most common features for active, metal and contact layer, therefore line width roughness (LWR) and local critical dimension uniformity (LCDU) are important indexes to monitor. Both LWR and LCDU are greatly influenced by photon and acid shot noise. In addition, LWR is also affected by resist mechanical properties, like pattern collapse. In this study, we studied the influence of different chemically amplified resist components, such as polymer, PAG and quencher for both types and concentrations in order to understand the relative extent of influences of deprotection, acid diffusion, and base neutralization on pattern fidelity. However, conventional methods to approach higher resolution or low LWR/LCDU by sacrificing the dose are not sustainable. In order to continue to improve resist performance, a new component, metal salt sensitizer, is introduced into the resist system. This metal salt is able to achieve 30% dose reduction by increasing EUV absorption, maintaining LWR. We believe metal sensitizer might give us a new way to challenge the RLS trade-off.

Temporal and spatial adaptation of transient responses to local features

PubMed Central

O'Carroll, David C.; Barnett, Paul D.; Nordström, Karin

2012-01-01

Interpreting visual motion within the natural environment is a challenging task, particularly considering that natural scenes vary enormously in brightness, contrast and spatial structure. The performance of current models for the detection of self-generated optic flow depends critically on these very parameters, but despite this, animals manage to successfully navigate within a broad range of scenes. Within global scenes local areas with more salient features are common. Recent work has highlighted the influence that local, salient features have on the encoding of optic flow, but it has been difficult to quantify how local transient responses affect responses to subsequent features and thus contribute to the global neural response. To investigate this in more detail we used experimenter-designed stimuli and recorded intracellularly from motion-sensitive neurons. We limited the stimulus to a small vertically elongated strip, to investigate local and global neural responses to pairs of local “doublet” features that were designed to interact with each other in the temporal and spatial domain. We show that the passage of a high-contrast doublet feature produces a complex transient response from local motion detectors consistent with predictions of a simple computational model. In the neuron, the passage of a high-contrast feature induces a local reduction in responses to subsequent low-contrast features. However, this neural contrast gain reduction appears to be recruited only when features stretch vertically (i.e., orthogonal to the direction of motion) across at least several aligned neighboring ommatidia. Horizontal displacement of the components of elongated features abolishes the local adaptation effect. It is thus likely that features in natural scenes with vertically aligned edges, such as tree trunks, recruit the greatest amount of response suppression. This property could emphasize the local responses to such features vs. those in nearby texture within the scene. PMID:23087617

Influence of hot spot features on the shock initiation of heterogenous nitromethane

NASA Astrophysics Data System (ADS)

Dattelbaum, Dana; Sheffield, Stephen; Stahl, David; Dattelbaum, Andrew

2009-06-01

The shock initiation sensitivity of heterogeneous explosives is known to be strongly related to the confluence of ``hot spots'' or localized regions of high pressure and temperature. Physical origins of hot spots within a material include dynamic pore collapse, friction from motion along closed cracks, and wave reflections from other in situ interfaces. A complex interplay among numerous physical and chemical factors, spanning several length scales, determines whether or not a hot spot will quench or lead to initiation. To further elucidate key features of hot spots on energetic materials sensitivity and initiation mechanisms, we have intentionally introduced well-defined particles into the homogeneous liquid explosive nitromethane which has been gelled so the particles are somewhat stationary. Gas-gun driven shock initiation experiments using embedded electromagnetic gauging methods have been performed on these materials, revealing new insights into the role of heterogeneities on the sensitivity of the explosives through shock input-to-run distance relationships (Pop-plots), and reactive chemistry growth in and behind the incident shock front. By logically mapping out these relationships, the data provide a scientific foundation for the development of predictive capabilities for modeling new formulations, and designing next-generation energetic materials.

Practiced musical style shapes auditory skills.

PubMed

Vuust, Peter; Brattico, Elvira; Seppänen, Miia; Näätänen, Risto; Tervaniemi, Mari

2012-04-01

Musicians' processing of sounds depends highly on instrument, performance practice, and level of expertise. Here, we measured the mismatch negativity (MMN), a preattentive brain response, to six types of musical feature change in musicians playing three distinct styles of music (classical, jazz, and rock/pop) and in nonmusicians using a novel, fast, and musical sounding multifeature MMN paradigm. We found MMN to all six deviants, showing that MMN paradigms can be adapted to resemble a musical context. Furthermore, we found that jazz musicians had larger MMN amplitude than all other experimental groups across all sound features, indicating greater overall sensitivity to auditory outliers. Furthermore, we observed a tendency toward shorter latency of the MMN to all feature changes in jazz musicians compared to band musicians. These findings indicate that the characteristics of the style of music played by musicians influence their perceptual skills and the brain processing of sound features embedded in music. © 2012 New York Academy of Sciences.

Tuberculosis disease diagnosis using artificial immune recognition system.

PubMed

Shamshirband, Shahaboddin; Hessam, Somayeh; Javidnia, Hossein; Amiribesheli, Mohsen; Vahdat, Shaghayegh; Petković, Dalibor; Gani, Abdullah; Kiah, Miss Laiha Mat

2014-01-01

There is a high risk of tuberculosis (TB) disease diagnosis among conventional methods. This study is aimed at diagnosing TB using hybrid machine learning approaches. Patient epicrisis reports obtained from the Pasteur Laboratory in the north of Iran were used. All 175 samples have twenty features. The features are classified based on incorporating a fuzzy logic controller and artificial immune recognition system. The features are normalized through a fuzzy rule based on a labeling system. The labeled features are categorized into normal and tuberculosis classes using the Artificial Immune Recognition Algorithm. Overall, the highest classification accuracy reached was for the 0.8 learning rate (α) values. The artificial immune recognition system (AIRS) classification approaches using fuzzy logic also yielded better diagnosis results in terms of detection accuracy compared to other empirical methods. Classification accuracy was 99.14%, sensitivity 87.00%, and specificity 86.12%.

Enabling systematic interrogation of protein-protein interactions in live cells with a versatile ultra-high-throughput biosensor platform | Office of Cancer Genomics

Cancer.gov

The vast datasets generated by next generation gene sequencing and expression profiling have transformed biological and translational research. However, technologies to produce large-scale functional genomics datasets, such as high-throughput detection of protein-protein interactions (PPIs), are still in early development. While a number of powerful technologies have been employed to detect PPIs, a singular PPI biosensor platform featured with both high sensitivity and robustness in a mammalian cell environment remains to be established.

MSM optical detector on the basis of II-type ZnSe/ZnTe superlattice

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

Kuznetzov, P. I., E-mail: pik218@ire216.msk.su; Averin, S. V., E-mail: sva278@ire216.msk.su; Zhitov, V. A.

2017-02-15

On the basis of a type-II ZnSe/ZnTe superlattice, a MSM (metal—semiconductor–metal) photodetector is fabricated and investigated. The detector features low dark currents and a high sensitivity. The spectral characteristic of the detector provides the possibility of the selective detection of three separate spectral portions of visible and near-infrared radiation.

Enhanced gamma ray sensitivity in bismuth triiodide sensors through volumetric defect control

DOE PAGES

Johns, Paul M.; Baciak, James E.; Nino, Juan C.

2016-09-02

In some of the more attractive semiconducting compounds for ambient temperature radiation detector applications are impacted by low charge collection efficiency due to the presence of point and volumetric defects. This has been particularly true in the case of BiI 3, which features very attractive properties (density, atomic number, band gap, etc.) to serve as a gamma ray detector, but has yet to demonstrate its full potential. Here, we show that by applying growth techniques tailored to reduce defects, the spectral performance of this promising semiconductor can be realized. Gamma ray spectra from >100 keV source emissions are now obtainedmore » from high quality Sb:BiI 3 bulk crystals with limited concentrations of defects (point and extended). The spectra acquired in these high quality crystals feature photopeaks with resolution of 2.2% at 662 keV. Infrared microscopy is used to compare the local microstructure between radiation sensitive and non-responsive crystals. Our work demonstrates that BiI 3 can be prepared in melt-grown detector-grade samples with superior quality and can acquire the spectra from a variety of gamma ray sources.« less

Convolutional neural networks for seizure prediction using intracranial and scalp electroencephalogram.

PubMed

Truong, Nhan Duy; Nguyen, Anh Duy; Kuhlmann, Levin; Bonyadi, Mohammad Reza; Yang, Jiawei; Ippolito, Samuel; Kavehei, Omid

2018-05-07

Seizure prediction has attracted growing attention as one of the most challenging predictive data analysis efforts to improve the life of patients with drug-resistant epilepsy and tonic seizures. Many outstanding studies have reported great results in providing sensible indirect (warning systems) or direct (interactive neural stimulation) control over refractory seizures, some of which achieved high performance. However, to achieve high sensitivity and a low false prediction rate, many of these studies relied on handcraft feature extraction and/or tailored feature extraction, which is performed for each patient independently. This approach, however, is not generalizable, and requires significant modifications for each new patient within a new dataset. In this article, we apply convolutional neural networks to different intracranial and scalp electroencephalogram (EEG) datasets and propose a generalized retrospective and patient-specific seizure prediction method. We use the short-time Fourier transform on 30-s EEG windows to extract information in both the frequency domain and the time domain. The algorithm automatically generates optimized features for each patient to best classify preictal and interictal segments. The method can be applied to any other patient from any dataset without the need for manual feature extraction. The proposed approach achieves sensitivity of 81.4%, 81.2%, and 75% and a false prediction rate of 0.06/h, 0.16/h, and 0.21/h on the Freiburg Hospital intracranial EEG dataset, the Boston Children's Hospital-MIT scalp EEG dataset, and the American Epilepsy Society Seizure Prediction Challenge dataset, respectively. Our prediction method is also statistically better than an unspecific random predictor for most of the patients in all three datasets. Copyright © 2018 Elsevier Ltd. All rights reserved.

New light-amplifier-based detector designs for high spatial resolution and high sensitivity CBCT mammography and fluoroscopy

PubMed Central

Rudin, Stephen; Kuhls, Andrew T.; Yadava, Girijesh K.; Josan, Gaurav C.; Wu, Ye; Chityala, Ravishankar N.; Rangwala, Hussain S.; Ciprian Ionita, N.; Hoffmann, Kenneth R.; Bednarek, Daniel R.

2011-01-01

New cone-beam computed tomographic (CBCT) mammography system designs are presented where the detectors provide high spatial resolution, high sensitivity, low noise, wide dynamic range, negligible lag and high frame rates similar to features required for high performance fluoroscopy detectors. The x-ray detectors consist of a phosphor coupled by a fiber-optic taper to either a high gain image light amplifier (LA) then CCD camera or to an electron multiplying CCD. When a square-array of such detectors is used, a field-of-view (FOV) to 20 × 20 cm can be obtained where the images have pixel-resolution of 100 µm or better. To achieve practical CBCT mammography scan-times, 30 fps may be acquired with quantum limited (noise free) performance below 0.2 µR detector exposure per frame. Because of the flexible voltage controlled gain of the LA’s and EMCCDs, large detector dynamic range is also achievable. Features of such detector systems with arrays of either generation 2 (Gen 2) or 3 (Gen 3) LAs optically coupled to CCD cameras or arrays of EMCCDs coupled directly are compared. Quantum accounting analysis is done for a variety of such designs where either the lowest number of information carriers off the LA photo-cathode or electrons released in the EMCCDs per x-ray absorbed in the phosphor are large enough to imply no quantum sink for the design. These new LA- or EMCCD-based systems could lead to vastly improved CBCT mammography, ROI-CT, or fluoroscopy performance compared to systems using flat panels. PMID:21297904

New light-amplifier-based detector designs for high spatial resolution and high sensitivity CBCT mammography and fluoroscopy

NASA Astrophysics Data System (ADS)

Rudin, Stephen; Kuhls, Andrew T.; Yadava, Girijesh K.; Josan, Gaurav C.; Wu, Ye; Chityala, Ravishankar N.; Rangwala, Hussain S.; Ionita, N. Ciprian; Hoffmann, Kenneth R.; Bednarek, Daniel R.

2006-03-01

New cone-beam computed tomographic (CBCT) mammography system designs are presented where the detectors provide high spatial resolution, high sensitivity, low noise, wide dynamic range, negligible lag and high frame rates similar to features required for high performance fluoroscopy detectors. The x-ray detectors consist of a phosphor coupled by a fiber-optic taper to either a high gain image light amplifier (LA) then CCD camera or to an electron multiplying CCD. When a square-array of such detectors is used, a field-of-view (FOV) to 20 x 20 cm can be obtained where the images have pixel-resolution of 100 μm or better. To achieve practical CBCT mammography scan-times, 30 fps may be acquired with quantum limited (noise free) performance below 0.2 μR detector exposure per frame. Because of the flexible voltage controlled gain of the LA's and EMCCDs, large detector dynamic range is also achievable. Features of such detector systems with arrays of either generation 2 (Gen 2) or 3 (Gen 3) LAs optically coupled to CCD cameras or arrays of EMCCDs coupled directly are compared. Quantum accounting analysis is done for a variety of such designs where either the lowest number of information carriers off the LA photo-cathode or electrons released in the EMCCDs per x-ray absorbed in the phosphor are large enough to imply no quantum sink for the design. These new LA- or EMCCD-based systems could lead to vastly improved CBCT mammography, ROI-CT, or fluoroscopy performance compared to systems using flat panels.

A urea biosensor based on pH-sensitive Sm2TiO5 electrolyte-insulator-semiconductor.

PubMed

Pan, Tung-Ming; Huang, Ming-De; Lin, Wan-Ying; Wu, Min-Hsien

2010-06-11

A urea biosensor based on pH-sensitive Sm(2)TiO(5) electrolyte-insulator-semiconductor (EIS) has been described. We used X-ray diffraction, Auger electron spectroscopy, and atomic force microscopy to investigate the structural and morphological features of high-k Sm(2)TiO(5) sensing membranes that had been subjected to annealing at different temperatures. The EIS device incorporating a high-k Sm(2)TiO(5) sensing film that had been annealed at 900 degrees C exhibited good sensing characteristics, including a high sensitivity of 60.5 mV/pH (in solutions from pH 2 to 12), a small hysteresis voltage of 2.72 mV (in the pH loop 7-->4-->7-->10-->7), and a low drift rate of 1.15 mV h(-1) (in the buffer solution at pH 7). The Sm(2)TiO(5) EIS device also showed a high selective response towards H(+). This improvement can be attributed to the small number of crystal defects and the large surface roughness. In addition, the urea biosensor based on pH-sensitive EIS incorporating a Sm(2)TiO(5) sensing membrane annealed at 900 degrees C allowed the potentiometric analysis of urea, at concentrations ranging from 0.1 to 32 mM, with a sensitivity of 72.85 mV/purea. Copyright 2010 Elsevier B.V. All rights reserved.

Better Learning with More Error: Probabilistic Feedback Increases Sensitivity to Correlated Cues in Categorization

ERIC Educational Resources Information Center

Little, Daniel R.; Lewandowsky, Stephan

2009-01-01

Despite the fact that categories are often composed of correlated features, the evidence that people detect and use these correlations during intentional category learning has been overwhelmingly negative to date. Nonetheless, on other categorization tasks, such as feature prediction, people show evidence of correlational sensitivity. A…

Scalable Online Network Modeling and Simulation

DTIC Science & Technology

2005-08-01

ONLINE NETWORK MODELING AND SIMULATION 6. AUTHOR(S) Boleslaw Szymanski , Shivkumar Kalyanaraman, Biplab Sikdar and Christopher Carothers 5...performance for a wide range of parameter values (parameter sensitivity), understanding of protocol stability and dynamics, and studying feature ...a wide range of parameter values (parameter sensitivity), understanding of protocol stability and dynamics, and studying feature interactions

Internalization of aggregated photosensitizers by tumor cells: subcellular time-resolved fluorescence spectroscopy on derivatives of pyropheophorbide-a ethers and chlorin e6 under femtosecond one- and two-photon excitations.

PubMed

Kelbauskas, L; Dietel, W

2002-12-01

Amphiphilic sensitizers self-associate in aqueous environments and form aggregated species that exhibit no or only negligible photodynamic activity. However, amphiphilic photosensitizers number among the most potent agents of photodynamic therapy. The processes by which these sensitizers are internalized into tumor cells have yet to be fully elucidated and thus remain the subject of debate. In this study the uptake of photosensitizer aggregates into tumor cells was examined directly using subcellular time-resolved fluorescence spectroscopy with a high temporal resolution (20-30 ps) and high sensitivity (time-correlated single-photon counting). The investigations were performed on selected sensitizers that exhibit short fluorescence decay times (< 50 ps) in aggregated form. Derivatives of pyropheophorbide-a ether and chlorin e6 with varying lipophilicity were used for the study. The characteristic fluorescence decay times and spectroscopic features of the sensitizer aggregates measured in aqueous solution also could be observed in A431 human endothelial carcinoma cells administered with these photosensitizers. This shows that tumor cells can internalize sensitizers in aggregated form. Uptake of aggregates and their monomerization inside cells were demonstrated directly for the first time by means of fluorescence lifetime imaging with a high temporal resolution. Internalization of the aggregates seems to be endocytosis mediated. The degree of their monomerization in tumor cells is strongly influenced by the lipophilicity of the compounds.

Shift-invariant discrete wavelet transform analysis for retinal image classification.

PubMed

Khademi, April; Krishnan, Sridhar

2007-12-01

This work involves retinal image classification and a novel analysis system was developed. From the compressed domain, the proposed scheme extracts textural features from wavelet coefficients, which describe the relative homogeneity of localized areas of the retinal images. Since the discrete wavelet transform (DWT) is shift-variant, a shift-invariant DWT was explored to ensure that a robust feature set was extracted. To combat the small database size, linear discriminant analysis classification was used with the leave one out method. 38 normal and 48 abnormal (exudates, large drusens, fine drusens, choroidal neovascularization, central vein and artery occlusion, histoplasmosis, arteriosclerotic retinopathy, hemi-central retinal vein occlusion and more) were used and a specificity of 79% and sensitivity of 85.4% were achieved (the average classification rate is 82.2%). The success of the system can be accounted to the highly robust feature set which included translation, scale and semi-rotational, features. Additionally, this technique is database independent since the features were specifically tuned to the pathologies of the human eye.

Recursive feature elimination for biomarker discovery in resting-state functional connectivity.

PubMed

Ravishankar, Hariharan; Madhavan, Radhika; Mullick, Rakesh; Shetty, Teena; Marinelli, Luca; Joel, Suresh E

2016-08-01

Biomarker discovery involves finding correlations between features and clinical symptoms to aid clinical decision. This task is especially difficult in resting state functional magnetic resonance imaging (rs-fMRI) data due to low SNR, high-dimensionality of images, inter-subject and intra-subject variability and small numbers of subjects compared to the number of derived features. Traditional univariate analysis suffers from the problem of multiple comparisons. Here, we adopt an alternative data-driven method for identifying population differences in functional connectivity. We propose a machine-learning approach to down-select functional connectivity features associated with symptom severity in mild traumatic brain injury (mTBI). Using this approach, we identified functional regions with altered connectivity in mTBI. including the executive control, visual and precuneus networks. We compared functional connections at multiple resolutions to determine which scale would be more sensitive to changes related to patient recovery. These modular network-level features can be used as diagnostic tools for predicting disease severity and recovery profiles.

Phase space interrogation of the empirical response modes for seismically excited structures

NASA Astrophysics Data System (ADS)

Paul, Bibhas; George, Riya C.; Mishra, Sudib K.

2017-07-01

Conventional Phase Space Interrogation (PSI) for structural damage assessment relies on exciting the structure with low dimensional chaotic waveform, thereby, significantly limiting their applicability to large structures. The PSI technique is presently extended for structure subjected to seismic excitations. The high dimensionality of the phase space for seismic response(s) are overcome by the Empirical Mode Decomposition (EMD), decomposing the responses to a number of intrinsic low dimensional oscillatory modes, referred as Intrinsic Mode Functions (IMFs). Along with their low dimensionality, a few IMFs, retain sufficient information of the system dynamics to reflect the damage induced changes. The mutually conflicting nature of low-dimensionality and the sufficiency of dynamic information are taken care by the optimal choice of the IMF(s), which is shown to be the third/fourth IMFs. The optimal IMF(s) are employed for the reconstruction of the Phase space attractor following Taken's embedding theorem. The widely referred Changes in Phase Space Topology (CPST) feature is then employed on these Phase portrait(s) to derive the damage sensitive feature, referred as the CPST of the IMFs (CPST-IMF). The legitimacy of the CPST-IMF is established as a damage sensitive feature by assessing its variation with a number of damage scenarios benchmarked in the IASC-ASCE building. The damage localization capability, remarkable tolerance to noise contamination and the robustness under different seismic excitations of the feature are demonstrated.

Automated Detection of Actinic Keratoses in Clinical Photographs

PubMed Central

Hames, Samuel C.; Sinnya, Sudipta; Tan, Jean-Marie; Morze, Conrad; Sahebian, Azadeh; Soyer, H. Peter; Prow, Tarl W.

2015-01-01

Background Clinical diagnosis of actinic keratosis is known to have intra- and inter-observer variability, and there is currently no non-invasive and objective measure to diagnose these lesions. Objective The aim of this pilot study was to determine if automatically detecting and circumscribing actinic keratoses in clinical photographs is feasible. Methods Photographs of the face and dorsal forearms were acquired in 20 volunteers from two groups: the first with at least on actinic keratosis present on the face and each arm, the second with no actinic keratoses. The photographs were automatically analysed using colour space transforms and morphological features to detect erythema. The automated output was compared with a senior consultant dermatologist’s assessment of the photographs, including the intra-observer variability. Performance was assessed by the correlation between total lesions detected by automated method and dermatologist, and whether the individual lesions detected were in the same location as the dermatologist identified lesions. Additionally, the ability to limit false positives was assessed by automatic assessment of the photographs from the no actinic keratosis group in comparison to the high actinic keratosis group. Results The correlation between the automatic and dermatologist counts was 0.62 on the face and 0.51 on the arms, compared to the dermatologist’s intra-observer variation of 0.83 and 0.93 for the same. Sensitivity of automatic detection was 39.5% on the face, 53.1% on the arms. Positive predictive values were 13.9% on the face and 39.8% on the arms. Significantly more lesions (p<0.0001) were detected in the high actinic keratosis group compared to the no actinic keratosis group. Conclusions The proposed method was inferior to assessment by the dermatologist in terms of sensitivity and positive predictive value. However, this pilot study used only a single simple feature and was still able to achieve sensitivity of detection of 53.1% on the arms.This suggests that image analysis is a feasible avenue of investigation for overcoming variability in clinical assessment. Future studies should focus on more sophisticated features to improve sensitivity for actinic keratoses without erythema and limit false positives associated with the anatomical structures on the face. PMID:25615930

Non-contact feature detection using ultrasonic Lamb waves

DOEpatents

Sinha, Dipen N [Los Alamos, NM

2011-06-28

Apparatus and method for non-contact ultrasonic detection of features on or within the walls of hollow pipes are described. An air-coupled, high-power ultrasonic transducer for generating guided waves in the pipe wall, and a high-sensitivity, air-coupled transducer for detecting these waves, are disposed at a distance apart and at chosen angle with respect to the surface of the pipe, either inside of or outside of the pipe. Measurements may be made in reflection or transmission modes depending on the relative position of the transducers and the pipe. Data are taken by sweeping the frequency of the incident ultrasonic waves, using a tracking narrow-band filter to reduce detected noise, and transforming the frequency domain data into the time domain using fast Fourier transformation, if required.

Genetic algorithm based feature selection combined with dual classification for the automated detection of proliferative diabetic retinopathy.

PubMed

Welikala, R A; Fraz, M M; Dehmeshki, J; Hoppe, A; Tah, V; Mann, S; Williamson, T H; Barman, S A

2015-07-01

Proliferative diabetic retinopathy (PDR) is a condition that carries a high risk of severe visual impairment. The hallmark of PDR is the growth of abnormal new vessels. In this paper, an automated method for the detection of new vessels from retinal images is presented. This method is based on a dual classification approach. Two vessel segmentation approaches are applied to create two separate binary vessel map which each hold vital information. Local morphology features are measured from each binary vessel map to produce two separate 4-D feature vectors. Independent classification is performed for each feature vector using a support vector machine (SVM) classifier. The system then combines these individual outcomes to produce a final decision. This is followed by the creation of additional features to generate 21-D feature vectors, which feed into a genetic algorithm based feature selection approach with the objective of finding feature subsets that improve the performance of the classification. Sensitivity and specificity results using a dataset of 60 images are 0.9138 and 0.9600, respectively, on a per patch basis and 1.000 and 0.975, respectively, on a per image basis. Copyright © 2015 Elsevier Ltd. All rights reserved.

Asymmetric bagging and feature selection for activities prediction of drug molecules.

PubMed

Li, Guo-Zheng; Meng, Hao-Hua; Lu, Wen-Cong; Yang, Jack Y; Yang, Mary Qu

2008-05-28

Activities of drug molecules can be predicted by QSAR (quantitative structure activity relationship) models, which overcomes the disadvantages of high cost and long cycle by employing the traditional experimental method. With the fact that the number of drug molecules with positive activity is rather fewer than that of negatives, it is important to predict molecular activities considering such an unbalanced situation. Here, asymmetric bagging and feature selection are introduced into the problem and asymmetric bagging of support vector machines (asBagging) is proposed on predicting drug activities to treat the unbalanced problem. At the same time, the features extracted from the structures of drug molecules affect prediction accuracy of QSAR models. Therefore, a novel algorithm named PRIFEAB is proposed, which applies an embedded feature selection method to remove redundant and irrelevant features for asBagging. Numerical experimental results on a data set of molecular activities show that asBagging improve the AUC and sensitivity values of molecular activities and PRIFEAB with feature selection further helps to improve the prediction ability. Asymmetric bagging can help to improve prediction accuracy of activities of drug molecules, which can be furthermore improved by performing feature selection to select relevant features from the drug molecules data sets.

The effect of defect cluster size and interpolation on radiographic image quality

NASA Astrophysics Data System (ADS)

Töpfer, Karin; Yip, Kwok L.

2011-03-01

For digital X-ray detectors, the need to control factory yield and cost invariably leads to the presence of some defective pixels. Recently, a standard procedure was developed to identify such pixels for industrial applications. However, no quality standards exist in medical or industrial imaging regarding the maximum allowable number and size of detector defects. While the answer may be application specific, the minimum requirement for any defect specification is that the diagnostic quality of the images be maintained. A more stringent criterion is to keep any changes in the images due to defects below the visual threshold. Two highly sensitive image simulation and evaluation methods were employed to specify the fraction of allowable defects as a function of defect cluster size in general radiography. First, the most critical situation of the defect being located in the center of the disease feature was explored using image simulation tools and a previously verified human observer model, incorporating a channelized Hotelling observer. Detectability index d' was obtained as a function of defect cluster size for three different disease features on clinical lung and extremity backgrounds. Second, four concentrations of defects of four different sizes were added to clinical images with subtle disease features and then interpolated. Twenty observers evaluated the images against the original on a single display using a 2-AFC method, which was highly sensitive to small changes in image detail. Based on a 50% just-noticeable difference, the fraction of allowed defects was specified vs. cluster size.

Ultrasonically spray coated silver layers from designed precursor inks for flexible electronics.

PubMed

Marchal, W; Vandevenne, G; D'Haen, J; Calmont de Andrade Almeida, A; Durand Sola, M A; van den Ham, E J; Drijkoningen, J; Elen, K; Deferme, W; Van Bael, M K; Hardy, A

2017-05-26

Integration of electronic circuit components onto flexible materials such as plastic foils, paper and textiles is a key challenge for the development of future smart applications. Therefore, conductive metal features need to be deposited on temperature sensitive substrates in a fast and straightforward way. The feasibility of these emerging (nano-) electronic technologies depends on the availability of well-designed deposition techniques and on novel functional metal inks. As ultrasonic spray coating (USSC) is one of the most promising techniques to meet the above requirements, innovative metal organic decomposition (MOD) inks are designed to deposit silver features on plastic foils. Various amine ligands were screened and their influence on the ink stability and the characteristics of the resulting metal depositions were evaluated to determine the optimal formulation. Eventually, silver layers with excellent performance in terms of conductivity (15% bulk silver conductivity), stability, morphology and adhesion could be obtained, while operating in a very low temperature window of 70 °C-120 °C. Moreover, the optimal deposition conditions were determined via an in-depth analysis of the ultrasonically sprayed silver layers. Applying these tailored MOD inks, the USSC technique enabled smooth, semi-transparent silver layers with a tunable thickness on large areas without time-consuming additional sintering steps after deposition. Therefore, this novel combination of nanoparticle-free Ag-inks and the USSC process holds promise for high throughput deposition of highly conductive silver features on heat sensitive substrates and even 3D objects.

Ultrasonically spray coated silver layers from designed precursor inks for flexible electronics

NASA Astrophysics Data System (ADS)

Marchal, W.; Vandevenne, G.; D'Haen, J.; Almeida, A. Calmont de Andrade; Durand Sola, M. A., Jr.; van den Ham, E. J.; Drijkoningen, J.; Elen, K.; Deferme, W.; Van Bael, M. K.; Hardy, A.

2017-05-01

Integration of electronic circuit components onto flexible materials such as plastic foils, paper and textiles is a key challenge for the development of future smart applications. Therefore, conductive metal features need to be deposited on temperature sensitive substrates in a fast and straightforward way. The feasibility of these emerging (nano-) electronic technologies depends on the availability of well-designed deposition techniques and on novel functional metal inks. As ultrasonic spray coating (USSC) is one of the most promising techniques to meet the above requirements, innovative metal organic decomposition (MOD) inks are designed to deposit silver features on plastic foils. Various amine ligands were screened and their influence on the ink stability and the characteristics of the resulting metal depositions were evaluated to determine the optimal formulation. Eventually, silver layers with excellent performance in terms of conductivity (15% bulk silver conductivity), stability, morphology and adhesion could be obtained, while operating in a very low temperature window of 70 °C-120 °C. Moreover, the optimal deposition conditions were determined via an in-depth analysis of the ultrasonically sprayed silver layers. Applying these tailored MOD inks, the USSC technique enabled smooth, semi-transparent silver layers with a tunable thickness on large areas without time-consuming additional sintering steps after deposition. Therefore, this novel combination of nanoparticle-free Ag-inks and the USSC process holds promise for high throughput deposition of highly conductive silver features on heat sensitive substrates and even 3D objects.

Central Sensitization and Neuropathic Features of Ongoing Pain in a Rat Model of Advanced Osteoarthritis.

PubMed

Havelin, Joshua; Imbert, Ian; Cormier, Jennifer; Allen, Joshua; Porreca, Frank; King, Tamara

2016-03-01

Osteoarthritis (OA) pain is most commonly characterized by movement-triggered joint pain. However, in advanced disease, OA pain becomes persistent, ongoing and resistant to treatment with nonsteroidal anti-inflammatory drugs (NSAIDs). The mechanisms underlying ongoing pain in advanced OA are poorly understood. We recently showed that intra-articular (i.a.) injection of monosodium iodoacetate (MIA) into the rat knee joint produces concentration-dependent outcomes. Thus, a low dose of i.a. MIA produces NSAID-sensitive weight asymmetry without evidence of ongoing pain and a high i.a. MIA dose produces weight asymmetry and NSAID-resistant ongoing pain. In the present study, palpation of the ipsilateral hind limb of rats treated 14 days previously with high, but not low, doses of i.a. MIA produced expression of the early oncogene, FOS, in the spinal dorsal horn. Inactivation of descending pain facilitatory pathways using a microinjection of lidocaine within the rostral ventromedial medulla induced conditioned place preference selectively in rats treated with the high dose of MIA. Conditioned place preference to intra-articular lidocaine was blocked by pretreatment with duloxetine (30 mg/kg, intraperitoneally at -30 minutes). These observations are consistent with the likelihood of a neuropathic component of OA that elicits ongoing, NSAID-resistant pain and central sensitization that is mediated, in part, by descending modulatory mechanisms. This model provides a basis for exploration of underlying mechanisms promoting neuropathic components of OA pain and for the identification of mechanisms that might guide drug discovery for treatment of advanced OA pain without the need for joint replacement. Difficulty in managing advanced OA pain often results in joint replacement therapy in these patients. Improved understanding of mechanisms driving NSAID-resistant ongoing OA pain might facilitate development of alternatives to joint replacement therapy. Our findings suggest that central sensitization and neuropathic features contribute to NSAID-resistant ongoing OA joint pain. Copyright © 2016 American Pain Society. Published by Elsevier Inc. All rights reserved.

Disclosure of sensitive behaviors across self-administered survey modes: a meta-analysis.

PubMed

Gnambs, Timo; Kaspar, Kai

2015-12-01

In surveys, individuals tend to misreport behaviors that are in contrast to prevalent social norms or regulations. Several design features of the survey procedure have been suggested to counteract this problem; particularly, computerized surveys are supposed to elicit more truthful responding. This assumption was tested in a meta-analysis of survey experiments reporting 460 effect sizes (total N =125,672). Self-reported prevalence rates of several sensitive behaviors for which motivated misreporting has been frequently observed were compared across self-administered paper-and-pencil versus computerized surveys. The results revealed that computerized surveys led to significantly more reporting of socially undesirable behaviors than comparable surveys administered on paper. This effect was strongest for highly sensitive behaviors and surveys administered individually to respondents. Moderator analyses did not identify interviewer effects or benefits of audio-enhanced computer surveys. The meta-analysis highlighted the advantages of computerized survey modes for the assessment of sensitive topics.

Structural Sensitivity of a Prokaryotic Pentameric Ligand-gated Ion Channel to Its Membrane Environment*

PubMed Central

Labriola, Jonathan M.; Pandhare, Akash; Jansen, Michaela; Blanton, Michael P.; Corringer, Pierre-Jean; Baenziger, John E.

2013-01-01

Although the activity of the nicotinic acetylcholine receptor (nAChR) is exquisitely sensitive to its membrane environment, the underlying mechanisms remain poorly defined. The homologous prokaryotic pentameric ligand-gated ion channel, Gloebacter ligand-gated ion channel (GLIC), represents an excellent model for probing the molecular basis of nAChR sensitivity because of its high structural homology, relative ease of expression, and amenability to crystallographic analysis. We show here that membrane-reconstituted GLIC exhibits structural and biophysical properties similar to those of the membrane-reconstituted nAChR, although GLIC is substantially more thermally stable. GLIC, however, does not possess the same exquisite lipid sensitivity. In particular, GLIC does not exhibit the same propensity to adopt an uncoupled conformation where agonist binding is uncoupled from channel gating. Structural comparisons provide insight into the chemical features that may predispose the nAChR to the formation of an uncoupled state. PMID:23463505

Electronic Raman scattering as an ultra-sensitive probe of strain effects in semiconductors.

PubMed

Fluegel, Brian; Mialitsin, Aleksej V; Beaton, Daniel A; Reno, John L; Mascarenhas, Angelo

2015-05-28

Semiconductor strain engineering has become a critical feature of high-performance electronics because of the significant device performance enhancements that it enables. These improvements, which emerge from strain-induced modifications to the electronic band structure, necessitate new ultra-sensitive tools to probe the strain in semiconductors. Here, we demonstrate that minute amounts of strain in thin semiconductor epilayers can be measured using electronic Raman scattering. We applied this strain measurement technique to two different semiconductor alloy systems using coherently strained epitaxial thin films specifically designed to produce lattice-mismatch strains as small as 10(-4). Comparing our strain sensitivity and signal strength in Al(x)Ga(1-x)As with those obtained using the industry-standard technique of phonon Raman scattering, we found that there was a sensitivity improvement of 200-fold and a signal enhancement of 4 × 10(3), thus obviating key constraints in semiconductor strain metrology.

Electronic Raman scattering as an ultra-sensitive probe of strain effects in semiconductors

PubMed Central

Fluegel, Brian; Mialitsin, Aleksej V.; Beaton, Daniel A.; Reno, John L.; Mascarenhas, Angelo

2015-01-01

Semiconductor strain engineering has become a critical feature of high-performance electronics because of the significant device performance enhancements that it enables. These improvements, which emerge from strain-induced modifications to the electronic band structure, necessitate new ultra-sensitive tools to probe the strain in semiconductors. Here, we demonstrate that minute amounts of strain in thin semiconductor epilayers can be measured using electronic Raman scattering. We applied this strain measurement technique to two different semiconductor alloy systems using coherently strained epitaxial thin films specifically designed to produce lattice-mismatch strains as small as 10−4. Comparing our strain sensitivity and signal strength in AlxGa1−xAs with those obtained using the industry-standard technique of phonon Raman scattering, we found that there was a sensitivity improvement of 200-fold and a signal enhancement of 4 × 103, thus obviating key constraints in semiconductor strain metrology. PMID:26017853

Applications of nanopipettes in bionanotechnology.

PubMed

Ying, Liming

2009-08-01

At present, technical hurdles remain in probing biochemical processes in living cells and organisms at nanometre spatial resolution, millisecond time resolution and with high specificity and single-molecule sensitivity. Owing to its unique shape, size and electrical properties, the nanopipette has been used to obtain high-resolution topographic images of live cells under physiological conditions, and to create nanoscale features by controlled delivery of biomolecules. In the present paper, I discuss recent progress in the development of a family of new methods for nanosensing and nanomanipulation using nanopipettes.

CCFpams: Atmospheric stellar parameters from cross-correlation functions

NASA Astrophysics Data System (ADS)

Malavolta, Luca; Lovis, Christophe; Pepe, Francesco; Sneden, Christopher; Udry, Stephane

2017-07-01

CCFpams allows the measurement of stellar temperature, metallicity and gravity within a few seconds and in a completely automated fashion. Rather than performing comparisons with spectral libraries, the technique is based on the determination of several cross-correlation functions (CCFs) obtained by including spectral features with different sensitivity to the photospheric parameters. Literature stellar parameters of high signal-to-noise (SNR) and high-resolution HARPS spectra of FGK Main Sequence stars are used to calibrate the stellar parameters as a function of CCF areas.

Time stamping of single optical photons with 10 ns resolution

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

Chakaberia, Irakli; Cotlet, Mircea; Fisher-Levine, Merlin

High spatial and temporal resolution are key features for many modern applications, e.g. mass spectrometry, probing the structure of materials via neutron scattering, studying molecular structure, etc. Fast imaging also provides the capability of coincidence detection, and the further addition of sensitivity to single optical photons with the capability of timestamping them further broadens the field of potential applications. Here, photon counting is already widely used in X-ray imaging, where the high energy of the photons makes their detection easier.

Time stamping of single optical photons with 10 ns resolution

DOE PAGES

Chakaberia, Irakli; Cotlet, Mircea; Fisher-Levine, Merlin; ...

2017-05-08

High spatial and temporal resolution are key features for many modern applications, e.g. mass spectrometry, probing the structure of materials via neutron scattering, studying molecular structure, etc. Fast imaging also provides the capability of coincidence detection, and the further addition of sensitivity to single optical photons with the capability of timestamping them further broadens the field of potential applications. Here, photon counting is already widely used in X-ray imaging, where the high energy of the photons makes their detection easier.

Clinical prediction of Gardnerella vaginalis in general practice

PubMed Central

O'Dowd, T.C.; West, R.R.

1987-01-01

In a study of 162 women with vaginal symptoms the clinical features of increased discharge, yellow discharge, 'high cheese' odour and pH greater than 5 were statistically strongly associated with the presence of Gardnerella vaginalis, confirmed by microbiological culture. The sensitivities and specificities of these clinical tests, although not as high as those of previously described sideroom tests using the amine test and microscopy for 'clue cells' nevertheless allow the clinician to predict G. vaginalis reliably and initiate treatment at first consultation. PMID:3499508

Magnetic sensor for high temperature using a laminate composite of magnetostrictive material and piezoelectric material

NASA Astrophysics Data System (ADS)

Ueno, Toshiyuki; Higuchi, Toshiro

2005-05-01

A high sensitive and heat-resistive magnetic sensor using a magnetostrictive/piezoelectric laminate composite is investigated. The sensing principle is based on the magnetostrictive- and piezoelectric effect, whereby a detected yoke displacement is transduced into a voltage on the piezoelectric materials. The sensor is intended to detect the displacement of a ferromagnetic object in a high temperature environment, where conventional magnetic sensors are not useful. Such applications include sensors in engine of automobile and machinery used in material processing. The sensor features combination of a laminate composite of magnetostrictive/piezoelectric materials with high Curie temperatures and an appropriate magnetic circuit to convert mechanical displacement to sensor voltages and suppress temperature fluctuation. This paper describes the sensing principle and shows experimental results using a composite of Terfenol-D and Lithium Niobate to assure high sensitivity of 50V/mm at bias gap of 0.1mm and a temperature operating range over 200 °C.

Diagnostic value of sleep stage dissociation as visualized on a 2-dimensional sleep state space in human narcolepsy.

PubMed

Olsen, Anders Vinther; Stephansen, Jens; Leary, Eileen; Peppard, Paul E; Sheungshul, Hong; Jennum, Poul Jørgen; Sorensen, Helge; Mignot, Emmanuel

2017-04-15

Type 1 narcolepsy (NT1) is characterized by symptoms believed to represent Rapid Eye Movement (REM) sleep stage dissociations, occurrences where features of wake and REM sleep are intermingled, resulting in a mixed state. We hypothesized that sleep stage dissociations can be objectively detected through the analysis of nocturnal Polysomnography (PSG) data, and that those affecting REM sleep can be used as a diagnostic feature for narcolepsy. A Linear Discriminant Analysis (LDA) model using 38 features extracted from EOG, EMG and EEG was used in control subjects to select features differentiating wake, stage N1, N2, N3 and REM sleep. Sleep stage differentiation was next represented in a 2D projection. Features characteristic of sleep stage differences were estimated from the residual sleep stage probability in the 2D space. Using this model we evaluated PSG data from NT1 and non-narcoleptic subjects. An LDA classifier was used to determine the best separation plane. This method replicates the specificity/sensitivity from the training set to the validation set better than many other methods. Eight prominent features could differentiate narcolepsy and controls in the validation dataset. Using a composite measure and a specificity cut off 95% in the training dataset, sensitivity was 43%. Specificity/sensitivity was 94%/38% in the validation set. Using hypersomnia subjects, specificity/sensitivity was 84%/15%. Analyzing treated narcoleptics the specificity/sensitivity was 94%/10%. Sleep stage dissociation can be used for the diagnosis of narcolepsy. However the use of some medications and presence of undiagnosed hypersomnolence patients impacts the result. Copyright © 2017 Elsevier B.V. All rights reserved.

Variability of temperature sensitivity of extreme precipitation from a regional-to-local impact scale perspective

NASA Astrophysics Data System (ADS)

Schroeer, K.; Kirchengast, G.

2016-12-01

Relating precipitation intensity to temperature is a popular approach to assess potential changes of extreme events in a warming climate. Potential increases in extreme rainfall induced hazards, such as flash flooding, serve as motivation. It has not been addressed whether the temperature-precipitation scaling approach is meaningful on a regional to local level, where the risk of climate and weather impact is dealt with. Substantial variability of temperature sensitivity of extreme precipitation has been found that results from differing methodological assumptions as well as from varying climatological settings of the study domains. Two aspects are consistently found: First, temperature sensitivities beyond the expected consistency with the Clausius-Clapeyron (CC) equation are a feature of short-duration, convective, sub-daily to sub-hourly high-percentile rainfall intensities at mid-latitudes. Second, exponential growth ceases or reverts at threshold temperatures that vary from region to region, as moisture supply becomes limited. Analyses of pooled data, or of single or dispersed stations over large areas make it difficult to estimate the consequences in terms of local climate risk. In this study we test the meaningfulness of the scaling approach from an impact scale perspective. Temperature sensitivities are assessed using quantile regression on hourly and sub-hourly precipitation data from 189 stations in the Austrian south-eastern Alpine region. The observed scaling rates vary substantially, but distinct regional and seasonal patterns emerge. High sensitivity exceeding CC-scaling is seen on the 10-minute scale more than on the hourly scale, in storms shorter than 2 hours duration, and in shoulder seasons, but it is not necessarily a significant feature of the extremes. To be impact relevant, change rates need to be linked to absolute rainfall amounts. We show that high scaling rates occur in lower temperature conditions and thus have smaller effect on absolute precipitation intensities. While reporting of mere percentage numbers can be misleading, scaling studies can add value to process understanding on the local scale, if the factors that influence scaling rates are considered from both a methodological and a physical perspective.

A comprehensive analysis of earthquake damage patterns using high dimensional model representation feature selection

NASA Astrophysics Data System (ADS)

Taşkin Kaya, Gülşen

2013-10-01

Recently, earthquake damage assessment using satellite images has been a very popular ongoing research direction. Especially with the availability of very high resolution (VHR) satellite images, a quite detailed damage map based on building scale has been produced, and various studies have also been conducted in the literature. As the spatial resolution of satellite images increases, distinguishability of damage patterns becomes more cruel especially in case of using only the spectral information during classification. In order to overcome this difficulty, textural information needs to be involved to the classification to improve the visual quality and reliability of damage map. There are many kinds of textural information which can be derived from VHR satellite images depending on the algorithm used. However, extraction of textural information and evaluation of them have been generally a time consuming process especially for the large areas affected from the earthquake due to the size of VHR image. Therefore, in order to provide a quick damage map, the most useful features describing damage patterns needs to be known in advance as well as the redundant features. In this study, a very high resolution satellite image after Iran, Bam earthquake was used to identify the earthquake damage. Not only the spectral information, textural information was also used during the classification. For textural information, second order Haralick features were extracted from the panchromatic image for the area of interest using gray level co-occurrence matrix with different size of windows and directions. In addition to using spatial features in classification, the most useful features representing the damage characteristic were selected with a novel feature selection method based on high dimensional model representation (HDMR) giving sensitivity of each feature during classification. The method called HDMR was recently proposed as an efficient tool to capture the input-output relationships in high-dimensional systems for many problems in science and engineering. The HDMR method is developed to improve the efficiency of the deducing high dimensional behaviors. The method is formed by a particular organization of low dimensional component functions, in which each function is the contribution of one or more input variables to the output variables.

Characterization of spatiotemporal changes for the classification of dynamic contrast-enhanced magnetic-resonance breast lesions.

PubMed

Milenković, Jana; Hertl, Kristijana; Košir, Andrej; Zibert, Janez; Tasič, Jurij Franc

2013-06-01

The early detection of breast cancer is one of the most important predictors in determining the prognosis for women with malignant tumours. Dynamic contrast-enhanced magnetic-resonance imaging (DCE-MRI) is an important imaging modality for detecting and interpreting the different breast lesions from a time sequence of images and has proved to be a very sensitive modality for breast-cancer diagnosis. However, DCE-MRI exhibits only a moderate specificity, thus leading to a high rate of false positives, resulting in unnecessary biopsies that are stressful and physically painful for the patient and lead to an increase in the cost of treatment. There is a strong medical need for a DCE-MRI computer-aided diagnosis tool that would offer a reliable support to the physician's decision providing a high level of sensitivity and specificity. In our study we investigated the possibility of increasing differentiation between the malignant and the benign lesions with respect to the spatial variation of the temporal enhancements of three parametric maps, i.e., the initial enhancement (IE) map, the post-initial enhancement (PIE) map and the signal enhancement ratio (SER) map, by introducing additional methods along with the grey-level co-occurrence matrix, i.e., a second-order statistical method already applied for quantifying the spatiotemporal variations. We introduced the grey-level run-length matrix and the grey-level difference matrix, representing two additional, second-order statistical methods, and the circular Gabor as a frequency-domain-based method. Each of the additional methods is for the first time applied to the DCE-MRI data to differentiate between the malignant and the benign breast lesions. We applied the least-square minimum-distance classifier (LSMD), logistic regression and least-squares support vector machine (LS-SVM) classifiers on a total of 115 (78 malignant and 37 benign) breast DCE-MRI cases. The performances were evaluated using ten experiments of a ten-fold cross-validation. Our experimental analysis revealed the PIE map, together with the feature subset in which the discriminating ability of the co-occurrence features was increased by adding the newly introduced features, to be the most significant for differentiation between the malignant and the benign lesions. That diagnostic test - the aforementioned combination of parametric map and the feature subset achieved the sensitivity of 0.9193 which is statistically significantly higher compared to other diagnostic tests after ten-experiments of a ten-fold cross-validation and gave a statistically significantly higher specificity of 0.7819 for the fixed 95% sensitivity after the receiver operating characteristic (ROC) curve analysis. Combining the information from all the three parametric maps significantly increased the area under the ROC curve (AUC) of the aforementioned diagnostic test for the LSMD and logistic regression; however, not for the LS-SVM. The LSMD classifier yielded the highest area under the ROC curve when using the combined information, increasing the AUC from 0.9651 to 0.9755. Introducing new features to those of the grey-level co-occurrence matrix significantly increased the differentiation between the malignant and the benign breast lesions, thus resulting in a high sensitivity and improved specificity. Copyright © 2013 Elsevier B.V. All rights reserved.

A fully battery-powered inexpensive spectrophotometric system for high-sensitivity point-of-care analysis on a microfluidic chip

PubMed Central

Dou, Maowei; Lopez, Juan; Rios, Misael; Garcia, Oscar; Xiao, Chuan; Eastman, Michael

2016-01-01

A cost-effective battery-powered spectrophotometric system (BASS) was developed for quantitative point-of-care (POC) analysis on a microfluidic chip. By using methylene blue as a model analyte, we first compared the performance of the BASS with a commercial spectrophotometric system, and further applied the BASS for loop-mediated isothermal amplification (LAMP) detection and subsequent quantitative nucleic acid analysis which exhibited a comparable limit of detection to that of Nanodrop. Compared to the commercial spectrophotometric system, our spectrophotometric system is lower-cost, consumes less reagents, and has a higher detection sensitivity. Most importantly, it does not rely on external power supplies. All these features make our spectrophotometric system highly suitable for a variety of POC analyses, such as field detection. PMID:27143408

Integration of a highly ordered gold nanowires array with glucose oxidase for ultra-sensitive glucose detection.

PubMed

Cui, Jiewu; Adeloju, Samuel B; Wu, Yucheng

2014-01-27

A highly sensitive amperometric nanobiosensor has been developed by integration of glucose oxidase (GO(x)) with a gold nanowires array (AuNWA) by cross-linking with a mixture of glutaraldehyde (GLA) and bovine serum albumin (BSA). An initial investigation of the morphology of the synthesized AuNWA by field emission scanning electron microscopy (FESEM) and field emission transmission electron microscopy (FETEM) revealed that the nanowires array was highly ordered with rough surface, and the electrochemical features of the AuNWA with/without modification were also investigated. The integrated AuNWA-BSA-GLA-GO(x) nanobiosensor with Nafion membrane gave a very high sensitivity of 298.2 μA cm(-2) mM(-1) for amperometric detection of glucose, while also achieving a low detection limit of 0.1 μM, and a wide linear range of 5-6000 μM. Furthermore, the nanobiosensor exhibited excellent anti-interference ability towards uric acid (UA) and ascorbic acid (AA) with the aid of Nafion membrane, and the results obtained for the analysis of human blood serum indicated that the device is capable of glucose detection in real samples. Copyright © 2013 Elsevier B.V. All rights reserved.

Effects of age, sex, and genotype on high-sensitivity metabolomic profiles in the fruit fly, Drosophila melanogaster

PubMed Central

Hoffman, Jessica M; Soltow, Quinlyn A; Li, Shuzhao; Sidik, Alfire; Jones, Dean P; Promislow, Daniel E L

2014-01-01

Researchers have used whole-genome sequencing and gene expression profiling to identify genes associated with age, in the hope of understanding the underlying mechanisms of senescence. But there is a substantial gap from variation in gene sequences and expression levels to variation in age or life expectancy. In an attempt to bridge this gap, here we describe the effects of age, sex, genotype, and their interactions on high-sensitivity metabolomic profiles in the fruit fly, Drosophila melanogaster. Among the 6800 features analyzed, we found that over one-quarter of all metabolites were significantly associated with age, sex, genotype, or their interactions, and multivariate analysis shows that individual metabolomic profiles are highly predictive of these traits. Using a metabolomic equivalent of gene set enrichment analysis, we identified numerous metabolic pathways that were enriched among metabolites associated with age, sex, and genotype, including pathways involving sugar and glycerophospholipid metabolism, neurotransmitters, amino acids, and the carnitine shuttle. Our results suggest that high-sensitivity metabolomic studies have excellent potential not only to reveal mechanisms that lead to senescence, but also to help us understand differences in patterns of aging among genotypes and between males and females. PMID:24636523

Sensing Using Rare-Earth-Doped Upconversion Nanoparticles

PubMed Central

Hao, Shuwei; Chen, Guanying; Yang, Chunhui

2013-01-01

Optical sensing plays an important role in theranostics due to its capability to detect hint biochemical entities or molecular targets as well as to precisely monitor specific fundamental psychological processes. Rare-earth (RE) doped upconversion nanoparticles (UCNPs) are promising for these endeavors due to their unique frequency converting capability; they emit efficient and sharp visible or ultraviolet (UV) luminescence via use of ladder-like energy levels of RE ions when excited at near infrared (NIR) light that are silent to tissues. These features allow not only a high penetration depth in biological tissues but also a high detection sensitivity. Indeed, the energy transfer between UCNPs and biomolecular or chemical indicators provide opportunities for high-sensitive bio- and chemical-sensing. A temperature-sensitive change of the intensity ratio between two close UC bands promises them for use in temperature mapping of a single living cell. In this work, we review recent investigations on using UCNPs for the detection of biomolecules (avidin, ATP, etc.), ions (cyanide, mecury, etc.), small gas molecules (oxygen, carbon dioxide, ammonia, etc.), as well as for in vitro temperature sensing. We also briefly summarize chemical methods in synthesizing UCNPs of high efficiency that are important for the detection limit. PMID:23650480

Tamm-plasmon and surface-plasmon hybrid-mode based refractometry in photonic bandgap structures.

PubMed

Das, Ritwick; Srivastava, Triranjita; Jha, Rajan

2014-02-15

The transverse magnetic (TM) polarized hybrid modes formed as a consequence of coupling between Tamm plasmon polariton (TM-TPP) mode and surface plasmon polariton (SPP) mode exhibit interesting dispersive features for realizing a highly sensitive and accurate surface plasmon resonance (SPR) sensor. We found that the TM-TPP modes, formed at the interface of distributed Bragg reflector and metal, are strongly dispersive as compared to SPP modes at optical frequencies. This causes an appreciably narrow interaction bandwidth between TM-TPP and SPP modes, which leads to highly accurate sensing. In addition, appropriate tailoring of dispersion characteristics of TM-TPP as well as SPP modes could ensure high sensitivity of a novel SPR platform. By suitably designing the Au/TiO₂/SiO₂-based geometry, we propose a TM-TPP/SPP hybrid-mode sensor and achieve a sensitivity ≥900  nm/RIU with high detection accuracy (≥30  μm⁻¹) for analyte refractive indices varying between 1.330 and 1.345 in 600-700 nm wavelength range. The possibility to achieve desired dispersive behavior in any spectral band makes the sensing configuration an extremely attractive candidate to design sensors depending on the availability of optical sources.

Energetic-Energetic Cocrystals of Diacetone Diperoxide (DADP): Dramatic and Divergent Sensitivity Modifications via Cocrystallization.

PubMed

Landenberger, Kira B; Bolton, Onas; Matzger, Adam J

2015-04-22

Here we report a series of energetic-energetic cocrystals that incorporate the primary explosive diacetone diperoxide (DADP) with a series of trihalotrinitrobenzene explosives: 1:1 DADP/1,3,5-trichloro-2,4,6-trinitrobenzene (TCTNB), 1:1 DADP/1,3,5-tribromo-2,4,6-trinitrobenzene (TBTNB), and 1:1 DADP/1,3,5-triiodo-2,4,6-trinitrobenzene (TITNB). Acetone peroxides are attractive for their inexpensive and facile synthesis, but undesirable properties such as poor stability, intractably high sensitivity and low density, an indicator for low explosive power, have limited their application. Here through cocrystallization the density, oxygen balance, and stability of DADP are dramatically improved. Regarding sensitivity, in the case of the DADP/TCTNB cocrystal, the high impact sensitivity of DADP is retained by the cocrystal, making it a denser and less volatile form of DADP that remains viable as a primary explosive. Conversely, the DADP/TITNB cocrystal features impact sensitivity that is greatly reduced relative to both pure DADP and pure TITNB, demonstrating for the first time an energetic cocrystal that is less sensitive to impact than either of its pure components. This dramatic difference in cocrystal sensitivities may stem from the significantly different halogen-peroxide interactions seen in each cocrystal structure. These results highlight how sensitivity is defined by complex relationships between inherent bond strengths and solid-state properties, and cocrystal series such as that presented here provide a powerful experimental platform to probe this relationship.

Discrete Adjoint Sensitivity Analysis of Hybrid Dynamical Systems With Switching [Discrete Adjoint Sensitivity Analysis of Hybrid Dynamical Systems

DOE PAGES

Zhang, Hong; Abhyankar, Shrirang; Constantinescu, Emil; ...

2017-01-24

Sensitivity analysis is an important tool for describing power system dynamic behavior in response to parameter variations. It is a central component in preventive and corrective control applications. The existing approaches for sensitivity calculations, namely, finite-difference and forward sensitivity analysis, require a computational effort that increases linearly with the number of sensitivity parameters. In this paper, we investigate, implement, and test a discrete adjoint sensitivity approach whose computational effort is effectively independent of the number of sensitivity parameters. The proposed approach is highly efficient for calculating sensitivities of larger systems and is consistent, within machine precision, with the function whosemore » sensitivity we are seeking. This is an essential feature for use in optimization applications. Moreover, our approach includes a consistent treatment of systems with switching, such as dc exciters, by deriving and implementing the adjoint jump conditions that arise from state-dependent and time-dependent switchings. The accuracy and the computational efficiency of the proposed approach are demonstrated in comparison with the forward sensitivity analysis approach. In conclusion, this paper focuses primarily on the power system dynamics, but the approach is general and can be applied to hybrid dynamical systems in a broader range of fields.« less

Discrete Adjoint Sensitivity Analysis of Hybrid Dynamical Systems With Switching [Discrete Adjoint Sensitivity Analysis of Hybrid Dynamical Systems

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

Zhang, Hong; Abhyankar, Shrirang; Constantinescu, Emil

Sensitivity analysis is an important tool for describing power system dynamic behavior in response to parameter variations. It is a central component in preventive and corrective control applications. The existing approaches for sensitivity calculations, namely, finite-difference and forward sensitivity analysis, require a computational effort that increases linearly with the number of sensitivity parameters. In this paper, we investigate, implement, and test a discrete adjoint sensitivity approach whose computational effort is effectively independent of the number of sensitivity parameters. The proposed approach is highly efficient for calculating sensitivities of larger systems and is consistent, within machine precision, with the function whosemore » sensitivity we are seeking. This is an essential feature for use in optimization applications. Moreover, our approach includes a consistent treatment of systems with switching, such as dc exciters, by deriving and implementing the adjoint jump conditions that arise from state-dependent and time-dependent switchings. The accuracy and the computational efficiency of the proposed approach are demonstrated in comparison with the forward sensitivity analysis approach. In conclusion, this paper focuses primarily on the power system dynamics, but the approach is general and can be applied to hybrid dynamical systems in a broader range of fields.« less

Interferometric Reflectance Imaging Sensor (IRIS)—A Platform Technology for Multiplexed Diagnostics and Digital Detection

PubMed Central

Avci, Oguzhan; Lortlar Ünlü, Nese; Yalçın Özkumur, Ayça; Ünlü, M. Selim

2015-01-01

Over the last decade, the growing need in disease diagnostics has stimulated rapid development of new technologies with unprecedented capabilities. Recent emerging infectious diseases and epidemics have revealed the shortcomings of existing diagnostics tools, and the necessity for further improvements. Optical biosensors can lay the foundations for future generation diagnostics by providing means to detect biomarkers in a highly sensitive, specific, quantitative and multiplexed fashion. Here, we review an optical sensing technology, Interferometric Reflectance Imaging Sensor (IRIS), and the relevant features of this multifunctional platform for quantitative, label-free and dynamic detection. We discuss two distinct modalities for IRIS: (i) low-magnification (ensemble biomolecular mass measurements) and (ii) high-magnification (digital detection of individual nanoparticles) along with their applications, including label-free detection of multiplexed protein chips, measurement of single nucleotide polymorphism, quantification of transcription factor DNA binding, and high sensitivity digital sensing and characterization of nanoparticles and viruses. PMID:26205273

Designing ternary blend bulk heterojunction solar cells with reduced carrier recombination and a fill factor of 77%

NASA Astrophysics Data System (ADS)

Gasparini, Nicola; Jiao, Xuechen; Heumueller, Thomas; Baran, Derya; Matt, Gebhard J.; Fladischer, Stefanie; Spiecker, Erdmann; Ade, Harald; Brabec, Christoph J.; Ameri, Tayebeh

2016-09-01

In recent years the concept of ternary blend bulk heterojunction (BHJ) solar cells based on organic semiconductors has been widely used to achieve a better match to the solar irradiance spectrum, and power conversion efficiencies beyond 10% have been reported. However, the fill factor of organic solar cells is still limited by the competition between recombination and extraction of free charges. Here, we design advanced material composites leading to a high fill factor of 77% in ternary blends, thus demonstrating how the recombination thresholds can be overcome. Extending beyond the typical sensitization concept, we add a highly ordered polymer that, in addition to enhanced absorption, overcomes limits predicted by classical recombination models. An effective charge transfer from the disordered host system onto the highly ordered sensitizer effectively avoids traps of the host matrix and features an almost ideal recombination behaviour.

Sensitivity of Dielectric Properties to Wear Process on Carbon Nanofiber/High-Density Polyethylene Composites.

PubMed

Liu, Tian; Wood, Weston; Zhong, Wei-Hong

2011-12-01

We examined the correlation of wear effects with dielectric properties of carbon nanofibers (CNFs; untreated and organosilane-treated)-reinforced high-density polyethylene (HDPE) composites. Wear testing for the nanocomposites over up to 120 h was carried out, and then, dielectric permittivity and dielectric loss factor of the polymer composites with the increased wear time were studied. Scanning electron microscope and optical microscope observations were made to analyze the microstructure features of the nanocomposites. The results reveal that there exist approximate linear relationships of permittivity with wear coefficient for the nanocomposites. Composites containing silanized CNFs with the sufficiently thick coating exhibited high wear resistance. The change in permittivity was more sensitive to the increased wear coefficient for the nanocomposites with lower wear resistance. This work provides potential for further research on the application of dielectric signals to detect the effects of wear process on lifetime of polymeric materials.

National and International Security Applications of Cryogenic Detectors—Mostly Nuclear Safeguards

NASA Astrophysics Data System (ADS)

Rabin, Michael W.

2009-12-01

As with science, so with security—in both arenas, the extraordinary sensitivity of cryogenic sensors enables high-confidence detection and high-precision measurement even of the faintest signals. Science applications are more mature, but several national and international security applications have been identified where cryogenic detectors have high potential payoff. International safeguards and nuclear forensics are areas needing new technology and methods to boost speed, sensitivity, precision and accuracy. Successfully applied, improved nuclear materials analysis will help constrain nuclear materials diversion pathways and contribute to treaty verification. Cryogenic microcalorimeter detectors for X-ray, gamma-ray, neutron, and alpha-particle spectrometry are under development with these aims in mind. In each case the unsurpassed energy resolution of microcalorimeters reveals previously invisible spectral features of nuclear materials. Preliminary results of quantitative analysis indicate substantial improvements are still possible, but significant work will be required to fully understand the ultimate performance limits.

Development of a sensitive setup for laser spectroscopy studies of very exotic calcium isotopes

NASA Astrophysics Data System (ADS)

Garcia Ruiz, R. F.; Gorges, C.; Bissell, M.; Blaum, K.; Gins, W.; Heylen, H.; Koenig, K.; Kaufmann, S.; Kowalska, M.; Krämer, J.; Lievens, P.; Malbrunot-Ettenauer, S.; Neugart, R.; Neyens, G.; Nörtershäuser, W.; Yordanov, D. T.; Yang, X. F.

2017-04-01

An experimental setup for sensitive high-resolution measurements of hyperfine structure spectra of exotic calcium isotopes has been developed and commissioned at the COLLAPS beam line at ISOLDE, CERN. The technique is based on the radioactive detection of decaying isotopes after optical pumping and state selective neutralization (ROC) (Vermeeren et al 1992 Phys. Rev. Lett. 68 1679). The improvements and developments necessary to extend the applicability of the experimental technique to calcium isotopes produced at rates as low as few ions s-1 are discussed. Numerical calculations of laser-ion interaction and ion-beam simulations were explored to obtain the optimum performance of the experimental setup. Among the implemented features are a multi-step optical pumping region for sensitive measurements of isotopes with hyperfine splitting, a high-voltage platform for adequate control of low-energy ion beams and simultaneous β-detection of neutralized and remaining ions. The commissioning of the experimental setup, and the first online results on neutron-rich calcium isotopes are presented.

TL and EPR studies of Cu, Ag and P doped Li2B4O7 phosphor

NASA Astrophysics Data System (ADS)

Can, N.; Karali, T.; Townsend, P. D.; Yildiz, F.

2006-05-01

Key characteristics of a newly prepared tissue-equivalent, highly sensitive thermoluminescence dosimeter, Li2B4O7:Cu,Ag,P, are presented. The material was developed at the Institute of Nuclear Sciences, Belgrade, in the form of sintered pellets. A new preparation procedure has greatly increased the sensitivity of the basic copper activated lithium borate and the glow curve of Li2B4O7 : Cu,Ag,P consists of a well-defined main dosimetric peak situated at about 460-465 K with a sensitivity which is about four to five times higher than that of LiF : Mg,Ti (TLD-100). The exceptionally good response features of Li2B4O7 : Cu,Ag,P are attributed to the incorporation of Cu as a dopant. Both low and high temperature emission spectra are presented and the origins of the various emission bands are considered. Additional data are provided from electron paramagnetic resonance measurements.

Quantum metrology with a single spin-3/2 defect in silicon carbide

NASA Astrophysics Data System (ADS)

Soykal, Oney O.; Reinecke, Thomas L.

We show that implementations for quantum sensing with exceptional sensitivity and spatial resolution can be made using the novel features of semiconductor high half-spin multiplet defects with easy-to-implement optical detection protocols. To achieve this, we use the spin- 3 / 2 silicon monovacancy deep center in hexagonal silicon carbide based on our rigorous derivation of this defect's ground state and of its electronic and optical properties. For a single VSi- defect, we obtain magnetic field sensitivities capable of detecting individual nuclear magnetic moments. We also show that its zero-field splitting has an exceptional strain and temperature sensitivity within the technologically desirable near-infrared window of biological systems. Other point defects, i.e. 3d transition metal or rare-earth impurities in semiconductors, may also provide similar opportunities in quantum sensing due to their similar high spin (S >= 3 / 2) configurations. This work was supported in part by ONR and by the Office of Secretary of Defense, Quantum Science and Engineering Program.

Precision muon physics

NASA Astrophysics Data System (ADS)

Gorringe, T. P.; Hertzog, D. W.

2015-09-01

The muon is playing a unique role in sub-atomic physics. Studies of muon decay both determine the overall strength and establish the chiral structure of weak interactions, as well as setting extraordinary limits on charged-lepton-flavor-violating processes. Measurements of the muon's anomalous magnetic moment offer singular sensitivity to the completeness of the standard model and the predictions of many speculative theories. Spectroscopy of muonium and muonic atoms gives unmatched determinations of fundamental quantities including the magnetic moment ratio μμ /μp, lepton mass ratio mμ /me, and proton charge radius rp. Also, muon capture experiments are exploring elusive features of weak interactions involving nucleons and nuclei. We will review the experimental landscape of contemporary high-precision and high-sensitivity experiments with muons. One focus is the novel methods and ingenious techniques that achieve such precision and sensitivity in recent, present, and planned experiments. Another focus is the uncommonly broad and topical range of questions in atomic, nuclear and particle physics that such experiments explore.

Dye-sensitized solar cells for efficient power generation under ambient lighting

NASA Astrophysics Data System (ADS)

Freitag, Marina; Teuscher, Joël; Saygili, Yasemin; Zhang, Xiaoyu; Giordano, Fabrizio; Liska, Paul; Hua, Jianli; Zakeeruddin, Shaik M.; Moser, Jacques-E.; Grätzel, Michael; Hagfeldt, Anders

2017-06-01

Solar cells that operate efficiently under indoor lighting are of great practical interest as they can serve as electric power sources for portable electronics and devices for wireless sensor networks or the Internet of Things. Here, we demonstrate a dye-sensitized solar cell (DSC) that achieves very high power-conversion efficiencies (PCEs) under ambient light conditions. Our photosystem combines two judiciously designed sensitizers, coded D35 and XY1, with the copper complex Cu(II/I)(tmby) as a redox shuttle (tmby, 4,4‧,6,6‧-tetramethyl-2,2‧-bipyridine), and features a high open-circuit photovoltage of 1.1 V. The DSC achieves an external quantum efficiency for photocurrent generation that exceeds 90% across the whole visible domain from 400 to 650 nm, and achieves power outputs of 15.6 and 88.5 μW cm-2 at 200 and 1,000 lux, respectively, under illumination from a model Osram 930 warm-white fluorescent light tube. This translates into a PCE of 28.9%.

Classification of ground glass opacity lesion characteristic based on texture feature using lung CT image

NASA Astrophysics Data System (ADS)

Sebatubun, M. M.; Haryawan, C.; Windarta, B.

2018-03-01

Lung cancer causes a high mortality rate in the world than any other cancers. That can be minimised if the symptoms and cancer cells have been detected early. One of the techniques used to detect lung cancer is by computed tomography (CT) scan. CT scan images have been used in this study to identify one of the lesion characteristics named ground glass opacity (GGO). It has been used to determine the level of malignancy of the lesion. There were three phases in identifying GGO: image cropping, feature extraction using grey level co-occurrence matrices (GLCM) and classification using Naïve Bayes Classifier. In order to improve the classification results, the most significant feature was sought by feature selection using gain ratio evaluation. Based on the results obtained, the most significant features could be identified by using feature selection method used in this research. The accuracy rate increased from 83.33% to 91.67%, the sensitivity from 82.35% to 94.11% and the specificity from 84.21% to 89.47%.

Differentiating risk for mania and borderline personality disorder: The nature of goal regulation and impulsivity.

PubMed

Fulford, Daniel; Eisner, Lori R; Johnson, Sheri L

2015-06-30

Researchers and clinicians have long noted the overlap among features and high comorbidity of bipolar disorder and borderline personality disorder. The shared features of impulsivity and labile mood in both disorders make them challenging to distinguish. We tested the hypothesis that variables related to goal dysregulation would be uniquely related to risk for mania, while emotion-relevant impulsivity would be related to risk for both disorders. We administered a broad range of measures related to goal regulation traits and impulsivity to 214 undergraduates. Findings confirmed that risk for mania, but not for borderline personality disorder, was related to higher sensitivity to reward and intense pursuit of goals. In contrast, borderline personality disorder symptoms related more strongly than did mania risk with threat sensitivity and with impulsivity in the context of negative affect. Results highlight potential differences and commonalities in mania risk versus borderline personality disorder risk. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Use of geographic information systems for applications on gas pipeline rights-of-way

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

Sydelko, P.J.; Wilkey, P.L.

1992-12-01

Geographic information system (GIS) applications for the siting and monitoring of gas pipeline rights-of-way (ROWS) were developed for areas near Rio Vista, California. The data layers developed for this project represent geographic features, such as landcover, elevation, aspect, slope, soils, hydrography, transportation, endangered species, wetlands, and public line surveys. A GIS was used to develop and store spatial data from several sources; to manipulate spatial data to evaluate environmental and engineering issues associated with the siting, permitting, construction, maintenance, and monitoring of gas pipeline ROWS; and to graphically display analysis results. Examples of these applications include (1) determination of environmentallymore » sensitive areas, such as endangered species habitat, wetlands, and areas of highly erosive soils; (2) evaluation of engineering constraints, including shallow depth to bedrock, major hydrographic features, and shallow water table; (3) classification of satellite imagery for landuse/landcover that will affect ROWS; and (4) identification of alternative ROW corridors that avoid environmentally sensitive areas or areas with severe engineering constraints.« less

GIS least-cost analysis approach for siting gas pipeline ROWs

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

Sydelko, P.J.; Wilkey, P.L.

1994-09-01

Geographic-information-system applications for the siting and monitoring of gas pipeline rights-of-way (ROWS) were developed for areas near Rio Vista, California. The data layers developed for this project represent geographic features, such as landcover, elevation, aspect, slope, soils, hydrography, transportation corridors, endangered species habitats, wetlands, and public line surveys. A geographic information system was used to develop and store spatial data from several sources; to manipulate spatial data to evaluate environmental and engineering issues associated with the siting, permitting, construction, maintenance, and monitoring of gas-pipeline ROWS; and to graphically display analysis results. Examples of these applications include (1) determination of environmentallymore » sensitive areas, such as endangered species habitat, wetlands, and areas of highly erosive soils; (2) evaluation of engineering constraints, including shallow depth to bedrock, major hydrographic features, and shallow water table; (3) classification of satellite imagery for landuse/landcover that will affect ROWS; and (4) identification of alternative ROW corridors that avoid environmentally sensitive areas or areas with severe engineering constraints.« less

Use of geographic information systems for applications on gas pipeline rights-of-way

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

Sydelko, P.J.

1993-10-01

Geographic information system (GIS) applications for the siting and monitoring of gas pipeline rights-of-way (ROWS) were developed for areas near Rio Vista, California. The data layers developed for this project represent geographic features, such as landcover, elevation, aspect, slope, soils, hydrography, transportation, endangered species, wetlands, and public line surveys. A GIS was used to develop and store spatial data from several sources; to manipulate spatial data to evaluate environmental and engineering issues associated with the siting, permitting, construction, maintenance, and monitoring of gas pipeline ROWS; and to graphically display analysis results. Examples of these applications include (1) determination of environmentallymore » sensitive areas, such as endangered species habitat, wetlands, and areas of highly erosive soils; (2) evaluation of engineering constraints, including shallow depth to bedrock, major hydrographic features, and shallow water table; (3) classification of satellite imagery for land use/landcover that will affect ROWS; and (4) identification of alternative ROW corridors that avoid environmentally sensitive areas or areas with severe engineering constraints.« less

Use of geographic information systems for applications on gas pipeline rights-of-way

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

Sydelko, P.J.; Wilkey, P.L.

1992-01-01

Geographic information system (GIS) applications for the siting and monitoring of gas pipeline rights-of-way (ROWS) were developed for areas near Rio Vista, California. The data layers developed for this project represent geographic features, such as landcover, elevation, aspect, slope, soils, hydrography, transportation, endangered species, wetlands, and public line surveys. A GIS was used to develop and store spatial data from several sources; to manipulate spatial data to evaluate environmental and engineering issues associated with the siting, permitting, construction, maintenance, and monitoring of gas pipeline ROWS; and to graphically display analysis results. Examples of these applications include (1) determination of environmentallymore » sensitive areas, such as endangered species habitat, wetlands, and areas of highly erosive soils; (2) evaluation of engineering constraints, including shallow depth to bedrock, major hydrographic features, and shallow water table; (3) classification of satellite imagery for landuse/landcover that will affect ROWS; and (4) identification of alternative ROW corridors that avoid environmentally sensitive areas or areas with severe engineering constraints.« less

Non-invasive Glucose Measurements Using Wavelength Modulated Differential Photothermal Radiometry (WM-DPTR)

NASA Astrophysics Data System (ADS)

Guo, X.; Mandelis, A.; Zinman, B.

2012-11-01

Wavelength-modulated differential laser photothermal radiometry (WM-DPTR) is introduced for potential development of clinically viable non-invasive glucose biosensors. WM-DPTR features unprecedented glucose-specificity and sensitivity by combining laser excitation by two out-of-phase modulated beams at wavelengths near the peak and the baseline of a prominent and isolated mid-IR glucose absorption band. Measurements on water-glucose phantoms (0 to 300 mg/dl glucose concentration) demonstrate high sensitivity to meet wide clinical detection requirements ranging from hypoglycemia to hyperglycemia. The measurement results have been validated by simulations based on fully developed WM-DPTR theory. For sensitive and accurate glucose measurements, the key is the selection and tight control of the intensity ratio and the phase shift of the two laser beams.

Dynamic Compression of the Signal in a Charge Sensitive Amplifier: From Concept to Design

NASA Astrophysics Data System (ADS)

Manghisoni, Massimo; Comotti, Daniele; Gaioni, Luigi; Ratti, Lodovico; Re, Valerio

2015-10-01

This work is concerned with the design of a low-noise Charge Sensitive Amplifier featuring a dynamic signal compression based on the non-linear features of an inversion-mode MOS capacitor. These features make the device suitable for applications where a non-linear characteristic of the front-end is required, such as in imaging instrumentation for free electron laser experiments. The aim of the paper is to discuss a methodology for the proper design of the feedback network enabling the dynamic signal compression. Starting from this compression solution, the design of a low-noise Charge Sensitive Amplifier is also discussed. The study has been carried out by referring to a 65 nm CMOS technology.

Engineering topological superconductors using surface atomic-layer/molecule hybrid materials

NASA Astrophysics Data System (ADS)

Uchihashi, Takashi

2015-08-01

Surface atomic-layer (SAL) superconductors consisting of epitaxially grown metal adatoms on a clean semiconductor surface have been recently established. Compared to conventional metal thin films, they have two important features: (i) space-inversion symmetry-breaking throughout the system and (ii) high sensitivity to surface adsorption of foreign species. These potentially lead to manifestation of the Rashba effect and a Zeeman field exerted by adsorbed magnetic organic molecules. After introduction of the archetypical SAL superconductor Si(111)-(√7 × √3)-In, we describe how these features are utilized to engineer a topological superconductor with Majorana fermions and discuss its promises and expected challenges.

Recurrence predictive models for patients with hepatocellular carcinoma after radiofrequency ablation using support vector machines with feature selection methods.

PubMed

Liang, Ja-Der; Ping, Xiao-Ou; Tseng, Yi-Ju; Huang, Guan-Tarn; Lai, Feipei; Yang, Pei-Ming

2014-12-01

Recurrence of hepatocellular carcinoma (HCC) is an important issue despite effective treatments with tumor eradication. Identification of patients who are at high risk for recurrence may provide more efficacious screening and detection of tumor recurrence. The aim of this study was to develop recurrence predictive models for HCC patients who received radiofrequency ablation (RFA) treatment. From January 2007 to December 2009, 83 newly diagnosed HCC patients receiving RFA as their first treatment were enrolled. Five feature selection methods including genetic algorithm (GA), simulated annealing (SA) algorithm, random forests (RF) and hybrid methods (GA+RF and SA+RF) were utilized for selecting an important subset of features from a total of 16 clinical features. These feature selection methods were combined with support vector machine (SVM) for developing predictive models with better performance. Five-fold cross-validation was used to train and test SVM models. The developed SVM-based predictive models with hybrid feature selection methods and 5-fold cross-validation had averages of the sensitivity, specificity, accuracy, positive predictive value, negative predictive value, and area under the ROC curve as 67%, 86%, 82%, 69%, 90%, and 0.69, respectively. The SVM derived predictive model can provide suggestive high-risk recurrent patients, who should be closely followed up after complete RFA treatment. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Highly sensitive catalytic spectrophotometric determination of ruthenium

NASA Astrophysics Data System (ADS)

Naik, Radhey M.; Srivastava, Abhishek; Prasad, Surendra

2008-01-01

A new and highly sensitive catalytic kinetic method (CKM) for the determination of ruthenium(III) has been established based on its catalytic effect on the oxidation of L-phenylalanine ( L-Pheala) by KMnO 4 in highly alkaline medium. The reaction has been followed spectrophotometrically by measuring the decrease in the absorbance at 526 nm. The proposed CKM is based on the fixed time procedure under optimum reaction conditions. It relies on the linear relationship where the change in the absorbance (Δ At) versus added Ru(III) amounts in the range of 0.101-2.526 ng ml -1 is plotted. Under the optimum conditions, the sensitivity of the proposed method, i.e. the limit of detection corresponding to 5 min is 0.08 ng ml -1, and decreases with increased time of analysis. The method is featured with good accuracy and reproducibility for ruthenium(III) determination. The ruthenium(III) has also been determined in presence of several interfering and non-interfering cations, anions and polyaminocarboxylates. No foreign ions interfered in the determination ruthenium(III) up to 20-fold higher concentration of foreign ions. In addition to standard solutions analysis, this method was successfully applied for the quantitative determination of ruthenium(III) in drinking water samples. The method is highly sensitive, selective and very stable. A review of recently published catalytic spectrophotometric methods for the determination of ruthenium(III) has also been presented for comparison.

Friction Stir Weld Inspection Through Conductivity Imaging Using Shaped Field MWM(Registered Trademark) - Arrays

NASA Technical Reports Server (NTRS)

Goldfine, Neil; Grundy, David; Zilberstein, Vladimir; Kinchen, David G.; McCool, Alex (Technical Monitor)

2002-01-01

Friction Stir Welds (FSW) of Al 2195-T8 and Al 2219-T8, provided by Lockheed Martin Michoud Operations, were inspected for lack-of-penetration (LOP) defects using a custom designed MWM-Array, a multi-element eddy-current sensor. MWM (registered trademark) electrical conductivity mapping demonstrated high sensitivity to LOP as small as 0.75 mm (0.03 in.), as confirmed by metallographic data that characterized the extent of LOP defects. High sensitivity and high spatial resolution was achieved via a 37-element custom designed MWM-Array allowing LOP detection using the normalized longitudinal component of the MWM measured conductivity. This permitted both LOP detection and correlation of MWM conductivity features with the LOP defect size, as changes in conductivity were apparently associated with metallurgical features within the near-surface layer of the LOP defect zone. MWM conductivity mapping reveals information similar to macro-etching as the MWM-Array is sensitive to small changes in conductivity due to changes in microstructure associated with material thermal processing, in this case welding. The electrical conductivity measured on the root side of FSWs varies across the weld due to microstructural differences introduced by the FSW process, as well as those caused by planar flaws. Weld metal, i.e., dynamically recrystallized zone (DXZ), thermomechanically affected zone (TMZ), heat-affected zone (HAZ), and parent metal (PM) are all evident in the conductivity maps. While prior efforts had met with limited success for NDE (Nondestructive Evaluation) of dissimilar alloy, Al2219 to Al2195 FSW, the new custom designed multi-element MWM-Array achieved detection of all LOP defects even in dissimilar metal welds.

Articular cartilage degeneration classification by means of high-frequency ultrasound.

PubMed

Männicke, N; Schöne, M; Oelze, M; Raum, K

2014-10-01

To date only single ultrasound parameters were regarded in statistical analyses to characterize osteoarthritic changes in articular cartilage and the potential benefit of using parameter combinations for characterization remains unclear. Therefore, the aim of this work was to utilize feature selection and classification of a Mankin subset score (i.e., cartilage surface and cell sub-scores) using ultrasound-based parameter pairs and investigate both classification accuracy and the sensitivity towards different degeneration stages. 40 punch biopsies of human cartilage were previously scanned ex vivo with a 40-MHz transducer. Ultrasound-based surface parameters, as well as backscatter and envelope statistics parameters were available. Logistic regression was performed with each unique US parameter pair as predictor and different degeneration stages as response variables. The best ultrasound-based parameter pair for each Mankin subset score value was assessed by highest classification accuracy and utilized in receiver operating characteristics (ROC) analysis. The classifications discriminating between early degenerations yielded area under the ROC curve (AUC) values of 0.94-0.99 (mean ± SD: 0.97 ± 0.03). In contrast, classifications among higher Mankin subset scores resulted in lower AUC values: 0.75-0.91 (mean ± SD: 0.84 ± 0.08). Variable sensitivities of the different ultrasound features were observed with respect to different degeneration stages. Our results strongly suggest that combinations of high-frequency ultrasound-based parameters exhibit potential to characterize different, particularly very early, degeneration stages of hyaline cartilage. Variable sensitivities towards different degeneration stages suggest that a concurrent estimation of multiple ultrasound-based parameters is diagnostically valuable. In-vivo application of the present findings is conceivable in both minimally invasive arthroscopic ultrasound and high-frequency transcutaneous ultrasound. Copyright © 2014 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

Sensor for Monitoring Nanodevice-Fabrication Plasmas

NASA Technical Reports Server (NTRS)

Bolshakov, Alexander

2004-01-01

The term plasma process diagnostics (PPD) refers to a spectroscopic technique and sensing hardware that have been proposed for monitoring plasma processes used to fabricate electronic devices that feature sizes as small as several nanometers. Nanometer dimensions are characteristic of the quantum level of miniaturization, where single impurity atoms or molecules can drastically change the local properties of the nanostructures. Such changes may be purposely used in nanoscale design but may also be extremely damaging or cause improper operation of the fabricated devices. Determination of temperature and densities of reactants near the developing features is important, since the structural synthesis is affected by characteristics of the local microenvironment. Consequently, sensors capable of nonintrusive monitoring with high sensitivity and high resolution are essential for real-time atomistic control of reaction kinetics and minimizing trace contamination in plasma processes used to fabricate electronic nanodevices. Such process-monitoring sensors are required to be compact, multiparametric, and immune to the harsh environments of processing plasmas. PPD is intended to satisfy these requirements. The specific technique used to implement plasma diagnostics with a PPD sensor would be an advanced version of continuous-wave cavity-ringdown spectroscopy (CW-CRDS) capable of profiling spectral line broadenings in order to derive both Doppler and Stark components. CRDS is based on measurements of the rate of absorption of laser light in an optical resonator. The ultimate sensitivity results from a very long absorption path length within the cavity and immunity to variations in incident laser intensity. The proposed version of this technique would involve the use of multiplexing tunable laser diodes and an actively modulated high-reflectivity optical resonator, thus offering a synergistic combination of simplicity, compactness, high sensitivity, and high resolution. The multiplexing capabilities of diode lasers could be utilized to make the PPD sensor a single, simple, compact, and inexpensive tool for the acquisition of multiparametric data. A PPD sensor would be capable of continuous measurement of such physical parameters as gas temperature, gas velocity, electron number density, and absolute densities of reacting chemical species. A laser beam can be easily adjusted to analyze the immediate vicinity of the growing nanostructures (or features etched down) in real time. The absorption enhancement in an optical cavity would afford the sensitivity needed for measurement of the temperature and densities of species at concentrations significantly lower than measurable by other nonintrusive techniques. It is anticipated that fully developed PPD sensors would enable simultaneous measurement of local temperature and determination of plasma species responsible for the synthesis and functionalization of nanodevices. These sensors would also enable tracking the pathways and origins of damaging contaminants, thereby providing feedback for adjustment of processes to optimize them and reduce contamination. The PPD sensors should also be useful for optimization of conventional microelectronics manufacturing plasma processes. Going beyond plasma processes for fabrication of electronic devices, PPD sensors could be used for monitoring of atoms, molecules, ions, radicals, clusters, and particles in a variety of other settings, including outer space. Because of their high sensitivity, such sensors could also prove useful for detecting traces of illegal drugs and explosives.

Inhibition of the spider heartbeat by gravity and vibration

NASA Technical Reports Server (NTRS)

Finck, A.

1984-01-01

The rate and vigor of the spider heartbeat is controlled by an external pacemaker. A mechanical feature of the spider cardio-vascular system is the production of high serum pressure in the prosoma and the legs. This appears to be the source for leg extension. The lyriform organ on the patella of the leg is sensitive to vibratory and kinesthetic stimuli. This sensitivity depends upon the degree of leg extension. Thus the activity of the heart and the response characteristics of the sense receptor are related. The effect of a supra-threshold vibratory or gravitational stimulus is to produce an inhibition and a tachycardia of the spider heartbeat.

Rapid Diagnosis of Tuberculosis from Analysis of Urine Volatile Organic Compounds

PubMed Central

Lim, Sung H.; Martino, Raymond; Anikst, Victoria; Xu, Zeyu; Mix, Samantha; Benjamin, Robert; Schub, Herbert; Eiden, Michael; Rhodes, Paul A.; Banaei, Niaz

2017-01-01

The World Health Organization has called for simple, sensitive, and non-sputum diagnostics for tuberculosis. We report development of a urine tuberculosis test using a colorimetric sensor array (CSA). The sensor comprised of 73 different indicators captures high-dimensional, spatiotemporal signatures of volatile chemicals emitted by human urine samples. The sensor responses to 63 urine samples collected from 22 tuberculosis cases and 41 symptomatic controls were measured under five different urine test conditions. Basified testing condition yielded the best accuracy with 85.5% sensitivity and 79.5% specificity. The CSA urine assay offers desired features needed for tuberculosis diagnosis in endemic settings. PMID:29057329

Non-volatile analysis in fruits by laser resonant ionization spectrometry: application to resveratrol (3,5,4'-trihydroxystilbene) in grapes

NASA Astrophysics Data System (ADS)

Montero, C.; Orea, J. M.; Soledad Muñoz, M.; Lobo, R. F. M.; González Ureña, A.

A laser desorption (LD) coupled with resonance-enhanced multiphoton ionisation (REMPI) and time-of-flight mass spectrometry (TOFMS) technique for non-volatile trace analysis compounds is presented. Essential features are: (a) an enhanced desorption yield due to the mixing of metal powder with the analyte in the sample preparation, (b) a high resolution, great sensitivity and low detection limit due to laser resonant ionisation and mass spectrometry detection. Application to resveratrol content in grapes demonstrated the capability of the analytical method with a sensitivity of 0.2 pg per single laser shot and a detection limit of 5 ppb.

Cover of tall trees best predicts California spotted owl habitat

Treesearch

Malcolm P. North; Jonathan T. Kane; Van R. Kane; Gregory P. Asner; William Berigan; Derek J. Churchill; Scott Conway; R.J. Gutiérrez; Sean Jeronimo; John Keane; Alexander Koltunov; Tina Mark; Monika Moskal; Thomas Munton; Zachary Peery; Carlos Ramirez; Rahel Sollmann; Angela White; Sheila Whitmore

2017-01-01

Restoration of western dry forests in the USA often focuses on reducing fuel loads. In the range of the spotted owl, these treatments may reduce canopy cover and tree density, which could reduce preferred habitat conditions for the owl and other sensitive species. In particular, high canopy cover (≥70%) has been widely reported to be an important feature of spotted owl...

Vaccine adverse event text mining system for extracting features from vaccine safety reports.

PubMed

Botsis, Taxiarchis; Buttolph, Thomas; Nguyen, Michael D; Winiecki, Scott; Woo, Emily Jane; Ball, Robert

2012-01-01

To develop and evaluate a text mining system for extracting key clinical features from vaccine adverse event reporting system (VAERS) narratives to aid in the automated review of adverse event reports. Based upon clinical significance to VAERS reviewing physicians, we defined the primary (diagnosis and cause of death) and secondary features (eg, symptoms) for extraction. We built a novel vaccine adverse event text mining (VaeTM) system based on a semantic text mining strategy. The performance of VaeTM was evaluated using a total of 300 VAERS reports in three sequential evaluations of 100 reports each. Moreover, we evaluated the VaeTM contribution to case classification; an information retrieval-based approach was used for the identification of anaphylaxis cases in a set of reports and was compared with two other methods: a dedicated text classifier and an online tool. The performance metrics of VaeTM were text mining metrics: recall, precision and F-measure. We also conducted a qualitative difference analysis and calculated sensitivity and specificity for classification of anaphylaxis cases based on the above three approaches. VaeTM performed best in extracting diagnosis, second level diagnosis, drug, vaccine, and lot number features (lenient F-measure in the third evaluation: 0.897, 0.817, 0.858, 0.874, and 0.914, respectively). In terms of case classification, high sensitivity was achieved (83.1%); this was equal and better compared to the text classifier (83.1%) and the online tool (40.7%), respectively. Our VaeTM implementation of a semantic text mining strategy shows promise in providing accurate and efficient extraction of key features from VAERS narratives.

Sensitivities of ionic explosives

NASA Astrophysics Data System (ADS)

Politzer, Peter; Lane, Pat; Murray, Jane S.

2017-03-01

We have investigated the relevance for ionic explosive sensitivity of three factors that have been demonstrated to be related to the sensitivities of molecular explosives. These are (1) the maximum available heat of detonation, (2) the amount of free space per molecule (or per formula unit) in the crystal lattice and (3) specific features of the electrostatic potential on the molecular or ionic surface. We find that for ionic explosives, just as for molecular ones, there is an overall tendency for impact sensitivity to increase as the maximum detonation heat release is greater. This means that the usual emphasis upon designing explosives with large heats of detonation needs to be tempered somewhat. We also show that a moderate detonation heat release does not preclude a high level of detonation performance for ionic explosives, as was already demonstrated for molecular ones. Relating the free space per formula unit to sensitivity may require a modified procedure for ionic explosives; this will continue to be investigated. Finally, an encouraging start has been made in linking impact sensitivities to the electrostatic potentials on ionic surfaces, although limited so far to ammonium salts.

Detecting bursts in the EEG of very and extremely premature infants using a multi-feature approach.

PubMed

O'Toole, John M; Boylan, Geraldine B; Lloyd, Rhodri O; Goulding, Robert M; Vanhatalo, Sampsa; Stevenson, Nathan J

2017-07-01

To develop a method that segments preterm EEG into bursts and inter-bursts by extracting and combining multiple EEG features. Two EEG experts annotated bursts in individual EEG channels for 36 preterm infants with gestational age < 30 weeks. The feature set included spectral, amplitude, and frequency-weighted energy features. Using a consensus annotation, feature selection removed redundant features and a support vector machine combined features. Area under the receiver operator characteristic (AUC) and Cohen's kappa (κ) evaluated performance within a cross-validation procedure. The proposed channel-independent method improves AUC by 4-5% over existing methods (p < 0.001, n=36), with median (95% confidence interval) AUC of 0.989 (0.973-0.997) and sensitivity-specificity of 95.8-94.4%. Agreement rates between the detector and experts' annotations, κ=0.72 (0.36-0.83) and κ=0.65 (0.32-0.81), are comparable to inter-rater agreement, κ=0.60 (0.21-0.74). Automating the visual identification of bursts in preterm EEG is achievable with a high level of accuracy. Multiple features, combined using a data-driven approach, improves on existing single-feature methods. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

An Evaluation of ALOS Data in Disaster Applications

NASA Astrophysics Data System (ADS)

Igarashi, Tamotsu; Igarashi, Tamotsu; Furuta, Ryoich; Ono, Makoto

ALOS is the advanced land observing satellite, providing image data from onboard sensors; PRISM, AVNIR-2 and PALSAR. PRISM is the sensor of panchromatic stereo, high resolution three-line-scanner to characterize the earth surface. The accuracy of position in image and height of Digital Surface Model (DSM) are high, therefore the geographic information extraction is improved in the field of disaster applications with providing images of disaster area. Especially pan-sharpened 3D image composed with PRISM and the four-band visible near-infrared radiometer AVNIR-2 data is expected to provide information to understand the geographic and topographic feature. PALSAR is the advanced multi-functional synthetic aperture radar (SAR) operated in L-band, appropriate for the use of land surface feature characterization. PALSAR has many improvements from JERS-1/SAR, such as high sensitivity, having high resolution, polarimetric and scan SAR observation modes. PALSAR is also applicable for SAR interferometry processing. This paper describes the evaluation of ALOS data characteristic from the view point of disaster applications, through some exercise applications.

Deep Learning in Label-free Cell Classification

PubMed Central

Chen, Claire Lifan; Mahjoubfar, Ata; Tai, Li-Chia; Blaby, Ian K.; Huang, Allen; Niazi, Kayvan Reza; Jalali, Bahram

2016-01-01

Label-free cell analysis is essential to personalized genomics, cancer diagnostics, and drug development as it avoids adverse effects of staining reagents on cellular viability and cell signaling. However, currently available label-free cell assays mostly rely only on a single feature and lack sufficient differentiation. Also, the sample size analyzed by these assays is limited due to their low throughput. Here, we integrate feature extraction and deep learning with high-throughput quantitative imaging enabled by photonic time stretch, achieving record high accuracy in label-free cell classification. Our system captures quantitative optical phase and intensity images and extracts multiple biophysical features of individual cells. These biophysical measurements form a hyperdimensional feature space in which supervised learning is performed for cell classification. We compare various learning algorithms including artificial neural network, support vector machine, logistic regression, and a novel deep learning pipeline, which adopts global optimization of receiver operating characteristics. As a validation of the enhanced sensitivity and specificity of our system, we show classification of white blood T-cells against colon cancer cells, as well as lipid accumulating algal strains for biofuel production. This system opens up a new path to data-driven phenotypic diagnosis and better understanding of the heterogeneous gene expressions in cells. PMID:26975219

Deep Learning in Label-free Cell Classification

NASA Astrophysics Data System (ADS)

Chen, Claire Lifan; Mahjoubfar, Ata; Tai, Li-Chia; Blaby, Ian K.; Huang, Allen; Niazi, Kayvan Reza; Jalali, Bahram

2016-03-01

Label-free cell analysis is essential to personalized genomics, cancer diagnostics, and drug development as it avoids adverse effects of staining reagents on cellular viability and cell signaling. However, currently available label-free cell assays mostly rely only on a single feature and lack sufficient differentiation. Also, the sample size analyzed by these assays is limited due to their low throughput. Here, we integrate feature extraction and deep learning with high-throughput quantitative imaging enabled by photonic time stretch, achieving record high accuracy in label-free cell classification. Our system captures quantitative optical phase and intensity images and extracts multiple biophysical features of individual cells. These biophysical measurements form a hyperdimensional feature space in which supervised learning is performed for cell classification. We compare various learning algorithms including artificial neural network, support vector machine, logistic regression, and a novel deep learning pipeline, which adopts global optimization of receiver operating characteristics. As a validation of the enhanced sensitivity and specificity of our system, we show classification of white blood T-cells against colon cancer cells, as well as lipid accumulating algal strains for biofuel production. This system opens up a new path to data-driven phenotypic diagnosis and better understanding of the heterogeneous gene expressions in cells.

Control-group feature normalization for multivariate pattern analysis of structural MRI data using the support vector machine.

PubMed

Linn, Kristin A; Gaonkar, Bilwaj; Satterthwaite, Theodore D; Doshi, Jimit; Davatzikos, Christos; Shinohara, Russell T

2016-05-15

Normalization of feature vector values is a common practice in machine learning. Generally, each feature value is standardized to the unit hypercube or by normalizing to zero mean and unit variance. Classification decisions based on support vector machines (SVMs) or by other methods are sensitive to the specific normalization used on the features. In the context of multivariate pattern analysis using neuroimaging data, standardization effectively up- and down-weights features based on their individual variability. Since the standard approach uses the entire data set to guide the normalization, it utilizes the total variability of these features. This total variation is inevitably dependent on the amount of marginal separation between groups. Thus, such a normalization may attenuate the separability of the data in high dimensional space. In this work we propose an alternate approach that uses an estimate of the control-group standard deviation to normalize features before training. We study our proposed approach in the context of group classification using structural MRI data. We show that control-based normalization leads to better reproducibility of estimated multivariate disease patterns and improves the classifier performance in many cases. Copyright © 2016 Elsevier Inc. All rights reserved.

The Solar Flare 4: 10 keV X-ray Spectrum

NASA Technical Reports Server (NTRS)

Phillips, K. J. H.

2004-01-01

The 4-10 keV solar flare spectrum includes highly excited lines of stripped Ca, Fe, and Ni ions as well as a continuum steeply falling with energy. Groups of lines at approximately 7 keV and approximately 8 keV, observed during flares by the broad-band RHESSI spectrometer and called here the Fe-line and Fe/Ni-line features, are formed mostly of Fe lines but with Ni lines contributing to the approximately 8 keV feature. Possible temperature indicators of these line features are discussed - the peak or centroid energies of the Fe-line feature, the line ratio of the Fe-line to the Fe/Ni-line features, and the equivalent width of the Fe-line feature. The equivalent width is by far the most sensitive to temperature. However, results will be confused if, as is commonly believed, the abundance of Fe varies from flare to flare, even during the course of a single flare. With temperature determined from the thermal continuum, the Fe-line feature becomes a diagnostic of the Fe abundance in flare plasmas. These results are of interest for other hot plasmas in coronal ionization equilibrium such as stellar flare plasmas, hot gas in galaxies, and older supernova remnants.

Computer aided diagnosis system for Alzheimer disease using brain diffusion tensor imaging features selected by Pearson's correlation.

PubMed

Graña, M; Termenon, M; Savio, A; Gonzalez-Pinto, A; Echeveste, J; Pérez, J M; Besga, A

2011-09-20

The aim of this paper is to obtain discriminant features from two scalar measures of Diffusion Tensor Imaging (DTI) data, Fractional Anisotropy (FA) and Mean Diffusivity (MD), and to train and test classifiers able to discriminate Alzheimer's Disease (AD) patients from controls on the basis of features extracted from the FA or MD volumes. In this study, support vector machine (SVM) classifier was trained and tested on FA and MD data. Feature selection is done computing the Pearson's correlation between FA or MD values at voxel site across subjects and the indicative variable specifying the subject class. Voxel sites with high absolute correlation are selected for feature extraction. Results are obtained over an on-going study in Hospital de Santiago Apostol collecting anatomical T1-weighted MRI volumes and DTI data from healthy control subjects and AD patients. FA features and a linear SVM classifier achieve perfect accuracy, sensitivity and specificity in several cross-validation studies, supporting the usefulness of DTI-derived features as an image-marker for AD and to the feasibility of building Computer Aided Diagnosis systems for AD based on them. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Context-specific effects of musical expertise on audiovisual integration

PubMed Central

Bishop, Laura; Goebl, Werner

2014-01-01

Ensemble musicians exchange auditory and visual signals that can facilitate interpersonal synchronization. Musical expertise improves how precisely auditory and visual signals are perceptually integrated and increases sensitivity to asynchrony between them. Whether expertise improves sensitivity to audiovisual asynchrony in all instrumental contexts or only in those using sound-producing gestures that are within an observer's own motor repertoire is unclear. This study tested the hypothesis that musicians are more sensitive to audiovisual asynchrony in performances featuring their own instrument than in performances featuring other instruments. Short clips were extracted from audio-video recordings of clarinet, piano, and violin performances and presented to highly-skilled clarinetists, pianists, and violinists. Clips either maintained the audiovisual synchrony present in the original recording or were modified so that the video led or lagged behind the audio. Participants indicated whether the audio and video channels in each clip were synchronized. The range of asynchronies most often endorsed as synchronized was assessed as a measure of participants' sensitivities to audiovisual asynchrony. A positive relationship was observed between musical training and sensitivity, with data pooled across stimuli. While participants across expertise groups detected asynchronies most readily in piano stimuli and least readily in violin stimuli, pianists showed significantly better performance for piano stimuli than for either clarinet or violin. These findings suggest that, to an extent, the effects of expertise on audiovisual integration can be instrument-specific; however, the nature of the sound-producing gestures that are observed has a substantial effect on how readily asynchrony is detected as well. PMID:25324819

Elevated hardness of peripheral gland on real-time elastography is an independent marker for high-risk prostate cancers.

PubMed

Zhang, Qi; Yao, Jing; Cai, Yehua; Zhang, Limin; Wu, Yishuo; Xiong, Jingyu; Shi, Jun; Wang, Yuanyuan; Wang, Yi

2017-12-01

To examine the role of quantitative real-time elastography (RTE) features on differentiation between high-risk prostate cancer (PCA) and non-high-risk prostatic diseases in the initial transperineal biopsy setting. We retrospectively included 103 patients with suspicious PCA who underwent both RTE and initial transperineal prostate biopsy. Patients were grouped into high-risk and non-high-risk categories according to the D'Amico's risk stratification. With computer assistance based on MATLAB programming, three features were extracted from RTE, i.e., the median hardness within peripheral gland (PG) (H med ), the ratio of the median hardness within PG to that outside PG (H ratio ), and the ratio of the hard area within PG to the total PG area (H ar ). A multiple regression model incorporating an RTE feature, age, transrectal ultrasound finding, and prostate volume was used to identify markers for high-risk PCA. Forty-seven patients (45.6%) were diagnosed with PCA and 34 (33.0%) were diagnosed with high-risk PCA. Three RTE features were all statistically higher in high-risk PCA than in non-high-risk diseases (p < 0.001), indicating that the PGs in high-risk PCA patients were harder than those in non-high-risk patients. A high H ratio , high age, and low prostate volume were found to be independent markers for PCAs (p < 0.05), among which the high H ratio was the only independent marker for high-risk PCAs (p = 0.012). When predicting high-risk PCAs, the multiple regression achieved an area under receiver operating characteristic curve of 0.755, sensitivity of 73.5%, and specificity of 71.0%. The elevated hardness of PG identified high-risk PCA and served as an independent marker of high-risk PCA. As a non-invasive imaging modality, the RTE could be potentially used in routine clinical practice for the detection of high-risk PCA to decrease unnecessary biopsies and reduce overtreatment.

Pressure-Sensitive and Conductive Carbon Aerogels from Poplars Catkins for Selective Oil Absorption and Oil/Water Separation.

PubMed

Li, Lingxiao; Hu, Tao; Sun, Hanxue; Zhang, Junping; Wang, Aiqin

2017-05-31

Multifunctional carbon aerogels that are both highly compressible and conductive have broad potential applications in the range of sound insulator, sensor, oil absorption, and electronics. However, the preparation of such carbon aerogels has been proven to be very challenging. Here, we report fabrication of pressure-sensitive and conductive (PSC) carbon aerogels by pyrolysis of cellulose aerogels composed of poplars catkin (PC) microfibers with a tubular structure. The wet PC gels can be dried directly in an oven without any deformation, in marked contrast to the brittle nature of traditional carbon aerogels. The resultant PSC aerogels exhibit ultralow density (4.3 mg cm -3 ), high compressibility (80%), high electrical conductivity (0.47 S cm -1 ), and high absorbency (80-161 g g -1 ) for oils and organic liquids. The PSC aerogels have potential applications in various fields such as elastomeric conductors, absorption of oils from water and oil/water separation, as the PSC aerogels feature simple preparation process with low-cost biomass as the precursor.

Reagent Strips as an Aid to Diagnosis of Neonatal Meningitis in a Resource-limited Setting.

PubMed

Burgoine, Kathy; Ikiror, Juliet; Naizuli, Ketty; Achom, Linda; Akol, Sylivia; Olupot-Olupot, Peter

2018-01-29

Without early recognition and treatment, neonatal meningitis (NM) has a high mortality and morbidity. Although some neonates have features of NM, many do not. In many low-resource settings, the laboratory support to diagnose NM is not available, and bedside diagnostics are needed. This retrospective study was conducted in a neonatal unit in Uganda. Clear cerebrospinal fluid samples were routinely screened for glucose, protein and leukocytes on a Combur®-10 urinalysis reagent strip. A definitive diagnosis was made using laboratory analysis. The results of the screening and definitive tests were compared. The reagent strip showed moderate sensitivity and high specificity for leukocytes ≥10×106 cells/l, high sensitivity for protein ≥100 mg/dl and high specificity for glucose <50 mg/dl. The use of reagent strips has the potential to improve and hasten the diagnosis of probable NM in settings where adequate or timely laboratory support is not available. © The Author(s) [2018]. Published by Oxford University Press.

Clinical Features and Associated Likelihood of Primary Ciliary Dyskinesia in Children and Adolescents.

PubMed

Leigh, Margaret W; Ferkol, Thomas W; Davis, Stephanie D; Lee, Hye-Seung; Rosenfeld, Margaret; Dell, Sharon D; Sagel, Scott D; Milla, Carlos; Olivier, Kenneth N; Sullivan, Kelli M; Zariwala, Maimoona A; Pittman, Jessica E; Shapiro, Adam J; Carson, Johnny L; Krischer, Jeffrey; Hazucha, Milan J; Knowles, Michael R

2016-08-01

Primary ciliary dyskinesia (PCD), a genetically heterogeneous, recessive disorder of motile cilia, is associated with distinct clinical features. Diagnostic tests, including ultrastructural analysis of cilia, nasal nitric oxide measurements, and molecular testing for mutations in PCD genes, have inherent limitations. To define a statistically valid combination of systematically defined clinical features that strongly associates with PCD in children and adolescents. Investigators at seven North American sites in the Genetic Disorders of Mucociliary Clearance Consortium prospectively and systematically assessed individuals (aged 0-18 yr) referred due to high suspicion for PCD. The investigators defined specific clinical questions for the clinical report form based on expert opinion. Diagnostic testing was performed using standardized protocols and included nasal nitric oxide measurement, ciliary biopsy for ultrastructural analysis of cilia, and molecular genetic testing for PCD-associated genes. Final diagnoses were assigned as "definite PCD" (hallmark ultrastructural defects and/or two mutations in a PCD-associated gene), "probable/possible PCD" (no ultrastructural defect or genetic diagnosis, but compatible clinical features and nasal nitric oxide level in PCD range), and "other diagnosis or undefined." Criteria were developed to define early childhood clinical features on the basis of responses to multiple specific queries. Each defined feature was tested by logistic regression. Sensitivity and specificity analyses were conducted to define the most robust set of clinical features associated with PCD. From 534 participants 18 years of age and younger, 205 were identified as having "definite PCD" (including 164 with two mutations in a PCD-associated gene), 187 were categorized as "other diagnosis or undefined," and 142 were defined as having "probable/possible PCD." Participants with "definite PCD" were compared with the "other diagnosis or undefined" group. Four criteria-defined clinical features were statistically predictive of PCD: laterality defect; unexplained neonatal respiratory distress; early-onset, year-round nasal congestion; and early-onset, year-round wet cough (adjusted odds ratios of 7.7, 6.6, 3.4, and 3.1, respectively). The sensitivity and specificity based on the number of criteria-defined clinical features were four features, 0.21 and 0.99, respectively; three features, 0.50 and 0.96, respectively; and two features, 0.80 and 0.72, respectively. Systematically defined early clinical features could help identify children, including infants, likely to have PCD. Clinical trial registered with ClinicalTrials.gov (NCT00323167).

A High Resolution Spectroscopic Observation of CAL 83 with XMM-Newton/RGS

NASA Technical Reports Server (NTRS)

Paerels, Frits; Rasmussen, Andrew P.; Hartmann, H. W.; Heise, J.; Brinkman, A. C.; deVries, C. P.; denHerder, J.-W.

2000-01-01

We present the first high resolution photospheric X-ray spectrum of a Supersoft X-ray Source, the famous CAL 83 in the Large Magellanic Cloud. The spectrum was obtained with the Reflection Grating Spectrometer on XMM-Newton during the Calibration/Performance Verification phase of the observatory. The spectrum covers the range 20-40 A at an approximately constant resolution of 0.05 A, and shows very significant, intricate detail, that is very sensitive to the physical properties of the object. We present the results of an initial investigation of the spectrum, from which we draw the conclusion that the spectral structure is probably dominated by numerous absorption features due to transitions in the Gshells of the mid-2 elements and the M-shell of Fe, in addition to a few strong K-shell features due to CNO.

Complementary spectroscopic studies of materials of security interest

NASA Astrophysics Data System (ADS)

Burnett, Andrew; Fan, Wenhui; Upadhya, Prashanth; Cunningham, John; Edwards, Howell; Munshi, Tasnim; Hargreaves, Michael; Linfield, Edmund; Davies, Giles

2006-09-01

We demonstrate that, through coherent measurement of the transmitted terahertz frequency electric fields, broadband (0.3 - 8 THz) time-domain spectroscopy can be used to measure far-infrared vibrational modes of a range of drugs-of-abuse and high explosives that are of interest to the forensic and security services. Our results indicate that absorption features in these materials are highly sensitive to the structural and spatial arrangement of the molecules. Terahertz frequency spectra are also compared with high-resolution low-frequency Raman spectra to assist in understanding the low-frequency inter- and intra-molecular vibrational modes of the molecules.

Analysis of drugs-of-abuse and explosives using terahertz time-domain and Raman spectroscopy

NASA Astrophysics Data System (ADS)

Burnett, Andrew; Fan, Wenhui; Upadhya, Prashanth; Cunningham, John; Linfield, Edmund; Davies, Giles; Edwards, Howell; Munshi, Tasnim; O'Neil, Andrew

2006-02-01

We demonstrate that, through coherent measurement of the transmitted terahertz electric fields, broadband (0.3-8THz) time-domain spectroscopy can be used to measure far-infrared vibrational modes of a range of illegal drugs and high explosives that are of interest to the forensic and security services. Our results show that these absorption features are highly sensitive to the structural and spatial arrangement of the molecules. Terahertz frequency spectra are also compared with high-resolution low-frequency Raman spectra to assist in understanding the low frequency inter- and intra-molecular vibrational modes of the molecules.

Altered subjective reward valuation among female heavy marijuana users.

PubMed

Hefner, Kathryn R; Starr, Mark J

2017-02-01

Maladaptive decision-making is a cardinal feature of drug use, contributing to ongoing use, and reflecting alterations in how drug users assess uncertain reward value. Accumulating evidence indicates the consequences of heavy marijuana use are worse for female versus male animals and humans, but research assessing sex differences in reward-related decision-making among marijuana users remains scarce. We examined sex differences in the subjective valuation of certain and uncertain rewards among heavy marijuana users (52; 26 male and 26 female) and controls (52; 26 male and 26 female). We offered male and female heavy marijuana users and controls monetary rewards of certain and uncertain (probabilistic) values. We measured how preferences for uncertain rewards varied by the objective value of those rewards, moderators of reward uncertainty, Marijuana Group and Sex. Men were more sensitive to changes in the objective value of uncertain rewards than women. However, this effect of Sex differed by Marijuana Group. Female heavy marijuana users were more sensitive to changes in uncertain reward value, particularly when the "stakes" were high (i.e., greater difference between potential uncertain rewards), than female controls. Female heavy marijuana users' sensitivity to changes in the value of high stakes uncertain rewards was comparable to male marijuana users and controls. In contrast, male marijuana users' sensitivity to changes in the value of high stakes uncertain rewards did not differ from male controls. These results suggest sex differences in sensitivity to high risk rewards may be one pathway contributing to severer consequences of heavy marijuana use among women. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Altered subjective reward valuation among female heavy marijuana users

PubMed Central

Hefner, Kathryn R.; Starr, Mark. J.

2016-01-01

Maladaptive decision-making is a cardinal feature of drug use, contributing to ongoing use, and reflecting alterations in how drug users assess uncertain reward value. Accumulating evidence indicates the consequences of heavy marijuana use are worse for female versus male animals and humans, but research assessing sex differences in reward-related decision-making among marijuana users remains scarce. We examined sex differences in the subjective valuation of certain and uncertain rewards among heavy marijuana users (52; 26 male and 26 female) and controls (52; 26 male and 26 female). We offered male and female heavy marijuana users and controls monetary rewards of certain and uncertain (probabilistic) values. We measured how preferences for uncertain rewards varied by the objective value of those rewards, moderators of reward uncertainty, marijuana use, and sex. Men were more sensitive to changes in the objective value of uncertain rewards than women. However, this effect of sex differed by marijuana group. Female heavy marijuana users were more sensitive to changes in uncertain reward value, particularly when the ‘stakes’ were high (i.e., greater difference between potential uncertain rewards), than female controls. Female heavy marijuana users’ sensitivity to changes in the value of high stakes uncertain rewards was comparable to male marijuana users and controls. In contrast, male marijuana users’ sensitivity to changes in the value of high stakes uncertain rewards did not differ from male controls. These results suggest sex differences in sensitivity to high risk rewards may be one pathway contributing to severer consequences of heavy marijuana use among women. PMID:27936816

VARS-TOOL: A Comprehensive, Efficient, and Robust Sensitivity Analysis Toolbox

NASA Astrophysics Data System (ADS)

Razavi, S.; Sheikholeslami, R.; Haghnegahdar, A.; Esfahbod, B.

2016-12-01

VARS-TOOL is an advanced sensitivity and uncertainty analysis toolbox, applicable to the full range of computer simulation models, including Earth and Environmental Systems Models (EESMs). The toolbox was developed originally around VARS (Variogram Analysis of Response Surfaces), which is a general framework for Global Sensitivity Analysis (GSA) that utilizes the variogram/covariogram concept to characterize the full spectrum of sensitivity-related information, thereby providing a comprehensive set of "global" sensitivity metrics with minimal computational cost. VARS-TOOL is unique in that, with a single sample set (set of simulation model runs), it generates simultaneously three philosophically different families of global sensitivity metrics, including (1) variogram-based metrics called IVARS (Integrated Variogram Across a Range of Scales - VARS approach), (2) variance-based total-order effects (Sobol approach), and (3) derivative-based elementary effects (Morris approach). VARS-TOOL is also enabled with two novel features; the first one being a sequential sampling algorithm, called Progressive Latin Hypercube Sampling (PLHS), which allows progressively increasing the sample size for GSA while maintaining the required sample distributional properties. The second feature is a "grouping strategy" that adaptively groups the model parameters based on their sensitivity or functioning to maximize the reliability of GSA results. These features in conjunction with bootstrapping enable the user to monitor the stability, robustness, and convergence of GSA with the increase in sample size for any given case study. VARS-TOOL has been shown to achieve robust and stable results within 1-2 orders of magnitude smaller sample sizes (fewer model runs) than alternative tools. VARS-TOOL, available in MATLAB and Python, is under continuous development and new capabilities and features are forthcoming.

New feature of the neutron color image intensifier

NASA Astrophysics Data System (ADS)

Nittoh, Koichi; Konagai, Chikara; Noji, Takashi; Miyabe, Keisuke

2009-06-01

We developed prototype neutron color image intensifiers with high-sensitivity, wide dynamic range and long-life characteristics. In the prototype intensifier (Gd-Type 1), a terbium-activated Gd 2O 2S is used as the input-screen phosphor. In the upgraded model (Gd-Type 2), Gd 2O 3 and CsI:Na are vacuum deposited to form the phosphor layer, which improved the sensitivity and the spatial uniformity. A europium-activated Y 2O 2S multi-color scintillator, emitting red, green and blue photons with different intensities, is utilized as the output screen of the intensifier. By combining this image intensifier with a suitably tuned high-sensitive color CCD camera, higher sensitivity and wider dynamic range could be simultaneously attained than that of the conventional P20-phosphor-type image intensifier. The results of experiments at the JRR-3M neutron radiography irradiation port (flux: 1.5×10 8 n/cm 2/s) showed that these neutron color image intensifiers can clearly image dynamic phenomena with a 30 frame/s video picture. It is expected that the color image intensifier will be used as a new two-dimensional neutron sensor in new application fields.

The Fowler-Nordheim behavior and mechanism of photo-sensitive field from SnS{sub 2} nanosheets

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

Suryawanshi, Sachin R.; Chaudhari, Nilima S.; Warule, Sambhaji S.

2015-06-24

Here in, we report photo-sensitive field emission measurements of SnS{sub 2} nanosheets at base pressure of ∼1×10{sup −8} mbar are reported. The nonlinear Fowler-Nordheim (F-N) plot is elucidate according to a (F-N) model of calculation based on shift in a saturation of conduction band current density after light illumination and prevalence of valence band current density at high electric field values. The model of calculation suggests that the slope variation before and after visible light illumination of the F-N plot, in the high-field and low-field regions, does not depend on the magnitude of saturation but also depend on charge carriermore » (electron) concentration get increased in conduction band. The F-N model of calculation is important for the fundamental understanding of the photo-sensitive field emission mechanism of semiconducting SnS{sub 2}. The replicate F-N plots exhibit similar features to those observed experimentally. The model calculation suggests that the nonlinearity of the F-N plot is a characteristic of the photo-enhanced energy band structure of the photo-sensitive semiconductor material.« less

Backscattered electron simulations to evaluate sensitivity against electron dosage of buried semiconductor features

NASA Astrophysics Data System (ADS)

Mukhtar, Maseeh; Thiel, Bradley

2018-03-01

In fabrication, overlay measurements of semiconductor device patterns have conventionally been performed using optical methods. Beginning with image-based techniques using box-in-box to the more recent diffraction-based overlay (DBO). Alternatively, use of SEM overlay is under consideration for in-device overlay. Two main application spaces are measurement features from multiple mask levels on the same surface and buried features. Modern CD-SEMs are adept at measuring overlay for cases where all features are on the surface. In order to measure overlay of buried features, HV-SEM is needed. Gate-to-fin and BEOL overlay are important use cases for this technique. A JMONSEL simulation exercise was performed for these two cases using 10 nm line/space gratings of graduated increase in depth of burial. Backscattered energy loss results of these simulations were used to calculate the sensitivity measurements of buried features versus electron dosage for an array of electron beam voltages.

Fall Detection Using Smartphone Audio Features.

PubMed

Cheffena, Michael

2016-07-01

An automated fall detection system based on smartphone audio features is developed. The spectrogram, mel frequency cepstral coefficents (MFCCs), linear predictive coding (LPC), and matching pursuit (MP) features of different fall and no-fall sound events are extracted from experimental data. Based on the extracted audio features, four different machine learning classifiers: k-nearest neighbor classifier (k-NN), support vector machine (SVM), least squares method (LSM), and artificial neural network (ANN) are investigated for distinguishing between fall and no-fall events. For each audio feature, the performance of each classifier in terms of sensitivity, specificity, accuracy, and computational complexity is evaluated. The best performance is achieved using spectrogram features with ANN classifier with sensitivity, specificity, and accuracy all above 98%. The classifier also has acceptable computational requirement for training and testing. The system is applicable in home environments where the phone is placed in the vicinity of the user.

Quantitative evaluation of in vivo vital-dye fluorescence endoscopic imaging for the detection of Barrett’s-associated neoplasia

PubMed Central

Thekkek, Nadhi; Lee, Michelle H.; Polydorides, Alexandros D.; Rosen, Daniel G.; Anandasabapathy, Sharmila; Richards-Kortum, Rebecca

2015-01-01

Abstract. Current imaging tools are associated with inconsistent sensitivity and specificity for detection of Barrett’s-associated neoplasia. Optical imaging has shown promise in improving the classification of neoplasia in vivo. The goal of this pilot study was to evaluate whether in vivo vital dye fluorescence imaging (VFI) has the potential to improve the accuracy of early-detection of Barrett’s-associated neoplasia. In vivo endoscopic VFI images were collected from 65 sites in 14 patients with confirmed Barrett’s esophagus (BE), dysplasia, or esophageal adenocarcinoma using a modular video endoscope and a high-resolution microendoscope (HRME). Qualitative image features were compared to histology; VFI and HRME images show changes in glandular structure associated with neoplastic progression. Quantitative image features in VFI images were identified for objective image classification of metaplasia and neoplasia, and a diagnostic algorithm was developed using leave-one-out cross validation. Three image features extracted from VFI images were used to classify tissue as neoplastic or not with a sensitivity of 87.8% and a specificity of 77.6% (AUC=0.878). A multimodal approach incorporating VFI and HRME imaging can delineate epithelial changes present in Barrett’s-associated neoplasia. Quantitative analysis of VFI images may provide a means for objective interpretation of BE during surveillance. PMID:25950645

Quantitative evaluation of in vivo vital-dye fluorescence endoscopic imaging for the detection of Barrett's-associated neoplasia.

PubMed

Thekkek, Nadhi; Lee, Michelle H; Polydorides, Alexandros D; Rosen, Daniel G; Anandasabapathy, Sharmila; Richards-Kortum, Rebecca

2015-05-01

Current imaging tools are associated with inconsistent sensitivity and specificity for detection of Barrett's-associated neoplasia. Optical imaging has shown promise in improving the classification of neoplasia in vivo. The goal of this pilot study was to evaluate whether in vivo vital dye fluorescence imaging (VFI) has the potential to improve the accuracy of early-detection of Barrett's-associated neoplasia. In vivo endoscopic VFI images were collected from 65 sites in 14 patients with confirmed Barrett's esophagus (BE), dysplasia, oresophageal adenocarcinoma using a modular video endoscope and a high-resolution microendoscope(HRME). Qualitative image features were compared to histology; VFI and HRME images show changes in glandular structure associated with neoplastic progression. Quantitative image features in VFI images were identified for objective image classification of metaplasia and neoplasia, and a diagnostic algorithm was developed using leave-one-out cross validation. Three image features extracted from VFI images were used to classify tissue as neoplastic or not with a sensitivity of 87.8% and a specificity of 77.6% (AUC = 0.878). A multimodal approach incorporating VFI and HRME imaging can delineate epithelial changes present in Barrett's-associated neoplasia. Quantitative analysis of VFI images may provide a means for objective interpretation of BE during surveillance.

Sensory subtypes in children with autism spectrum disorder: latent profile transition analysis using a national survey of sensory features.

PubMed

Ausderau, Karla K; Furlong, Melissa; Sideris, John; Bulluck, John; Little, Lauren M; Watson, Linda R; Boyd, Brian A; Belger, Aysenil; Dickie, Virginia A; Baranek, Grace T

2014-08-01

Sensory features are highly prevalent and heterogeneous among children with ASD. There is a need to identify homogenous groups of children with ASD based on sensory features (i.e., sensory subtypes) to inform research and treatment. Sensory subtypes and their stability over 1 year were identified through latent profile transition analysis (LPTA) among a national sample of children with ASD. Data were collected from caregivers of children with ASD ages 2-12 years at two time points (Time 1 N = 1294; Time 2 N = 884). Four sensory subtypes (Mild; Sensitive-Distressed; Attenuated-Preoccupied; Extreme-Mixed) were identified, which were supported by fit indices from the LPTA as well as current theoretical models that inform clinical practice. The Mild and Extreme-Mixed subtypes reflected quantitatively different sensory profiles, while the Sensitive-Distressed and Attenuated-Preoccupied subtypes reflected qualitatively different profiles. Further, subtypes reflected differential child (i.e., gender, developmental age, chronological age, autism severity) and family (i.e., income, mother's education) characteristics. Ninety-one percent of participants remained stable in their subtypes over 1 year. Characterizing the nature of homogenous sensory subtypes may facilitate assessment and intervention, as well as potentially inform biological mechanisms. © 2014 The Authors. Journal of Child Psychology and Psychiatry. © 2014 Association for Child and Adolescent Mental Health.

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

Sandstrom, Mary M.; Brown, Geoffrey W.; Preston, Daniel N.

The Integrated Data Collection Analysis (IDCA) program is conducting a proficiency study for Small- Scale Safety and Thermal (SSST) testing of homemade explosives (HMEs). Described here are the results for impact, friction, electrostatic discharge, and differential scanning calorimetry analysis of PETN Class 4. The PETN was found to have: 1) an impact sensitivity (DH 50) range of 6 to 12 cm, 2) a BAM friction sensitivity (F 50) range 7 to 11 kg, TIL (0/10) of 3.7 to 7.2 kg, 3) a ABL friction sensitivity threshold of 5 or less psig at 8 fps, 4) an ABL ESD sensitivity thresholdmore » of 0.031 to 0.326 j/g, and 5) a thermal sensitivity of an endothermic feature with T min = ~ 141 °C, and a exothermic feature with a T max = ~205°C.« less

Vibration-based damage detection in a concrete beam under temperature variations using AR models and state-space approaches

NASA Astrophysics Data System (ADS)

Clément, A.; Laurens, S.

2011-07-01

The Structural Health Monitoring of civil structures subjected to ambient vibrations is very challenging. Indeed, the variations of environmental conditions and the difficulty to characterize the excitation make the damage detection a hard task. Auto-regressive (AR) models coefficients are often used as damage sensitive feature. The presented work proposes a comparison of the AR approach with a state-space feature formed by the Jacobian matrix of the dynamical process. Since the detection of damage can be formulated as a novelty detection problem, Mahalanobis distance is applied to track new points from an undamaged reference collection of feature vectors. Data from a concrete beam subjected to temperature variations and damaged by several static loading are analyzed. It is observed that the damage sensitive features are effectively sensitive to temperature variations. However, the use of the Mahalanobis distance makes possible the detection of cracking with both of them. Early damage (before cracking) is only revealed by the AR coefficients with a good sensibility.

Efficient processing of fluorescence images using directional multiscale representations.

PubMed

Labate, D; Laezza, F; Negi, P; Ozcan, B; Papadakis, M

2014-01-01

Recent advances in high-resolution fluorescence microscopy have enabled the systematic study of morphological changes in large populations of cells induced by chemical and genetic perturbations, facilitating the discovery of signaling pathways underlying diseases and the development of new pharmacological treatments. In these studies, though, due to the complexity of the data, quantification and analysis of morphological features are for the vast majority handled manually, slowing significantly data processing and limiting often the information gained to a descriptive level. Thus, there is an urgent need for developing highly efficient automated analysis and processing tools for fluorescent images. In this paper, we present the application of a method based on the shearlet representation for confocal image analysis of neurons. The shearlet representation is a newly emerged method designed to combine multiscale data analysis with superior directional sensitivity, making this approach particularly effective for the representation of objects defined over a wide range of scales and with highly anisotropic features. Here, we apply the shearlet representation to problems of soma detection of neurons in culture and extraction of geometrical features of neuronal processes in brain tissue, and propose it as a new framework for large-scale fluorescent image analysis of biomedical data.

Efficient processing of fluorescence images using directional multiscale representations

PubMed Central

Labate, D.; Laezza, F.; Negi, P.; Ozcan, B.; Papadakis, M.

2017-01-01

Recent advances in high-resolution fluorescence microscopy have enabled the systematic study of morphological changes in large populations of cells induced by chemical and genetic perturbations, facilitating the discovery of signaling pathways underlying diseases and the development of new pharmacological treatments. In these studies, though, due to the complexity of the data, quantification and analysis of morphological features are for the vast majority handled manually, slowing significantly data processing and limiting often the information gained to a descriptive level. Thus, there is an urgent need for developing highly efficient automated analysis and processing tools for fluorescent images. In this paper, we present the application of a method based on the shearlet representation for confocal image analysis of neurons. The shearlet representation is a newly emerged method designed to combine multiscale data analysis with superior directional sensitivity, making this approach particularly effective for the representation of objects defined over a wide range of scales and with highly anisotropic features. Here, we apply the shearlet representation to problems of soma detection of neurons in culture and extraction of geometrical features of neuronal processes in brain tissue, and propose it as a new framework for large-scale fluorescent image analysis of biomedical data. PMID:28804225

Applicability of the two-angle differential method to response measurement of neutron-sensitive devices at the RCNP high-energy neutron facility

NASA Astrophysics Data System (ADS)

Masuda, Akihiko; Matsumoto, Tetsuro; Iwamoto, Yosuke; Hagiwara, Masayuki; Satoh, Daiki; Sato, Tatsuhiko; Iwase, Hiroshi; Yashima, Hiroshi; Nakane, Yoshihiro; Nishiyama, Jun; Shima, Tatsushi; Tamii, Atsushi; Hatanaka, Kichiji; Harano, Hideki; Nakamura, Takashi

2017-03-01

Quasi-monoenergetic high-energy neutron fields induced by 7Li(p,n) reactions are used for the response evaluation of neutron-sensitive devices. The quasi-monoenergetic high-energy field consists of high-energy monoenergetic peak neutrons and unwanted continuum neutrons down to the low-energy region. A two-angle differential method has been developed to compensate for the effect of the continuum neutrons in the response measurements. In this study, the two-angle differential method was demonstrated for Bonner sphere detectors, which are typical examples of moderator-based neutron-sensitive detectors, to investigate the method's applicability and its dependence on detector characteristics. Experiments were performed under 96-387 MeV quasi-monoenergetic high-energy neutron fields at the Research Center for Nuclear Physics (RCNP), Osaka University. The measurement results for large high-density polyethylene (HDPE) sphere detectors agreed well with Monte Carlo calculations, which verified the adequacy of the two-angle differential method. By contrast, discrepancies were observed in the results for small HDPE sphere detectors and metal-induced sphere detectors. The former indicated that detectors that are particularly sensitive to low-energy neutrons may be affected by penetrating neutrons owing to the geometrical features of the RCNP facility. The latter discrepancy could be consistently explained by a problem in the evaluated cross-section data for the metals used in the calculation. Through those discussions, the adequacy of the two-angle differential method was experimentally verified, and practical suggestions were made pertaining to this method.

The highly sensitive brain: an fMRI study of sensory processing sensitivity and response to others' emotions.

PubMed

Acevedo, Bianca P; Aron, Elaine N; Aron, Arthur; Sangster, Matthew-Donald; Collins, Nancy; Brown, Lucy L

2014-07-01

Theory and research suggest that sensory processing sensitivity (SPS), found in roughly 20% of humans and over 100 other species, is a trait associated with greater sensitivity and responsiveness to the environment and to social stimuli. Self-report studies have shown that high-SPS individuals are strongly affected by others' moods, but no previous study has examined neural systems engaged in response to others' emotions. This study examined the neural correlates of SPS (measured by the standard short-form Highly Sensitive Person [HSP] scale) among 18 participants (10 females) while viewing photos of their romantic partners and of strangers displaying positive, negative, or neutral facial expressions. One year apart, 13 of the 18 participants were scanned twice. Across all conditions, HSP scores were associated with increased brain activation of regions involved in attention and action planning (in the cingulate and premotor area [PMA]). For happy and sad photo conditions, SPS was associated with activation of brain regions involved in awareness, integration of sensory information, empathy, and action planning (e.g., cingulate, insula, inferior frontal gyrus [IFG], middle temporal gyrus [MTG], and PMA). As predicted, for partner images and for happy facial photos, HSP scores were associated with stronger activation of brain regions involved in awareness, empathy, and self-other processing. These results provide evidence that awareness and responsiveness are fundamental features of SPS, and show how the brain may mediate these traits.

The highly sensitive brain: an fMRI study of sensory processing sensitivity and response to others' emotions

PubMed Central

Acevedo, Bianca P; Aron, Elaine N; Aron, Arthur; Sangster, Matthew-Donald; Collins, Nancy; Brown, Lucy L

2014-01-01

Background Theory and research suggest that sensory processing sensitivity (SPS), found in roughly 20% of humans and over 100 other species, is a trait associated with greater sensitivity and responsiveness to the environment and to social stimuli. Self-report studies have shown that high-SPS individuals are strongly affected by others' moods, but no previous study has examined neural systems engaged in response to others' emotions. Methods This study examined the neural correlates of SPS (measured by the standard short-form Highly Sensitive Person [HSP] scale) among 18 participants (10 females) while viewing photos of their romantic partners and of strangers displaying positive, negative, or neutral facial expressions. One year apart, 13 of the 18 participants were scanned twice. Results Across all conditions, HSP scores were associated with increased brain activation of regions involved in attention and action planning (in the cingulate and premotor area [PMA]). For happy and sad photo conditions, SPS was associated with activation of brain regions involved in awareness, integration of sensory information, empathy, and action planning (e.g., cingulate, insula, inferior frontal gyrus [IFG], middle temporal gyrus [MTG], and PMA). Conclusions As predicted, for partner images and for happy facial photos, HSP scores were associated with stronger activation of brain regions involved in awareness, empathy, and self-other processing. These results provide evidence that awareness and responsiveness are fundamental features of SPS, and show how the brain may mediate these traits. PMID:25161824

Cloning SU8 silicon masters using epoxy resins to increase feature replicability and production for cell culture devices.

PubMed

Kamande, J W; Wang, Y; Taylor, A M

2015-05-01

In recent years, there has been a dramatic increase in the use of poly(dimethylsiloxane) (PDMS) devices for cell-based studies. Commonly, the negative tone photoresist, SU8, is used to pattern features onto silicon wafers to create masters (SU8-Si) for PDMS replica molding. However, the complexity in the fabrication process, low feature reproducibility (master-to-master variability), silane toxicity, and short life span of these masters have been deterrents for using SU8-Si masters for the production of cell culture based PDMS microfluidic devices. While other techniques have demonstrated the ability to generate multiple devices from a single master, they often do not match the high feature resolution (∼0.1 μm) and low surface roughness that soft lithography masters offer. In this work, we developed a method to fabricate epoxy-based masters that allows for the replication of features with high fidelity directly from SU8-Si masters via their PDMS replicas. By this method, we show that we could obtain many epoxy based masters with equivalent features to a single SU8-Si master with a low feature variance of 1.54%. Favorable feature transfer resolutions were also obtained by using an appropriate Tg epoxy based system to ensure minimal shrinkage of features ranging in size from ∼100 μm to <10 μm in height. We further show that surface coating epoxy masters with Cr/Au lead to effective demolding and yield PDMS chambers that are suitable for long-term culturing of sensitive primary hippocampal neurons. Finally, we incorporated pillars within the Au-epoxy masters to eliminate the process of punching media reservoirs and thereby reducing substantial artefacts and wastage.

Cloning SU8 silicon masters using epoxy resins to increase feature replicability and production for cell culture devices

PubMed Central

Kamande, J. W.; Wang, Y.; Taylor, A. M.

2015-01-01

In recent years, there has been a dramatic increase in the use of poly(dimethylsiloxane) (PDMS) devices for cell-based studies. Commonly, the negative tone photoresist, SU8, is used to pattern features onto silicon wafers to create masters (SU8-Si) for PDMS replica molding. However, the complexity in the fabrication process, low feature reproducibility (master-to-master variability), silane toxicity, and short life span of these masters have been deterrents for using SU8-Si masters for the production of cell culture based PDMS microfluidic devices. While other techniques have demonstrated the ability to generate multiple devices from a single master, they often do not match the high feature resolution (∼0.1 μm) and low surface roughness that soft lithography masters offer. In this work, we developed a method to fabricate epoxy-based masters that allows for the replication of features with high fidelity directly from SU8-Si masters via their PDMS replicas. By this method, we show that we could obtain many epoxy based masters with equivalent features to a single SU8-Si master with a low feature variance of 1.54%. Favorable feature transfer resolutions were also obtained by using an appropriate Tg epoxy based system to ensure minimal shrinkage of features ranging in size from ∼100 μm to <10 μm in height. We further show that surface coating epoxy masters with Cr/Au lead to effective demolding and yield PDMS chambers that are suitable for long-term culturing of sensitive primary hippocampal neurons. Finally, we incorporated pillars within the Au-epoxy masters to eliminate the process of punching media reservoirs and thereby reducing substantial artefacts and wastage. PMID:26180572

Primary central nervous system lymphoma and glioblastoma differentiation based on conventional magnetic resonance imaging by high-throughput SIFT features.

PubMed

Chen, Yinsheng; Li, Zeju; Wu, Guoqing; Yu, Jinhua; Wang, Yuanyuan; Lv, Xiaofei; Ju, Xue; Chen, Zhongping

2018-07-01

Due to the totally different therapeutic regimens needed for primary central nervous system lymphoma (PCNSL) and glioblastoma (GBM), accurate differentiation of the two diseases by noninvasive imaging techniques is important for clinical decision-making. Thirty cases of PCNSL and 66 cases of GBM with conventional T1-contrast magnetic resonance imaging (MRI) were analyzed in this study. Convolutional neural networks was used to segment tumor automatically. A modified scale invariant feature transform (SIFT) method was utilized to extract three-dimensional local voxel arrangement information from segmented tumors. Fisher vector was proposed to normalize the dimension of SIFT features. An improved genetic algorithm (GA) was used to extract SIFT features with PCNSL and GBM discrimination ability. The data-set was divided into a cross-validation cohort and an independent validation cohort by the ratio of 2:1. Support vector machine with the leave-one-out cross-validation based on 20 cases of PCNSL and 44 cases of GBM was employed to build and validate the differentiation model. Among 16,384 high-throughput features, 1356 features show significant differences between PCNSL and GBM with p < 0.05 and 420 features with p < 0.001. A total of 496 features were finally chosen by improved GA algorithm. The proposed method produces PCNSL vs. GBM differentiation with an area under the curve (AUC) curve of 99.1% (98.2%), accuracy 95.3% (90.6%), sensitivity 85.0% (80.0%) and specificity 100% (95.5%) on the cross-validation cohort (and independent validation cohort). Since the local voxel arrangement characterization provided by SIFT features, proposed method produced more competitive PCNSL and GBM differentiation performance by using conventional MRI than methods based on advanced MRI.

Speech Inconsistency in Children With Childhood Apraxia of Speech, Language Impairment, and Speech Delay: Depends on the Stimuli.

PubMed

Iuzzini-Seigel, Jenya; Hogan, Tiffany P; Green, Jordan R

2017-05-24

The current research sought to determine (a) if speech inconsistency is a core feature of childhood apraxia of speech (CAS) or if it is driven by comorbid language impairment that affects a large subset of children with CAS and (b) if speech inconsistency is a sensitive and specific diagnostic marker that can differentiate between CAS and speech delay. Participants included 48 children ranging between 4;7 to 17;8 (years;months) with CAS (n = 10), CAS + language impairment (n = 10), speech delay (n = 10), language impairment (n = 9), or typical development (n = 9). Speech inconsistency was assessed at phonemic and token-to-token levels using a variety of stimuli. Children with CAS and CAS + language impairment performed equivalently on all inconsistency assessments. Children with language impairment evidenced high levels of speech inconsistency on the phrase "buy Bobby a puppy." Token-to-token inconsistency of monosyllabic words and the phrase "buy Bobby a puppy" was sensitive and specific in differentiating children with CAS and speech delay, whereas inconsistency calculated on other stimuli (e.g., multisyllabic words) was less efficacious in differentiating between these disorders. Speech inconsistency is a core feature of CAS and is efficacious in differentiating between children with CAS and speech delay; however, sensitivity and specificity are stimuli dependent.

A Feature Selection Algorithm to Compute Gene Centric Methylation from Probe Level Methylation Data.

PubMed

Baur, Brittany; Bozdag, Serdar

2016-01-01

DNA methylation is an important epigenetic event that effects gene expression during development and various diseases such as cancer. Understanding the mechanism of action of DNA methylation is important for downstream analysis. In the Illumina Infinium HumanMethylation 450K array, there are tens of probes associated with each gene. Given methylation intensities of all these probes, it is necessary to compute which of these probes are most representative of the gene centric methylation level. In this study, we developed a feature selection algorithm based on sequential forward selection that utilized different classification methods to compute gene centric DNA methylation using probe level DNA methylation data. We compared our algorithm to other feature selection algorithms such as support vector machines with recursive feature elimination, genetic algorithms and ReliefF. We evaluated all methods based on the predictive power of selected probes on their mRNA expression levels and found that a K-Nearest Neighbors classification using the sequential forward selection algorithm performed better than other algorithms based on all metrics. We also observed that transcriptional activities of certain genes were more sensitive to DNA methylation changes than transcriptional activities of other genes. Our algorithm was able to predict the expression of those genes with high accuracy using only DNA methylation data. Our results also showed that those DNA methylation-sensitive genes were enriched in Gene Ontology terms related to the regulation of various biological processes.

Anticancer drug sensitivity prediction in cell lines from baseline gene expression through recursive feature selection.

PubMed

Dong, Zuoli; Zhang, Naiqian; Li, Chun; Wang, Haiyun; Fang, Yun; Wang, Jun; Zheng, Xiaoqi

2015-06-30

An enduring challenge in personalized medicine is to select right drug for individual patients. Testing drugs on patients in large clinical trials is one way to assess their efficacy and toxicity, but it is impractical to test hundreds of drugs currently under development. Therefore the preclinical prediction model is highly expected as it enables prediction of drug response to hundreds of cell lines in parallel. Recently, two large-scale pharmacogenomic studies screened multiple anticancer drugs on over 1000 cell lines in an effort to elucidate the response mechanism of anticancer drugs. To this aim, we here used gene expression features and drug sensitivity data in Cancer Cell Line Encyclopedia (CCLE) to build a predictor based on Support Vector Machine (SVM) and a recursive feature selection tool. Robustness of our model was validated by cross-validation and an independent dataset, the Cancer Genome Project (CGP). Our model achieved good cross validation performance for most drugs in the Cancer Cell Line Encyclopedia (≥80% accuracy for 10 drugs, ≥75% accuracy for 19 drugs). Independent tests on eleven common drugs between CCLE and CGP achieved satisfactory performance for three of them, i.e., AZD6244, Erlotinib and PD-0325901, using expression levels of only twelve, six and seven genes, respectively. These results suggest that drug response could be effectively predicted from genomic features. Our model could be applied to predict drug response for some certain drugs and potentially play a complementary role in personalized medicine.

A comprehensive sensitivity analysis of microarray breast cancer classification under feature variability

PubMed Central

2009-01-01

Background Large discrepancies in signature composition and outcome concordance have been observed between different microarray breast cancer expression profiling studies. This is often ascribed to differences in array platform as well as biological variability. We conjecture that other reasons for the observed discrepancies are the measurement error associated with each feature and the choice of preprocessing method. Microarray data are known to be subject to technical variation and the confidence intervals around individual point estimates of expression levels can be wide. Furthermore, the estimated expression values also vary depending on the selected preprocessing scheme. In microarray breast cancer classification studies, however, these two forms of feature variability are almost always ignored and hence their exact role is unclear. Results We have performed a comprehensive sensitivity analysis of microarray breast cancer classification under the two types of feature variability mentioned above. We used data from six state of the art preprocessing methods, using a compendium consisting of eight diferent datasets, involving 1131 hybridizations, containing data from both one and two-color array technology. For a wide range of classifiers, we performed a joint study on performance, concordance and stability. In the stability analysis we explicitly tested classifiers for their noise tolerance by using perturbed expression profiles that are based on uncertainty information directly related to the preprocessing methods. Our results indicate that signature composition is strongly influenced by feature variability, even if the array platform and the stratification of patient samples are identical. In addition, we show that there is often a high level of discordance between individual class assignments for signatures constructed on data coming from different preprocessing schemes, even if the actual signature composition is identical. Conclusion Feature variability can have a strong impact on breast cancer signature composition, as well as the classification of individual patient samples. We therefore strongly recommend that feature variability is considered in analyzing data from microarray breast cancer expression profiling experiments. PMID:19941644

A Fault Alarm and Diagnosis Method Based on Sensitive Parameters and Support Vector Machine

NASA Astrophysics Data System (ADS)

Zhang, Jinjie; Yao, Ziyun; Lv, Zhiquan; Zhu, Qunxiong; Xu, Fengtian; Jiang, Zhinong

2015-08-01

Study on the extraction of fault feature and the diagnostic technique of reciprocating compressor is one of the hot research topics in the field of reciprocating machinery fault diagnosis at present. A large number of feature extraction and classification methods have been widely applied in the related research, but the practical fault alarm and the accuracy of diagnosis have not been effectively improved. Developing feature extraction and classification methods to meet the requirements of typical fault alarm and automatic diagnosis in practical engineering is urgent task. The typical mechanical faults of reciprocating compressor are presented in the paper, and the existing data of online monitoring system is used to extract fault feature parameters within 15 types in total; the inner sensitive connection between faults and the feature parameters has been made clear by using the distance evaluation technique, also sensitive characteristic parameters of different faults have been obtained. On this basis, a method based on fault feature parameters and support vector machine (SVM) is developed, which will be applied to practical fault diagnosis. A better ability of early fault warning has been proved by the experiment and the practical fault cases. Automatic classification by using the SVM to the data of fault alarm has obtained better diagnostic accuracy.

Perceived Pain Extent is Not Associated With Widespread Pressure Pain Sensitivity, Clinical Features, Related Disability, Anxiety, or Depression in Women With Episodic Migraine.

PubMed

Fernández-de-Las-Peñas, Cesar; Falla, Deborah; Palacios-Ceña, María; Fuensalida-Novo, Stella; Arias-Buría, Jose L; Schneebeli, Alessandro; Arend-Nielsen, Lars; Barbero, Marco

2018-03-01

People with migraine present with varying pain extent and an expanded distribution of perceived pain may reflect central sensitization. The relationship between pain extent and clinical features, psychological outcomes, related disability, and pressure pain sensitivity in migraine has been poorly investigated. Our aim was to investigate whether the perceived pain extent, assessed from pain drawings, relates to measures of pressure pain sensitivity, clinical, psychological outcomes, and related disability in women with episodic migraine. A total of 72 women with episodic migraine completed pain drawings, which were subsequently digitized allowing pain extent to be calculated utilising novel software. Pressure pain thresholds were assessed bilaterally over the temporalis muscle (trigeminal area), the cervical spine (extratrigeminal area), and tibialis anterior muscle (distant pain-free area). Clinical features of migraine, migraine-related disability (migraine disability assessment questionnaire [MIDAS]), and anxiety and depression (Hospital Anxiety-Depression Scale [HADS]) were also assessed. Spearman ρ correlation coefficients were computed to reveal correlations between pain extent and the remaining outcomes. No significant associations were observed between pain extent and pressure pain thresholds in trigeminal, extratrigeminal or distant pain-free areas, migraine pain features, or psychological variables including anxiety or depression, and migraine-related disability. Pain extent within the trigeminocervical area was not associated with any of the measured clinical outcomes and not related to the degree of pressure pain sensitization in women with episodic migraine. Further research is needed to determine if the presence of expanded pain areas outside of the trigeminal area can play a relevant role in the sensitization processes in migraine.

High dynamic range vision sensor for automotive applications

NASA Astrophysics Data System (ADS)

Grenet, Eric; Gyger, Steve; Heim, Pascal; Heitger, Friedrich; Kaess, Francois; Nussbaum, Pascal; Ruedi, Pierre-Francois

2005-02-01

A 128 x 128 pixels, 120 dB vision sensor extracting at the pixel level the contrast magnitude and direction of local image features is used to implement a lane tracking system. The contrast representation (relative change of illumination) delivered by the sensor is independent of the illumination level. Together with the high dynamic range of the sensor, it ensures a very stable image feature representation even with high spatial and temporal inhomogeneities of the illumination. Dispatching off chip image feature is done according to the contrast magnitude, prioritizing features with high contrast magnitude. This allows to reduce drastically the amount of data transmitted out of the chip, hence the processing power required for subsequent processing stages. To compensate for the low fill factor (9%) of the sensor, micro-lenses have been deposited which increase the sensitivity by a factor of 5, corresponding to an equivalent of 2000 ASA. An algorithm exploiting the contrast representation output by the vision sensor has been developed to estimate the position of a vehicle relative to the road markings. The algorithm first detects the road markings based on the contrast direction map. Then, it performs quadratic fits on selected kernel of 3 by 3 pixels to achieve sub-pixel accuracy on the estimation of the lane marking positions. The resulting precision on the estimation of the vehicle lateral position is 1 cm. The algorithm performs efficiently under a wide variety of environmental conditions, including night and rainy conditions.

WRF model sensitivity to land surface model and cumulus parameterization under short-term climate extremes over the southern Great Plains of the United States

Treesearch

Lisi Pei; Nathan Moore; Shiyuan Zhong; Lifeng Luo; David W. Hyndman; Warren E. Heilman; Zhiqiu Gao

2014-01-01

Extreme weather and climate events, especially short-term excessive drought and wet periods over agricultural areas, have received increased attention. The Southern Great Plains (SGP) is one of the largest agricultural regions in North America and features the underlying Ogallala-High Plains Aquifer system worth great economic value in large part due to production...

Results from a new 193nm die-to-database reticle inspection platform

NASA Astrophysics Data System (ADS)

Broadbent, William H.; Alles, David S.; Giusti, Michael T.; Kvamme, Damon F.; Shi, Rui-fang; Sousa, Weston L.; Walsh, Robert; Xiong, Yalin

2010-05-01

A new 193nm wavelength high resolution reticle defect inspection platform has been developed for both die-to-database and die-to-die inspection modes. In its initial configuration, this innovative platform has been designed to meet the reticle qualification requirements of the IC industry for the 22nm logic and 3xhp memory generations (and shrinks) with planned extensions to the next generation. The 22nm/3xhp IC generation includes advanced 193nm optical lithography using conventional RET, advanced computational lithography, and double patterning. Further, EUV pilot line lithography is beginning. This advanced 193nm inspection platform has world-class performance and the capability to meet these diverse needs in optical and EUV lithography. The architecture of the new 193nm inspection platform is described. Die-to-database inspection results are shown on a variety of reticles from industry sources; these reticles include standard programmed defect test reticles, as well as advanced optical and EUV product and product-like reticles. Results show high sensitivity and low false and nuisance detections on complex optical reticle designs and small feature size EUV reticles. A direct comparison with the existing industry standard 257nm wavelength inspection system shows measurable sensitivity improvement for small feature sizes

Classification of highly unbalanced CYP450 data of drugs using cost sensitive machine learning techniques.

PubMed

Eitrich, T; Kless, A; Druska, C; Meyer, W; Grotendorst, J

2007-01-01

In this paper, we study the classifications of unbalanced data sets of drugs. As an example we chose a data set of 2D6 inhibitors of cytochrome P450. The human cytochrome P450 2D6 isoform plays a key role in the metabolism of many drugs in the preclinical drug discovery process. We have collected a data set from annotated public data and calculated physicochemical properties with chemoinformatics methods. On top of this data, we have built classifiers based on machine learning methods. Data sets with different class distributions lead to the effect that conventional machine learning methods are biased toward the larger class. To overcome this problem and to obtain sensitive but also accurate classifiers we combine machine learning and feature selection methods with techniques addressing the problem of unbalanced classification, such as oversampling and threshold moving. We have used our own implementation of a support vector machine algorithm as well as the maximum entropy method. Our feature selection is based on the unsupervised McCabe method. The classification results from our test set are compared structurally with compounds from the training set. We show that the applied algorithms enable the effective high throughput in silico classification of potential drug candidates.

Computer-aided detection and diagnosis of masses and clustered microcalcifications from digital mammograms

NASA Astrophysics Data System (ADS)

Nishikawa, Robert M.; Giger, Maryellen L.; Doi, Kunio; Vyborny, Carl J.; Schmidt, Robert A.; Metz, Charles E.; Wu, Chris Y.; Yin, Fang-Fang; Jiang, Yulei; Huo, Zhimin; Lu, Ping; Zhang, Wei; Ema, Takahiro; Bick, Ulrich; Papaioannou, John; Nagel, Rufus H.

1993-07-01

We are developing an 'intelligent' workstation to assist radiologists in diagnosing breast cancer from mammograms. The hardware for the workstation will consist of a film digitizer, a high speed computer, a large volume storage device, a film printer, and 4 high resolution CRT monitors. The software for the workstation is a comprehensive package of automated detection and classification schemes. Two rule-based detection schemes have been developed, one for breast masses and the other for clustered microcalcifications. The sensitivity of both schemes is 85% with a false-positive rate of approximately 3.0 and 1.5 false detections per image, for the mass and cluster detection schemes, respectively. Computerized classification is performed by an artificial neural network (ANN). The ANN has a sensitivity of 100% with a specificity of 60%. Currently, the ANN, which is a three-layer, feed-forward network, requires as input ratings of 14 different radiographic features of the mammogram that were determined subjectively by a radiologist. We are in the process of developing automated techniques to objectively determine these 14 features. The workstation will be placed in the clinical reading area of the radiology department in the near future, where controlled clinical tests will be performed to measure its efficacy.

Application of machine vision to pup loaf bread evaluation

NASA Astrophysics Data System (ADS)

Zayas, Inna Y.; Chung, O. K.

1996-12-01

Intrinsic end-use quality of hard winter wheat breeding lines is routinely evaluated at the USDA, ARS, USGMRL, Hard Winter Wheat Quality Laboratory. Experimental baking test of pup loaves is the ultimate test for evaluating hard wheat quality. Computer vision was applied to developing an objective methodology for bread quality evaluation for the 1994 and 1995 crop wheat breeding line samples. Computer extracted features for bread crumb grain were studied, using subimages (32 by 32 pixel) and features computed for the slices with different threshold settings. A subsampling grid was located with respect to the axis of symmetry of a slice to provide identical topological subimage information. Different ranking techniques were applied to the databases. Statistical analysis was run on the database with digital image and breadmaking features. Several ranking algorithms and data visualization techniques were employed to create a sensitive scale for porosity patterns of bread crumb. There were significant linear correlations between machine vision extracted features and breadmaking parameters. Crumb grain scores by human experts were correlated more highly with some image features than with breadmaking parameters.

Design Optimization and Fabrication of a Novel Structural SOI Piezoresistive Pressure Sensor with High Accuracy

PubMed Central

Li, Chuang; Cordovilla, Francisco; Jagdheesh, R.

2018-01-01

This paper presents a novel structural piezoresistive pressure sensor with four-grooved membrane combined with rood beam to measure low pressure. In this investigation, the design, optimization, fabrication, and measurements of the sensor are involved. By analyzing the stress distribution and deflection of sensitive elements using finite element method, a novel structure featuring high concentrated stress profile (HCSP) and locally stiffened membrane (LSM) is built. Curve fittings of the mechanical stress and deflection based on FEM simulation results are performed to establish the relationship between mechanical performance and structure dimension. A combination of FEM and curve fitting method is carried out to determine the structural dimensions. The optimized sensor chip is fabricated on a SOI wafer by traditional MEMS bulk-micromachining and anodic bonding technology. When the applied pressure is 1 psi, the sensor achieves a sensitivity of 30.9 mV/V/psi, a pressure nonlinearity of 0.21% FSS and an accuracy of 0.30%, and thereby the contradiction between sensitivity and linearity is alleviated. In terms of size, accuracy and high temperature characteristic, the proposed sensor is a proper choice for measuring pressure of less than 1 psi. PMID:29393916

Sunlight-Sensitive Anti-Fouling Nanostructured TiO2 coated Cu Meshes for Ultrafast Oily Water Treatment

PubMed Central

Liu, HaoRan; Raza, Aikifa; Aili, Abulimiti; Lu, JinYou; AlGhaferi, Amal; Zhang, TieJun

2016-01-01

Nanostructured materials with desired wettability and optical property can play an important role in reducing the energy consumption of oily water treatment technologies. For effective oily water treatment, membrane materials with high strength, sunlight-sensitive anti-fouling, relative low fabrication cost, and controllable wettability are being explored. In the proposed oily water treatment approach, nanostructured TiO2-coated copper (TNS-Cu) meshes are used. These TNS-Cu meshes exhibit robust superhydrophilicity and underwater oleophobicity (high oil intrusion pressure) as well as excellent chemical and thermal stability (≈250 °C). They have demonstrated high separation efficiency (oil residue in the filtrate ≤21.3 ppm), remarkable filtration flux (≥400 kL h−1 m−2), and sunlight-sensitive anti-fouling properties. Both our theoretical analysis and experimental characterization have confirmed the enhanced light absorption property of TNS-Cu meshes in the visible region (40% of the solar spectrum) and consequently strong anti-fouling capability upon direct solar light illumination. With these features, the proposed approach promises great potential in treating produced oily wastewater from industry and daily life. PMID:27160349

Predicting the risk of malignancy in adnexal masses based on the Simple Rules from the International Ovarian Tumor Analysis group.

PubMed

Timmerman, Dirk; Van Calster, Ben; Testa, Antonia; Savelli, Luca; Fischerova, Daniela; Froyman, Wouter; Wynants, Laure; Van Holsbeke, Caroline; Epstein, Elisabeth; Franchi, Dorella; Kaijser, Jeroen; Czekierdowski, Artur; Guerriero, Stefano; Fruscio, Robert; Leone, Francesco P G; Rossi, Alberto; Landolfo, Chiara; Vergote, Ignace; Bourne, Tom; Valentin, Lil

2016-04-01

Accurate methods to preoperatively characterize adnexal tumors are pivotal for optimal patient management. A recent metaanalysis concluded that the International Ovarian Tumor Analysis algorithms such as the Simple Rules are the best approaches to preoperatively classify adnexal masses as benign or malignant. We sought to develop and validate a model to predict the risk of malignancy in adnexal masses using the ultrasound features in the Simple Rules. This was an international cross-sectional cohort study involving 22 oncology centers, referral centers for ultrasonography, and general hospitals. We included consecutive patients with an adnexal tumor who underwent a standardized transvaginal ultrasound examination and were selected for surgery. Data on 5020 patients were recorded in 3 phases from 2002 through 2012. The 5 Simple Rules features indicative of a benign tumor (B-features) and the 5 features indicative of malignancy (M-features) are based on the presence of ascites, tumor morphology, and degree of vascularity at ultrasonography. Gold standard was the histopathologic diagnosis of the adnexal mass (pathologist blinded to ultrasound findings). Logistic regression analysis was used to estimate the risk of malignancy based on the 10 ultrasound features and type of center. The diagnostic performance was evaluated by area under the receiver operating characteristic curve, sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR-), positive predictive value (PPV), negative predictive value (NPV), and calibration curves. Data on 4848 patients were analyzed. The malignancy rate was 43% (1402/3263) in oncology centers and 17% (263/1585) in other centers. The area under the receiver operating characteristic curve on validation data was very similar in oncology centers (0.917; 95% confidence interval, 0.901-0.931) and other centers (0.916; 95% confidence interval, 0.873-0.945). Risk estimates showed good calibration. In all, 23% of patients in the validation data set had a very low estimated risk (<1%) and 48% had a high estimated risk (≥30%). For the 1% risk cutoff, sensitivity was 99.7%, specificity 33.7%, LR+ 1.5, LR- 0.010, PPV 44.8%, and NPV 98.9%. For the 30% risk cutoff, sensitivity was 89.0%, specificity 84.7%, LR+ 5.8, LR- 0.13, PPV 75.4%, and NPV 93.9%. Quantification of the risk of malignancy based on the Simple Rules has good diagnostic performance both in oncology centers and other centers. A simple classification based on these risk estimates may form the basis of a clinical management system. Patients with a high risk may benefit from surgery by a gynecological oncologist, while patients with a lower risk may be managed locally. Copyright © 2016 Elsevier Inc. All rights reserved.

Dual frequency parametric excitation of a nonlinear, multi degree of freedom mechanical amplifier with electronically modified topology

NASA Astrophysics Data System (ADS)

Dolev, A.; Bucher, I.

2018-04-01

Mechanical or electromechanical amplifiers can exploit the high-Q and low noise features of mechanical resonance, in particular when parametric excitation is employed. Multi-frequency parametric excitation introduces tunability and is able to project weak input signals on a selected resonance. The present paper addresses multi degree of freedom mechanical amplifiers or resonators whose analysis and features require treatment of the spatial as well as temporal behavior. In some cases, virtual electronic coupling can alter the given topology of the resonator to better amplify specific inputs. An analytical development is followed by a numerical and experimental sensitivity and performance verifications, illustrating the advantages and disadvantages of such topologies.

Moderate-resolution spectral standards from lambda 5600 to lambda 9000

NASA Technical Reports Server (NTRS)

Allen, Lori E.; Strom, Karen M.

1995-01-01

We present a grid of stellar classification spectra of moderate resolution (R approximately 1500) in the range lambda lambda 5600-9000 A, compiled from high signal-to noise spectra of 275 stars, most in the open clusters Praesepe and M67. The grid covers dwarfs from types B8 through M5, giants from G8 through M7, and subgiants from F5 through K0. We catalog atomic and molecular absorption features useful for stellar classification, and demonstrate the use of luminosity-sensitive features to distinguish between late-type dwarf and giant stars. The entire database is made available in digital format on anonymous ftp and through the World Wide Web.

A 300MHz Embedded Flash Memory with Pipeline Architecture and Offset-Free Sense Amplifiers for Dual-Core Automotive Microcontrollers

NASA Astrophysics Data System (ADS)

Kajiyama, Shinya; Fujito, Masamichi; Kasai, Hideo; Mizuno, Makoto; Yamaguchi, Takanori; Shinagawa, Yutaka

A novel 300MHz embedded flash memory for dual-core microcontrollers with a shared ROM architecture is proposed. One of its features is a three-stage pipeline read operation, which enables reduced access pitch and therefore reduces performance penalty due to conflict of shared ROM accesses. Another feature is a highly sensitive sense amplifier that achieves efficient pipeline operation with two-cycle latency one-cycle pitch as a result of a shortened sense time of 0.63ns. The combination of the pipeline architecture and proposed sense amplifiers significantly reduces access-conflict penalties with shared ROM and enhances performance of 32-bit RISC dual-core microcontrollers by 30%.

Exploiting the IR: Solar and stellar spectroscopy in the IR

NASA Technical Reports Server (NTRS)

Deming, Drake

1987-01-01

Recent instrumental advances have provided the capability to perform high resolution spectroscopy, in the thermal infrared region of the solar spectrum, with high sensitivity. The 8 to 12 micron region was extensively observed using Fourier transform (FTS) and laser heterodyne techniques. The continuous opacity of the solar atmosphere, due to H(-), increases with wavelength in the infrared region longward of 1.6 microns. Consequently thermal infrared observations probe the upper photosphere, and give an insight into the dynamics and structure of this region. The most notable spectral features in the 10 micron window include pure rotation lines of OH, and emission lines due to high-n states in MgI and AlI. The high-n lines due to MgI and AlI are important to solar and stellar physics because of their very large Zeeman sensitivity. The recent development of a cryogenic grating postdispenser for the FTS has allowed low-noise solar observations of these lines in 90 seconds. Limited mapping of the lines in a sunspot penumbra was performed, and gives information of the structure of the penumbral magnetic field. Although the MgI lines were detected in red giant spectra, instrumental sensitivity is not yet sufficient to see them in stars where significant magnetic fields are expected.

Fabrication of Highly Sensitive Nonenzymatic Electrochemical H₂O₂ Sensor Based on Pt Nanoparticles Anchored Reduced Graphene Oxide.

PubMed

Dhara, Keerthy; Ramachandran, T; Nair, Bipin G; Babu, T G Satheesh

2018-06-01

A highly sensitive nonenzymatic hydrogen peroxide (H2O2) sensor was fabricated using platinum nanoparticles decorated reduced graphene oxide (Pt/rGO) nanocomposite. The Pt/rGO nanocomposite was prepared by single-step chemical reduction method. Nanocomposite was characterized by various analytical techniques including Raman spectroscopy, X-ray diffraction, field emission scanning electron microscope and high-resolution transmission electron microscopy. Screen printed electrodes (SPEs) were fabricated and the nanocomposite was cast on the working area of the SPE. Cyclic voltammetry and amperometry demonstrated that the Pt/rGO/SPE displayed much higher electrocatalytic activity towards the reduction of H2O2 than the other modified electrodes. The sensor exhibited wide linear detection range (from 10 μM to 8 mM), very high sensitivity of 1848 μA mM-1 cm-2 and a lower limit of detection of 0.06 μM. The excellent performance of Pt/rGO/SPE sensor were attributed to the reduced graphene oxide being used as an effective matrix to load a number of Pt nanoparticles and the synergistic amplification effect of the two kinds of nanomaterials. Moreover, the sensor showed remarkable features such as good reproducibility, repeatability, long-term stability, and selectivity.

Development of a High-Sensitivity Wireless Accelerometer for Structural Health Monitoring

PubMed Central

Zhu, Li; Fu, Yuguang; Chow, Raymond; Spencer, Billie F.; Park, Jong Woong; Mechitov, Kirill

2018-01-01

Structural health monitoring (SHM) is playing an increasingly important role in ensuring the safety of structures. A shift of SHM research away from traditional wired methods toward the use of wireless smart sensors (WSS) has been motivated by the attractive features of wireless smart sensor networks (WSSN). The progress achieved in Micro Electro-Mechanical System (MEMS) technologies and wireless data transmission, has extended the effectiveness and range of applicability of WSSNs. One of the most common sensors employed in SHM strategies is the accelerometer; however, most accelerometers in WSS nodes have inadequate resolution for measurement of the typical accelerations found in many SHM applications. In this study, a high-resolution and low-noise tri-axial digital MEMS accelerometer is incorporated in a next-generation WSS platform, the Xnode. In addition to meeting the acceleration sensing demands of large-scale civil infrastructure applications, this new WSS node provides powerful hardware and a robust software framework to enable edge computing that can deliver actionable information. Hardware and software integration challenges are presented, and the associate resolutions are discussed. The performance of the wireless accelerometer is demonstrated experimentally through comparison with high-sensitivity wired accelerometers. This new high-sensitivity wireless accelerometer will extend the use of WSSN to a broader class of SHM applications. PMID:29342102

Development of a High-Sensitivity Wireless Accelerometer for Structural Health Monitoring.

PubMed

Zhu, Li; Fu, Yuguang; Chow, Raymond; Spencer, Billie F; Park, Jong Woong; Mechitov, Kirill

2018-01-17

Structural health monitoring (SHM) is playing an increasingly important role in ensuring the safety of structures. A shift of SHM research away from traditional wired methods toward the use of wireless smart sensors (WSS) has been motivated by the attractive features of wireless smart sensor networks (WSSN). The progress achieved in Micro Electro-Mechanical System (MEMS) technologies and wireless data transmission, has extended the effectiveness and range of applicability of WSSNs. One of the most common sensors employed in SHM strategies is the accelerometer; however, most accelerometers in WSS nodes have inadequate resolution for measurement of the typical accelerations found in many SHM applications. In this study, a high-resolution and low-noise tri-axial digital MEMS accelerometer is incorporated in a next-generation WSS platform, the Xnode. In addition to meeting the acceleration sensing demands of large-scale civil infrastructure applications, this new WSS node provides powerful hardware and a robust software framework to enable edge computing that can deliver actionable information. Hardware and software integration challenges are presented, and the associate resolutions are discussed. The performance of the wireless accelerometer is demonstrated experimentally through comparison with high-sensitivity wired accelerometers. This new high-sensitivity wireless accelerometer will extend the use of WSSN to a broader class of SHM applications.

DNA decorated carbon nanotube sensors on CMOS circuitry for environmental monitoring

NASA Astrophysics Data System (ADS)

Liu, Yu; Chen, Chia-Ling; Agarwal, V.; Li, Xinghui; Sonkusale, S.; Dokmeci, Mehmet R.; Wang, Ming L.

2010-04-01

Single-walled carbon nanotubes (SWNTs) with their large surface area, high aspect ratio are one of the novel materials which have numerous attractive features amenable for high sensitivity sensors. Several nanotube based sensors including, gas, chemical and biosensors have been demonstrated. Moreover, most of these sensors require off chip components to detect the variations in the signals making them complicated and hard to commercialize. Here we present a novel complementary metal oxide semiconductor (CMOS) integrated carbon nanotube sensors for portable high sensitivity chemical sensing applications. Multiple zincation steps have been developed to ascertain proper electrical connectivity between the carbon nanotubes and the foundry made CMOS circuitry. The SWNTs have been integrated onto (CMOS) circuitry as the feedback resistor of a Miller compensated operational amplifier utilizing low temperature Dielectrophoretic (DEP) assembly process which has been tailored to be compatible with the post-CMOS integration at the die level. Building nanotube sensors directly on commercial CMOS circuitry allows single chip solutions eliminating the need for long parasitic lines and numerous wire bonds. The carbon nanotube sensors realized on CMOS circuitry show strong response to various vapors including Dimethyl methylphosphonate and Dinitrotoluene. The remarkable set of attributes of the SWNTs realized on CMOS electronic chips provides an attractive platform for high sensitivity portable nanotube based bio and chemical sensors.

Nanoparticles for Cardiovascular Imaging and Therapeutic Delivery, Part 1: Compositions and Features.

PubMed

Stendahl, John C; Sinusas, Albert J

2015-10-01

Imaging agents made from nanoparticles are functionally versatile and have unique properties that may translate to clinical utility in several key cardiovascular imaging niches. Nanoparticles exhibit size-based circulation, biodistribution, and elimination properties different from those of small molecules and microparticles. In addition, nanoparticles provide versatile platforms that can be engineered to create both multimodal and multifunctional imaging agents with tunable properties. With these features, nanoparticulate imaging agents can facilitate fusion of high-sensitivity and high-resolution imaging modalities and selectively bind tissues for targeted molecular imaging and therapeutic delivery. Despite their intriguing attributes, nanoparticulate imaging agents have thus far achieved only limited clinical use. The reasons for this restricted advancement include an evolving scope of applications, the simplicity and effectiveness of existing small-molecule agents, pharmacokinetic limitations, safety concerns, and a complex regulatory environment. This review describes general features of nanoparticulate imaging agents and therapeutics and discusses challenges associated with clinical translation. A second, related review to appear in a subsequent issue of JNM highlights nuclear-based nanoparticulate probes in preclinical cardiovascular imaging. © 2015 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Using multiple classifiers for predicting the risk of endovascular aortic aneurysm repair re-intervention through hybrid feature selection.

PubMed

Attallah, Omneya; Karthikesalingam, Alan; Holt, Peter Je; Thompson, Matthew M; Sayers, Rob; Bown, Matthew J; Choke, Eddie C; Ma, Xianghong

2017-11-01

Feature selection is essential in medical area; however, its process becomes complicated with the presence of censoring which is the unique character of survival analysis. Most survival feature selection methods are based on Cox's proportional hazard model, though machine learning classifiers are preferred. They are less employed in survival analysis due to censoring which prevents them from directly being used to survival data. Among the few work that employed machine learning classifiers, partial logistic artificial neural network with auto-relevance determination is a well-known method that deals with censoring and perform feature selection for survival data. However, it depends on data replication to handle censoring which leads to unbalanced and biased prediction results especially in highly censored data. Other methods cannot deal with high censoring. Therefore, in this article, a new hybrid feature selection method is proposed which presents a solution to high level censoring. It combines support vector machine, neural network, and K-nearest neighbor classifiers using simple majority voting and a new weighted majority voting method based on survival metric to construct a multiple classifier system. The new hybrid feature selection process uses multiple classifier system as a wrapper method and merges it with iterated feature ranking filter method to further reduce features. Two endovascular aortic repair datasets containing 91% censored patients collected from two centers were used to construct a multicenter study to evaluate the performance of the proposed approach. The results showed the proposed technique outperformed individual classifiers and variable selection methods based on Cox's model such as Akaike and Bayesian information criterions and least absolute shrinkage and selector operator in p values of the log-rank test, sensitivity, and concordance index. This indicates that the proposed classifier is more powerful in correctly predicting the risk of re-intervention enabling doctor in selecting patients' future follow-up plan.

Shell feature: a new radiomics descriptor for predicting distant failure after radiotherapy in non-small cell lung cancer and cervix cancer

NASA Astrophysics Data System (ADS)

Hao, Hongxia; Zhou, Zhiguo; Li, Shulong; Maquilan, Genevieve; Folkert, Michael R.; Iyengar, Puneeth; Westover, Kenneth D.; Albuquerque, Kevin; Liu, Fang; Choy, Hak; Timmerman, Robert; Yang, Lin; Wang, Jing

2018-05-01

Distant failure is the main cause of human cancer-related mortalities. To develop a model for predicting distant failure in non-small cell lung cancer (NSCLC) and cervix cancer (CC) patients, a shell feature, consisting of outer voxels around the tumor boundary, was constructed using pre-treatment positron emission tomography (PET) images from 48 NSCLC patients received stereotactic body radiation therapy and 52 CC patients underwent external beam radiation therapy and concurrent chemotherapy followed with high-dose-rate intracavitary brachytherapy. The hypothesis behind this feature is that non-invasive and invasive tumors may have different morphologic patterns in the tumor periphery, in turn reflecting the differences in radiological presentations in the PET images. The utility of the shell was evaluated by the support vector machine classifier in comparison with intensity, geometry, gray level co-occurrence matrix-based texture, neighborhood gray tone difference matrix-based texture, and a combination of these four features. The results were assessed in terms of accuracy, sensitivity, specificity, and AUC. Collectively, the shell feature showed better predictive performance than all the other features for distant failure prediction in both NSCLC and CC cohorts.

Mouse epileptic seizure detection with multiple EEG features and simple thresholding technique

NASA Astrophysics Data System (ADS)

Tieng, Quang M.; Anbazhagan, Ashwin; Chen, Min; Reutens, David C.

2017-12-01

Objective. Epilepsy is a common neurological disorder characterized by recurrent, unprovoked seizures. The search for new treatments for seizures and epilepsy relies upon studies in animal models of epilepsy. To capture data on seizures, many applications require prolonged electroencephalography (EEG) with recordings that generate voluminous data. The desire for efficient evaluation of these recordings motivates the development of automated seizure detection algorithms. Approach. A new seizure detection method is proposed, based on multiple features and a simple thresholding technique. The features are derived from chaos theory, information theory and the power spectrum of EEG recordings and optimally exploit both linear and nonlinear characteristics of EEG data. Main result. The proposed method was tested with real EEG data from an experimental mouse model of epilepsy and distinguished seizures from other patterns with high sensitivity and specificity. Significance. The proposed approach introduces two new features: negative logarithm of adaptive correlation integral and power spectral coherence ratio. The combination of these new features with two previously described features, entropy and phase coherence, improved seizure detection accuracy significantly. Negative logarithm of adaptive correlation integral can also be used to compute the duration of automatically detected seizures.

Experimental study on the measurement of uranium casting enrichment by time-dependent coincidence method

NASA Astrophysics Data System (ADS)

Xie, Wen-Xiong; Li, Jian-Sheng; Gong, Jian; Zhu, Jian-Yu; Huang, Po

2013-10-01

Based on the time-dependent coincidence method, a preliminary experiment has been performed on uranium metal castings with similar quality (about 8-10 kg) and shape (hemispherical shell) in different enrichments using neutron from Cf fast fission chamber and timing DT accelerator. Groups of related parameters can be obtained by analyzing the features of time-dependent coincidence counts between source-detector and two detectors to characterize the fission signal. These parameters have high sensitivity to the enrichment, the sensitivity coefficient (defined as (ΔR/Δm)/R¯) can reach 19.3% per kg of 235U. We can distinguish uranium castings with different enrichments to hold nuclear weapon verification.

Simultaneous determination of indoor ammonia pollution and its biological metabolite in the human body with a recyclable nanocrystalline lanthanide-functionalized MOF.

PubMed

Hao, Ji-Na; Yan, Bing

2016-02-07

A Eu(3+) post-functionalized metal-organic framework of nanosized Ga(OH)bpydc(Eu(3+)@Ga(OH)bpydc, 1a) with intense luminescence is synthesized and characterized. Luminescence measurements reveal that 1a can detect ammonia gas selectively and sensitively among various indoor air pollutants. 1a can simultaneously determine a biological ammonia metabolite (urinary urea) in the human body, which is a rare example of a luminescent sensor that can monitor pollutants in the environment and also detect their biological markers. Furthermore, 1a exhibits appealing features including high selectivity and sensitivity, fast response, simple and quick regeneration, and excellent recyclability.

Miniature triaxial metastable ionization detector for gas chromatographic trace analysis of extraterrestrial volatiles

NASA Technical Reports Server (NTRS)

Woeller, F. H.; Kojiro, D. R.; Carle, G. C.

1984-01-01

The present investigation is concerned with a miniature metastable ionization detector featuring an unconventional electrode configuration, whose performance characteristics parallel those of traditional design. The ionization detector is to be incorporated in a flight gas chromatograph (GC) for use in the Space Shuttle. The design of the detector is discussed, taking into account studies which verified the sensitivity of the detector. The triaxial design of the detector is compared with a flat-plate style. The obtained results show that the principal goal of developing a miniature, highly sensitive ionization detector for flight applications was achieved. Improved fabrication techniques will utilize glass-to-metal seals and brazing procedures.

Fixation to features and neural processing of facial expressions in a gender discrimination task

PubMed Central

Neath, Karly N.; Itier, Roxane J.

2017-01-01

Early face encoding, as reflected by the N170 ERP component, is sensitive to fixation to the eyes. Whether this sensitivity varies with facial expressions of emotion and can also be seen on other ERP components such as P1 and EPN, was investigated. Using eye-tracking to manipulate fixation on facial features, we found the N170 to be the only eye-sensitive component and this was true for fearful, happy and neutral faces. A different effect of fixation to features was seen for the earlier P1 that likely reflected general sensitivity to face position. An early effect of emotion (~120 ms) for happy faces was seen at occipital sites and was sustained until ~350 ms post-stimulus. For fearful faces, an early effect was seen around 80 ms followed by a later effect appearing at ~150 ms until ~300 ms at lateral posterior sites. Results suggests that in this emotion-irrelevant gender discrimination task, processing of fearful and happy expressions occurred early and largely independently of the eye-sensitivity indexed by the N170. Processing of the two emotions involved different underlying brain networks active at different times. PMID:26277653

New features and improved uncertainty analysis in the NEA nuclear data sensitivity tool (NDaST)

NASA Astrophysics Data System (ADS)

Dyrda, J.; Soppera, N.; Hill, I.; Bossant, M.; Gulliford, J.

2017-09-01

Following the release and initial testing period of the NEA's Nuclear Data Sensitivity Tool [1], new features have been designed and implemented in order to expand its uncertainty analysis capabilities. The aim is to provide a free online tool for integral benchmark testing, that is both efficient and comprehensive, meeting the needs of the nuclear data and benchmark testing communities. New features include access to P1 sensitivities for neutron scattering angular distribution [2] and constrained Chi sensitivities for the prompt fission neutron energy sampling. Both of these are compatible with covariance data accessed via the JANIS nuclear data software, enabling propagation of the resultant uncertainties in keff to a large series of integral experiment benchmarks. These capabilities are available using a number of different covariance libraries e.g., ENDF/B, JEFF, JENDL and TENDL, allowing comparison of the broad range of results it is possible to obtain. The IRPhE database of reactor physics measurements is now also accessible within the tool in addition to the criticality benchmarks from ICSBEP. Other improvements include the ability to determine and visualise the energy dependence of a given calculated result in order to better identify specific regions of importance or high uncertainty contribution. Sorting and statistical analysis of the selected benchmark suite is now also provided. Examples of the plots generated by the software are included to illustrate such capabilities. Finally, a number of analytical expressions, for example Maxwellian and Watt fission spectra will be included. This will allow the analyst to determine the impact of varying such distributions within the data evaluation, either through adjustment of parameters within the expressions, or by comparison to a more general probability distribution fitted to measured data. The impact of such changes is verified through calculations which are compared to a `direct' measurement found by adjustment of the original ENDF format file.

Pattern Recognition Approaches for Breast Cancer DCE-MRI Classification: A Systematic Review.

PubMed

Fusco, Roberta; Sansone, Mario; Filice, Salvatore; Carone, Guglielmo; Amato, Daniela Maria; Sansone, Carlo; Petrillo, Antonella

2016-01-01

We performed a systematic review of several pattern analysis approaches for classifying breast lesions using dynamic, morphological, and textural features in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Several machine learning approaches, namely artificial neural networks (ANN), support vector machines (SVM), linear discriminant analysis (LDA), tree-based classifiers (TC), and Bayesian classifiers (BC), and features used for classification are described. The findings of a systematic review of 26 studies are presented. The sensitivity and specificity are respectively 91 and 83 % for ANN, 85 and 82 % for SVM, 96 and 85 % for LDA, 92 and 87 % for TC, and 82 and 85 % for BC. The sensitivity and specificity are respectively 82 and 74 % for dynamic features, 93 and 60 % for morphological features, 88 and 81 % for textural features, 95 and 86 % for a combination of dynamic and morphological features, and 88 and 84 % for a combination of dynamic, morphological, and other features. LDA and TC have the best performance. A combination of dynamic and morphological features gives the best performance.

Long-term reproducibility of relative sensitivity factors obtained with CAMECA Wf

NASA Astrophysics Data System (ADS)

Gui, D.; Xing, Z. X.; Huang, Y. H.; Mo, Z. Q.; Hua, Y. N.; Zhao, S. P.; Cha, L. Z.

2008-12-01

As the wafer size continues to increase and the feature size of the integrated circuits (IC) continues to shrink, process control of IC manufacturing becomes ever more important to reduce the cost of failures caused by the drift of processes or equipments. Characterization tools with high precision and reproducibility are required to capture any abnormality of the process. Although Secondary ion mass spectrometry (SIMS) has been widely used in dopant profile control, it was reported that magnetic sector SIMS, compared to quadrupole SIMS, has lower short-term repeatability and long-term reproducibility due to the high extraction field applied between sample and extraction lens. In this paper, we demonstrate that CAMECA Wf can deliver high long-term reproducibility because of its high-level automation and improved design of immersion lens. The relative standard deviation (R.S.D.) of the relative sensitivity factors (RSF) of three typical elements, i.e., boron (B), phosphorous (P) and nitrogen (N), over 3 years are 3.7%, 5.5% and 4.1%, respectively. The high reproducibility results have a practical implication that deviation can be estimated without testing the standards.

Inductively coupled plasma mass spectrometry (ICP MS): a versatile tool.

PubMed

Ammann, Adrian A

2007-04-01

Inductively coupled plasma (ICP) mass spectrometry (MS) is routinely used in many diverse research fields such as earth, environmental, life and forensic sciences and in food, material, chemical, semiconductor and nuclear industries. The high ion density and the high temperature in a plasma provide an ideal atomizer and element ionizer for all types of samples and matrices introduced by a variety of specialized devices. Outstanding properties such as high sensitivity (ppt-ppq), relative salt tolerance, compound-independent element response and highest quantitation accuracy lead to the unchallenged performance of ICP MS in efficiently detecting, identifying and reliably quantifying trace elements. The increasing availability of relevant reference compounds and high separation selectivity extend the molecular identification capability of ICP MS hyphenated to species-specific separation techniques. While molecular ion source MS is specialized in determining the structure of unknown molecules, ICP MS is an efficient and highly sensitive tool for target-element orientated discoveries of relevant and unknown compounds. This special-feature, tutorial article presents the principle and advantages of ICP MS, highlighting these using examples from recently published investigations. Copyright 2007 John Wiley & Sons, Ltd.

Development and evaluation of a computer-aided diagnostic scheme for lung nodule detection in chest radiographs by means of two-stage nodule enhancement with support vector classification

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

Chen Sheng; Suzuki, Kenji; MacMahon, Heber

2011-04-15

Purpose: To develop a computer-aided detection (CADe) scheme for nodules in chest radiographs (CXRs) with a high sensitivity and a low false-positive (FP) rate. Methods: The authors developed a CADe scheme consisting of five major steps, which were developed for improving the overall performance of CADe schemes. First, to segment the lung fields accurately, the authors developed a multisegment active shape model. Then, a two-stage nodule-enhancement technique was developed for improving the conspicuity of nodules. Initial nodule candidates were detected and segmented by using the clustering watershed algorithm. Thirty-one shape-, gray-level-, surface-, and gradient-based features were extracted from each segmentedmore » candidate for determining the feature space, including one of the new features based on the Canny edge detector to eliminate a major FP source caused by rib crossings. Finally, a nonlinear support vector machine (SVM) with a Gaussian kernel was employed for classification of the nodule candidates. Results: To evaluate and compare the scheme to other published CADe schemes, the authors used a publicly available database containing 140 nodules in 140 CXRs and 93 normal CXRs. The CADe scheme based on the SVM classifier achieved sensitivities of 78.6% (110/140) and 71.4% (100/140) with averages of 5.0 (1165/233) FPs/image and 2.0 (466/233) FPs/image, respectively, in a leave-one-out cross-validation test, whereas the CADe scheme based on a linear discriminant analysis classifier had a sensitivity of 60.7% (85/140) at an FP rate of 5.0 FPs/image. For nodules classified as ''very subtle'' and ''extremely subtle,'' a sensitivity of 57.1% (24/42) was achieved at an FP rate of 5.0 FPs/image. When the authors used a database developed at the University of Chicago, the sensitivities was 83.3% (40/48) and 77.1% (37/48) at an FP rate of 5.0 (240/48) FPs/image and 2.0 (96/48) FPs /image, respectively. Conclusions: These results compare favorably to those described for other commercial and noncommercial CADe nodule detection systems.« less

Recognizing emotions from EEG subbands using wavelet analysis.

PubMed

Candra, Henry; Yuwono, Mitchell; Handojoseno, Ardi; Chai, Rifai; Su, Steven; Nguyen, Hung T

2015-01-01

Objectively recognizing emotions is a particularly important task to ensure that patients with emotional symptoms are given the appropriate treatments. The aim of this study was to develop an emotion recognition system using Electroencephalogram (EEG) signals to identify four emotions including happy, sad, angry, and relaxed. We approached this objective by firstly investigating the relevant EEG frequency band followed by deciding the appropriate feature extraction method. Two features were considered namely: 1. Wavelet Energy, and 2. Wavelet Entropy. EEG Channels reduction was then implemented to reduce the complexity of the features. The ground truth emotional states of each subject were inferred using Russel's circumplex model of emotion, that is, by mapping the subjectively reported degrees of valence (pleasure) and arousal to the appropriate emotions - for example, an emotion with high valence and high arousal is equivalent to a `happy' emotional state, while low valence and low arousal is equivalent to a `sad' emotional state. The Support Vector Machine (SVM) classifier was then used for mapping each feature vector into corresponding discrete emotions. The results presented in this study indicated thatWavelet features extracted from alpha, beta and gamma bands seem to provide the necessary information for describing the aforementioned emotions. Using the DEAP (Dataset for Emotion Analysis using electroencephalogram, Physiological and Video Signals), our proposed method achieved an average sensitivity and specificity of 77.4% ± 14.1% and 69.1% ± 12.8%, respectively.

Conditional Variational Autoencoder for Prediction and Feature Recovery Applied to Intrusion Detection in IoT.

PubMed

Lopez-Martin, Manuel; Carro, Belen; Sanchez-Esguevillas, Antonio; Lloret, Jaime

2017-08-26

The purpose of a Network Intrusion Detection System is to detect intrusive, malicious activities or policy violations in a host or host's network. In current networks, such systems are becoming more important as the number and variety of attacks increase along with the volume and sensitiveness of the information exchanged. This is of particular interest to Internet of Things networks, where an intrusion detection system will be critical as its economic importance continues to grow, making it the focus of future intrusion attacks. In this work, we propose a new network intrusion detection method that is appropriate for an Internet of Things network. The proposed method is based on a conditional variational autoencoder with a specific architecture that integrates the intrusion labels inside the decoder layers. The proposed method is less complex than other unsupervised methods based on a variational autoencoder and it provides better classification results than other familiar classifiers. More important, the method can perform feature reconstruction, that is, it is able to recover missing features from incomplete training datasets. We demonstrate that the reconstruction accuracy is very high, even for categorical features with a high number of distinct values. This work is unique in the network intrusion detection field, presenting the first application of a conditional variational autoencoder and providing the first algorithm to perform feature recovery.

Conditional Variational Autoencoder for Prediction and Feature Recovery Applied to Intrusion Detection in IoT

PubMed Central

Carro, Belen; Sanchez-Esguevillas, Antonio

2017-01-01

The purpose of a Network Intrusion Detection System is to detect intrusive, malicious activities or policy violations in a host or host’s network. In current networks, such systems are becoming more important as the number and variety of attacks increase along with the volume and sensitiveness of the information exchanged. This is of particular interest to Internet of Things networks, where an intrusion detection system will be critical as its economic importance continues to grow, making it the focus of future intrusion attacks. In this work, we propose a new network intrusion detection method that is appropriate for an Internet of Things network. The proposed method is based on a conditional variational autoencoder with a specific architecture that integrates the intrusion labels inside the decoder layers. The proposed method is less complex than other unsupervised methods based on a variational autoencoder and it provides better classification results than other familiar classifiers. More important, the method can perform feature reconstruction, that is, it is able to recover missing features from incomplete training datasets. We demonstrate that the reconstruction accuracy is very high, even for categorical features with a high number of distinct values. This work is unique in the network intrusion detection field, presenting the first application of a conditional variational autoencoder and providing the first algorithm to perform feature recovery. PMID:28846608

Development of machine learning models for diagnosis of glaucoma.

PubMed

Kim, Seong Jae; Cho, Kyong Jin; Oh, Sejong

2017-01-01

The study aimed to develop machine learning models that have strong prediction power and interpretability for diagnosis of glaucoma based on retinal nerve fiber layer (RNFL) thickness and visual field (VF). We collected various candidate features from the examination of retinal nerve fiber layer (RNFL) thickness and visual field (VF). We also developed synthesized features from original features. We then selected the best features proper for classification (diagnosis) through feature evaluation. We used 100 cases of data as a test dataset and 399 cases of data as a training and validation dataset. To develop the glaucoma prediction model, we considered four machine learning algorithms: C5.0, random forest (RF), support vector machine (SVM), and k-nearest neighbor (KNN). We repeatedly composed a learning model using the training dataset and evaluated it by using the validation dataset. Finally, we got the best learning model that produces the highest validation accuracy. We analyzed quality of the models using several measures. The random forest model shows best performance and C5.0, SVM, and KNN models show similar accuracy. In the random forest model, the classification accuracy is 0.98, sensitivity is 0.983, specificity is 0.975, and AUC is 0.979. The developed prediction models show high accuracy, sensitivity, specificity, and AUC in classifying among glaucoma and healthy eyes. It will be used for predicting glaucoma against unknown examination records. Clinicians may reference the prediction results and be able to make better decisions. We may combine multiple learning models to increase prediction accuracy. The C5.0 model includes decision rules for prediction. It can be used to explain the reasons for specific predictions.

A Highly Sensitive Diagnostic System for Detecting Dengue Viruses Using the Interaction between a Sulfated Sugar Chain and a Virion.

PubMed

Saksono, Budi; Dewi, Beti Ernawati; Nainggolan, Leonardo; Suda, Yasuo

2015-01-01

We propose a novel method of detecting trace amounts of dengue virus (DENVs) from serum. Our method is based on the interaction between a sulfated sugar chain and a DENV surface glycoprotein. After capturing DENV with the sulfated sugar chain-immobilized gold nanoparticles (SGNPs), the resulting complex is precipitated and viral RNA content is measured using the reverse-transcription quantitative polymerase chain reaction SYBR Green I (RT-qPCR-Syb) method. Sugar chains that bind to DENVs were identified using the array-type sugar chain immobilized chip (Sugar Chip) and surface plasmon resonance (SPR) imaging. Heparin and low-molecular-weight dextran sulfate were identified as binding partners, and immobilized on gold nanoparticles to prepare 3 types of SGNPs. The capacity of these SGNPs to capture and concentrate trace amounts of DENVs was evaluated in vitro. The SGNP with greatest sensitivity was tested using clinical samples in Indonesia in 2013-2014. As a result, the novel method was able to detect low concentrations of DENVs using only 6 μL of serum, with similar sensitivity to that of a Qiagen RNA extraction kit using 140 μL of serum. In addition, this method allows for multiplex-like identification of serotypes of DENVs. This feature is important for good healthcare management of DENV infection in order to safely diagnose the dangerous, highly contagious disease quickly, with high sensitivity.

Non-Faradaic Electrochemical Detection of Exocytosis from Mast and Chromaffin Cells Using Floating-Gate MOS Transistors.

PubMed

Jayant, Krishna; Singhai, Amit; Cao, Yingqiu; Phelps, Joshua B; Lindau, Manfred; Holowka, David A; Baird, Barbara A; Kan, Edwin C

2015-12-21

We present non-faradaic electrochemical recordings of exocytosis from populations of mast and chromaffin cells using chemoreceptive neuron MOS (CνMOS) transistors. In comparison to previous cell-FET-biosensors, the CνMOS features control (CG), sensing (SG) and floating gates (FG), allows the quiescent point to be independently controlled, is CMOS compatible and physically isolates the transistor channel from the electrolyte for stable long-term recordings. We measured exocytosis from RBL-2H3 mast cells sensitized by IgE (bound to high-affinity surface receptors FcεRI) and stimulated using the antigen DNP-BSA. Quasi-static I-V measurements reflected a slow shift in surface potential () which was dependent on extracellular calcium ([Ca]o) and buffer strength, which suggests sensitivity to protons released during exocytosis. Fluorescent imaging of dextran-labeled vesicle release showed evidence of a similar time course, while un-sensitized cells showed no response to stimulation. Transient recordings revealed fluctuations with a rapid rise and slow decay. Chromaffin cells stimulated with high KCl showed both slow shifts and extracellular action potentials exhibiting biphasic and inverted capacitive waveforms, indicative of varying ion-channel distributions across the cell-transistor junction. Our approach presents a facile method to simultaneously monitor exocytosis and ion channel activity with high temporal sensitivity without the need for redox chemistry.

Non-Faradaic Electrochemical Detection of Exocytosis from Mast and Chromaffin Cells Using Floating-Gate MOS Transistors

PubMed Central

Jayant, Krishna; Singhai, Amit; Cao, Yingqiu; Phelps, Joshua B.; Lindau, Manfred; Holowka, David A.; Baird, Barbara A.; Kan, Edwin C.

2015-01-01

We present non-faradaic electrochemical recordings of exocytosis from populations of mast and chromaffin cells using chemoreceptive neuron MOS (CνMOS) transistors. In comparison to previous cell-FET-biosensors, the CνMOS features control (CG), sensing (SG) and floating gates (FG), allows the quiescent point to be independently controlled, is CMOS compatible and physically isolates the transistor channel from the electrolyte for stable long-term recordings. We measured exocytosis from RBL-2H3 mast cells sensitized by IgE (bound to high-affinity surface receptors FcεRI) and stimulated using the antigen DNP-BSA. Quasi-static I-V measurements reflected a slow shift in surface potential () which was dependent on extracellular calcium ([Ca]o) and buffer strength, which suggests sensitivity to protons released during exocytosis. Fluorescent imaging of dextran-labeled vesicle release showed evidence of a similar time course, while un-sensitized cells showed no response to stimulation. Transient recordings revealed fluctuations with a rapid rise and slow decay. Chromaffin cells stimulated with high KCl showed both slow shifts and extracellular action potentials exhibiting biphasic and inverted capacitive waveforms, indicative of varying ion-channel distributions across the cell-transistor junction. Our approach presents a facile method to simultaneously monitor exocytosis and ion channel activity with high temporal sensitivity without the need for redox chemistry. PMID:26686301

Electronic Raman scattering as an ultra-sensitive probe of strain effects in semiconductors

DOE PAGES

Fluegel., Brian; Mialitsin, Aleksej V.; Beaton, Daniel A.; ...

2015-05-28

In this study, the semiconductor strain engineering has become a critical feature of high-performance electronics because of the significant device performance enhancements that it enables. These improvements, which emerge from strain-induced modifications to the electronic band structure, necessitate new ultra-sensitive tools to probe the strain in semiconductors. Here, we demonstrate that minute amounts of strain in thin semiconductor epilayers can be measured using electronic Raman scattering. We applied this strain measurement technique to two different semiconductor alloy systems using coherently strained epitaxial thin films specifically designed to produce lattice-mismatch strains as small as 10 –4. Comparing our strain sensitivity andmore » signal strength in Al xGa 1–xAs with those obtained using the industry-standard technique of phonon Raman scattering, we found that there was a sensitivity improvement of 200-fold and a signal enhancement of 4 × 10 3, thus obviating key constraints in semiconductor strain metrology.« less

A sensitivity-enhanced refractive index sensor using a single-mode thin-core fiber incorporating an abrupt taper.

PubMed

Shi, Jie; Xiao, Shilin; Yi, Lilin; Bi, Meihua

2012-01-01

A sensitivity-enhanced fiber-optic refractive index (RI) sensor based on a tapered single-mode thin-core diameter fiber is proposed and experimentally demonstrated. The sensor head is formed by splicing a section of tapered thin-core diameter fiber (TCF) between two sections of single-mode fibers (SMFs). The cladding modes are excited at the first SMF-TCF interface, and then interfere with the core mode at the second interface, thus forming an inter-modal interferometer (IMI). An abrupt taper (tens of micrometers long) made by the electric-arc-heating method is utilized, and plays an important role in improving sensing sensitivity. The whole manufacture process only involves fiber splicing and tapering, and all the fabrication process can be achieved by a commercial fiber fusion splicer. Using glycerol and water mixture solution as an example, the experimental results show that the refractive index sensitivity is measured to be 0.591 nm for 1% change of surrounding RI. The proposed sensor structure features simple structure, low cost, easy fabrication, and high sensitivity.

Prostate cancer detection using machine learning techniques by employing combination of features extracting strategies.

PubMed

Hussain, Lal; Ahmed, Adeel; Saeed, Sharjil; Rathore, Saima; Awan, Imtiaz Ahmed; Shah, Saeed Arif; Majid, Abdul; Idris, Adnan; Awan, Anees Ahmed

2018-02-06

Prostate is a second leading causes of cancer deaths among men. Early detection of cancer can effectively reduce the rate of mortality caused by Prostate cancer. Due to high and multiresolution of MRIs from prostate cancer require a proper diagnostic systems and tools. In the past researchers developed Computer aided diagnosis (CAD) systems that help the radiologist to detect the abnormalities. In this research paper, we have employed novel Machine learning techniques such as Bayesian approach, Support vector machine (SVM) kernels: polynomial, radial base function (RBF) and Gaussian and Decision Tree for detecting prostate cancer. Moreover, different features extracting strategies are proposed to improve the detection performance. The features extracting strategies are based on texture, morphological, scale invariant feature transform (SIFT), and elliptic Fourier descriptors (EFDs) features. The performance was evaluated based on single as well as combination of features using Machine Learning Classification techniques. The Cross validation (Jack-knife k-fold) was performed and performance was evaluated in term of receiver operating curve (ROC) and specificity, sensitivity, Positive predictive value (PPV), negative predictive value (NPV), false positive rate (FPR). Based on single features extracting strategies, SVM Gaussian Kernel gives the highest accuracy of 98.34% with AUC of 0.999. While, using combination of features extracting strategies, SVM Gaussian kernel with texture + morphological, and EFDs + morphological features give the highest accuracy of 99.71% and AUC of 1.00.

Take a byte out of MEEF: VAMPIRE: Vehicle for Advanced Mask Pattern Inspection Readiness Evaluations

NASA Astrophysics Data System (ADS)

Badger, Karen D.; Rankin, Jed; Turley, Christina; Seki, Kazunori; Dechene, Dan J.; Abdelghany, Hesham

2016-09-01

MEEF, or Mask Error Enhancement Factor, is simply defined as the ratio of the change in printed wafer feature width to the change in mask feature width scaled to wafer level. It is important in chip manufacturing that leads to the amplification of mask errors, creating challenges with both achieving dimensional control tolerances and ensuring defect free masks, as measured by on-wafer image quality. As lithographic imaging continues to be stressed, using lower and lower k1 factor resolution enhancement techniques, the high MEEF areas present on advanced optical masks creates an environment where the need for increased mask defect sensitivity in high-MEEF areas becomes more and more critical. There are multiple approaches to mask inspection that may or may not provide enough sensitivity to detect all wafer-printable defects; the challenge in the application of these techniques is simultaneously maintaining an acceptable level of mask inspectability. The higher the MEEF, the harder the challenge will be to achieve and appropriate level of sensitivity while maintaining inspectability…and to do so on the geometries that matter. The predominant photomask fabrication inspection approach in use today compares the features on the reticle directly with the design database using high-NA optics. This approach has the ability to detect small defects, however, when inspecting aggressive OPC, it can lead to the over-detection of inconsequential, or nuisance defects. To minimize these nuisance detections, changing the sensitivity of the inspection can improve the inspectability of a mask inspected in high-NA mode, however, it leads to the inability to detect subtle, yet wafer-printable defects in High-MEEF geometry, due to the fact that this `desense' must be applied globally. There are also `lithography-emulating' approaches to inspection that use various means to provide high defect sensitivity and the ability to tolerate inconsequential, non-printing defects by using scanner-like conditions to determine which defects are wafer printable. This inspection technique is commonly referred to as being `lithography plane' or `litho plane,' since it's assessing the mask quality based on how the mask appears to the imaging optics during use, as proposed to traditional `reticle plane' inspection which is comparing the mask only with its target design. Regardless of how the defects are detected, the real question is when should they be detected? For larger technology nodes, defects are considered `statistical risks'…i.e., first they have to occur, and then they have to fall in high-MEEF areas in order to be of concern, and be below the detection limits of traditional reticle-plane inspection. In short, the `perfect storm' has to happen in order to miss printable defects using well-optimized traditional inspection approaches. The introduction of lithographic inspection techniques has revealed this statistical game is a much higher risk than originally estimated, in that very subtle waferprintable CD errors typically fall into the desense band for traditional reticle plane inspection. Because printability is largely influenced by MEEF, designs with high-MEEF values are at greater risk of traditional inspection missing printable CD errors. The question is… how high is high… and at what MEEF is optical inspection at the reticle plane sufficient? This paper will provide evaluation results for both reticle-plane and litho-plane inspections as they pertain to varying degrees of MEEF. A newly designed high-MEEF programmed defect test mask, named VAMPIRE, will be introduced. This test mask is based on 7 nm node technology and contains intentionally varying degrees of MEEF as well as a variety of programmed defects in high-MEEF environments…all of which have been verified for defect lithographic significance on a Zeiss AIMS system.

Chemical Sensing Applications of ZnO Nanomaterials

PubMed Central

Chaudhary, Savita; Umar, Ahmad; Bhasin, K. K.

2018-01-01

Recent advancement in nanoscience and nanotechnology has witnessed numerous triumphs of zinc oxide (ZnO) nanomaterials due to their various exotic and multifunctional properties and wide applications. As a remarkable and functional material, ZnO has attracted extensive scientific and technological attention, as it combines different properties such as high specific surface area, biocompatibility, electrochemical activities, chemical and photochemical stability, high-electron communicating features, non-toxicity, ease of syntheses, and so on. Because of its various interesting properties, ZnO nanomaterials have been used for various applications ranging from electronics to optoelectronics, sensing to biomedical and environmental applications. Further, due to the high electrochemical activities and electron communication features, ZnO nanomaterials are considered as excellent candidates for electrochemical sensors. The present review meticulously introduces the current advancements of ZnO nanomaterial-based chemical sensors. Various operational factors such as the effect of size, morphologies, compositions and their respective working mechanisms along with the selectivity, sensitivity, detection limit, stability, etc., are discussed in this article. PMID:29439528

Smartphone-Based Fluorescent Diagnostic System for Highly Pathogenic H5N1 Viruses.

PubMed

Yeo, Seon-Ju; Choi, Kyunghan; Cuc, Bui Thi; Hong, Nguyen Ngoc; Bao, Duong Tuan; Ngoc, Nguyen Minh; Le, Mai Quynh; Hang, Nguyen Le Khanh; Thach, Nguyen Co; Mallik, Shyam Kumar; Kim, Hak Sung; Chong, Chom-Kyu; Choi, Hak Soo; Sung, Haan Woo; Yu, Kyoungsik; Park, Hyun

2016-01-01

Field diagnostic tools for avian influenza (AI) are indispensable for the prevention and controlled management of highly pathogenic AI-related diseases. More accurate, faster and networked on-site monitoring is demanded to detect such AI viruses with high sensitivity as well as to maintain up-to-date information about their geographical transmission. In this work, we assessed the clinical and field-level performance of a smartphone-based fluorescent diagnostic device with an efficient reflective light collection module using a coumarin-derived dendrimer-based fluorescent lateral flow immunoassay. By application of an optimized bioconjugate, a smartphone-based diagnostic device had a two-fold higher detectability as compared to that of the table-top fluorescence strip reader for three different AI subtypes (H5N3, H7N1, and H9N2). Additionally, in a clinical study of H5N1-confirmed patients, the smartphone-based diagnostic device showed a sensitivity of 96.55% (28/29) [95% confidence interval (CI): 82.24 to 99.91] and a specificity of 98.55% (68/69) (95% CI: 92.19 to 99.96). The measurement results from the distributed individual smartphones were wirelessly transmitted via short messaging service and collected by a centralized database system for further information processing and data mining. Smartphone-based diagnosis provided highly sensitive measurement results for H5N1 detection within 15 minutes. Because of its high sensitivity, portability and automatic reporting feature, the proposed device will enable agile identification of patients and efficient control of AI dissemination.

Smartphone-Based Fluorescent Diagnostic System for Highly Pathogenic H5N1 Viruses

PubMed Central

Yeo, Seon-Ju; Choi, Kyunghan; Cuc, Bui Thi; Hong, Nguyen Ngoc; Bao, Duong Tuan; Ngoc, Nguyen Minh; Le, Mai Quynh; Hang, Nguyen Le Khanh; Thach, Nguyen Co; Mallik, Shyam Kumar; Kim, Hak Sung; Chong, Chom-Kyu; Choi, Hak Soo; Sung, Haan Woo; Yu, Kyoungsik; Park, Hyun

2016-01-01

Field diagnostic tools for avian influenza (AI) are indispensable for the prevention and controlled management of highly pathogenic AI-related diseases. More accurate, faster and networked on-site monitoring is demanded to detect such AI viruses with high sensitivity as well as to maintain up-to-date information about their geographical transmission. In this work, we assessed the clinical and field-level performance of a smartphone-based fluorescent diagnostic device with an efficient reflective light collection module using a coumarin-derived dendrimer-based fluorescent lateral flow immunoassay. By application of an optimized bioconjugate, a smartphone-based diagnostic device had a two-fold higher detectability as compared to that of the table-top fluorescence strip reader for three different AI subtypes (H5N3, H7N1, and H9N2). Additionally, in a clinical study of H5N1-confirmed patients, the smartphone-based diagnostic device showed a sensitivity of 96.55% (28/29) [95% confidence interval (CI): 82.24 to 99.91] and a specificity of 98.55% (68/69) (95% CI: 92.19 to 99.96). The measurement results from the distributed individual smartphones were wirelessly transmitted via short messaging service and collected by a centralized database system for further information processing and data mining. Smartphone-based diagnosis provided highly sensitive measurement results for H5N1 detection within 15 minutes. Because of its high sensitivity, portability and automatic reporting feature, the proposed device will enable agile identification of patients and efficient control of AI dissemination. PMID:26877781

Association of pentraxin and high-sensitive C-reactive protein as inflammatory biomarkers in patients with chronic periodontitis and peripheral arterial disease.

PubMed

Boyapati, Ramanarayana; Chinthalapani, Srikanth; Ramisetti, Arpita; Salavadhi, Shyam Sunder; Ramachandran, Radhika

2018-01-01

Inflammation is a common feature of both peripheral artery disease (PAD) and periodontal disease. The aim of this study is to evaluate the relationship between PAD and periodontal disease by examining the levels of inflammatory cytokines, pentraxin-3 (PTX-3), and high-sensitive C-reactive protein from serum. A total of 50 patients were included in this cross-sectional study. Patients were divided into two groups: those with PAD (test group) and those with the non-PAD group (control group) based on ankle-brachial index values. Periodontal examinations and biochemical analysis for PTX-3 and high-sensitive C-reactive protein were performed to compare the two groups. All the obtained data were sent for statistical analyses using SPSS version 18. In the clinical parameters, there is statistically significant difference present between plaque index, clinical attachment loss, and periodontal inflammatory surface area with higher mean values in patients with PAD having periodontitis. There is statistical significant ( P < 0.01) difference in all biochemical parameters ( P < 0.05) considered in the study between PAD patients and non-PAD patients with higher mean values of total cholesterol (TC), low-density lipoprotein (LDL), high-sensitive C-reactive protein (hs-CRP), and PTX-3. PTX-3 and acute-phase cytokine such as hs-CRP can be regarded as one of the best indicators to show the association between the PAD and periodontitis followed by hs-CRP, TC, very LDL (VLDL), and LDL. However, high-density lipoprotein (HDL) is a poor indicator for its association with chronic periodontitis and PAD.

Comparison of machine learning methods for classifying mediastinal lymph node metastasis of non-small cell lung cancer from 18F-FDG PET/CT images.

PubMed

Wang, Hongkai; Zhou, Zongwei; Li, Yingci; Chen, Zhonghua; Lu, Peiou; Wang, Wenzhi; Liu, Wanyu; Yu, Lijuan

2017-12-01

This study aimed to compare one state-of-the-art deep learning method and four classical machine learning methods for classifying mediastinal lymph node metastasis of non-small cell lung cancer (NSCLC) from 18 F-FDG PET/CT images. Another objective was to compare the discriminative power of the recently popular PET/CT texture features with the widely used diagnostic features such as tumor size, CT value, SUV, image contrast, and intensity standard deviation. The four classical machine learning methods included random forests, support vector machines, adaptive boosting, and artificial neural network. The deep learning method was the convolutional neural networks (CNN). The five methods were evaluated using 1397 lymph nodes collected from PET/CT images of 168 patients, with corresponding pathology analysis results as gold standard. The comparison was conducted using 10 times 10-fold cross-validation based on the criterion of sensitivity, specificity, accuracy (ACC), and area under the ROC curve (AUC). For each classical method, different input features were compared to select the optimal feature set. Based on the optimal feature set, the classical methods were compared with CNN, as well as with human doctors from our institute. For the classical methods, the diagnostic features resulted in 81~85% ACC and 0.87~0.92 AUC, which were significantly higher than the results of texture features. CNN's sensitivity, specificity, ACC, and AUC were 84, 88, 86, and 0.91, respectively. There was no significant difference between the results of CNN and the best classical method. The sensitivity, specificity, and ACC of human doctors were 73, 90, and 82, respectively. All the five machine learning methods had higher sensitivities but lower specificities than human doctors. The present study shows that the performance of CNN is not significantly different from the best classical methods and human doctors for classifying mediastinal lymph node metastasis of NSCLC from PET/CT images. Because CNN does not need tumor segmentation or feature calculation, it is more convenient and more objective than the classical methods. However, CNN does not make use of the import diagnostic features, which have been proved more discriminative than the texture features for classifying small-sized lymph nodes. Therefore, incorporating the diagnostic features into CNN is a promising direction for future research.

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

Kirtley, John R., E-mail: jkirtley@stanford.edu; Rosenberg, Aaron J.; Palmstrom, Johanna C.

Superconducting QUantum Interference Device (SQUID) microscopy has excellent magnetic field sensitivity, but suffers from modest spatial resolution when compared with other scanning probes. This spatial resolution is determined by both the size of the field sensitive area and the spacing between this area and the sample surface. In this paper we describe scanning SQUID susceptometers that achieve sub-micron spatial resolution while retaining a white noise floor flux sensitivity of ≈2μΦ{sub 0}/Hz{sup 1/2}. This high spatial resolution is accomplished by deep sub-micron feature sizes, well shielded pickup loops fabricated using a planarized process, and a deep etch step that minimizes themore » spacing between the sample surface and the SQUID pickup loop. We describe the design, modeling, fabrication, and testing of these sensors. Although sub-micron spatial resolution has been achieved previously in scanning SQUID sensors, our sensors not only achieve high spatial resolution but also have integrated modulation coils for flux feedback, integrated field coils for susceptibility measurements, and batch processing. They are therefore a generally applicable tool for imaging sample magnetization, currents, and susceptibilities with higher spatial resolution than previous susceptometers.« less

A nanoscale Zr-based fluorescent metal-organic framework for selective and sensitive detection of hydrogen sulfide

NASA Astrophysics Data System (ADS)

Li, Yanping; Zhang, Xin; Zhang, Ling; Jiang, Ke; Cui, Yuanjing; Yang, Yu; Qian, Guodong

2017-11-01

Hydrogen sulfide (H2S) has been commonly viewed as a gas signaling molecule in various physiological and pathological processes. However, the highly efficient H2S detection still remains challenging. Herein, we designed a new robust nano metal-organic framework (MOF) UiO-66-CH=CH2 as a fluorescent probe for rapid, sensitive and selective detection of biological H2S. UiO-66-CH=CH2 was prepared by heating ZrCl4 and 2-vinylterephthalic acid via a simple method. UiO-66-CH=CH2 displayed fluorescence quenching to H2S and kept excellent selectivity in the presence of biological relevant analytes especially the cysteine and glutathione. This MOF-based probe also exhibited fast response (10 s) and high sensitivity with a detection limit of 6.46 μM which was within the concentration range of biological H2S in living system. Moreover, this constructed MOF featured water-stability, nanoscale (20-30 nm) and low toxicity, which made it a promising candidate for biological H2S sensing.

Preparation of highly stable fullerene C60 decorated graphene oxide nanocomposite and its sensitive electrochemical detection of dopamine in rat brain and pharmaceutical samples.

PubMed

Thirumalraj, Balamurugan; Palanisamy, Selvakumar; Chen, Shen-Ming; Lou, Bih-Show

2016-01-15

The research community has continuously paid much attention on the preparation of hybrid of carbon nanomaterials owing to combine their unique properties. Herein, we report the preparation of highly stable fullerene C60 (C60) wrapped graphene oxide (GO) nanocomposite by using a simple sonication method. The fabricated GO-C60 nanocomposite modified glassy carbon electrode shows a good sensitivity and lower oxidation overpotential towards dopamine (DA) than that of pristine GO and C60. The fabricated sensor detects the DA in the linear response range of 0.02-73.5μM. The limit of detection is estimated to be 0.008μM based on 3σ with a sensitivity of 4.23μAμM(-1)cm(-2). The fabricated sensor also exhibits other features such as good selectivity, stability, reproducibility and repeatability. The proposed sensor exhibits good practicality towards the detection of DA in rat brain and commercial DA injection samples. Copyright © 2015 Elsevier Inc. All rights reserved.

Translational Research and Plasma Proteomic in Cancer.

PubMed

Santini, Annamaria Chiara; Giovane, Giancarlo; Auletta, Adelaide; Di Carlo, Angelina; Fiorelli, Alfonso; Cito, Letizia; Astarita, Carlo; Giordano, Antonio; Alfano, Roberto; Feola, Antonia; Di Domenico, Marina

2016-04-01

Proteomics is a recent field of research in molecular biology that can help in the fight against cancer through the search for biomarkers that can detect this disease in the early stages of its development. Proteomic is a speedily growing technology, also thanks to the development of even more sensitive and fast mass spectrometry analysis. Although this technique is the most widespread for the discovery of new cancer biomarkers, it still suffers of a poor sensitivity and insufficient reproducibility, essentially due to the tumor heterogeneity. Common technical shortcomings include limitations in the sensitivity of detecting low abundant biomarkers and possible systematic biases in the observed data. Current research attempts are trying to develop high-resolution proteomic instrumentation for high-throughput monitoring of protein changes that occur in cancer. In this review, we describe the basic features of the proteomic tools which have proven to be useful in cancer research, showing their advantages and disadvantages. The application of these proteomic tools could provide early biomarkers detection in various cancer types and could improve the understanding the mechanisms of tumor growth and dissemination. © 2015 Wiley Periodicals, Inc.

Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network

PubMed Central

Li, Ke; Zhang, Qiuju; Wang, Kun; Chen, Peng; Wang, Huaqing

2016-01-01

A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method. PMID:26761006

Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network.

PubMed

Li, Ke; Zhang, Qiuju; Wang, Kun; Chen, Peng; Wang, Huaqing

2016-01-08

A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method.

Protein attributes contribute to halo-stability, bioinformatics approach

PubMed Central

2011-01-01

Halophile proteins can tolerate high salt concentrations. Understanding halophilicity features is the first step toward engineering halostable crops. To this end, we examined protein features contributing to the halo-toleration of halophilic organisms. We compared more than 850 features for halophilic and non-halophilic proteins with various screening, clustering, decision tree, and generalized rule induction models to search for patterns that code for halo-toleration. Up to 251 protein attributes selected by various attribute weighting algorithms as important features contribute to halo-stability; from them 14 attributes selected by 90% of models and the count of hydrogen gained the highest value (1.0) in 70% of attribute weighting models, showing the importance of this attribute in feature selection modeling. The other attributes mostly were the frequencies of di-peptides. No changes were found in the numbers of groups when K-Means and TwoStep clustering modeling were performed on datasets with or without feature selection filtering. Although the depths of induced trees were not high, the accuracies of trees were higher than 94% and the frequency of hydrophobic residues pointed as the most important feature to build trees. The performance evaluation of decision tree models had the same values and the best correctness percentage recorded with the Exhaustive CHAID and CHAID models. We did not find any significant difference in the percent of correctness, performance evaluation, and mean correctness of various decision tree models with or without feature selection. For the first time, we analyzed the performance of different screening, clustering, and decision tree algorithms for discriminating halophilic and non-halophilic proteins and the results showed that amino acid composition can be used to discriminate between halo-tolerant and halo-sensitive proteins. PMID:21592393

A generalized procedure for analyzing sustained and dynamic vocal fold vibrations from laryngeal high-speed videos using phonovibrograms.

PubMed

Unger, Jakob; Schuster, Maria; Hecker, Dietmar J; Schick, Bernhard; Lohscheller, Jörg

2016-01-01

This work presents a computer-based approach to analyze the two-dimensional vocal fold dynamics of endoscopic high-speed videos, and constitutes an extension and generalization of a previously proposed wavelet-based procedure. While most approaches aim for analyzing sustained phonation conditions, the proposed method allows for a clinically adequate analysis of both dynamic as well as sustained phonation paradigms. The analysis procedure is based on a spatio-temporal visualization technique, the phonovibrogram, that facilitates the documentation of the visible laryngeal dynamics. From the phonovibrogram, a low-dimensional set of features is computed using a principle component analysis strategy that quantifies the type of vibration patterns, irregularity, lateral symmetry and synchronicity, as a function of time. Two different test bench data sets are used to validate the approach: (I) 150 healthy and pathologic subjects examined during sustained phonation. (II) 20 healthy and pathologic subjects that were examined twice: during sustained phonation and a glissando from a low to a higher fundamental frequency. In order to assess the discriminative power of the extracted features, a Support Vector Machine is trained to distinguish between physiologic and pathologic vibrations. The results for sustained phonation sequences are compared to the previous approach. Finally, the classification performance of the stationary analyzing procedure is compared to the transient analysis of the glissando maneuver. For the first test bench the proposed procedure outperformed the previous approach (proposed feature set: accuracy: 91.3%, sensitivity: 80%, specificity: 97%, previous approach: accuracy: 89.3%, sensitivity: 76%, specificity: 96%). Comparing the classification performance of the second test bench further corroborates that analyzing transient paradigms provides clear additional diagnostic value (glissando maneuver: accuracy: 90%, sensitivity: 100%, specificity: 80%, sustained phonation: accuracy: 75%, sensitivity: 80%, specificity: 70%). The incorporation of parameters describing the temporal evolvement of vocal fold vibration clearly improves the automatic identification of pathologic vibration patterns. Furthermore, incorporating a dynamic phonation paradigm provides additional valuable information about the underlying laryngeal dynamics that cannot be derived from sustained conditions. The proposed generalized approach provides a better overall classification performance than the previous approach, and hence constitutes a new advantageous tool for an improved clinical diagnosis of voice disorders. Copyright © 2015 Elsevier B.V. All rights reserved.

The development and advantages of helium ion microscopy for the study of block copolymer nanopatterns

NASA Astrophysics Data System (ADS)

Bell, Alan P.; Senthamaraikannan, Ramsankar; Ghoshal, Tandra; Chaudhari, Atul; Leeson, Michael; Morris, Mick A.

2015-03-01

Helium ion microscopy (HIM) has been used to study nanopatterns formed in block copolymer (BCP) thin films. Owing to its' small spot size, minimal forward scattering of the incident ion and reduced velocity compared to electrons of comparable energy, HIM has considerable advantages and provides pattern information and resolution not attainable with other commercial microscopic techniques. In order to realize the full potential of BCP nanolithography in producing high density ultra-small features, the dimensions and geometry of these BCP materials will need to be accurately characterized through pattern formation, development and pattern transfer processes. The preferred BCP pattern inspection techniques (to date) are principally atomic force microscopy (AFM) and secondary electron microscopy (SEM) but suffer disadvantages in poor lateral resolution (AFM) and the ability to discriminate individual polymer domains (SEM). SEM suffers from reduced resolution when a more surface sensitive low accelerating voltage is used and low surface signal when a high accelerating voltage is used. In addition to these drawbacks, SEM can require the use of a conductive coating on these insulating materials and this reduces surface detail as well as increasing the dimensions of coated features. AFM is limited by the dimensions of the probe tip and a skewing of lateral dimension results. This can be eliminated through basic geometry for large sparse features, but when dense small features need to be characterized AFM lacks reliability. With this in mind, BCP inspection by HIM can offer greater insight into block ordering, critical dimensions and, critically, line edge roughness (LER) a critical parameter whose measurement is well suited to HIM because of its' enhanced edge contrast. In this work we demonstrate the resolution capabilities of HIM using various BCP systems (lamellar and cylinder structures). Imaging of BCP patterns of low molecular weight (MW)/low feature size which challenges the resolution of HIM technique. Further, studies of BCP patterns with domains of similar chemistry will be presented demonstrating the superior chemical contrast compared to SEM. From the data, HIM excels as a BCP inspection tool in four distinct areas. Firstly, HIM offers higher resolution at standard imaging conditions than SEM. Secondly, the signal generated from He+ is more surface sensitive and enables visualization of features that cannot be resolved using SEM. Thirdly; superior chemical contrast enables the imaging of un etched samples with almost identical chemical composition. Finally, dimensional measurement accuracy is high and consistent with requirements for advanced lithographic masks.

The dielectric signature of glass density

NASA Astrophysics Data System (ADS)

Rams-Baron, M.; Wojnarowska, Z.; Knapik-Kowalczuk, J.; Jurkiewicz, K.; Burian, A.; Wojtyniak, M.; Pionteck, J.; Jaworska, M.; Rodríguez-Tinoco, C.; Paluch, M.

2017-09-01

At present, we are witnessing a renewed interest in the properties of densified glasses prepared by isobaric cooling of a liquid at elevated pressure. As high-pressure densification emerges as a promising approach in the development of glasses with customized features, understanding and controlling their unique properties represent a contemporary scientific and technological goal. The results presented herein indicate that the applied high-pressure preparation route leads to a glassy state with higher density (˜1%) and a reduced free volume of about 7%. We show that these subtle structural changes remarkably influence the dielectric response and spectral features of β-relaxation in etoricoxib glass. Our study, combining dynamical and structural techniques, reveal that β-relaxation in etoricoxib is extremely sensitive to the variations in molecular packing and can be used to probe the changes in glass density. Such connection is technologically relevant and may advance further progress in the field.

Short-term dynamics of the high-latitude auroral distribution

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

Murphree, J.S.; Elphinstone, R.D.; Cogger, L.L.

During two consecutive orbits of the Viking satellite on March 24, 1986, UV observations of the northern hemisphere auroral distribution revealed rapid growth and decay of large-scale polar arcs. Evolution of these features occurred from the nightside auroral distribution (to which they are optically connected) toward the dayside. The connection on the dayside was short-lived ({approx} 2 min) and the arc retreated at similar speeds to its development ({approx} 5 km/s). Time scales for growth (at least to the level of the sensitivity of the instrument) can also be less than 1 min. Examples of arc occurrences during a half-hourmore » time period show that arcs can extend from the nightside to the dayside and disappear and another extended arc can appear at a widely separated position. These types of dynamic polar features appear consistent with the dynamic energization and precipitation of boundary layer electrons at high latitudes.« less

Central auditory neurons have composite receptive fields.

PubMed

Kozlov, Andrei S; Gentner, Timothy Q

2016-02-02

High-level neurons processing complex, behaviorally relevant signals are sensitive to conjunctions of features. Characterizing the receptive fields of such neurons is difficult with standard statistical tools, however, and the principles governing their organization remain poorly understood. Here, we demonstrate multiple distinct receptive-field features in individual high-level auditory neurons in a songbird, European starling, in response to natural vocal signals (songs). We then show that receptive fields with similar characteristics can be reproduced by an unsupervised neural network trained to represent starling songs with a single learning rule that enforces sparseness and divisive normalization. We conclude that central auditory neurons have composite receptive fields that can arise through a combination of sparseness and normalization in neural circuits. Our results, along with descriptions of random, discontinuous receptive fields in the central olfactory neurons in mammals and insects, suggest general principles of neural computation across sensory systems and animal classes.

Biophysical Adaptations of Prokaryotic Voltage-Gated Sodium Channels.

PubMed

Vien, T N; DeCaen, P G

2016-01-01

This chapter describes the adaptive features found in voltage-gated sodium channels (NaVs) of prokaryotes and eukaryotes. These two families are distinct, having diverged early in evolutionary history but maintain a surprising degree of convergence in function. While prokaryotic NaVs are required for growth and motility, eukaryotic NaVs selectively conduct fast electrical currents for short- and long-range signaling across cell membranes in mammalian organs. Current interest in prokaryotic NaVs is stoked by their resolved high-resolution structures and functional features which are reminiscent of eukaryotic NaVs. In this chapter, comparisons between eukaryotic and prokaryotic NaVs are made to highlight the shared and unique aspects of ion selectivity, voltage sensitivity, and pharmacology. Examples of prokaryotic and eukaryotic NaV convergent evolution will be discussed within the context of their structural features. Copyright © 2016 Elsevier Inc. All rights reserved.

An improved strategy for skin lesion detection and classification using uniform segmentation and feature selection based approach.

PubMed

Nasir, Muhammad; Attique Khan, Muhammad; Sharif, Muhammad; Lali, Ikram Ullah; Saba, Tanzila; Iqbal, Tassawar

2018-02-21

Melanoma is the deadliest type of skin cancer with highest mortality rate. However, the annihilation in early stage implies a high survival rate therefore, it demands early diagnosis. The accustomed diagnosis methods are costly and cumbersome due to the involvement of experienced experts as well as the requirements for highly equipped environment. The recent advancements in computerized solutions for these diagnoses are highly promising with improved accuracy and efficiency. In this article, we proposed a method for the classification of melanoma and benign skin lesions. Our approach integrates preprocessing, lesion segmentation, features extraction, features selection, and classification. Preprocessing is executed in the context of hair removal by DullRazor, whereas lesion texture and color information are utilized to enhance the lesion contrast. In lesion segmentation, a hybrid technique has been implemented and results are fused using additive law of probability. Serial based method is applied subsequently that extracts and fuses the traits such as color, texture, and HOG (shape). The fused features are selected afterwards by implementing a novel Boltzman Entropy method. Finally, the selected features are classified by Support Vector Machine. The proposed method is evaluated on publically available data set PH2. Our approach has provided promising results of sensitivity 97.7%, specificity 96.7%, accuracy 97.5%, and F-score 97.5%, which are significantly better than the results of existing methods available on the same data set. The proposed method detects and classifies melanoma significantly good as compared to existing methods. © 2018 Wiley Periodicals, Inc.

A neural network approach to lung nodule segmentation

NASA Astrophysics Data System (ADS)

Hu, Yaoxiu; Menon, Prahlad G.

2016-03-01

Computed tomography (CT) imaging is a sensitive and specific lung cancer screening tool for the high-risk population and shown to be promising for detection of lung cancer. This study proposes an automatic methodology for detecting and segmenting lung nodules from CT images. The proposed methods begin with thorax segmentation, lung extraction and reconstruction of the original shape of the parenchyma using morphology operations. Next, a multi-scale hessian-based vesselness filter is applied to extract lung vasculature in lung. The lung vasculature mask is subtracted from the lung region segmentation mask to extract 3D regions representing candidate pulmonary nodules. Finally, the remaining structures are classified as nodules through shape and intensity features which are together used to train an artificial neural network. Up to 75% sensitivity and 98% specificity was achieved for detection of lung nodules in our testing dataset, with an overall accuracy of 97.62%+/-0.72% using 11 selected features as input to the neural network classifier, based on 4-fold cross-validation studies. Receiver operator characteristics for identifying nodules revealed an area under curve of 0.9476.

Classification of prostate cancer grade using temporal ultrasound: in vivo feasibility study

NASA Astrophysics Data System (ADS)

Ghavidel, Sahar; Imani, Farhad; Khallaghi, Siavash; Gibson, Eli; Khojaste, Amir; Gaed, Mena; Moussa, Madeleine; Gomez, Jose A.; Siemens, D. Robert; Leveridge, Michael; Chang, Silvia; Fenster, Aaron; Ward, Aaron D.; Abolmaesumi, Purang; Mousavi, Parvin

2016-03-01

Temporal ultrasound has been shown to have high classification accuracy in differentiating cancer from benign tissue. In this paper, we extend the temporal ultrasound method to classify lower grade Prostate Cancer (PCa) from all other grades. We use a group of nine patients with mostly lower grade PCa, where cancerous regions are also limited. A critical challenge is to train a classifier with limited aggressive cancerous tissue compared to low grade cancerous tissue. To resolve the problem of imbalanced data, we use Synthetic Minority Oversampling Technique (SMOTE) to generate synthetic samples for the minority class. We calculate spectral features of temporal ultrasound data and perform feature selection using Random Forests. In leave-one-patient-out cross-validation strategy, an area under receiver operating characteristic curve (AUC) of 0.74 is achieved with overall sensitivity and specificity of 70%. Using an unsupervised learning approach prior to proposed method improves sensitivity and AUC to 80% and 0.79. This work represents promising results to classify lower and higher grade PCa with limited cancerous training samples, using temporal ultrasound.

Terahertz response in the quantum-Hall-effect regime of a quantum-well-based charge-sensitive infrared phototransistor

NASA Astrophysics Data System (ADS)

Nakagawa, Daisuke; Takizawa, Kazuhiro; Ikushima, Kenji; Kim, Sunmi; Patrashin, Mikhail; Hosako, Iwao; Komiyama, Susumu

2018-04-01

The characteristics of a charge-sensitive infrared phototransistor (CSIP) based on a GaAs/AlGaAs multiple quantum-well (QW) structure are studied under a magnetic field. In the CSIP, the upper QWs serve as a floating gate that is charged by photoexcitation. The photoinduced charges are detected using the resistance of the lowest QW conducting channel. The conducting channel exhibits the integer quantum Hall effect (QHE) in a perpendicular high magnetic field, yielding the magnetic field dependence of the terahertz (THz) response ΔR. We found two different features of ΔR. One is that ΔR switches sign across the QHE plateau, which is explained simply by an increased electron density in the conducting channel. The other feature is observed as an enhanced positive ΔR when a potential barrier is formed in the conducting channel. The latter mechanism can be interpreted as the promotion of edge/bulk scattering due to photoinduced charges. These findings suggest ways to enhance the THz response by using magnetic fields and potential barriers.

Differential sensitivity of Glioma stem cells to Aurora kinase A inhibitors: implications for stem cell mitosis and centrosome dynamics.

PubMed

Mannino, Mariella; Gomez-Roman, Natividad; Hochegger, Helfrid; Chalmers, Anthony J

2014-07-01

Glioma stem-cell-like cells are considered to be responsible for treatment resistance and tumour recurrence following chemo-radiation in glioblastoma patients, but specific targets by which to kill the cancer stem cell population remain elusive. A characteristic feature of stem cells is their ability to undergo both symmetric and asymmetric cell divisions. In this study we have analysed specific features of glioma stem cell mitosis. We found that glioma stem cells appear to be highly prone to undergo aberrant cell division and polyploidization. Moreover, we discovered a pronounced change in the dynamic of mitotic centrosome maturation in these cells. Accordingly, glioma stem cell survival appeared to be strongly dependent on Aurora A activity. Unlike differentiated cells, glioma stem cells responded to moderate Aurora A inhibition with spindle defects, polyploidization and a dramatic increase in cellular senescence, and were selectively sensitive to Aurora A and Plk1 inhibitor treatment. Our study proposes inhibition of centrosomal kinases as a novel strategy to selectively target glioma stem cells. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

Use of geographic information systems for applications on gas pipeline rights-of-way. Final report, December 1989--December 1991

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

Thompson, P.J.

1991-12-01

Geographic information system (GIS) applications for the siting and monitoring of gas pipeline rights-of-way for this project (ROWs) were developed for areas near Rio Vista, California. The data layers developed for this project represent geographic features, such as landcover, elevation, aspect, slope, soils, hydrography, transportation, endangered species, wetlands, and public line surveys. A GIS was used to develop and store spatial data from several sources; to manipulate spatial data to evaluate environmental and engineering issues associated with the siting, permitting, construction, maintenance, and monitoring of gas pipeline ROWS; and to graphically display analysis results. Examples of these applications include (1)more » determination of environmentally sensitive areas, such as endangered species habitat, wetlands, and areas of highly erosive soils; (2) evaluation of engineering constraints, including shallow depth to bedrock, major hydrographic features, and shallow water table; (3) classification of satellite imagery for landuse/landcover that will affect ROWs; and (4) identification of alternative ROW corridors that avoid environmentally sensitive areas or areas with severe engineering constraints.« less

Use of geographic information systems for applications on gas pipeline rights-of-way

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

Thompson, P.J.

1991-12-01

Geographic information system (GIS) applications for the siting and monitoring of gas pipeline rights-of-way for this project (ROWs) were developed for areas near Rio Vista, California. The data layers developed for this project represent geographic features, such as landcover, elevation, aspect, slope, soils, hydrography, transportation, endangered species, wetlands, and public line surveys. A GIS was used to develop and store spatial data from several sources; to manipulate spatial data to evaluate environmental and engineering issues associated with the siting, permitting, construction, maintenance, and monitoring of gas pipeline ROWS; and to graphically display analysis results. Examples of these applications include (1)more » determination of environmentally sensitive areas, such as endangered species habitat, wetlands, and areas of highly erosive soils; (2) evaluation of engineering constraints, including shallow depth to bedrock, major hydrographic features, and shallow water table; (3) classification of satellite imagery for landuse/landcover that will affect ROWs; and (4) identification of alternative ROW corridors that avoid environmentally sensitive areas or areas with severe engineering constraints.« less

IdentiPy: An Extensible Search Engine for Protein Identification in Shotgun Proteomics.

PubMed

Levitsky, Lev I; Ivanov, Mark V; Lobas, Anna A; Bubis, Julia A; Tarasova, Irina A; Solovyeva, Elizaveta M; Pridatchenko, Marina L; Gorshkov, Mikhail V

2018-06-18

We present an open-source, extensible search engine for shotgun proteomics. Implemented in Python programming language, IdentiPy shows competitive processing speed and sensitivity compared with the state-of-the-art search engines. It is equipped with a user-friendly web interface, IdentiPy Server, enabling the use of a single server installation accessed from multiple workstations. Using a simplified version of X!Tandem scoring algorithm and its novel "autotune" feature, IdentiPy outperforms the popular alternatives on high-resolution data sets. Autotune adjusts the search parameters for the particular data set, resulting in improved search efficiency and simplifying the user experience. IdentiPy with the autotune feature shows higher sensitivity compared with the evaluated search engines. IdentiPy Server has built-in postprocessing and protein inference procedures and provides graphic visualization of the statistical properties of the data set and the search results. It is open-source and can be freely extended to use third-party scoring functions or processing algorithms and allows customization of the search workflow for specialized applications.

Morphological and wavelet features towards sonographic thyroid nodules evaluation.

PubMed

Tsantis, Stavros; Dimitropoulos, Nikos; Cavouras, Dionisis; Nikiforidis, George

2009-03-01

This paper presents a computer-based classification scheme that utilized various morphological and novel wavelet-based features towards malignancy risk evaluation of thyroid nodules in ultrasonography. The study comprised 85 ultrasound images-patients that were cytological confirmed (54 low-risk and 31 high-risk). A set of 20 features (12 based on nodules boundary shape and 8 based on wavelet local maxima located within each nodule) has been generated. Two powerful pattern recognition algorithms (support vector machines and probabilistic neural networks) have been designed and developed in order to quantify the power of differentiation of the introduced features. A comparative study has also been held, in order to estimate the impact speckle had onto the classification procedure. The diagnostic sensitivity and specificity of both classifiers was made by means of receiver operating characteristics (ROC) analysis. In the speckle-free feature set, the area under the ROC curve was 0.96 for the support vector machines classifier whereas for the probabilistic neural networks was 0.91. In the feature set with speckle, the corresponding areas under the ROC curves were 0.88 and 0.86 respectively for the two classifiers. The proposed features can increase the classification accuracy and decrease the rate of missing and misdiagnosis in thyroid cancer control.

Rapid, low dose X-ray diffractive imaging of the malaria parasite Plasmodium falciparum.

PubMed

Jones, Michael W M; Dearnley, Megan K; van Riessen, Grant A; Abbey, Brian; Putkunz, Corey T; Junker, Mark D; Vine, David J; McNulty, Ian; Nugent, Keith A; Peele, Andrew G; Tilley, Leann

2014-08-01

Phase-diverse X-ray coherent diffractive imaging (CDI) provides a route to high sensitivity and spatial resolution with moderate radiation dose. It also provides a robust solution to the well-known phase-problem, making on-line image reconstruction feasible. Here we apply phase-diverse CDI to a cellular sample, obtaining images of an erythrocyte infected by the sexual stage of the malaria parasite, Plasmodium falciparum, with a radiation dose significantly lower than the lowest dose previously reported for cellular imaging using CDI. The high sensitivity and resolution allow key biological features to be identified within intact cells, providing complementary information to optical and electron microscopy. This high throughput method could be used for fast tomographic imaging, or to generate multiple replicates in two-dimensions of hydrated biological systems without freezing or fixing. This work demonstrates that phase-diverse CDI is a valuable complementary imaging method for the biological sciences and ready for immediate application. © 2013 Elsevier B.V. All rights reserved.

Carbonaceous materials and their advances as a counter electrode in dye-sensitized solar cells: challenges and prospects.

PubMed

Kouhnavard, Mojgan; Ludin, Norasikin Ahmad; Ghaffari, Babak V; Sopian, Kamarozzaman; Ikeda, Shoichiro

2015-05-11

Dye-sensitized solar cells (DSSCs) serve as low-costing alternatives to silicon solar cells because of their low material and fabrication costs. Usually, they utilize Pt as the counter electrode (CE) to catalyze the iodine redox couple and to complete the electric circuit. Given that Pt is a rare and expensive metal, various carbon materials have been intensively investigated because of their low costs, high surface areas, excellent electrochemical stabilities, reasonable electrochemical activities, and high corrosion resistances. In this feature article, we provide an overview of recent studies on the electrochemical properties and photovoltaic performances of carbon-based CEs (e.g., activated carbon, nanosized carbon, carbon black, graphene, graphite, carbon nanotubes, and composite carbon). We focus on scientific challenges associated with each material and highlight recent advances achieved in overcoming these obstacles. Finally, we discuss possible future directions for this field of research aimed at obtaining highly efficient DSSCs. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

Gilbert, Andrew J.; Miller, Brian W.; Robinson, Sean M.

Imaging technology is generally considered too invasive for arms control inspections due to the concern that it cannot properly secure sensitive features of the inspected item. However, this same sensitive information, which could include direct information on the form and function of the items under inspection, could be used for robust arms control inspections. The single-pixel X-ray imager (SPXI) is introduced as a method to make such inspections, capturing the salient spatial information of an object in a secure manner while never forming an actual image. The method is built on the theory of compressive sensing and the single pixelmore » optical camera. The performance of the system is quantified here using simulated inspections of simple objects. Measures of the robustness and security of the method are introduced and used to determine how such an inspection would be made which can maintain high robustness and security. In particular, it is found that an inspection with low noise (<1%) and high undersampling (>256×) exhibits high robustness and security.« less

Sensitive Nonenzymatic Electrochemical Glucose Detection Based on Hollow Porous NiO

NASA Astrophysics Data System (ADS)

He, Gege; Tian, Liangliang; Cai, Yanhua; Wu, Shenping; Su, Yongyao; Yan, Hengqing; Pu, Wanrong; Zhang, Jinkun; Li, Lu

2018-01-01

Transition metal oxides (TMOs) have attracted extensive research attentions as promising electrocatalytic materials. Despite low cost and high stability, the electrocatalytic activity of TMOs still cannot satisfy the requirements of applications. Inspired by kinetics, the design of hollow porous structure is considered as a promising strategy to achieve superior electrocatalytic performance. In this work, cubic NiO hollow porous architecture (NiO HPA) was constructed through coordinating etching and precipitating (CEP) principle followed by post calcination. Being employed to detect glucose, NiO HPA electrode exhibits outstanding electrocatalytic activity in terms of high sensitivity (1323 μA mM-1 cm-2) and low detection limit (0.32 μM). The excellent electrocatalytic activity can be ascribed to large specific surface area (SSA), ordered diffusion channels, and accelerated electron transfer rate derived from the unique hollow porous features. The results demonstrate that the NiO HPA could have practical applications in the design of nonenzymatic glucose sensors. The construction of hollow porous architecture provides an effective nanoengineering strategy for high-performance electrocatalysts.

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

Hornemann, Andrea, E-mail: andrea.hornemann@ptb.de; Hoehl, Arne, E-mail: arne.hoehl@ptb.de; Ulm, Gerhard, E-mail: gerhard.ulm@ptb.de

Bio-diagnostic assays of high complexity rely on nanoscaled assay recognition elements that can provide unique selectivity and design-enhanced sensitivity features. High throughput performance requires the simultaneous detection of various analytes combined with appropriate bioassay components. Nanoparticle induced sensitivity enhancement, and subsequent multiplexed capability Surface-Enhanced InfraRed Absorption (SEIRA) assay formats are fitting well these purposes. SEIRA constitutes an ideal platform to isolate the vibrational signatures of targeted bioassay and active molecules. The potential of several targeted biolabels, here fluorophore-labeled antibody conjugates, chemisorbed onto low-cost biocompatible gold nano-aggregates substrates have been explored for their use in assay platforms. Dried films were analyzedmore » by synchrotron radiation based FTIR/SEIRA spectro-microscopy and the resulting complex hyperspectral datasets were submitted to automated statistical analysis, namely Principal Components Analysis (PCA). The relationships between molecular fingerprints were put in evidence to highlight their spectral discrimination capabilities. We demonstrate that robust spectral encoding via SEIRA fingerprints opens up new opportunities for fast, reliable and multiplexed high-end screening not only in biodiagnostics but also in vitro biochemical imaging.« less

Unlocking Sensitivity for Visibility-based Estimators of the 21 cm Reionization Power Spectrum

NASA Astrophysics Data System (ADS)

Zhang, Yunfan Gerry; Liu, Adrian; Parsons, Aaron R.

2018-01-01

Radio interferometers designed to measure the cosmological 21 cm power spectrum require high sensitivity. Several modern low-frequency interferometers feature drift-scan antennas placed on a regular grid to maximize the number of instantaneously coherent (redundant) measurements. However, even for such maximum-redundancy arrays, significant sensitivity comes through partial coherence between baselines. Current visibility-based power-spectrum pipelines, though shown to ease control of systematics, lack the ability to make use of this partial redundancy. We introduce a method to leverage partial redundancy in such power-spectrum pipelines for drift-scan arrays. Our method cross-multiplies baseline pairs at a time lag and quantifies the sensitivity contributions of each pair of baselines. Using the configurations and beams of the 128-element Donald C. Backer Precision Array for Probing the Epoch of Reionization (PAPER-128) and staged deployments of the Hydrogen Epoch of Reionization Array, we illustrate how our method applies to different arrays and predict the sensitivity improvements associated with pairing partially coherent baselines. As the number of antennas increases, we find partial redundancy to be of increasing importance in unlocking the full sensitivity of upcoming arrays.

Static black holes with back reaction from vacuum energy

NASA Astrophysics Data System (ADS)

Ho, Pei-Ming; Matsuo, Yoshinori

2018-03-01

We study spherically symmetric static solutions to the semi-classical Einstein equation sourced by the vacuum energy of quantum fields in the curved space-time of the same solution. We found solutions that are small deformations of the Schwarzschild metric for distant observers, but without horizon. Instead of being a robust feature of objects with high densities, the horizon is sensitive to the energy–momentum tensor in the near-horizon region.

Automatic discrimination between safe and unsafe swallowing using a reputation-based classifier

PubMed Central

2011-01-01

Background Swallowing accelerometry has been suggested as a potential non-invasive tool for bedside dysphagia screening. Various vibratory signal features and complementary measurement modalities have been put forth in the literature for the potential discrimination between safe and unsafe swallowing. To date, automatic classification of swallowing accelerometry has exclusively involved a single-axis of vibration although a second axis is known to contain additional information about the nature of the swallow. Furthermore, the only published attempt at automatic classification in adult patients has been based on a small sample of swallowing vibrations. Methods In this paper, a large corpus of dual-axis accelerometric signals were collected from 30 older adults (aged 65.47 ± 13.4 years, 15 male) referred to videofluoroscopic examination on the suspicion of dysphagia. We invoked a reputation-based classifier combination to automatically categorize the dual-axis accelerometric signals into safe and unsafe swallows, as labeled via videofluoroscopic review. From these participants, a total of 224 swallowing samples were obtained, 164 of which were labeled as unsafe swallows (swallows where the bolus entered the airway) and 60 as safe swallows. Three separate support vector machine (SVM) classifiers and eight different features were selected for classification. Results With selected time, frequency and information theoretic features, the reputation-based algorithm distinguished between safe and unsafe swallowing with promising accuracy (80.48 ± 5.0%), high sensitivity (97.1 ± 2%) and modest specificity (64 ± 8.8%). Interpretation of the most discriminatory features revealed that in general, unsafe swallows had lower mean vibration amplitude and faster autocorrelation decay, suggestive of decreased hyoid excursion and compromised coordination, respectively. Further, owing to its performance-based weighting of component classifiers, the static reputation-based algorithm outperformed the democratic majority voting algorithm on this clinical data set. Conclusion Given its computational efficiency and high sensitivity, reputation-based classification of dual-axis accelerometry ought to be considered in future developments of a point-of-care swallow assessment where clinical informatics are desired. PMID:22085802

High-field fMRI unveils orientation columns in humans.

PubMed

Yacoub, Essa; Harel, Noam; Ugurbil, Kâmil

2008-07-29

Functional (f)MRI has revolutionized the field of human brain research. fMRI can noninvasively map the spatial architecture of brain function via localized increases in blood flow after sensory or cognitive stimulation. Recent advances in fMRI have led to enhanced sensitivity and spatial accuracy of the measured signals, indicating the possibility of detecting small neuronal ensembles that constitute fundamental computational units in the brain, such as cortical columns. Orientation columns in visual cortex are perhaps the best known example of such a functional organization in the brain. They cannot be discerned via anatomical characteristics, as with ocular dominance columns. Instead, the elucidation of their organization requires functional imaging methods. However, because of insufficient sensitivity, spatial accuracy, and image resolution of the available mapping techniques, thus far, they have not been detected in humans. Here, we demonstrate, by using high-field (7-T) fMRI, the existence and spatial features of orientation- selective columns in humans. Striking similarities were found with the known spatial features of these columns in monkeys. In addition, we found that a larger number of orientation columns are devoted to processing orientations around 90 degrees (vertical stimuli with horizontal motion), whereas relatively similar fMRI signal changes were observed across any given active column. With the current proliferation of high-field MRI systems and constant evolution of fMRI techniques, this study heralds the exciting prospect of exploring unmapped and/or unknown columnar level functional organizations in the human brain.

Disproportionate Cochlear Length in Genus Homo Shows a High Phylogenetic Signal during Apes' Hearing Evolution.

PubMed

Braga, J; Loubes, J-M; Descouens, D; Dumoncel, J; Thackeray, J F; Kahn, J-L; de Beer, F; Riberon, A; Hoffman, K; Balaresque, P; Gilissen, E

2015-01-01

Changes in lifestyles and body weight affected mammal life-history evolution but little is known about how they shaped species' sensory systems. Since auditory sensitivity impacts communication tasks and environmental acoustic awareness, it may have represented a deciding factor during mammal evolution, including apes. Here, we statistically measure the influence of phylogeny and allometry on the variation of five cochlear morphological features associated with hearing capacities across 22 living and 5 fossil catarrhine species. We find high phylogenetic signals for absolute and relative cochlear length only. Comparisons between fossil cochleae and reconstructed ape ancestral morphotypes show that Australopithecus absolute and relative cochlear lengths are explicable by phylogeny and concordant with the hypothetized ((Pan,Homo),Gorilla) and (Pan,Homo) most recent common ancestors. Conversely, deviations of the Paranthropus oval window area from these most recent common ancestors are not explicable by phylogeny and body weight alone, but suggest instead rapid evolutionary changes (directional selection) of its hearing organ. Premodern (Homo erectus) and modern human cochleae set apart from living non-human catarrhines and australopiths. They show cochlear relative lengths and oval window areas larger than expected for their body mass, two features corresponding to increased low-frequency sensitivity more recent than 2 million years ago. The uniqueness of the "hypertrophied" cochlea in the genus Homo (as opposed to the australopiths) and the significantly high phylogenetic signal of this organ among apes indicate its usefulness to identify homologies and monophyletic groups in the hominid fossil record.

Disproportionate Cochlear Length in Genus Homo Shows a High Phylogenetic Signal during Apes’ Hearing Evolution

PubMed Central

Braga, J.; Loubes, J-M.; Descouens, D.; Dumoncel, J.; Thackeray, J. F.; Kahn, J-L.; de Beer, F.; Riberon, A.; Hoffman, K.; Balaresque, P.; Gilissen, E.

2015-01-01

Changes in lifestyles and body weight affected mammal life-history evolution but little is known about how they shaped species’ sensory systems. Since auditory sensitivity impacts communication tasks and environmental acoustic awareness, it may have represented a deciding factor during mammal evolution, including apes. Here, we statistically measure the influence of phylogeny and allometry on the variation of five cochlear morphological features associated with hearing capacities across 22 living and 5 fossil catarrhine species. We find high phylogenetic signals for absolute and relative cochlear length only. Comparisons between fossil cochleae and reconstructed ape ancestral morphotypes show that Australopithecus absolute and relative cochlear lengths are explicable by phylogeny and concordant with the hypothetized ((Pan,Homo),Gorilla) and (Pan,Homo) most recent common ancestors. Conversely, deviations of the Paranthropus oval window area from these most recent common ancestors are not explicable by phylogeny and body weight alone, but suggest instead rapid evolutionary changes (directional selection) of its hearing organ. Premodern (Homo erectus) and modern human cochleae set apart from living non-human catarrhines and australopiths. They show cochlear relative lengths and oval window areas larger than expected for their body mass, two features corresponding to increased low-frequency sensitivity more recent than 2 million years ago. The uniqueness of the “hypertrophied” cochlea in the genus Homo (as opposed to the australopiths) and the significantly high phylogenetic signal of this organ among apes indicate its usefulness to identify homologies and monophyletic groups in the hominid fossil record. PMID:26083484

Spectral and spatial selectivity of luminance vision in reef fish.

PubMed

Siebeck, Ulrike E; Wallis, Guy Michael; Litherland, Lenore; Ganeshina, Olga; Vorobyev, Misha

2014-01-01

Luminance vision has high spatial resolution and is used for form vision and texture discrimination. In humans, birds and bees luminance channel is spectrally selective-it depends on the signals of the long-wavelength sensitive photoreceptors (bees) or on the sum of long- and middle-wavelength sensitive cones (humans), but not on the signal of the short-wavelength sensitive (blue) photoreceptors. The reasons of such selectivity are not fully understood. The aim of this study is to reveal the inputs of cone signals to high resolution luminance vision in reef fish. Sixteen freshly caught damselfish, Pomacentrus amboinensis, were trained to discriminate stimuli differing either in their color or in their fine patterns (stripes vs. cheques). Three colors ("bright green", "dark green" and "blue") were used to create two sets of color and two sets of pattern stimuli. The "bright green" and "dark green" were similar in their chromatic properties for fish, but differed in their lightness; the "dark green" differed from "blue" in the signal for the blue cone, but yielded similar signals in the long-wavelength and middle-wavelength cones. Fish easily learned to discriminate "bright green" from "dark green" and "dark green" from "blue" stimuli. Fish also could discriminate the fine patterns created from "dark green" and "bright green". However, fish failed to discriminate fine patterns created from "blue" and "dark green" colors, i.e., the colors that provided contrast for the blue-sensitive photoreceptor, but not for the long-wavelength sensitive one. High resolution luminance vision in damselfish, Pomacentrus amboinensis, does not have input from the blue-sensitive cone, which may indicate that the spectral selectivity of luminance channel is a general feature of visual processing in both aquatic and terrestrial animals.

Standoff detection: distinction of bacteria by hyperspectral laser induced fluorescence

NASA Astrophysics Data System (ADS)

Walter, Arne; Duschek, Frank; Fellner, Lea; Grünewald, Karin M.; Hausmann, Anita; Julich, Sandra; Pargmann, Carsten; Tomaso, Herbert; Handke, Jürgen

2016-05-01

Sensitive detection and rapid identification of hazardous bioorganic material with high sensitivity and specificity are essential topics for defense and security. A single method can hardly cover these requirements. While point sensors allow a highly specific identification, they only provide localized information and are comparatively slow. Laser based standoff systems allow almost real-time detection and classification of potentially hazardous material in a wide area and can provide information on how the aerosol may spread. The coupling of both methods may be a promising solution to optimize the acquisition and identification of hazardous substances. The capability of the outdoor LIF system at DLR Lampoldshausen test facility as an online classification tool has already been demonstrated. Here, we present promising data for further differentiation among bacteria. Bacteria species can express unique fluorescence spectra after excitation at 280 nm and 355 nm. Upon deactivation, the spectral features change depending on the deactivation method.

Advertising Via Mobile Terminals - Delivering Context Sensitive and Personalized Advertising While Guaranteeing Privacy

NASA Astrophysics Data System (ADS)

Bulander, Rebecca; Decker, Michael; Schiefer, Gunther; Kölmel, Bernhard

Mobile terminals like cellular phones and PDAs are a promising target platform for mobile advertising: The devices are widely spread, are able to present interactive multimedia content and offer as almost permanently carried along personal communication devices a high degree of reachability. But particular because of the latter feature it is important to pay great attention to privacy aspects and avoidance of spam-messages when designing an application for mobile advertising. Furthermore the limited user interface of mobile devices is a special challenge. The following article describes the solution approach for mobile advertising developed within the project MoMa, which was funded by the Federal Ministry of Economics and Labour of Germany (BMWA). MoMa enables highly personalized and context sensitive mobile advertising while guaranteeing data protection. To achieve this we have to distinguish public and private context information.

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

Gilbert, Andrew J.; Miller, Brian W.; Robinson, Sean M.

Imaging technology is generally considered too invasive for arms control inspections due to the concern that it cannot properly secure sensitive features of the inspected item. But, this same sensitive information, which could include direct information on the form and function of the items under inspection, could be used for robust arms control inspections. The single-pixel X-ray imager (SPXI) is introduced as a method to make such inspections, capturing the salient spatial information of an object in a secure manner while never forming an actual image. We built this method on the theory of compressive sensing and the single pixelmore » optical camera. The performance of the system is quantified using simulated inspections of simple objects. Measures of the robustness and security of the method are introduced and used to determine how robust and secure such an inspection would be. Particularly, it is found that an inspection with low noise (<1%) and high undersampling (>256×) exhibits high robustness and security.« less

Parahydrogen-enhanced zero-field nuclear magnetic resonance

NASA Astrophysics Data System (ADS)

Theis, T.; Ganssle, P.; Kervern, G.; Knappe, S.; Kitching, J.; Ledbetter, M. P.; Budker, D.; Pines, A.

2011-07-01

Nuclear magnetic resonance, conventionally detected in magnetic fields of several tesla, is a powerful analytical tool for the determination of molecular identity, structure and function. With the advent of prepolarization methods and detection schemes using atomic magnetometers or superconducting quantum interference devices, interest in NMR in fields comparable to the Earth's magnetic field and below (down to zero field) has been revived. Despite the use of superconducting quantum interference devices or atomic magnetometers, low-field NMR typically suffers from low sensitivity compared with conventional high-field NMR. Here we demonstrate direct detection of zero-field NMR signals generated through parahydrogen-induced polarization, enabling high-resolution NMR without the use of any magnets. The sensitivity is sufficient to observe spectra exhibiting 13C-1H scalar nuclear spin-spin couplings (known as J couplings) in compounds with 13C in natural abundance, without the need for signal averaging. The resulting spectra show distinct features that aid chemical fingerprinting.

A highly sensitive and accurate gene expression analysis by sequencing ("bead-seq") for a single cell.

PubMed

Matsunaga, Hiroko; Goto, Mari; Arikawa, Koji; Shirai, Masataka; Tsunoda, Hiroyuki; Huang, Huan; Kambara, Hideki

2015-02-15

Analyses of gene expressions in single cells are important for understanding detailed biological phenomena. Here, a highly sensitive and accurate method by sequencing (called "bead-seq") to obtain a whole gene expression profile for a single cell is proposed. A key feature of the method is to use a complementary DNA (cDNA) library on magnetic beads, which enables adding washing steps to remove residual reagents in a sample preparation process. By adding the washing steps, the next steps can be carried out under the optimal conditions without losing cDNAs. Error sources were carefully evaluated to conclude that the first several steps were the key steps. It is demonstrated that bead-seq is superior to the conventional methods for single-cell gene expression analyses in terms of reproducibility, quantitative accuracy, and biases caused during sample preparation and sequencing processes. Copyright © 2014 Elsevier Inc. All rights reserved.

A fluorescence high throughput screening method for the detection of reactive electrophiles as potential skin sensitizers.

PubMed

Avonto, Cristina; Chittiboyina, Amar G; Rua, Diego; Khan, Ikhlas A

2015-12-01

Skin sensitization is an important toxicological end-point in the risk assessment of chemical allergens. Because of the complexity of the biological mechanisms associated with skin sensitization, integrated approaches combining different chemical, biological and in silico methods are recommended to replace conventional animal tests. Chemical methods are intended to characterize the potential of a sensitizer to induce earlier molecular initiating events. The presence of an electrophilic mechanistic domain is considered one of the essential chemical features to covalently bind to the biological target and induce further haptenation processes. Current in chemico assays rely on the quantification of unreacted model nucleophiles after incubation with the candidate sensitizer. In the current study, a new fluorescence-based method, 'HTS-DCYA assay', is proposed. The assay aims at the identification of reactive electrophiles based on their chemical reactivity toward a model fluorescent thiol. The reaction workflow enabled the development of a High Throughput Screening (HTS) method to directly quantify the reaction adducts. The reaction conditions have been optimized to minimize solubility issues, oxidative side reactions and increase the throughput of the assay while minimizing the reaction time, which are common issues with existing methods. Thirty-six chemicals previously classified with LLNA, DPRA or KeratinoSens™ were tested as a proof of concept. Preliminary results gave an estimated 82% accuracy, 78% sensitivity, 90% specificity, comparable to other in chemico methods such as Cys-DPRA. In addition to validated chemicals, six natural products were analyzed and a prediction of their sensitization potential is presented for the first time. Copyright © 2015 Elsevier Inc. All rights reserved.

Deep Learning in Label-free Cell Classification

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

Chen, Claire Lifan; Mahjoubfar, Ata; Tai, Li-Chia

Label-free cell analysis is essential to personalized genomics, cancer diagnostics, and drug development as it avoids adverse effects of staining reagents on cellular viability and cell signaling. However, currently available label-free cell assays mostly rely only on a single feature and lack sufficient differentiation. Also, the sample size analyzed by these assays is limited due to their low throughput. Here, we integrate feature extraction and deep learning with high-throughput quantitative imaging enabled by photonic time stretch, achieving record high accuracy in label-free cell classification. Our system captures quantitative optical phase and intensity images and extracts multiple biophysical features of individualmore » cells. These biophysical measurements form a hyperdimensional feature space in which supervised learning is performed for cell classification. We compare various learning algorithms including artificial neural network, support vector machine, logistic regression, and a novel deep learning pipeline, which adopts global optimization of receiver operating characteristics. As a validation of the enhanced sensitivity and specificity of our system, we show classification of white blood T-cells against colon cancer cells, as well as lipid accumulating algal strains for biofuel production. In conclusion, this system opens up a new path to data-driven phenotypic diagnosis and better understanding of the heterogeneous gene expressions in cells.« less

Automated embolic signal detection using Deep Convolutional Neural Network.

PubMed

Sombune, Praotasna; Phienphanich, Phongphan; Phuechpanpaisal, Sutanya; Muengtaweepongsa, Sombat; Ruamthanthong, Anuchit; Tantibundhit, Charturong

2017-07-01

This work investigated the potential of Deep Neural Network in detection of cerebral embolic signal (ES) from transcranial Doppler ultrasound (TCD). The resulting system is aimed to couple with TCD devices in diagnosing a risk of stroke in real-time with high accuracy. The Adaptive Gain Control (AGC) approach developed in our previous study is employed to capture suspected ESs in real-time. By using spectrograms of the same TCD signal dataset as that of our previous work as inputs and the same experimental setup, Deep Convolutional Neural Network (CNN), which can learn features while training, was investigated for its ability to bypass the traditional handcrafted feature extraction and selection process. Extracted feature vectors from the suspected ESs are later determined whether they are of an ES, artifact (AF) or normal (NR) interval. The effectiveness of the developed system was evaluated over 19 subjects going under procedures generating emboli. The CNN-based system could achieve in average of 83.0% sensitivity, 80.1% specificity, and 81.4% accuracy, with considerably much less time consumption in development. The certainly growing set of training samples and computational resources will contribute to high performance. Besides having potential use in various clinical ES monitoring settings, continuation of this promising study will benefit developments of wearable applications by leveraging learnable features to serve demographic differentials.

Deep Learning in Label-free Cell Classification

DOE PAGES

Chen, Claire Lifan; Mahjoubfar, Ata; Tai, Li-Chia; ...

2016-03-15

Label-free cell analysis is essential to personalized genomics, cancer diagnostics, and drug development as it avoids adverse effects of staining reagents on cellular viability and cell signaling. However, currently available label-free cell assays mostly rely only on a single feature and lack sufficient differentiation. Also, the sample size analyzed by these assays is limited due to their low throughput. Here, we integrate feature extraction and deep learning with high-throughput quantitative imaging enabled by photonic time stretch, achieving record high accuracy in label-free cell classification. Our system captures quantitative optical phase and intensity images and extracts multiple biophysical features of individualmore » cells. These biophysical measurements form a hyperdimensional feature space in which supervised learning is performed for cell classification. We compare various learning algorithms including artificial neural network, support vector machine, logistic regression, and a novel deep learning pipeline, which adopts global optimization of receiver operating characteristics. As a validation of the enhanced sensitivity and specificity of our system, we show classification of white blood T-cells against colon cancer cells, as well as lipid accumulating algal strains for biofuel production. In conclusion, this system opens up a new path to data-driven phenotypic diagnosis and better understanding of the heterogeneous gene expressions in cells.« less

Prioritization of anticancer drugs against a cancer using genomic features of cancer cells: A step towards personalized medicine

PubMed Central

Gupta, Sudheer; Chaudhary, Kumardeep; Kumar, Rahul; Gautam, Ankur; Nanda, Jagpreet Singh; Dhanda, Sandeep Kumar; Brahmachari, Samir Kumar; Raghava, Gajendra P. S.

2016-01-01

In this study, we investigated drug profile of 24 anticancer drugs tested against a large number of cell lines in order to understand the relation between drug resistance and altered genomic features of a cancer cell line. We detected frequent mutations, high expression and high copy number variations of certain genes in both drug resistant cell lines and sensitive cell lines. It was observed that a few drugs, like Panobinostat, are effective against almost all types of cell lines, whereas certain drugs are effective against only a limited type of cell lines. Tissue-specific preference of drugs was also seen where a drug is more effective against cell lines belonging to a specific tissue. Genomic features based models have been developed for each anticancer drug and achieved average correlation between predicted and actual growth inhibition of cell lines in the range of 0.43 to 0.78. We hope, our study will throw light in the field of personalized medicine, particularly in designing patient-specific anticancer drugs. In order to serve the scientific community, a webserver, CancerDP, has been developed for predicting priority/potency of an anticancer drug against a cancer cell line using its genomic features (http://crdd.osdd.net/raghava/cancerdp/). PMID:27030518

Prediction of human disease-associated phosphorylation sites with combined feature selection approach and support vector machine.

PubMed

Xu, Xiaoyi; Li, Ao; Wang, Minghui

2015-08-01

Phosphorylation is a crucial post-translational modification, which regulates almost all cellular processes in life. It has long been recognised that protein phosphorylation has close relationship with diseases, and therefore many researches are undertaken to predict phosphorylation sites for disease treatment and drug design. However, despite the success achieved by these approaches, no method focuses on disease-associated phosphorylation sites prediction. Herein, for the first time the authors propose a novel approach that is specially designed to identify associations between phosphorylation sites and human diseases. To take full advantage of local sequence information, a combined feature selection method-based support vector machine (CFS-SVM) that incorporates minimum-redundancy-maximum-relevance filtering process and forward feature selection process is developed. Performance evaluation shows that CFS-SVM is significantly better than the widely used classifiers including Bayesian decision theory, k nearest neighbour and random forest. With the extremely high specificity of 99%, CFS-SVM can still achieve a high sensitivity. Besides, tests on extra data confirm the effectiveness and general applicability of CFS-SVM approach on a variety of diseases. Finally, the analysis of selected features and corresponding kinases also help the understanding of the potential mechanism of disease-phosphorylation relationships and guide further experimental validations.

On-chip spectroscopy with thermally tuned high-Q photonic crystal cavities

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

Liapis, Andreas C., E-mail: andreas.liapis@gmail.com; Gao, Boshen; Siddiqui, Mahmudur R.

2016-01-11

Spectroscopic methods are a sensitive way to determine the chemical composition of potentially hazardous materials. Here, we demonstrate that thermally tuned high-Q photonic crystal cavities can be used as a compact high-resolution on-chip spectrometer. We have used such a chip-scale spectrometer to measure the absorption spectra of both acetylene and hydrogen cyanide in the 1550 nm spectral band and show that we can discriminate between the two chemical species even though the two materials have spectral features in the same spectral region. Our results pave the way for the development of chip-size chemical sensors that can detect toxic substances.

Machine Learning Classification Combining Multiple Features of A Hyper-Network of fMRI Data in Alzheimer's Disease

PubMed Central

Guo, Hao; Zhang, Fan; Chen, Junjie; Xu, Yong; Xiang, Jie

2017-01-01

Exploring functional interactions among various brain regions is helpful for understanding the pathological underpinnings of neurological disorders. Brain networks provide an important representation of those functional interactions, and thus are widely applied in the diagnosis and classification of neurodegenerative diseases. Many mental disorders involve a sharp decline in cognitive ability as a major symptom, which can be caused by abnormal connectivity patterns among several brain regions. However, conventional functional connectivity networks are usually constructed based on pairwise correlations among different brain regions. This approach ignores higher-order relationships, and cannot effectively characterize the high-order interactions of many brain regions working together. Recent neuroscience research suggests that higher-order relationships between brain regions are important for brain network analysis. Hyper-networks have been proposed that can effectively represent the interactions among brain regions. However, this method extracts the local properties of brain regions as features, but ignores the global topology information, which affects the evaluation of network topology and reduces the performance of the classifier. This problem can be compensated by a subgraph feature-based method, but it is not sensitive to change in a single brain region. Considering that both of these feature extraction methods result in the loss of information, we propose a novel machine learning classification method that combines multiple features of a hyper-network based on functional magnetic resonance imaging in Alzheimer's disease. The method combines the brain region features and subgraph features, and then uses a multi-kernel SVM for classification. This retains not only the global topological information, but also the sensitivity to change in a single brain region. To certify the proposed method, 28 normal control subjects and 38 Alzheimer's disease patients were selected to participate in an experiment. The proposed method achieved satisfactory classification accuracy, with an average of 91.60%. The abnormal brain regions included the bilateral precuneus, right parahippocampal gyrus\\hippocampus, right posterior cingulate gyrus, and other regions that are known to be important in Alzheimer's disease. Machine learning classification combining multiple features of a hyper-network of functional magnetic resonance imaging data in Alzheimer's disease obtains better classification performance. PMID:29209156

Neural Measures Reveal Implicit Learning during Language Processing.

PubMed

Batterink, Laura J; Cheng, Larry Y; Paller, Ken A

2016-10-01

Language input is highly variable; phonological, lexical, and syntactic features vary systematically across different speakers, geographic regions, and social contexts. Previous evidence shows that language users are sensitive to these contextual changes and that they can rapidly adapt to local regularities. For example, listeners quickly adjust to accented speech, facilitating comprehension. It has been proposed that this type of adaptation is a form of implicit learning. This study examined a similar type of adaptation, syntactic adaptation, to address two issues: (1) whether language comprehenders are sensitive to a subtle probabilistic contingency between an extraneous feature (font color) and syntactic structure and (2) whether this sensitivity should be attributed to implicit learning. Participants read a large set of sentences, 40% of which were garden-path sentences containing temporary syntactic ambiguities. Critically, but unbeknownst to participants, font color probabilistically predicted the presence of a garden-path structure, with 75% of garden-path sentences (and 25% of normative sentences) appearing in a given font color. ERPs were recorded during sentence processing. Almost all participants indicated no conscious awareness of the relationship between font color and sentence structure. Nonetheless, after sufficient time to learn this relationship, ERPs time-locked to the point of syntactic ambiguity resolution in garden-path sentences differed significantly as a function of font color. End-of-sentence grammaticality judgments were also influenced by font color, suggesting that a match between font color and sentence structure increased processing fluency. Overall, these findings indicate that participants can implicitly detect subtle co-occurrences between physical features of sentences and abstract, syntactic properties, supporting the notion that implicit learning mechanisms are generally operative during online language processing.

Implementation of Novel Design Features for qPCR-Based eDNA Assessment

PubMed Central

Veldhoen, Nik; Hobbs, Jared; Ikonomou, Georgios; Hii, Michael; Lesperance, Mary; Helbing, Caren C.

2016-01-01

Environmental stewardship requires timely, accurate information related to the status of a given ecosystem and the species that occupy it. Recent advances in the application of the highly sensitive real-time quantitative polymerase chain reaction (qPCR) towards identification of constituents within environmental DNA (eDNA) now allow targeted detection of the presence of species-specific biological material within a localized geographic region. However, as with all molecular techniques predicated on the specificity and sensitivity of the PCR assay, careful validation of each eDNA qPCR assay in development must be performed both under controlled laboratory conditions and when challenged with field-derived eDNA samples. Such a step-wise approach forms the basis for incorporation of innovative qPCR design features that strengthen the implementation and interpretation of the eDNA assay. This includes empirical determination that the qPCR assay is refractory to the presence of human DNA and the use of a tripartite assay approach comprised of 1) a primer set targeting plant chloroplast that evaluates the presence of amplifiable DNA from field samples to increase confidence in a negative result, 2) an animal group primer set to increase confidence in the assay result, and 3) a species-specific primer set to assess presence of DNA from the target species. To demonstrate this methodology, we generated eDNA assays specific for the North American bullfrog (Lithobates (Rana) catesbeiana) and the Rocky Mountain tailed frog (Ascaphus montanus) and characterized each with respect to detection sensitivity and specificity with demonstrated performance in a field survey scenario. The qPCR design features presented herein address specific challenges of eDNA assays thereby increasing their interpretative power. PMID:27802293

Anatomy and Neurophysiology of Cough

PubMed Central

Canning, Brendan J.; Chang, Anne B.; Bolser, Donald C.; Smith, Jaclyn A.; Mazzone, Stuart B.; Adams, Todd M.; Altman, Kenneth W.; Barker, Alan F.; Birring, Surinder S.; Blackhall, Fiona; Bolser, Donald, C.; Boulet, Louis-Philippe; Braman, Sidney S.; Brightling, Christopher; Callahan-Lyon, Priscilla; Canning, Brendan; Chang, Anne Bernadette; Coeytaux, Remy; Cowley, Terrie; Davenport, Paul; Diekemper, Rebecca L.; Ebihara, Satoru; El Solh, Ali A.; Escalante, Patricio; Feinstein, Anthony; Field, Stephen K.; Fisher, Dina; French, Cynthia T.; Gibson, Peter; Gold, Philip; Grant, Cameron; Harding, Susan M.; Harnden, Anthony; Hill, Adam T.; Irwin, Richard S.; Kahrilas, Peter J.; Keogh, Karina A.; Lane, Andrew P.; Lewis, Sandra Zelman; Lim, Kaiser; Malesker, Mark A.; Mazzone, Peter; Mazzone, Stuart; Molasiotis, Alex; Murad, M. Hassan; Newcombe, Peter; Nguyen, Huong Q.; Oppenheimer, John; Prezant, David; Pringsheim, Tamara; Restrepo, Marcos I.; Rosen, Mark; Rubin, Bruce; Ryu, Jay H.; Smith, Jaclyn; Tarlo, Susan M.; Turner, Ronald B.; Vertigan, Anne; Wang, Gang; Weir, Kelly

2014-01-01

Bronchopulmonary C-fibers and a subset of mechanically sensitive, acid-sensitive myelinated sensory nerves play essential roles in regulating cough. These vagal sensory nerves terminate primarily in the larynx, trachea, carina, and large intrapulmonary bronchi. Other bronchopulmonary sensory nerves, sensory nerves innervating other viscera, as well as somatosensory nerves innervating the chest wall, diaphragm, and abdominal musculature regulate cough patterning and cough sensitivity. The responsiveness and morphology of the airway vagal sensory nerve subtypes and the extrapulmonary sensory nerves that regulate coughing are described. The brainstem and higher brain control systems that process this sensory information are complex, but our current understanding of them is considerable and increasing. The relevance of these neural systems to clinical phenomena, such as urge to cough and psychologic methods for treatment of dystussia, is high, and modern imaging methods have revealed potential neural substrates for some features of cough in the human. PMID:25188530

Thermoelectricity in atom-sized junctions at room temperatures

PubMed Central

Tsutsui, Makusu; Morikawa, Takanori; Arima, Akihide; Taniguchi, Masateru

2013-01-01

Atomic and molecular junctions are an emerging class of thermoelectric materials that exploit quantum confinement effects to obtain an enhanced figure of merit. An important feature in such nanoscale systems is that the electron and heat transport become highly sensitive to the atomic configurations. Here we report the characterization of geometry-sensitive thermoelectricity in atom-sized junctions at room temperatures. We measured the electrical conductance and thermoelectric power of gold nanocontacts simultaneously down to the single atom size. We found junction conductance dependent thermoelectric voltage oscillations with period 2e2/h. We also observed quantum suppression of thermovoltage fluctuations in fully-transparent contacts. These quantum confinement effects appeared only statistically due to the geometry-sensitive nature of thermoelectricity in the atom-sized junctions. The present method can be applied to various nanomaterials including single-molecules or nanoparticles and thus may be used as a useful platform for developing low-dimensional thermoelectric building blocks. PMID:24270238

Near-surface compressional and shear wave speeds constrained by body-wave polarization analysis

NASA Astrophysics Data System (ADS)

Park, Sunyoung; Ishii, Miaki

2018-06-01

A new technique to constrain near-surface seismic structure that relates body-wave polarization direction to the wave speed immediately beneath a seismic station is presented. The P-wave polarization direction is only sensitive to shear wave speed but not to compressional wave speed, while the S-wave polarization direction is sensitive to both wave speeds. The technique is applied to data from the High-Sensitivity Seismograph Network in Japan, and the results show that the wave speed estimates obtained from polarization analysis are compatible with those from borehole measurements. The lateral variations in wave speeds correlate with geological and physical features such as topography and volcanoes. The technique requires minimal computation resources, and can be used on any number of three-component teleseismic recordings, opening opportunities for non-invasive and inexpensive study of the shallowest (˜100 m) crustal structures.

Correlation of Rupture Life, Creep Rate, and Microstructure for Type 304 Stainless Steel

NASA Technical Reports Server (NTRS)

Swindeman, R. W.; Moteff, J.

1983-01-01

The stress and temperature sensitivites of the rupture life and secondary creep rate were examined in detail for a single heat of type 304 stainless steel (9T2796). Assuming that the rupture life has a power law stress dependency, relatively small differences in the stress exponent were observed over a broad range of stress and temperature. In contrast, large changes were observed for equivalent parameter for secondary creep rate. As a result of these differences, the Monkman-Grant correlation was sensitive to stress and temperature below 650 C. Metallurgical studies based on light and transmission electron microscopy suggested that the temperature and stress sensitivities of secondary creep rate at temperatures below 650 C were related to features of the substructure not present at higher temperature. Specifically, the presence of a fine dislocation network stabilized by precipitates altered the stress and temperature sensitivities relative to what might be expected from high temperature studies.

Predicting metabolic syndrome using decision tree and support vector machine methods.

PubMed

Karimi-Alavijeh, Farzaneh; Jalili, Saeed; Sadeghi, Masoumeh

2016-05-01

Metabolic syndrome which underlies the increased prevalence of cardiovascular disease and Type 2 diabetes is considered as a group of metabolic abnormalities including central obesity, hypertriglyceridemia, glucose intolerance, hypertension, and dyslipidemia. Recently, artificial intelligence based health-care systems are highly regarded because of its success in diagnosis, prediction, and choice of treatment. This study employs machine learning technics for predict the metabolic syndrome. This study aims to employ decision tree and support vector machine (SVM) to predict the 7-year incidence of metabolic syndrome. This research is a practical one in which data from 2107 participants of Isfahan Cohort Study has been utilized. The subjects without metabolic syndrome according to the ATPIII criteria were selected. The features that have been used in this data set include: gender, age, weight, body mass index, waist circumference, waist-to-hip ratio, hip circumference, physical activity, smoking, hypertension, antihypertensive medication use, systolic blood pressure (BP), diastolic BP, fasting blood sugar, 2-hour blood glucose, triglycerides (TGs), total cholesterol, low-density lipoprotein, high density lipoprotein-cholesterol, mean corpuscular volume, and mean corpuscular hemoglobin. Metabolic syndrome was diagnosed based on ATPIII criteria and two methods of decision tree and SVM were selected to predict the metabolic syndrome. The criteria of sensitivity, specificity and accuracy were used for validation. SVM and decision tree methods were examined according to the criteria of sensitivity, specificity and accuracy. Sensitivity, specificity and accuracy were 0.774 (0.758), 0.74 (0.72) and 0.757 (0.739) in SVM (decision tree) method. The results show that SVM method sensitivity, specificity and accuracy is more efficient than decision tree. The results of decision tree method show that the TG is the most important feature in predicting metabolic syndrome. According to this study, in cases where only the final result of the decision is regarded significant, SVM method can be used with acceptable accuracy in decision making medical issues. This method has not been implemented in the previous research.

Conversion Discriminative Analysis on Mild Cognitive Impairment Using Multiple Cortical Features from MR Images.

PubMed

Guo, Shengwen; Lai, Chunren; Wu, Congling; Cen, Guiyin

2017-01-01

Neuroimaging measurements derived from magnetic resonance imaging provide important information required for detecting changes related to the progression of mild cognitive impairment (MCI). Cortical features and changes play a crucial role in revealing unique anatomical patterns of brain regions, and further differentiate MCI patients from normal states. Four cortical features, namely, gray matter volume, cortical thickness, surface area, and mean curvature, were explored for discriminative analysis among three groups including the stable MCI (sMCI), the converted MCI (cMCI), and the normal control (NC) groups. In this study, 158 subjects (72 NC, 46 sMCI, and 40 cMCI) were selected from the Alzheimer's Disease Neuroimaging Initiative. A sparse-constrained regression model based on the l2-1-norm was introduced to reduce the feature dimensionality and retrieve essential features for the discrimination of the three groups by using a support vector machine (SVM). An optimized strategy of feature addition based on the weight of each feature was adopted for the SVM classifier in order to achieve the best classification performance. The baseline cortical features combined with the longitudinal measurements for 2 years of follow-up data yielded prominent classification results. In particular, the cortical thickness produced a classification with 98.84% accuracy, 97.5% sensitivity, and 100% specificity for the sMCI-cMCI comparison; 92.37% accuracy, 84.78% sensitivity, and 97.22% specificity for the cMCI-NC comparison; and 93.75% accuracy, 92.5% sensitivity, and 94.44% specificity for the sMCI-NC comparison. The best performances obtained by the SVM classifier using the essential features were 5-40% more than those using all of the retained features. The feasibility of the cortical features for the recognition of anatomical patterns was certified; thus, the proposed method has the potential to improve the clinical diagnosis of sub-types of MCI and predict the risk of its conversion to Alzheimer's disease.

Non-linear feature extraction from HRV signal for mortality prediction of ICU cardiovascular patient.

PubMed

Karimi Moridani, Mohammad; Setarehdan, Seyed Kamaledin; Motie Nasrabadi, Ali; Hajinasrollah, Esmaeil

2016-01-01

Intensive care unit (ICU) patients are at risk of in-ICU morbidities and mortality, making specific systems for identifying at-risk patients a necessity for improving clinical care. This study presents a new method for predicting in-hospital mortality using heart rate variability (HRV) collected from the times of a patient's ICU stay. In this paper, a HRV time series processing based method is proposed for mortality prediction of ICU cardiovascular patients. HRV signals were obtained measuring R-R time intervals. A novel method, named return map, is then developed that reveals useful information from the HRV time series. This study also proposed several features that can be extracted from the return map, including the angle between two vectors, the area of triangles formed by successive points, shortest distance to 45° line and their various combinations. Finally, a thresholding technique is proposed to extract the risk period and to predict mortality. The data used to evaluate the proposed algorithm obtained from 80 cardiovascular ICU patients, from the first 48 h of the first ICU stay of 40 males and 40 females. This study showed that the angle feature has on average a sensitivity of 87.5% (with 12 false alarms), the area feature has on average a sensitivity of 89.58% (with 10 false alarms), the shortest distance feature has on average a sensitivity of 85.42% (with 14 false alarms) and, finally, the combined feature has on average a sensitivity of 92.71% (with seven false alarms). The results showed that the last half an hour before the patient's death is very informative for diagnosing the patient's condition and to save his/her life. These results confirm that it is possible to predict mortality based on the features introduced in this paper, relying on the variations of the HRV dynamic characteristics.

MnO Nanoparticle@Mesoporous Carbon Composites Grown on Conducting Substrates Featuring High-performance Lithium-ion Battery, Supercapacitor and Sensor

PubMed Central

Wang, Tianyu; Peng, Zheng; Wang, Yuhang; Tang, Jing; Zheng, Gengfeng

2013-01-01

We demonstrate a facile, two-step coating/calcination approach to grow a uniform MnO nanoparticle@mesoporous carbon (MnO@C) composite on conducting substrates, by direct coating of the Mn-oleate precursor solution without any conducting/binding reagents, and subsequent thermal calcination. The monodispersed, sub-10 nm MnO nanoparticles offer high theoretical energy storage capacities and catalytic properties, and the mesoporous carbon coating allows for enhanced electrolyte transport and charge transfer towards/from MnO surface. In addition, the direct growth and attachment of the MnO@C nanocomposite in the supporting conductive substrates provide much reduced contact resistances and efficient charge transfer. These excellent features allow the use of MnO@C nanocomposites as lithium-ion battery and supercapacitor electrodes for energy storage, with high reversible capacity at large current densities, as well as excellent cycling and mechanical stabilities. Moreover, this MnO@C nanocomposite has also demonstrated a high sensitivity for H2O2 detection, and also exhibited attractive potential for the tumor cell analysis. PMID:24045767

Utilization of Short-Simulations for Tuning High-Resolution Climate Model

NASA Astrophysics Data System (ADS)

Lin, W.; Xie, S.; Ma, P. L.; Rasch, P. J.; Qian, Y.; Wan, H.; Ma, H. Y.; Klein, S. A.

2016-12-01

Many physical parameterizations in atmospheric models are sensitive to resolution. Tuning the models that involve a multitude of parameters at high resolution is computationally expensive, particularly when relying primarily on multi-year simulations. This work describes a complementary set of strategies for tuning high-resolution atmospheric models, using ensembles of short simulations to reduce the computational cost and elapsed time. Specifically, we utilize the hindcast approach developed through the DOE Cloud Associated Parameterization Testbed (CAPT) project for high-resolution model tuning, which is guided by a combination of short (< 10 days ) and longer ( 1 year) Perturbed Parameters Ensemble (PPE) simulations at low resolution to identify model feature sensitivity to parameter changes. The CAPT tests have been found to be effective in numerous previous studies in identifying model biases due to parameterized fast physics, and we demonstrate that it is also useful for tuning. After the most egregious errors are addressed through an initial "rough" tuning phase, longer simulations are performed to "hone in" on model features that evolve over longer timescales. We explore these strategies to tune the DOE ACME (Accelerated Climate Modeling for Energy) model. For the ACME model at 0.25° resolution, it is confirmed that, given the same parameters, major biases in global mean statistics and many spatial features are consistent between Atmospheric Model Intercomparison Project (AMIP)-type simulations and CAPT-type hindcasts, with just a small number of short-term simulations for the latter over the corresponding season. The use of CAPT hindcasts to find parameter choice for the reduction of large model biases dramatically improves the turnaround time for the tuning at high resolution. Improvement seen in CAPT hindcasts generally translates to improved AMIP-type simulations. An iterative CAPT-AMIP tuning approach is therefore adopted during each major tuning cycle, with the former to survey the likely responses and narrow the parameter space, and the latter to verify the results in climate context along with assessment in greater detail once an educated set of parameter choice is selected. Limitations on using short-term simulations for tuning climate model are also discussed.

Clinical Features and Associated Likelihood of Primary Ciliary Dyskinesia in Children and Adolescents

PubMed Central

Ferkol, Thomas W.; Davis, Stephanie D.; Lee, Hye-Seung; Rosenfeld, Margaret; Dell, Sharon D.; Sagel, Scott D.; Milla, Carlos; Olivier, Kenneth N.; Sullivan, Kelli M.; Zariwala, Maimoona A.; Pittman, Jessica E.; Shapiro, Adam J.; Carson, Johnny L.; Krischer, Jeffrey; Hazucha, Milan J.

2016-01-01

Rationale: Primary ciliary dyskinesia (PCD), a genetically heterogeneous, recessive disorder of motile cilia, is associated with distinct clinical features. Diagnostic tests, including ultrastructural analysis of cilia, nasal nitric oxide measurements, and molecular testing for mutations in PCD genes, have inherent limitations. Objectives: To define a statistically valid combination of systematically defined clinical features that strongly associates with PCD in children and adolescents. Methods: Investigators at seven North American sites in the Genetic Disorders of Mucociliary Clearance Consortium prospectively and systematically assessed individuals (aged 0–18 yr) referred due to high suspicion for PCD. The investigators defined specific clinical questions for the clinical report form based on expert opinion. Diagnostic testing was performed using standardized protocols and included nasal nitric oxide measurement, ciliary biopsy for ultrastructural analysis of cilia, and molecular genetic testing for PCD-associated genes. Final diagnoses were assigned as “definite PCD” (hallmark ultrastructural defects and/or two mutations in a PCD-associated gene), “probable/possible PCD” (no ultrastructural defect or genetic diagnosis, but compatible clinical features and nasal nitric oxide level in PCD range), and “other diagnosis or undefined.” Criteria were developed to define early childhood clinical features on the basis of responses to multiple specific queries. Each defined feature was tested by logistic regression. Sensitivity and specificity analyses were conducted to define the most robust set of clinical features associated with PCD. Measurements and Main Results: From 534 participants 18 years of age and younger, 205 were identified as having “definite PCD” (including 164 with two mutations in a PCD-associated gene), 187 were categorized as “other diagnosis or undefined,” and 142 were defined as having “probable/possible PCD.” Participants with “definite PCD” were compared with the “other diagnosis or undefined” group. Four criteria-defined clinical features were statistically predictive of PCD: laterality defect; unexplained neonatal respiratory distress; early-onset, year-round nasal congestion; and early-onset, year-round wet cough (adjusted odds ratios of 7.7, 6.6, 3.4, and 3.1, respectively). The sensitivity and specificity based on the number of criteria-defined clinical features were four features, 0.21 and 0.99, respectively; three features, 0.50 and 0.96, respectively; and two features, 0.80 and 0.72, respectively. Conclusions: Systematically defined early clinical features could help identify children, including infants, likely to have PCD. Clinical trial registered with ClinicalTrials.gov (NCT00323167). PMID:27070726

Are Psychopaths Morally Sensitive?

ERIC Educational Resources Information Center

Maxwell, Bruce; Le Sage, Leonie

2009-01-01

Philosophical and psychological opinion is divided over whether moral sensitivity, understood as the ability to pick out a situation's morally salient features, necessarily involves emotional engagement. This paper seeks to offer insight into this question. It reasons that if moral sensitivity does draw significantly on affective capacities of…

Early diagnosis of genital mucosal melanoma: how good are our dermoscopic criteria?

PubMed

Rogers, Tova; Pulitzer, Melissa; Marino, Maria L; Marghoob, Ashfaq A; Zivanovic, Oliver; Marchetti, Michael A

2016-10-01

There are limited studies on the dermoscopic features of mucosal melanoma, particularly early-stage lesions. Described criteria include the presence of blue, gray, or white colors, with a reported sensitivity of 100%. It is unclear if these features will aid in the detection of early mucosal melanoma or improve diagnostic accuracy compared to naked-eye examination alone. An Asian female in her fifties was referred for evaluation of an asymptomatic, irregularly pigmented patch of the clitoral hood and labia minora of unknown duration. Her past medical history was notable for Stage IV non-small cell lung cancer. She denied a personal or family history of skin cancer. Dermoscopic evaluation of the vulvar lesion revealed heterogeneous brown and black pigmentation mostly composed of thick lines. There were no other colors or structures present. As the differential diagnosis included vulvar melanosis and mucosal melanoma, the patient was recommended to undergo biopsy, which was delayed due to complications from her underlying lung cancer. Repeat dermoscopic imaging performed three months later revealed significant changes concerning for melanoma, including increase in size, asymmetric darkening, and the appearance of structureless areas and central blue and pink colors. Histopathological examination of a biopsy and subsequent resection confirmed the diagnosis of melanoma in situ. Previously described dermoscopic features for mucosal melanoma may not have high sensitivity for early melanomas. Additional studies are needed to define the dermoscopic characteristics of mucosal melanomas that aid in early detection. Health care providers should have a low threshold for biopsy of mucosal lesions that show any clinical or dermoscopic features of melanoma, especially in older women.

Learning about the internal structure of categories through classification and feature inference.

PubMed

Jee, Benjamin D; Wiley, Jennifer

2014-01-01

Previous research on category learning has found that classification tasks produce representations that are skewed toward diagnostic feature dimensions, whereas feature inference tasks lead to richer representations of within-category structure. Yet, prior studies often measure category knowledge through tasks that involve identifying only the typical features of a category. This neglects an important aspect of a category's internal structure: how typical and atypical features are distributed within a category. The present experiments tested the hypothesis that inference learning results in richer knowledge of internal category structure than classification learning. We introduced several new measures to probe learners' representations of within-category structure. Experiment 1 found that participants in the inference condition learned and used a wider range of feature dimensions than classification learners. Classification learners, however, were more sensitive to the presence of atypical features within categories. Experiment 2 provided converging evidence that classification learners were more likely to incorporate atypical features into their representations. Inference learners were less likely to encode atypical category features, even in a "partial inference" condition that focused learners' attention on the feature dimensions relevant to classification. Overall, these results are contrary to the hypothesis that inference learning produces superior knowledge of within-category structure. Although inference learning promoted representations that included a broad range of category-typical features, classification learning promoted greater sensitivity to the distribution of typical and atypical features within categories.