Optimization of cloud point extraction and solid phase extraction methods for speciation of arsenic in natural water using multivariate technique.

PubMed

Baig, Jameel A; Kazi, Tasneem G; Shah, Abdul Q; Arain, Mohammad B; Afridi, Hassan I; Kandhro, Ghulam A; Khan, Sumaira

2009-09-28

The simple and rapid pre-concentration techniques viz. cloud point extraction (CPE) and solid phase extraction (SPE) were applied for the determination of As(3+) and total inorganic arsenic (iAs) in surface and ground water samples. The As(3+) was formed complex with ammonium pyrrolidinedithiocarbamate (APDC) and extracted by surfactant-rich phases in the non-ionic surfactant Triton X-114, after centrifugation the surfactant-rich phase was diluted with 0.1 mol L(-1) HNO(3) in methanol. While total iAs in water samples was adsorbed on titanium dioxide (TiO(2)); after centrifugation, the solid phase was prepared to be slurry for determination. The extracted As species were determined by electrothermal atomic absorption spectrometry. The multivariate strategy was applied to estimate the optimum values of experimental factors for the recovery of As(3+) and total iAs by CPE and SPE. The standard addition method was used to validate the optimized methods. The obtained result showed sufficient recoveries for As(3+) and iAs (>98.0%). The concentration factor in both cases was found to be 40.

Spectrophotometric determination of paracetamol in urine with tetrahydroxycalix[4]arene as a coupling reagent and preconcentration with triton X-114 using cloud point extraction.

PubMed

Filik, Hayati; Sener, Izzet; Cekiç, Sema Demirci; Kiliç, Emine; Apak, Reşat

2006-06-01

In the present paper, conventional spectrophotometry in conjunction with cloud point extraction-preconcentration were investigated as alternative methods for paracetamol (PCT) assay in urine samples. Cloud point extraction (CPE) was employed for the preconcentration of p-aminophenol (PAP) prior to spectrophotometric determination using the non-ionic surfactant Triton X-114 (TX-114) as an extractant. The developed methods were based on acidic hydrolysis of PCT to PAP, which reacted at room temperature with 25,26,27,28-tetrahydroxycalix[4]arene (CAL4) in the presence of an oxidant (KIO(4)) to form an blue colored product. The PAP-CAL4 blue dye formed was subsequently entrapped in the surfactant micelles of Triton X-114. Cloud point phase separation with the aid of Triton X-114 induced by addition of Na(2)SO(4) solution was performed at room temperature as an advantage over other CPE assays requiring elevated temperatures. The 580 nm-absorbance maximum of the formed product was shifted bathochromically to 590 nm with CPE. The working range of 1.5-12 microg ml(-1) achieved by conventional spectrophotometry was reduced down to 0.14-1.5 microg ml(-1) with cloud point extraction, which was lower than those of most literature flow-through assays that also suffer from nonspecific absorption in the UV region. By preconcentrating 10 ml sample solution, a detection limit as low as 40.0 ng ml(-1) was obtained after a single-step extraction, achieving a preconcentration factor of 10. The stoichiometric composition of the dye was found to be 1 : 4 (PAP : CAL4). The impact of a number of parameters such as concentrations of CAL4, KIO(4), Triton X-100 (TX-100), and TX-114, extraction temperature, time periods for incubation and centrifugation, and sample volume were investigated in detail. The determination of PAP in the presence of paracetamol in micellar systems under these conditions is limited. The established procedures were successfully adopted for the determination of PCT in urine samples. Since the drug is rapidly absorbed and excreted largely in urine and its high doses have been associated with lethal hepatic necrosis and renal failure, development of a rapid, sensitive and selective assay of PCT is of vital importance for fast urinary screening and antidote administration before applying more sophisticated, but costly and laborious hyphenated instrumental techniques of HPLC-SPE-NMR-MS.

Determination of xanthohumol in beer based on cloud point extraction coupled with high performance liquid chromatography.

PubMed

Chen, Ligang; Zhao, Qi; Jin, Haiyan; Zhang, Xiaopan; Xu, Yang; Yu, Aimin; Zhang, Hanqi; Ding, Lan

2010-04-15

A method based on coupling of cloud point extraction (CPE) with high performance liquid chromatography separation and ultraviolet detection was developed for determination of xanthohumol in beer. The nonionic surfactant Triton X-114 was chosen as the extraction medium. The parameters affecting the CPE were evaluated and optimized. The highest extraction yield of xanthohumol was obtained with 2.5% of Triton X-114 (v/v) at pH 5.0, 15% of sodium chloride (w/v), 70 degrees C of equilibrium temperature and 10 min of equilibrium time. Under these conditions, the limit of detection of xanthohumol is 0.003 mg L(-1). The intra- and inter-day precisions expressed as relative standard deviations are 4.6% and 6.3%, respectively. The proposed method was successfully applied for determination of xanthohumol in various beer samples. The contents of xanthohumol in these samples are in the range of 0.052-0.628 mg L(-1), and the recoveries ranging from 90.7% to 101.9% were obtained. The developed method was demonstrated to be efficient, green, rapid and inexpensive for extraction and determination of xanthohumol in beer. (c) 2010 Elsevier B.V. All rights reserved.

Determination of trace uranium by resonance fluorescence method coupled with photo-catalytic technology and dual cloud point extraction

NASA Astrophysics Data System (ADS)

Li, Jiekang; Li, Guirong; Han, Qian

2016-12-01

In this paper, two kinds of salophens (Sal) with different solubilities, Sal1 and Sal2, have been respectively synthesized, and they all can combine with uranyl to form stable complexes: [UO22 +-Sal1] and [UO22 +-Sal2]. Among them, [UO22 +-Sal1] was used as ligand to extract uranium in complex samples by dual cloud point extraction (dCPE), and [UO22 +-Sal2] was used as catalyst for the determination of uranium by photocatalytic resonance fluorescence (RF) method. The photocatalytic characteristic of [UO22 +-Sal2] on the oxidized pyronine Y (PRY) by potassium bromate which leads to the decrease of RF intensity of PRY were studied. The reduced value of RF intensity of reaction system (ΔF) is in proportional to the concentration of uranium (c), and a novel photo-catalytic RF method was developed for the determination of trace uranium (VI) after dCPE. The combination of photo-catalytic RF techniques and dCPE procedure endows the presented methods with enhanced sensitivity and selectivity. Under optimal conditions, the linear calibration curves range for 0.067 to 6.57 ng mL- 1, the linear regression equation was ΔF = 438.0 c (ng mL- 1) + 175.6 with the correlation coefficient r = 0.9981. The limit of detection was 0.066 ng mL- 1. The proposed method was successfully applied for the separation and determination of uranium in real samples with the recoveries of 95.0-103.5%. The mechanisms of the indicator reaction and dCPE are discussed.

Determination of total selenium in food samples by d-CPE and HG-AFS.

PubMed

Wang, Mei; Zhong, Yizhou; Qin, Jinpeng; Zhang, Zehua; Li, Shan; Yang, Bingyi

2017-07-15

A dual-cloud point extraction (d-CPE) procedure was developed for the simultaneous preconcentration and determination of trace level Se in food samples by hydride generation-atomic fluorescence spectrometry (HG-AFS). The Se(IV) was complexed with ammonium pyrrolidinedithiocarbamate (APDC) in a Triton X-114 surfactant-rich phase, which was then treated with a mixture of 16% (v/v) HCl and 20% (v/v) H 2 O 2 . This converted the Se(IV)-APDC into free Se(IV), which was back extracted into an aqueous phase at the second cloud point extraction stage. This aqueous phase was analyzed directly by HG-AFS. Optimization of the experimental conditions gave a limit of detection of 0.023μgL -1 with an enhancement factor of 11.8 when 50mL of sample solution was preconcentrated to 3mL. The relative standard deviation was 4.04% (c=6.0μgL -1 , n=10). The proposed method was applied to determine the Se contents in twelve food samples with satisfactory recoveries of 95.6-105.2%. Copyright © 2016 Elsevier Ltd. All rights reserved.

Cloud point extraction coupled with microwave-assisted back-extraction (CPE-MABE) for determination of Eszopiclone (Z-drug) using UV-Visible, HPLC and mass spectroscopic (MS) techniques: Spiked and in vivo analysis.

PubMed

Kori, Shivpoojan; Parmar, Ankush; Goyal, Jony; Sharma, Shweta

2018-02-01

A procedure for the determination of Eszopiclone (ESZ) from complex matrices i.e. in vitro (spiked matrices), as well as in vivo (mice model) was developed using cloud point extraction coupled with microwave-assisted back-extraction (CPE-MABE). Analytical measurements have been carried using UV-Visible, HPLC and MS techniques. The proposed method has been validated according to ICH guidelines and legitimate reproducible and reliability of protocol is assessed through intraday and inter-day precision <3.61% and <4.70%, respectively. Limit of detection has been obtained as 0.083μg/mL and 0.472μg/mL respectively, for HPLC and UV-Visible techniques, corresponding to assessed linearity range. The coaservate phase in CPE was back extracted under microwaves exposure, with isooctane at pre-concentration factor ~50 when 5mL of sample solution was pre-concentrated to 0.1mL. Under optimized conditions i.e. Aqueous-Triton X-114 4% (w/v), pH4.0, NaCl 4% (w/v) and equilibrium temperature of 45°C for 20min, average extraction recovery has been obtained between 89.8 and 99.2% and 84.0-99.2% from UV-Visible and HPLC analysis, respectively. The method has been successfully applied to the pharmacokinetic estimation (post intraperitoneal administration) of ESZ in mice. MS analysis precisely depicted the presence of active N‑desmethyl zopiclone in impales as well as in mice plasma. Copyright © 2018 Elsevier B.V. All rights reserved.

Cloud-point extraction and reversed-phase high-performance liquid chromatography for the determination of synthetic phenolic antioxidants in edible oils.

PubMed

Chen, Miao; Xia, Qinghai; Liu, Mousheng; Yang, Yaling

2011-01-01

A cloud-point extraction (CPE) method using Triton X-114 (TX-114) nonionic surfactant was developed for the extraction and preconcentration of propyl gallate (PG), tertiary butyl hydroquinone (TBHQ), butylated hydroxyanisole (BHA), and butylated hydroxytoluene (BHT) from edible oils. The optimum conditions of CPE were 2.5% (v/v) TX-114, 0.5% (w/v) NaCl and 40 min equilibration time at 50 °C. The surfactant-rich phase was then analyzed by reversed-phase high-performance liquid chromatography with ultraviolet detection at 280 nm, using a gradient mobile phase consisting of methanol and 1.5% (v/v) acetic acid. Under the studied conditions, 4 synthetic phenolic antioxidants (SPAs) were successfully separated within 24 min. The limits of detection (LOD) were 1.9 ng mL(-1) for PG, 11 ng mL(-1) for TBHQ, 2.3 ng mL(-1) for BHA, and 5.9 ng mL(-1) for BHT. Recoveries of the SPAs spiked into edible oil were in the range 81% to 88%. The CPE method was shown to be potentially useful for the preconcentration of the target analytes, with a preconcentration factor of 14. Moreover, the method is simple, has high sensitivity, consumes much less solvent than traditional methods, and is environment-friendly. Practical Application: The method established in this article uses less organic solvent to extract SPAs from edible oils; it is simple, highly sensitive and results in no pollution to the environment.

Determination of Ultra-trace Rhodium in Water Samples by Graphite Furnace Atomic Absorption Spectrometry after Cloud Point Extraction Using 2-(5-Iodo-2-Pyridylazo)-5-Dimethylaminoaniline as a Chelating Agent.

PubMed

Han, Quan; Huo, Yanyan; Wu, Jiangyan; He, Yaping; Yang, Xiaohui; Yang, Longhu

2017-03-24

A highly sensitive method based on cloud point extraction (CPE) separation/preconcentration and graphite furnace atomic absorption spectrometry (GFAAS) detection has been developed for the determination of ultra-trace amounts of rhodium in water samples. A new reagent, 2-(5-iodo-2-pyridylazo)-5-dimethylaminoaniline (5-I-PADMA), was used as the chelating agent and the nonionic surfactant TritonX-114 was chosen as extractant. In a HAc-NaAc buffer solution at pH 5.5, Rh(III) reacts with 5-I-PADMA to form a stable chelate by heating in a boiling water bath for 10 min. Subsequently, the chelate is extracted into the surfactant phase and separated from bulk water. The factors affecting CPE were investigated. Under the optimized conditions, the calibration graph was linear in the range of 0.1-6.0 ng/mL, the detection limit was 0.023 ng/mL for rhodium and relative standard deviation was 3.67% ( c = 1.0 ng/mL, n = 11)．The method has been applied to the determination of trace rhodium in water samples with satisfactory results.

Determination of trace uranium by resonance fluorescence method coupled with photo-catalytic technology and dual cloud point extraction.

PubMed

Li, Jiekang; Li, Guirong; Han, Qian

2016-12-05

In this paper, two kinds of salophens (Sal) with different solubilities, Sal1 and Sal2, have been respectively synthesized, and they all can combine with uranyl to form stable complexes: [UO2(2+)-Sal1] and [UO2(2+)-Sal2]. Among them, [UO2(2+)-Sal1] was used as ligand to extract uranium in complex samples by dual cloud point extraction (dCPE), and [UO2(2+)-Sal2] was used as catalyst for the determination of uranium by photocatalytic resonance fluorescence (RF) method. The photocatalytic characteristic of [UO2(2+)-Sal2] on the oxidized pyronine Y (PRY) by potassium bromate which leads to the decrease of RF intensity of PRY were studied. The reduced value of RF intensity of reaction system (ΔF) is in proportional to the concentration of uranium (c), and a novel photo-catalytic RF method was developed for the determination of trace uranium (VI) after dCPE. The combination of photo-catalytic RF techniques and dCPE procedure endows the presented methods with enhanced sensitivity and selectivity. Under optimal conditions, the linear calibration curves range for 0.067 to 6.57ngmL(-1), the linear regression equation was ΔF=438.0 c (ngmL(-1))+175.6 with the correlation coefficient r=0.9981. The limit of detection was 0.066ngmL(-1). The proposed method was successfully applied for the separation and determination of uranium in real samples with the recoveries of 95.0-103.5%. The mechanisms of the indicator reaction and dCPE are discussed. Copyright © 2016 Elsevier B.V. All rights reserved.

Cloud-point extraction of green-polymers from Cupriavidus necator lysate using thermoseparating-based aqueous two-phase extraction.

PubMed

Leong, Yoong Kit; Lan, John Chi-Wei; Loh, Hwei-San; Ling, Tau Chuan; Ooi, Chien Wei; Show, Pau Loke

2017-03-01

Polyhydroxyalkanoates (PHAs), a class of renewable and biodegradable green polymers, have gained attraction as a potential substitute for the conventional plastics due to the increasing concern towards environmental pollution as well as the rapidly depleting petroleum reserve. Nevertheless, the high cost of downstream processing of PHA has been a bottleneck for the wide adoption of PHAs. Among the options of PHAs recovery techniques, aqueous two-phase extraction (ATPE) outshines the others by having the advantages of providing a mild environment for bioseparation, being green and non-toxic, the capability to handle a large operating volume and easily scaled-up. Utilizing unique properties of thermo-responsive polymer which has decreasing solubility in its aqueous solution as the temperature rises, cloud point extraction (CPE) is an ATPE technique that allows its phase-forming component to be recycled and reused. A thorough literature review has shown that this is the first time isolation and recovery of PHAs from Cupriavidus necator H16 via CPE was reported. The optimum condition for PHAs extraction (recovery yield of 94.8% and purification factor of 1.42 fold) was achieved under the conditions of 20 wt/wt % ethylene oxide-propylene oxide (EOPO) with molecular weight of 3900 g/mol and 10 mM of sodium chloride addition at thermoseparating temperature of 60°C with crude feedstock limit of 37.5 wt/wt %. Recycling and reutilization of EOPO 3900 can be done at least twice with satisfying yield and PF. CPE has been demonstrated as an effective technique for the extraction of PHAs from microbial crude culture. Copyright © 2016 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Dual cloud point extraction coupled with hydrodynamic-electrokinetic two-step injection followed by micellar electrokinetic chromatography for simultaneous determination of trace phenolic estrogens in water samples.

PubMed

Wen, Yingying; Li, Jinhua; Liu, Junshen; Lu, Wenhui; Ma, Jiping; Chen, Lingxin

2013-07-01

A dual cloud point extraction (dCPE) off-line enrichment procedure coupled with a hydrodynamic-electrokinetic two-step injection online enrichment technique was successfully developed for simultaneous preconcentration of trace phenolic estrogens (hexestrol, dienestrol, and diethylstilbestrol) in water samples followed by micellar electrokinetic chromatography (MEKC) analysis. Several parameters affecting the extraction and online injection conditions were optimized. Under optimal dCPE-two-step injection-MEKC conditions, detection limits of 7.9-8.9 ng/mL and good linearity in the range from 0.05 to 5 μg/mL with correlation coefficients R(2) ≥ 0.9990 were achieved. Satisfactory recoveries ranging from 83 to 108% were obtained with lake and tap water spiked at 0.1 and 0.5 μg/mL, respectively, with relative standard deviations (n = 6) of 1.3-3.1%. This method was demonstrated to be convenient, rapid, cost-effective, and environmentally benign, and could be used as an alternative to existing methods for analyzing trace residues of phenolic estrogens in water samples.

Non-chromatographic speciation of chromium at sub-ppb levels using cloud point extraction in the presence of unmodified silver nanoparticles.

PubMed

López-García, Ignacio; Vicente-Martínez, Yesica; Hernández-Córdoba, Manuel

2015-01-01

The cloud point extraction (CPE) of silver nanoparticles (AgNPs) by Triton X-114 allows chromium (III) ions to be transferred to the surfactant-rich phase, where they can be measured by electrothermal atomic absorption spectrometry. Using 20 mL sample and 50 μL Triton X-114 (30% w/v), the enrichment factor was 1150, and calibration graphs were obtained in the 5-100 ng L(-1) chromium range in the presence of 5 µg L(-1) AgNPs. Speciation of trivalent and hexavalent chromium was achieved by carrying out two CPE experiments, one of them in the presence of ethylenediaminetetraacetate. While in the first experiment, in absence of the complexing agent, the concentration of total chromium was obtained, the analytical signal measured in the presence of this chemical allowed the chromium (VI) concentration to be measured, being that of chromium (III) calculated by difference. The reliability of the procedure was verified by using three standard reference materials before applying to water, beer and wine samples. Copyright © 2014 Elsevier B.V. All rights reserved.

Species selective preconcentration and quantification of gold nanoparticles using cloud point extraction and electrothermal atomic absorption spectrometry.

PubMed

Hartmann, Georg; Schuster, Michael

2013-01-25

The determination of metallic nanoparticles in environmental samples requires sample pretreatment that ideally combines pre-concentration and species selectivity. With cloud point extraction (CPE) using the surfactant Triton X-114 we present a simple and cost effective separation technique that meets both criteria. Effective separation of ionic gold species and Au nanoparticles (Au-NPs) is achieved by using sodium thiosulphate as a complexing agent. The extraction efficiency for Au-NP ranged from 1.01 ± 0.06 (particle size 2 nm) to 0.52 ± 0.16 (particle size 150 nm). An enrichment factor of 80 and a low limit of detection of 5 ng L(-1) is achieved using electrothermal atomic absorption spectrometry (ET-AAS) for quantification. TEM measurements showed that the particle size is not affected by the CPE process. Natural organic matter (NOM) is tolerated up to a concentration of 10 mg L(-1). The precision of the method expressed as the standard deviation of 12 replicates at an Au-NP concentration of 100 ng L(-1) is 9.5%. A relation between particle concentration and the extraction efficiency was not observed. Spiking experiments showed a recovery higher than 91% for environmental water samples. Copyright © 2012 Elsevier B.V. All rights reserved.

Cloud point extraction thermospray flame quartz furnace atomic absorption spectrometry for determination of ultratrace cadmium in water and urine

NASA Astrophysics Data System (ADS)

Wu, Peng; Zhang, Yunchang; Lv, Yi; Hou, Xiandeng

2006-12-01

A simple, low cost and highly sensitive method based on cloud point extraction (CPE) for separation/preconcentration and thermospray flame quartz furnace atomic absorption spectrometry was proposed for the determination of ultratrace cadmium in water and urine samples. The analytical procedure involved the formation of analyte-entrapped surfactant micelles by mixing the analyte solution with an ammonium pyrrolidinedithiocarbamate (APDC) solution and a Triton X-114 solution. When the temperature of the system was higher than the cloud point of Triton X-114, the complex of cadmium-PDC entered the surfactant-rich phase and thus separation of the analyte from the matrix was achieved. Under optimal chemical and instrumental conditions, the limit of detection was 0.04 μg/L for cadmium with a sample volume of 10 mL. The analytical results of cadmium in water and urine samples agreed well with those by ICP-MS.

An evaluation of the bioaccessibility of arsenic in corn and rice samples based on cloud point extraction and hydride generation coupled to atomic fluorescence spectrometry.

PubMed

Castor, José Martín Rosas; Portugal, Lindomar; Ferrer, Laura; Hinojosa-Reyes, Laura; Guzmán-Mar, Jorge Luis; Hernández-Ramírez, Aracely; Cerdà, Víctor

2016-08-01

A simple, inexpensive and rapid method was proposed for the determination of bioaccessible arsenic in corn and rice samples using an in vitro bioaccessibility assay. The method was based on the preconcentration of arsenic by cloud point extraction (CPE) using o,o-diethyldithiophosphate (DDTP) complex, which was generated from an in vitro extract using polyethylene glycol tert-octylphenyl ether (Triton X-114) as a surfactant prior to its detection by atomic fluorescence spectrometry with a hydride generation system (HG-AFS). The CPE method was optimized by a multivariate approach (two-level full factorial and Doehlert designs). A photo-oxidation step of the organic species prior to HG-AFS detection was included for the accurate quantification of the total As. The limit of detection was 1.34μgkg(-1) and 1.90μgkg(-1) for rice and corn samples, respectively. The accuracy of the method was confirmed by analyzing certified reference material ERM BC-211 (rice powder). The corn and rice samples that were analyzed showed a high bioaccessible arsenic content (72-88% and 54-96%, respectively), indicating a potential human health risk. Copyright © 2016 Elsevier Ltd. All rights reserved.

Development of a cloud point extraction and spectrophotometry-based microplate method for the determination of nitrite in human urine and blood.

PubMed

Zhao, Jiao; Lu, Yunhui; Fan, Chongyang; Wang, Jun; Yang, Yaling

2015-02-05

A novel and simple method for the sensitive determination of trace amounts of nitrite in human urine and blood has been developed by combination of cloud point extraction (CPE) and microplate assay. The method is based on the Griess reaction and the reaction product is extracted into nonionic surfactant Triton-X114 using CPE technique. In this study, decolorization treatment of urine and blood was applied to overcome the interference of matrix and enhance the sensitivity of nitrite detection. Multi-sample can be simultaneously detected thanks to a 96-well microplate technique. The effects of different operating parameters such as type of decolorizing agent, concentration of surfactant (Triton X-114), addition of (NH4)2SO4, extraction temperature and time, interfering elements were studied and optimum conditions were obtained. Under the optimum conditions, a linear calibration graph was obtained in the range of 10-400 ng mL(-1) of nitrite with limit of detection (LOD) of 2.5 ng mL(-1). The relative standard deviation (RSD) for determination of 100 ng mL(-1) of nitrite was 2.80%. The proposed method was successfully applied for the determination of nitrite in the urine and blood samples with recoveries of 92.6-101.2%. Copyright © 2014 Elsevier B.V. All rights reserved.

Spectrophotometric determination of low levels arsenic species in beverages after ion-pairing vortex-assisted cloud-point extraction with acridine red.

PubMed

Altunay, Nail; Gürkan, Ramazan; Kır, Ufuk

2016-01-01

A new, low-cost, micellar-sensitive and selective spectrophotometric method was developed for the determination of inorganic arsenic (As) species in beverage samples. Vortex-assisted cloud-point extraction (VA-CPE) was used for the efficient pre-concentration of As(V) in the selected samples. The method is based on selective and sensitive ion-pairing of As(V) with acridine red (ARH(+)) in the presence of pyrogallol and sequential extraction into the micellar phase of Triton X-45 at pH 6.0. Under the optimised conditions, the calibration curve was highly linear in the range of 0.8-280 µg l(-1) for As(V). The limits of detection and quantification of the method were 0.25 and 0.83 µg l(-1), respectively. The method was successfully applied to the determination of trace As in the pre-treated and digested samples under microwave and ultrasonic power. As(V) and total As levels in the samples were spectrophotometrically determined after pre-concentration with VA-CPE at 494 nm before and after oxidation with acidic KMnO4. The As(III) levels were calculated from the difference between As(V) and total As levels. The accuracy of the method was demonstrated by analysis of two certified reference materials (CRMs) where the measured values for As were statistically within the 95% confidence limit for the certified values.

A green and efficient procedure for the preconcentration and determination of cadmium, nickel and zinc from freshwater, hemodialysis solutions and tuna fish samples by cloud point extraction and flame atomic absorption spectrometry.

PubMed

Galbeiro, Rafaela; Garcia, Samara; Gaubeur, Ivanise

2014-04-01

Cloud point extraction (CPE) was used to simultaneously preconcentrate trace-level cadmium, nickel and zinc for determination by flame atomic absorption spectrometry (FAAS). 1-(2-Pyridilazo)-2-naphthol (PAN) was used as a complexing agent, and the metal complexes were extracted from the aqueous phase by the surfactant Triton X-114 ((1,1,3,3-tetramethylbutyl)phenyl-polyethylene glycol). Under optimized complexation and extraction conditions, the limits of detection were 0.37μgL(-1) (Cd), 2.6μgL(-1) (Ni) and 2.3μgL(-1) (Zn). This extraction was quantitative with a preconcentration factor of 30 and enrichment factor estimated to be 42, 40 and 43, respectively. The method was applied to different complex samples, and the accuracy was evaluated by analyzing a water standard reference material (NIST SRM 1643e), yielding results in agreement with the certified values. Copyright © 2013 Elsevier GmbH. All rights reserved.

A simple method for determination of carmine in food samples based on cloud point extraction and spectrophotometric detection.

PubMed

Heydari, Rouhollah; Hosseini, Mohammad; Zarabi, Sanaz

2015-01-01

In this paper, a simple and cost effective method was developed for extraction and pre-concentration of carmine in food samples by using cloud point extraction (CPE) prior to its spectrophotometric determination. Carmine was extracted from aqueous solution using Triton X-100 as extracting solvent. The effects of main parameters such as solution pH, surfactant and salt concentrations, incubation time and temperature were investigated and optimized. Calibration graph was linear in the range of 0.04-5.0 μg mL(-1) of carmine in the initial solution with regression coefficient of 0.9995. The limit of detection (LOD) and limit of quantification were 0.012 and 0.04 μg mL(-1), respectively. Relative standard deviation (RSD) at low concentration level (0.05 μg mL(-1)) of carmine was 4.8% (n=7). Recovery values in different concentration levels were in the range of 93.7-105.8%. The obtained results demonstrate the proposed method can be applied satisfactory to determine the carmine in food samples. Copyright © 2015 Elsevier B.V. All rights reserved.

A new method of UA_CPE coupled with spectrophotometry for the faster and cost-effective detection of proline in fruit juice, honey, and wine.

PubMed

Dağdeviren, Semahat; Altunay, Nail; Sayman, Yasin; Gürkan, Ramazan

2018-07-30

The study developed a new method for proline detection in honey, wine and fruit juice using ultrasound assisted-cloud point extraction (UA-CPE) and spectrophotometry. Initially, a quaternary complex was built, containing proline, histamine, Cu(II), and fluorescein at pH 5.5. Samples were treated with ethanol-water mixture before extraction and preconcentration, using an ultrasonic bath for 10 min at 40 °C (40 kHz, 300 W). After the optimization of variables affecting extraction efficiency, good linearity was obtained between 15 and 600 µg L -1 with sensitivity enhancement factor of 105. The limits of detection and quantification were 5.7 and 19.0 µg L -1 , respectively. The recovery percentage and relative standard deviations (RSD %) were between 95.3 and 103.3%, and 2.5 and 4.2%, respectively. The accuracy of the method was verified by the analysis of a standard reference material (SRM 2389a). Copyright © 2018 Elsevier Ltd. All rights reserved.

Cloud point extraction and diffuse reflectance-Fourier transform infrared spectroscopic determination of chromium(VI): A probe to adulteration in food stuffs.

PubMed

Tiwari, Swapnil; Deb, Manas Kanti; Sen, Bhupendra K

2017-04-15

A new cloud point extraction (CPE) method for the determination of hexavalent chromium i.e. Cr(VI) in food samples is established with subsequent diffuse reflectance-Fourier transform infrared (DRS-FTIR) analysis. The method demonstrates enrichment of Cr(VI) after its complexation with 1,5-diphenylcarbazide. The reddish-violet complex formed showed λ max at 540nm. Micellar phase separation at cloud point temperature of non-ionic surfactant, Triton X-100 occurred and complex was entrapped in surfactant and analyzed using DRS-FTIR. Under optimized conditions, the limit of detection (LOD) and quantification (LOQ) were 1.22 and 4.02μgmL -1 , respectively. Excellent linearity with correlation coefficient value of 0.94 was found for the concentration range of 1-100μgmL -1 . At 10μgmL -1 the standard deviation for 7 replicate measurements was found to be 0.11μgmL -1 . The method was successfully applied to commercially marketed food stuffs, and good recoveries (81-112%) were obtained by spiking the real samples. Copyright © 2016 Elsevier Ltd. All rights reserved.

Highly efficient micellar extraction of toxic picric acid into novel ionic liquid: Effect of parameters, solubilization isotherm, evaluation of thermodynamics and design parameters.

PubMed

Bhatt, Darshak R; Maheria, Kalpana C; Parikh, Jigisha K

2015-12-30

A simple and new approach in cloud point extraction (CPE) method was developed for removal of picric acid (PA) by the addition of N,N,N,N',N',N'-hexaethyl-ethane-1,2-diammonium dibromide ionic liquid (IL) in non-ionic surfactant Triton X-114 (TX-114). A significant increase in extraction efficiency was found upon the addition of dicationic ionic liquid (DIL) at both nearly neutral and high acidic pH. The effects of different operating parameters such as pH, temperature, time, concentration of surfactant, PA and DIL on extraction of PA were investigated and optimum conditions were established. The extraction mechanism was also proposed. A developed Langmuir isotherm was used to compute the feed surfactant concentration required for the removal of PA up to an extraction efficiency of 90%. The effects of temperature and concentration of surfactant on various thermodynamic parameters were examined. It was found that the values of ΔG° increased with temperature and decreased with surfactant concentration. The values of ΔH° and ΔS° increased with surfactant concentration. The developed approach for DIL mediated CPE has proved to be an efficient and green route for extraction of PA from water sample. Copyright © 2015 Elsevier B.V. All rights reserved.

Cloud point extraction-flame atomic absorption spectrometry for pre-concentration and determination of trace amounts of silver ions in water samples.

PubMed

Yang, Xiupei; Jia, Zhihui; Yang, Xiaocui; Li, Gu; Liao, Xiangjun

2017-03-01

A cloud point extraction (CPE) method was used as a pre-concentration strategy prior to the determination of trace levels of silver in water by flame atomic absorption spectrometry (FAAS) The pre-concentration is based on the clouding phenomena of non-ionic surfactant, triton X-114, with Ag (I)/diethyldithiocarbamate (DDTC) complexes in which the latter is soluble in a micellar phase composed by the former. When the temperature increases above its cloud point, the Ag (I)/DDTC complexes are extracted into the surfactant-rich phase. The factors affecting the extraction efficiency including pH of the aqueous solution, concentration of the DDTC, amount of the surfactant, incubation temperature and time were investigated and optimized. Under the optimal experimental conditions, no interference was observed for the determination of 100 ng·mL -1 Ag + in the presence of various cations below their maximum concentrations allowed in this method, for instance, 50 μg·mL -1 for both Zn 2+ and Cu 2+ , 80 μg·mL -1 for Pb 2+ , 1000 μg·mL -1 for Mn 2+ , and 100 μg·mL -1 for both Cd 2+ and Ni 2+ . The calibration curve was linear in the range of 1-500 ng·mL -1 with a limit of detection (LOD) at 0.3 ng·mL -1 . The developed method was successfully applied for the determination of trace levels of silver in water samples such as river water and tap water.

Determination of cadmium(II), cobalt(II), nickel(II), lead(II), zinc(II), and copper(II) in water samples using dual-cloud point extraction and inductively coupled plasma emission spectrometry.

PubMed

Zhao, Lingling; Zhong, Shuxian; Fang, Keming; Qian, Zhaosheng; Chen, Jianrong

2012-11-15

A dual-cloud point extraction (d-CPE) procedure has been developed for simultaneous pre-concentration and separation of heavy metal ions (Cd2+, Co2+, Ni2+, Pb2+, Zn2+, and Cu2+ ion) in water samples by inductively coupled plasma optical emission spectrometry (ICP-OES). The procedure is based on forming complexes of metal ion with 8-hydroxyquinoline (8-HQ) into the as-formed Triton X-114 surfactant rich phase. Instead of direct injection or analysis, the surfactant rich phase containing the complexes was treated by nitric acid, and the detected ions were back extracted again into aqueous phase at the second cloud point extraction stage, and finally determined by ICP-OES. Under the optimum conditions (pH=7.0, Triton X-114=0.05% (w/v), 8-HQ=2.0×10(-4) mol L(-1), HNO3=0.8 mol L(-1)), the detection limits for Cd2+, Co2+, Ni2+, Pb2+, Zn2+, and Cu2+ ions were 0.01, 0.04, 0.01, 0.34, 0.05, and 0.04 μg L(-1), respectively. Relative standard deviation (RSD) values for 10 replicates at 100 μg L(-1) were lower than 6.0%. The proposed method could be successfully applied to the determination of Cd2+, Co2+, Ni2+, Pb2+, Zn2+, and Cu2+ ion in water samples. Copyright © 2012 Elsevier B.V. All rights reserved.

Dual-cloud point extraction coupled to high performance liquid chromatography for simultaneous determination of trace sulfonamide antimicrobials in urine and water samples.

PubMed

Nong, Chunyan; Niu, Zongliang; Li, Pengyao; Wang, Chunping; Li, Wanyu; Wen, Yingying

2017-04-15

Dual-cloud point extraction (dCPE) was successfully developed for simultaneous extraction of trace sulfonamides (SAs) including sulfamerazine (SMZ), sulfadoxin (SDX), sulfathiazole (STZ) in urine and water samples. Several parameters affecting the extraction were optimized, such as sample pH, concentration of Triton X-114, extraction temperature and time, centrifugation rate and time, back-extraction solution pH, back-extraction temperature and time, back-extraction centrifugation rate and time. High performance liquid chromatography (HPLC) was applied for the SAs analysis. Under the optimum extraction and detection conditions, successful separation of the SAs was achieved within 9min, and excellent analytical performances were attained. Good linear relationships (R 2 ≥0.9990) between peak area and concentration for SMZ and STZ were optimized from 0.02 to 10μg/mL, for SDX from 0.01 to 10μg/mL. Detection limits of 3.0-6.2ng/mL were achieved. Satisfactory recoveries ranging from 85 to 108% were determined with urine, lake and tap water spiked at 0.2, 0.5 and 1μg/mL, respectively, with relative standard deviations (RSDs, n=6) of 1.5-7.7%. This method was demonstrated to be convenient, rapid, cost-effective and environmentally benign, and could be used as an alternative tool to existing methods for analysing trace residues of SAs in urine and water samples. Copyright © 2017 Elsevier B.V. All rights reserved.

Determination of arsenic species in rice samples using CPE and ETAAS.

PubMed

Costa, Bruno Elias Dos Santos; Coelho, Nívia Maria Melo; Coelho, Luciana Melo

2015-07-01

A highly sensitive and selective procedure for the determination of arsenate and total arsenic in food by electrothermal atomic absorption spectrometry after cloud point extraction (ETAAS/CPE) was developed. The procedure is based on the formation of a complex of As(V) ions with molybdate in the presence of 50.0 mmol L(-1) sulfuric acid. The complex was extracted into the surfactant-rich phase of 0.06% (w/v) Triton X-114. The variables affecting the complex formation, extraction and phase separation were optimized using factorial designs. Under the optimal conditions, the calibration graph was linear in the range of 0.05-10.0 μg L(-1). The detection and quantification limits were 10 and 33 ng L(-1), respectively and the corresponding value for the relative standard deviation for 10 replicates was below 5%. Recovery values of between 90.8% and 113.1% were obtained for spiked samples. The accuracy of the method was evaluated by comparison with the results obtained for the analysis of a rice flour sample (certified material IRMM-804) and no significant difference at the 95% confidence level was observed. The method was successfully applied to the determination of As(V) and total arsenic in rice samples. Copyright © 2015 Elsevier Ltd. All rights reserved.

A green method using a micellar system for determination of andrographolide and dehydroandrographolide in human plasma.

PubMed

Zhao, Qi; Ding, Jie; Jin, Haiyan; Ding, Lan; Ren, Nanqi

2013-04-01

A method based on cloud point extraction (CPE) coupled with high-performance liquid chromatography separation and ultraviolet (UV) detection was developed to determine andrographolide and dehydroandrographolide in human plasma. The nonionic surfactant Triton X-114 was chosen as the extraction medium. Variable parameters affecting the CPE efficiency were evaluated and optimized, such as concentrations of Triton X-114 and NaCl, pH, equilibration temperature and equilibration time. A Zorbax SB C18 column (250 × 4.6 mm i.d., 5 µm) was used for separation of the two analytes at 30°C. The UV detection was performed at 254 nm. Under the optimum conditions, the limits of detection of andrographolide and dehydroandrographolide are 0.032 and 0.019 µg/mL, respectively. The intra-day and inter-day precisions expressed as relative standard deviation ranged from 3.2 to 7.3% and from 2.9 and 8.6%. The recoveries of andrographolide and dehydroandrographolide were in the range of 76.8-98.6% at three fortified concentrations of 0.1, 0.5 and 1.0 µg/mL. This method was efficient, environmentally friendly, rapid and inexpensive for the extraction and determination of andrographolide and dehydroandrographolide in human plasma.

A new cloud point extraction procedure for determination of inorganic antimony species in beverages and biological samples by flame atomic absorption spectrometry.

PubMed

Altunay, Nail; Gürkan, Ramazan

2015-05-15

A new cloud-point extraction (CPE) for the determination of antimony species in biological and beverages samples has been established with flame atomic absorption spectrometry (FAAS). The method is based on the fact that formation of the competitive ion-pairing complex of Sb(III) and Sb(V) with Victoria Pure Blue BO (VPB(+)) at pH 10. The antimony species were individually detected by FAAS. Under the optimized conditions, the calibration range for Sb(V) is 1-250 μg L(-1) with a detection limit of 0.25 μg L(-1) and sensitive enhancement factor of 76.3 while the calibration range for Sb(III) is 10-400 μg L(-1) with a detection limit of 5.15 μg L(-1) and sensitive enhancement factor of 48.3. The precision as a relative standard deviation is in range of 0.24-2.35%. The method was successfully applied to the speciative determination of antimony species in the samples. The validation was verified by analysis of certified reference materials (CRMs). Copyright © 2014 Elsevier Ltd. All rights reserved.

Development of a simple, sensitive and inexpensive ion-pairing cloud point extraction approach for the determination of trace inorganic arsenic species in spring water, beverage and rice samples by UV-Vis spectrophotometry.

PubMed

Gürkan, Ramazan; Kır, Ufuk; Altunay, Nail

2015-08-01

The determination of inorganic arsenic species in water, beverages and foods become crucial in recent years, because arsenic species are considered carcinogenic and found at high concentrations in the samples. This communication describes a new cloud-point extraction (CPE) method for the determination of low quantity of arsenic species in the samples, purchased from the local market by UV-Visible Spectrophotometer (UV-Vis). The method is based on selective ternary complex of As(V) with acridine orange (AOH(+)) being a versatile fluorescence cationic dye in presence of tartaric acid and polyethylene glycol tert-octylphenyl ether (Triton X-114) at pH 5.0. Under the optimized conditions, a preconcentration factor of 65 and detection limit (3S blank/m) of 1.14 μg L(-1) was obtained from the calibration curve constructed in the range of 4-450 μg L(-1) with a correlation coefficient of 0.9932 for As(V). The method is validated by the analysis of certified reference materials (CRMs). Copyright © 2015 Elsevier Ltd. All rights reserved.

Utility of ultrasound assisted-cloud point extraction and spectophotometry as a preconcentration and determination tool for the sensitive quantification of mercury species in fish samples

NASA Astrophysics Data System (ADS)

Altunay, Nail

2018-01-01

The current study reports, for the first time, the development of a new analytical method employing ultrasound assisted-cloud point extraction (UA-CPE) for the extraction of CH3Hg+ and Hg2 + species from fish samples. Detection and quantification of mercury species were performed at 550 nm by spectrophotometry. The analytical variables affecting complex formation and extraction efficiency were extensively evaluated and optimized by univariate method. Due to behave 14-fold more sensitive and selective of thiophene 2,5-dicarboxylic acid (H2TDC) to Hg2 + ions than CH3Hg+ in presence of mixed surfactant, Tween 20 and SDS at pH 5.0, the amounts of free Hg2 + and total Hg were spectrophotometrically established at 550 nm by monitoring Hg2 + in the pretreated- and extracted-fish samples in ultrasonic bath to speed up extraction using diluted acid mixture (1:1:1, v/v, 4 mol L- 1 HNO3, 4 mol L- 1 HCl, and 0.5 mol L- 1 H2O2), before and after pre-oxidation with permanganate in acidic media. The amount of CH3Hg+ was calculated from difference between total Hg and Hg2 + amounts. The UA-CPE method showed to be suitable for the extraction and determination of mercury species in certified reference materials. The results were in a good agreement (with Student's t-test at 95% confidence limit) with the certified values, and the relative standard deviation was lower than 3.2%. The limits of detection have been 0.27 and 1.20 μg L- 1, for Hg2 + from aqueous calibration solutions and matrix-matched calibration solutions spiked before digestion, respectively, while it is 2.43 μg L- 1 for CH3Hg+ from matrix-matched calibration solutions. A significant matrix effect was not observed from comparison of slopes of both calibration curves, so as to represent the sample matrix. The method was applied to fish samples for speciation analysis of Hg2 + and CH3Hg+. In terms of speciation, while total Hg is detected in range of 2.42-32.08 μg kg- 1, the distribution of mercury in fish were in range of 0.7-11.06 μg kg- 1 for CH3Hg+ and in range of 1.72-24.56 μg kg- 1 for Hg2 +.

Determination of parabens using two microextraction methods coupled with capillary liquid chromatography-UV detection.

PubMed

Chen, Chen-Wen; Hsu, Wen-Chan; Lu, Ya-Chen; Weng, Jing-Ru; Feng, Chia-Hsien

2018-02-15

Parabens are common preservatives and environmental hormones. As such, possible detrimental health effects could be amplified through their widespread use in foods, cosmetics, and pharmaceutical products. Thus, the determination of parabens in such products is of particular importance. This study explored vortex-assisted dispersive liquid-liquid microextraction techniques based on the solidification of a floating organic drop (VA-DLLME-SFO) and salt-assisted cloud point extraction (SA-CPE) for paraben extraction. Microanalysis was performed using a capillary liquid chromatography-ultraviolet detection system. These techniques were modified successfully to determine four parabens in 19 commercial products. The regression equations of these parabens exhibited good linearity (r 2 =0.998, 0.1-10μg/mL), good precision (RSD<5%) and accuracy (RE<5%), reduced reagent consumption and reaction times (<6min), and excellent sample versatility. VA-DLLME-SFO was also particularly convenient due to the use of a solidified extract. Thus, the VA-DLLME-SFO technique was better suited to the extraction of parabens from complex matrices. Copyright © 2017 Elsevier Ltd. All rights reserved.

Efficacy of cocoa pod extract as antiwrinkle gel on human skin surface.

PubMed

Abdul Karim, Azila; Azlan, Azrina; Ismail, Amin; Hashim, Puziah; Abd Gani, Siti Salwa; Zainudin, Badrul Hisyam; Abdullah, Nur Azilah

2016-09-01

Cocoa pods are abundant waste materials of cocoa plantation, which are usually discarded onto plantation floors. However, due to poor plantation management, the discarded cocoa pods can create suitable breeding ground for Phytophthora palmivora, which is regarded as the causal agent of the black pod disease. On the other hand, cocoa pods potentially contain antioxidant compounds. Antioxidant compounds are related to the protection of skin from wrinkles and can be used as functional cosmetic ingredients. Therefore, in this study, cocoa pods were extracted and to be used as active ingredients for antiwrinkles. The active compounds in cocoa pod extracts (CPE) were screened using liquid chromatography-mass spectrometry (LC-MS). Fibroblast cells were used to determine the effective concentration of CPE to maintain the viability for at least 50% of the cells (EC50 ). The gel was tested by 12 panelists to determine the efficacy of CPE in gel form using Visioscan to reduce skin wrinkles and improve skin condition. CPE was detected to contain malic acid, procyanidin B1, rosmarinic acid, procyanidin C1, apigenin, and ellagic acid, all of which may contribute to functional cosmetic properties of CPE. The EC50 value of cocoa pod extracts was used to calculate the amount of CPE to be incorporated into gel so that the formulated product could reach an effective concentration of extract while being nonintoxicant to the skin cell. The results showed that CPE is potential ingredient to reduce wrinkles. Skin wrinkles reduced at 6.38 ± 1.23% with the application of the CPE gel within 3 weeks and significantly improved further (12.39 ± 1.59%) after 5 weeks. The skin hydration increased (3.181 ± 1.06%) after 3 weeks of the CPE gel application. Flavonoid compounds in CPE contributed to the functional cosmetic properties of CPE. The CPE which is nontoxic to skin cells help to reduce wrinkles on skin after 3 weeks of application. CPE can be used as the active ingredients in antiwrinkle products, and prolonged application may result in significant visual changes to the naked eyes. © 2016 Wiley Periodicals, Inc.

Non-aqueous phase cold vapor generation and determination of trace cadmium by atomic fluorescence spectrometry.

PubMed

Lei, Zirong; Chen, Luqiong; Hu, Kan; Yang, Shengchun; Wen, Xiaodong

2018-06-05

Cold vapor generation (CVG) of cadmium was firstly accomplished in non-aqueous media by using solid reductant of potassium borohydride (KBH 4 ) as a derivation reagent. The mixture of surfactant Triton X-114 micelle and octanol was innovatively used as the non-aqueous media for the CVG and atomic fluorescence spectrometry (AFS) was used for the elemental determination. The analyte ions were firstly extracted into the non-aqueous media from the bulk aqueous phase of analyte/sample solution via a novelly established ultrasound-assisted rapidly synergistic cloud point extraction (UARS-CPE) process and then directly mixed with the solid redcutant KBH 4 to generate volatile elemental state cadmium in a specially designed reactor, which was then rapidly transported to a commercial atomic fluorescence spectrometer for detection. Under the optimal conditions, the limit of detection (LOD) for cadmium was 0.004 μg L -1 . Compared to conventional hydride generation (HG)-AFS, the efficiency of non-aqueous phase CVG and the analytical performance of the developed system was considerably improved. Copyright © 2018 Elsevier B.V. All rights reserved.

Phenolic composition, antioxidant, anti-wrinkles and tyrosinase inhibitory activities of cocoa pod extract.

PubMed

Karim, Azila Abdul; Azlan, Azrina; Ismail, Amin; Hashim, Puziah; Abd Gani, Siti Salwa; Zainudin, Badrul Hisyam; Abdullah, Nur Azilah

2014-10-07

Cocoa pod is an outer part of cocoa fruits being discarded during cocoa bean processing. Authors found out that data on its usage in literature as cosmetic materials was not recorded in vast. In this study, cocoa pod extract was investigated for its potential as a cosmetic ingredient. Cocoa pod extract (CPE) composition was accomplished using UHPLC. The antioxidant capacity were measured using scavenging assay of 1,2-diphenyl-2-picrylhydrazyl (DPPH), β-carotene bleaching assay (BCB) and ferric reducing antioxidant power (FRAP). Inhibiting effect on skin degradation enzymes was carried out using elastase and collagenase assays. The skin whitening effect of CPE was determined based on mushroom tyrosinase assay and sun screening effect (UV-absorbance at 200-400 nm wavelength). LC-MS/MS data showed the presence of carboxylic acid, phenolic acid, fatty acid, flavonoids (flavonol and flavones), stilbenoids and terpenoids in CPE. Results for antioxidant activity exhibited that CPE possessed good antioxidant activity, based on the mechanism of the assays compared with ascorbic acid (AA) and standardized pine bark extract (PBE); DPPH: AA > CPE > PBE; FRAP: PBE > CPE > AA; and BCB: BHT > CPE > PBE. Cocoa pod extract showed better action against elastase and collagenase enzymes in comparison with PBE and AA. Higher inhibition towards tyrosinase enzyme was exhibited by CPE than kojic acid and AA, although lower than PBE. CPE induced proliferation when tested on human fibroblast cell at low concentration. CPE also exhibited a potential as UVB sunscreen despite its low performance as a UVA sunscreen agent. Therefore, the CPE has high potential as a cosmetic ingredient due to its anti-wrinkle, skin whitening, and sunscreen effects.

An optimized work-flow to reduce time-to-detection of carbapenemase-producing Enterobacteriaceae (CPE) using direct testing from rectal swabs.

PubMed

O'Connor, C; Kiernan, M G; Finnegan, C; O'Hara, M; Power, L; O'Connell, N H; Dunne, C P

2017-05-04

Rapid detection of patients with carbapenemase-producing Enterobacteriaceae (CPE) is essential for the prevention of nosocomial cross-transmission, allocation of isolation facilities and to protect patient safety. Here, we aimed to design a new laboratory work-flow, utilizing existing laboratory resources, in order to reduce time-to-diagnosis of CPE. A review of the current CPE testing processes and of the literature was performed to identify a real-time commercial polymerase chain reaction (PCR) assay that could facilitate batch testing of CPE clinical specimens, with adequate CPE gene coverage. Stool specimens (210) were collected; CPE-positive inpatients (n = 10) and anonymized community stool specimens (n = 200). Rectal swabs (eSwab™) were inoculated from collected stool specimens and a manual DNA extraction method (QIAamp® DNA Stool Mini Kit) was employed. Extracted DNA was then processed on the Check-Direct CPE® assay. The three step process of making the eSwab™, extracting DNA manually and running the Check-Direct CPE® assay, took <5 min, 1 h 30 min and 1 h 50 min, respectively. It was time efficient with a result available in under 4 h, comparing favourably with the existing method of CPE screening; average time-to-diagnosis of 48/72 h. Utilizing this CPE work-flow would allow a 'same-day' result. Antimicrobial susceptibility testing results, as is current practice, would remain a 'next-day' result. In conclusion, the Check-Direct CPE® assay was easily integrated into a local laboratory work-flow and could facilitate a large volume of CPE screening specimens in a single batch, making it cost-effective and convenient for daily CPE testing.

Determination of Prometryne in water and soil by HPLC-UV using cloud-point extraction.

PubMed

Zhou, Jihai; Chen, Jiandong; Cheng, Yanhong; Li, Daming; Hu, Feng; Li, Huixin

2009-07-15

A CPE-HPLC (UV) method has been developed for the determination of Prometryne. In this method, non-ionic surfactant Triton X-114 was first used to extract and pre-concentrate Prometryne from water and soil samples. The separation and determination of Prometryne were then carried out in an HPLC-UV system with isocratic elution using a detector set at 254 nm wavelength. The parameters and variables that affected the extraction were also investigated and the optimal conditions were found to be 0.5% of Triton X-114 (w/v), 3% of NaCl (w/v) and heat-assisted at 50 degrees C for 30 min. Using these conditions, the recovery rates of Prometryne ranged from 92.84% to 99.23% in water and 85.48% to 93.67% in soil, respectively, with all the relative standard deviations less than 3.05%. Limit of detection (LOD) and limit of quantification (LOQ) were 3.5 microg L(-1) and 11.0 microg L(-1) in water and 4.0 microg kg(-1) and 13.0 microg kg(-1) in soil, respectively. Thus, we developed a method that has proven to be an efficient, green, rapid and inexpensive approach for extraction and determination of Prometryne from soil samples.

Comparison of antioxidant, antimicrobial activities and chemical profiles of three coffee (Coffea arabica L.) pulp aqueous extracts.

PubMed

Duangjai, Acharaporn; Suphrom, Nungruthai; Wungrath, Jukkrit; Ontawong, Atcharaporn; Nuengchamnong, Nitra; Yosboonruang, Atchariya

2016-12-01

This study explored the bioactivities and nutrient compositions of coffee ( Coffea Arabica L.) pulp which was prepared in three different ways [Coffee Pulp Extracts (CPE) 1-3]. The coffee pulp was prepared in three different ways by distinct selecting and freezing processes. The nutritional values, polyphenol contents, antioxidant activity, and antibacterial properties of the coffee pulp as well as the characterization of the active ingredients by liquid chromatography-electrospray ionization-quadrupole-time-of-flight mass spectrometry (LC-ESI-Q-TOF-MS) were evaluated. The chemical profiles of three aqueous extracts were compared and characterized using LC-ESI-QTOF-MS. They showed slightly different nutrient compositions. The total phenolic content was highest in CPE1, and decreased in the following order: CPE1 > CPE2 > CPE3. Among the CPEs tested, CPE1 showed the most potent antioxidant activity with IC 50 18 μg/mL and 82 μg/mL by 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid) and 1,1-diphenyl-2-picryl-hydrazyl assay, respectively. Chlorogenic acid and caffeine were the most prominent in CPE1 and it contained more compounds than the others. Moreover, CPE1 demonstrated antibacterial activity against both gram-positive ( Staphylococcus aureus and Staphylococcus epidermidis ) and gram-negative bacteria ( Pseudomonas aeruginosa and Escherichia coli ). These findings indicated that CPE1 has powerful nutrients with antioxidant and antibacterial properties-the potency of which is impacted by the preparation process.

Citrange fruit extracts alleviate obesity-associated metabolic disorder in high-fat diet-induced obese C57BL/6 mouse.

PubMed

Lu, Yan; Xi, Wanpeng; Ding, Xiaobo; Fan, Shengjie; Zhang, Yu; Jiang, Dong; Li, Yiming; Huang, Cheng; Zhou, Zhiqin

2013-12-05

Obesity is becoming one of the global epidemics of the 21st century. In this study, the effects of citrange (Citrus sinensis × Poncirus trifoliata) fruit extracts in high-fat (HF) diet-induced obesity mice were studied. Female C57BL/6 mice were fed respectively a chow diet (control), an HF diet, HF diet supplemented with 1% w/w citrange peel extract (CPE) or 1% w/w citrange flesh and seed extract (CFSE) for 8 weeks. Our results showed that both CPE and CFSE regulated the glucose metabolic disorders of obese mice. In CPE and CFSE-treated groups, the body weight gain, blood glucose, serum total cholesterol (TC) and low density lipoprotein cholesterol (LDL-c) levels were significantly (p<0.05) reduced relative to those in the HF group. To explore the mechanisms of action of CPE and CFSE on the metabolism of glucose and lipid, related genes' expressions in liver were assayed. In liver tissue, the expression level of peroxisome proliferator-activated receptor γ (PPARγ) and its target genes were down-regulated by CPE and CFSE supplementation as revealed by qPCR tests. In addition, both CPE and CFSE decreased the expression level of liver X receptor (LXR) α and β, which are involved in lipid and glucose metabolism. Taken together, these results suggest that CPE and CFSE administration could ameliorate obesity and related metabolic disorders in HF diet-induced obesity mice probably through the inhibition of PPARγ and LXRs gene expressions.

Citrange Fruit Extracts Alleviate Obesity-Associated Metabolic Disorder in High-Fat Diet-Induced Obese C57BL/6 Mouse

PubMed Central

Lu, Yan; Xi, Wanpeng; Ding, Xiaobo; Fan, Shengjie; Zhang, Yu; Jiang, Dong; Li, Yiming; Huang, Cheng; Zhou, Zhiqin

2013-01-01

Obesity is becoming one of the global epidemics of the 21st century. In this study, the effects of citrange (Citrus sinensis × Poncirus trifoliata) fruit extracts in high-fat (HF) diet-induced obesity mice were studied. Female C57BL/6 mice were fed respectively a chow diet (control), an HF diet, HF diet supplemented with 1% w/w citrange peel extract (CPE) or 1% w/w citrange flesh and seed extract (CFSE) for 8 weeks. Our results showed that both CPE and CFSE regulated the glucose metabolic disorders of obese mice. In CPE and CFSE-treated groups, the body weight gain, blood glucose, serum total cholesterol (TC) and low density lipoprotein cholesterol (LDL-c) levels were significantly (p < 0.05) reduced relative to those in the HF group. To explore the mechanisms of action of CPE and CFSE on the metabolism of glucose and lipid, related genes’ expressions in liver were assayed. In liver tissue, the expression level of peroxisome proliferator-activated receptor γ (PPARγ) and its target genes were down-regulated by CPE and CFSE supplementation as revealed by qPCR tests. In addition, both CPE and CFSE decreased the expression level of liver X receptor (LXR) α and β, which are involved in lipid and glucose metabolism. Taken together, these results suggest that CPE and CFSE administration could ameliorate obesity and related metabolic disorders in HF diet-induced obesity mice probably through the inhibition of PPARγ and LXRs gene expressions. PMID:24317433

LIDAR Point Cloud Data Extraction and Establishment of 3D Modeling of Buildings

NASA Astrophysics Data System (ADS)

Zhang, Yujuan; Li, Xiuhai; Wang, Qiang; Liu, Jiang; Liang, Xin; Li, Dan; Ni, Chundi; Liu, Yan

2018-01-01

This paper takes the method of Shepard’s to deal with the original LIDAR point clouds data, and generate regular grid data DSM, filters the ground point cloud and non ground point cloud through double least square method, and obtains the rules of DSM. By using region growing method for the segmentation of DSM rules, the removal of non building point cloud, obtaining the building point cloud information. Uses the Canny operator to extract the image segmentation is needed after the edges of the building, uses Hough transform line detection to extract the edges of buildings rules of operation based on the smooth and uniform. At last, uses E3De3 software to establish the 3D model of buildings.

Joint classification and contour extraction of large 3D point clouds

NASA Astrophysics Data System (ADS)

Hackel, Timo; Wegner, Jan D.; Schindler, Konrad

2017-08-01

We present an effective and efficient method for point-wise semantic classification and extraction of object contours of large-scale 3D point clouds. What makes point cloud interpretation challenging is the sheer size of several millions of points per scan and the non-grid, sparse, and uneven distribution of points. Standard image processing tools like texture filters, for example, cannot handle such data efficiently, which calls for dedicated point cloud labeling methods. It turns out that one of the major drivers for efficient computation and handling of strong variations in point density, is a careful formulation of per-point neighborhoods at multiple scales. This allows, both, to define an expressive feature set and to extract topologically meaningful object contours. Semantic classification and contour extraction are interlaced problems. Point-wise semantic classification enables extracting a meaningful candidate set of contour points while contours help generating a rich feature representation that benefits point-wise classification. These methods are tailored to have fast run time and small memory footprint for processing large-scale, unstructured, and inhomogeneous point clouds, while still achieving high classification accuracy. We evaluate our methods on the semantic3d.net benchmark for terrestrial laser scans with >109 points.

Analgesic and anti-inflammatory effects of the dry matter of culture broth of Termitomyces albuminosus and its extracts.

PubMed

Lu, Yi-Yu; Ao, Zong-Hua; Lu, Zhen-Ming; Xu, Hong-Yu; Zhang, Xiao-Mei; Dou, Wen-Fang; Xu, Zheng-Hong

2008-12-08

The objectives of this study were to investigate the analgesic and anti-inflammatory effects of the dry matter of culture broth (DMCB) of Termitomyces albuminosus in submerged culture and its crude saponin extract (CSE) and crude polysaccharide extract (CPE). The analgesic effects of DMCB, CSE and CPE were evaluated with models of acetic acid-induced writhing response and formalin test in mouse. The anti-inflammatory effects of DMCB, CSE and CPE were evaluated by using models of xylene-induced mouse ear swelling and carrageen-induced mouse paw edema. The DMCB, CSE and CPE significantly decreased the acetic acid-induced writhing response and the licking time on the late phase in the formalin test. Treatment of DMCB (1000mg/kg), CSE (200mg/kg) or CPE (200mg/kg) inhibited the mouse ear swelling by 61.8%, 79.0% and 81.6%, respectively. In the carrageen-induced mouse paw edema test, the group treated with indomethacin showed the strongest inhibition of edema formation by 77.8% in the third hour after carrageenan administration, while DMCB (1000mg/kg), CSE (200mg/kg) and CPE (200mg/kg) showed 48.4%, 55.6% and 40.5%, respectively. The results suggested that DMCB of Termitomyces albuminosus possessed the analgesic and anti-inflammatory activities. Saponins and polysaccharides were proposed to be the major active constituents of Termitomyces albuminosus in submerged culture.

Chemical characterization, pharmacological effects, and toxicity of an ethanol extract of Celtis pallida Torr. (Cannabaceae) aerial parts.

PubMed

Rojas-Bedolla, Edgar Isaac; Gutiérrez-Pérez, Jorge Luis; Arenas-López, Mario Iván; González-Chávez, Marco Martin; Zapata-Morales, Juan Ramón; Mendoza-Macías, Claudia Leticia; Carranza-Álvarez, Candy; Maldonado-Miranda, Juan José; Deveze-Álvarez, Martha Alicia; Alonso-Castro, Angel Josabad

2018-06-12

Celtis pallida Torr (Cannabaceae) is employed as a folk medicine for the treatment of inflammation, pain, skin infections, and diarrhea, among other diseases. The purpose of this work was to assess the chemical composition, the in vitro and in vivo toxicity, the antimicrobial, anti-inflammatory, antidiarrheal, antinociceptive, locomotor, and sedative effects of an ethanolic extract obtained from Celtis pallida aerial parts (CPE). The composition of CPE was carried out by GC-MS. The in vitro and in vivo toxic activity of CPE was estimated with the comet assay (10-1000 µg/ml) for 5 h in peripheral blood mononuclear cells, and the acute toxicity test (500-5000 mg/kg p.o.), for 14 days, respectively. The antimicrobial effect of CPE was evaluated using the minimum inhibitory concentration (MIC) assay, whereas the antidiarrheal activity (10-200 mg/kg p.o.) was calculated using the castor oil test. The antinociceptive effects of CPE (50-200 mg/kg p.o.) were estimated with the acetic acid and formalin tests, as well as the hot plate test. The sedative and locomotor activities of CPE (50-200 mg/kg p.o.) were assessed with the pentobarbital-induced sleeping time test and the rotarod test, respectively. The main compound found in CPE was the triterpene ursolic acid (22% of the extract). CPE at concentrations of 100 µg/ml or higher induced genotoxicity in vitro and showed low in vivo toxicity (LD 50 > 5000 mg/kg p.o.). Additionally, CPE lacked (MIC > 400 µg/ml) antimicrobial activity but exerts antinociceptive (ED 50 = 12.5 ± 1.5 mg/kg) and antidiarrheal effects (ED 50 = 2.8 mg/kg), without inducing sedative effects or altering the locomotor activity. The antinociceptive activity of CPE suggests the participation of adrenoceptors, as well as the nitric oxide/cyclic guanosine monophosphate (cGMP) pathway. C. pallida exerts its antinociceptive effects probably mediated by the nitric oxide/cyclic guanosine monophosphate (cGMP) pathway. Copyright © 2018 Elsevier B.V. All rights reserved.

Evaluation of Caesalpinia pulcherrima Linn. for anti-inflammatory and antiulcer activities

PubMed Central

Sharma, Vivek; Rajani, G.P.

2011-01-01

Objective: To evaluate the ethanolic and aqueous extracts of aerial parts of Caesalpinia pulcherrima (Linn.) Sw. for anti-inflammatory and antiulcer activities. Materials and Methods: Anti-inflammatory action of the ethanolic and aqueous extracts of C. pulcherrima (100 and 200 mg/kg b.w.) (CPE and CPA) were evaluated by cotton pellet granuloma models. Pylorus ligation and aspirin induced ulcer models were employed for evaluating antiulcer activity for both the extracts. Ulcerogenic potential of CP was also evaluated. Result: The ethanolic and aqueous extracts of C. pulcherrima significantly decreased (P<0.01) the granuloma tissue development. CPE and CPA at both the doses exhibited significant (P<0.01) antiulcer activity by decreasing the ulcer score in both the ulcer models and it was not ulcerogenic. Conclusion: The ethanolic and aqueous extracts of aerial parts of C. pulcherrima (CPE and CPA) possess significant anti-inflammatory and antiulcer activities. PMID:21572651

Point Cloud Classification of Tesserae from Terrestrial Laser Data Combined with Dense Image Matching for Archaeological Information Extraction

NASA Astrophysics Data System (ADS)

Poux, F.; Neuville, R.; Billen, R.

2017-08-01

Reasoning from information extraction given by point cloud data mining allows contextual adaptation and fast decision making. However, to achieve this perceptive level, a point cloud must be semantically rich, retaining relevant information for the end user. This paper presents an automatic knowledge-based method for pre-processing multi-sensory data and classifying a hybrid point cloud from both terrestrial laser scanning and dense image matching. Using 18 features including sensor's biased data, each tessera in the high-density point cloud from the 3D captured complex mosaics of Germigny-des-prés (France) is segmented via a colour multi-scale abstraction-based featuring extracting connectivity. A 2D surface and outline polygon of each tessera is generated by a RANSAC plane extraction and convex hull fitting. Knowledge is then used to classify every tesserae based on their size, surface, shape, material properties and their neighbour's class. The detection and semantic enrichment method shows promising results of 94% correct semantization, a first step toward the creation of an archaeological smart point cloud.

COCOA (Theobroma cacao) Polyphenol-Rich Extract Increases the Chronological Lifespan of Saccharomyces cerevisiae.

PubMed

Baiges, I; Arola, L

2016-01-01

BACKGROUND: Saccharomyces cerevisiae is a model organism with conserved aging pathways. Yeast chronological lifespan experiments mimic the processes involved in human non-dividing tissues, such as the nervous system or skeletal muscle, and can speed up the search for biomolecules with potential anti-aging effects before proceeding to animal studies. OBJECTIVE: To test the effectiveness of a cocoa polyphenol-rich extract (CPE) in expanding the S. cerevisiae chronological lifespan in two conditions: in the stationary phase reached after glucose depletion and under severe caloric restriction. MEASUREMENTS: Using a high-throughput method, wild-type S. cerevisiae and its mitochondrial manganese-dependent superoxide dismutase null mutant (sod2Δ) were cultured in synthetic complete dextrose medium. After 2 days, 0, 5 and 20 mg/ml of CPE were added, and viability was measured throughout the stationary phase. The effects of the major components of CPE were also evaluated. To determine yeast lifespan under severe caloric restriction conditions, cultures were washed with water 24 h after the addition of 0 and 20 mg/ml of CPE, and viability was followed over time. RESULTS : CPE increased the chronological lifespan of S. cerevisiae during the stationary phase in a dose-dependent manner. A similar increase was also observed in (sod2Δ). None of the major CPE components (theobromine, caffeine, maltodextrin, (-)-epicatechin, (+)-catechin and procyanidin B2) was able to increase the yeast lifespan. CPE further increased the yeast lifespan under severe caloric restriction. CONCLUSION: CPE increases the chronological lifespan of S. cerevisiae through a SOD2-independent mechanism. The extract also extends yeast lifespan under severe caloric restriction conditions. The high-throughput assay used makes it possible to simply and rapidly test the efficacy of a large number of compounds on yeast aging, requiring only small amounts, and is thus a convenient screening assay to accelerate the search for biomolecules with potential anti-aging effects.

Phytochemical Characteristics, Free Radical Scavenging Activities, and Neuroprotection of Five Medicinal Plant Extracts

PubMed Central

Chang, Chia Lin; Lin, Che San; Lai, Guia Hung

2012-01-01

The objective of this study was to determine phytochemical characteristics, chemiluminescence antioxidant capacities, and neuroprotective effects on PC12 cells for methanol extracts of Spatholobus suberectus, Uncaria rhynchophylla, Alpinia officinarum, Drynaria fortunei, and Crataegus pinnatifida. The C. pinnatifida extract (CPE) afforded the greatest yield and total phenolic content. The S. suberectus extract (SSE) yielded the greatest total flavonoid content. The U. rhynchophylla extract (URE) produced the greatest total tannin content, and the A. officinarum extract (AOE) produced the greatest total triterpenoid content. The D. fortunei extract, assayed using horseradish peroxidase-luminol-hydrogen peroxide (H2O2), and AOE using pyrogallol-luminol assay each exhibited better antioxidant activity than the L-ascorbic acid and 6-hydroxy-2,5,7,8-tetramethylchroman-2-carboxylic acid did. The CPE, SSE, and URE presented neurogrowth effects and neuroprotective activities on H2O2-induced PC12 cell death at 0.5–5.0 μg/mL. The CPE represents a promising medicinal plant source for the treatment of H2O2-induced neurodegenerative disease, because of its useful phytochemical characteristics. PMID:21845204

Towards 3D Matching of Point Clouds Derived from Oblique and Nadir Airborne Imagery

NASA Astrophysics Data System (ADS)

Zhang, Ming

Because of the low-expense high-efficient image collection process and the rich 3D and texture information presented in the images, a combined use of 2D airborne nadir and oblique images to reconstruct 3D geometric scene has a promising market for future commercial usage like urban planning or first responders. The methodology introduced in this thesis provides a feasible way towards fully automated 3D city modeling from oblique and nadir airborne imagery. In this thesis, the difficulty of matching 2D images with large disparity is avoided by grouping the images first and applying the 3D registration afterward. The procedure starts with the extraction of point clouds using a modified version of the RIT 3D Extraction Workflow. Then the point clouds are refined by noise removal and surface smoothing processes. Since the point clouds extracted from different image groups use independent coordinate systems, there are translation, rotation and scale differences existing. To figure out these differences, 3D keypoints and their features are extracted. For each pair of point clouds, an initial alignment and a more accurate registration are applied in succession. The final transform matrix presents the parameters describing the translation, rotation and scale requirements. The methodology presented in the thesis has been shown to behave well for test data. The robustness of this method is discussed by adding artificial noise to the test data. For Pictometry oblique aerial imagery, the initial alignment provides a rough alignment result, which contains a larger offset compared to that of test data because of the low quality of the point clouds themselves, but it can be further refined through the final optimization. The accuracy of the final registration result is evaluated by comparing it to the result obtained from manual selection of matched points. Using the method introduced, point clouds extracted from different image groups could be combined with each other to build a more complete point cloud, or be used as a complement to existing point clouds extracted from other sources. This research will both improve the state of the art of 3D city modeling and inspire new ideas in related fields.

Prevention of oral food allergy sensitization via skin application of food allergen in a mouse model.

PubMed

Li, W; Zhang, Z; Saxon, A; Zhang, K

2012-05-01

Treatment options for food allergy remain limited. Development of novel approaches for the prevention and/or treatment of severe peanut allergy and other food allergies is urgently needed. The objective of this study was to test whether skin application of food allergen can be used as a prophylactic and/or therapeutic intervention for food allergy. Balb/C mice were given 5 weekly cutaneous application of complete peanut extract (CPE) or ovalbumin (OVA) ranging from 10 to 1000 μg on the shaved back skin, followed by 5 weekly treatments with oral CPE or OVA plus cholera toxin to induce allergic reactivity to the food. At various time points, the immunologic responses and allergic clinical manifestations to allergens were examined. Skin application of a 10-1000 μg dose of CPE or OVA to structurally intact skin did not lead to allergic sensitization to peanut or OVA. Rather, cutaneous allergen application blocked, in a dose-dependent fashion, the subsequent induction of the oral sensitization including inhibiting oral sensitization-induced CPE-specific IgE, IgG1, and IgG2a production, suppressing the peanut anaphylaxis, and modulating the oral sensitization-promoted cytokine production. The cutaneous OVA application also resulted in similar results as seen with CPE application. Cutaneous application of intact skin with peanut or OVA can block the development of orally induced corresponding food allergies, suggesting that allergic tolerance to peanuts and OVA might be achieved via allergen cutaneous application. © 2012 John Wiley & Sons A/S.

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

Warner-Schmid, D.; Hoshi, Suwaru; Armstrong, D.W.

Aqueous solutions of nonionic surfactants are known to undergo phase separations at elevated temperatures. This phenomenon is known as clouding,' and the temperature at which it occurs is refereed to as the cloud point. Permethylhydroxypropyl-[beta]-cyclodextrin (PMHP-[beta]-CD) was synthesized and aqueous solutions containing it were found to undergo similar cloud-point behavior. Factors that affect the phase separation of PMHP-[beta]-CD were investigated. Subsequently, the cloud-point extractions of several aromatic compounds (i.e., acetanilide, aniline, 2,2[prime]-dihydroxybiphenyl, N-methylaniline, 2-naphthol, o-nitroaniline, m-nitroaniline, p-nitroaniline, nitrobenzene, o-nitrophenol, m-nitrophenol, p-nitrophenol, 4-phenazophenol, 3-phenylphenol, and 2-phenylbenzimidazole) from dilute aqueous solution were evaluated. Although the extraction efficiency of the compounds varied, mostmore » can be quantitatively extracted if sufficient PMHP-[beta]-CD is used. For those few compounds that are not extracted (e.g., o-nitroacetanilide), the cloud-point procedure may be an effective one-step isolation or purification method. 18 refs., 2 figs., 3 tabs.« less

The Segmentation of Point Clouds with K-Means and ANN (artifical Neural Network)

NASA Astrophysics Data System (ADS)

Kuçak, R. A.; Özdemir, E.; Erol, S.

2017-05-01

Segmentation of point clouds is recently used in many Geomatics Engineering applications such as the building extraction in urban areas, Digital Terrain Model (DTM) generation and the road or urban furniture extraction. Segmentation is a process of dividing point clouds according to their special characteristic layers. The present paper discusses K-means and self-organizing map (SOM) which is a type of ANN (Artificial Neural Network) segmentation algorithm which treats the segmentation of point cloud. The point clouds which generate with photogrammetric method and Terrestrial Lidar System (TLS) were segmented according to surface normal, intensity and curvature. Thus, the results were evaluated. LIDAR (Light Detection and Ranging) and Photogrammetry are commonly used to obtain point clouds in many remote sensing and geodesy applications. By photogrammetric method or LIDAR method, it is possible to obtain point cloud from terrestrial or airborne systems. In this study, the measurements were made with a Leica C10 laser scanner in LIDAR method. In photogrammetric method, the point cloud was obtained from photographs taken from the ground with a 13 MP non-metric camera.

Scan Line Based Road Marking Extraction from Mobile LiDAR Point Clouds.

PubMed

Yan, Li; Liu, Hua; Tan, Junxiang; Li, Zan; Xie, Hong; Chen, Changjun

2016-06-17

Mobile Mapping Technology (MMT) is one of the most important 3D spatial data acquisition technologies. The state-of-the-art mobile mapping systems, equipped with laser scanners and named Mobile LiDAR Scanning (MLS) systems, have been widely used in a variety of areas, especially in road mapping and road inventory. With the commercialization of Advanced Driving Assistance Systems (ADASs) and self-driving technology, there will be a great demand for lane-level detailed 3D maps, and MLS is the most promising technology to generate such lane-level detailed 3D maps. Road markings and road edges are necessary information in creating such lane-level detailed 3D maps. This paper proposes a scan line based method to extract road markings from mobile LiDAR point clouds in three steps: (1) preprocessing; (2) road points extraction; (3) road markings extraction and refinement. In preprocessing step, the isolated LiDAR points in the air are removed from the LiDAR point clouds and the point clouds are organized into scan lines. In the road points extraction step, seed road points are first extracted by Height Difference (HD) between trajectory data and road surface, then full road points are extracted from the point clouds by moving least squares line fitting. In the road markings extraction and refinement step, the intensity values of road points in a scan line are first smoothed by a dynamic window median filter to suppress intensity noises, then road markings are extracted by Edge Detection and Edge Constraint (EDEC) method, and the Fake Road Marking Points (FRMPs) are eliminated from the detected road markings by segment and dimensionality feature-based refinement. The performance of the proposed method is evaluated by three data samples and the experiment results indicate that road points are well extracted from MLS data and road markings are well extracted from road points by the applied method. A quantitative study shows that the proposed method achieves an average completeness, correctness, and F-measure of 0.96, 0.93, and 0.94, respectively. The time complexity analysis shows that the scan line based road markings extraction method proposed in this paper provides a promising alternative for offline road markings extraction from MLS data.

Line segment extraction for large scale unorganized point clouds

NASA Astrophysics Data System (ADS)

Lin, Yangbin; Wang, Cheng; Cheng, Jun; Chen, Bili; Jia, Fukai; Chen, Zhonggui; Li, Jonathan

2015-04-01

Line segment detection in images is already a well-investigated topic, although it has received considerably less attention in 3D point clouds. Benefiting from current LiDAR devices, large-scale point clouds are becoming increasingly common. Most human-made objects have flat surfaces. Line segments that occur where pairs of planes intersect give important information regarding the geometric content of point clouds, which is especially useful for automatic building reconstruction and segmentation. This paper proposes a novel method that is capable of accurately extracting plane intersection line segments from large-scale raw scan points. The 3D line-support region, namely, a point set near a straight linear structure, is extracted simultaneously. The 3D line-support region is fitted by our Line-Segment-Half-Planes (LSHP) structure, which provides a geometric constraint for a line segment, making the line segment more reliable and accurate. We demonstrate our method on the point clouds of large-scale, complex, real-world scenes acquired by LiDAR devices. We also demonstrate the application of 3D line-support regions and their LSHP structures on urban scene abstraction.

Effects of Extraction Methods on Phytochemicals of Rice Bran Oils Produced from Colored Rice.

PubMed

Mingyai, Sukanya; Srikaeo, Khongsak; Kettawan, Aikkarach; Singanusong, Riantong; Nakagawa, Kiyotaka; Kimura, Fumiko; Ito, Junya

2018-02-01

Rice bran oil (RBO) especially from colored rice is rich in phytochemicals and has become popular in food, cosmetic, nutraceutical and pharmaceutical applications owing to its offering health benefits. This study determined the contents of phytochemicals including oryzanols, phytosterols, tocopherols (Toc) and tocotrienols (T3) in RBOs extracted using different methods namely cold-press extraction (CPE), solvent extraction (SE) and supercritical CO 2 extraction (SC-CO 2 ). Two colored rice, Red Jasmine rice (RJM, red rice) and Hom-nin rice (HN, black rice), were studied in comparison with the popular Thai fragrant rice Khao Dawk Mali 105 (KDML 105, white rice). RBOs were found to be the rich source of oryzanols, phytosterols, Toc and T3. Rice varieties had a greater effect on the phytochemicals concentrations than extraction methods. HN rice showed the significantly highest concentration of all phytochemicals, followed by RJM and KDML 105 rice, indicating that colored rice contained high concentration of phytochemicals in the oil than non-colored rice. The RBO samples extracted by the CPE method had a greater concentration of the phytochemicals than those extracted by the SC-CO 2 and SE methods, respectively. In terms of phytochemical contents, HN rice extracted using CPE method was found to be the best.

3D local feature BKD to extract road information from mobile laser scanning point clouds

NASA Astrophysics Data System (ADS)

Yang, Bisheng; Liu, Yuan; Dong, Zhen; Liang, Fuxun; Li, Bijun; Peng, Xiangyang

2017-08-01

Extracting road information from point clouds obtained through mobile laser scanning (MLS) is essential for autonomous vehicle navigation, and has hence garnered a growing amount of research interest in recent years. However, the performance of such systems is seriously affected due to varying point density and noise. This paper proposes a novel three-dimensional (3D) local feature called the binary kernel descriptor (BKD) to extract road information from MLS point clouds. The BKD consists of Gaussian kernel density estimation and binarization components to encode the shape and intensity information of the 3D point clouds that are fed to a random forest classifier to extract curbs and markings on the road. These are then used to derive road information, such as the number of lanes, the lane width, and intersections. In experiments, the precision and recall of the proposed feature for the detection of curbs and road markings on an urban dataset and a highway dataset were as high as 90%, thus showing that the BKD is accurate and robust against varying point density and noise.

Assessment of extraction parameters on antioxidant capacity, polyphenol content, epigallocatechin gallate (EGCG), epicatechin gallate (ECG) and iriflophenone 3-C-β-glucoside of agarwood (Aquilaria crassna) young leaves.

PubMed

Tay, Pei Yin; Tan, Chin Ping; Abas, Faridah; Yim, Hip Seng; Ho, Chun Wai

2014-08-14

The effects of ethanol concentration (0%-100%, v/v), solid-to-solvent ratio (1:10-1:60, w/v) and extraction time (30-180 min) on the extraction of polyphenols from agarwood (Aquilaria crassna) were examined. Total phenolic content (TPC), total flavonoid content (TFC) and total flavanol (TF) assays and HPLC-DAD were used for the determination and quantification of polyphenols, flavanol gallates (epigallocatechin gallate--EGCG and epicatechin gallate--ECG) and a benzophenone (iriflophenone 3-C-β-glucoside) from the crude polyphenol extract (CPE) of A. crassna. 2,2'-Diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity was used to evaluate the antioxidant capacity of the CPE. Experimental results concluded that ethanol concentration and solid-to-solvent ratio had significant effects (p<0.05) on the yields of polyphenol and antioxidant capacity. Extraction time had an insignificant influence on the recovery of EGCG, ECG and iriflophenone 3-C-β-glucoside, as well as radical scavenging capacity from the CPE. The extraction parameters that exhibited maximum yields were 40% (v/v) ethanol, 1:60 (w/v) for 30 min where the TPC, TFC, TF, DPPH, EGCG, ECG and iriflophenone 3-C-β-glucoside levels achieved were 183.5 mg GAE/g DW, 249.0 mg QE/g DW, 4.9 mg CE/g DW, 93.7%, 29.1 mg EGCG/g DW, 44.3 mg ECG/g DW and 39.9 mg iriflophenone 3-C-β-glucoside/g DW respectively. The IC50 of the CPE was 24.6 mg/L.

Peptidomics of Cpefat/fat mouse brain regions: Implications for neuropeptide processing

PubMed Central

Zhang, Xin; Che, Fa-Yun; Berezniuk, Iryna; Sonmez, Kemal; Toll, Lawrence; Fricker, Lloyd D.

2009-01-01

SUMMARY Quantitative peptidomics was used to compare levels of peptides in wild type and Cpefat/fat mice, which lack carboxypeptidase E (CPE) activity due to a point mutation. Six different brain regions were analyzed: amygdala, hippocampus, hypothalamus, prefrontal cortex, striatum, and thalamus. Altogether, 111 neuropeptides or other peptides derived from secretory pathway proteins were identified in wild type mouse brain extracts by tandem mass spectrometry, and another 47 peptides were tentatively identified based on mass and other criteria. Most secretory pathway peptides were much lower in Cpefat/fat mouse brain, relative to wild type mouse brain, indicating that CPE plays a major role in their biosynthesis. Other peptides were only partially reduced in the Cpefat/fat mice, indicating that another enzyme (presumably carboxypeptidase D) contributes to their biosynthesis. Approximately 10% of the secretory pathway peptides were present in the Cpefat/fat mouse brain at levels similar to those in wild type mouse brain. Many peptides were greatly elevated in the Cpefat/fat mice; these peptide processing intermediates with C-terminal Lys and/or Arg were generally not detectable in wild type mice. Taken together, these results indicate that CPE contributes, either directly or indirectly, to the production of the majority of neuropeptides. PMID:19014391

Terrain Extraction by Integrating Terrestrial Laser Scanner Data and Spectral Information

NASA Astrophysics Data System (ADS)

Lau, C. L.; Halim, S.; Zulkepli, M.; Azwan, A. M.; Tang, W. L.; Chong, A. K.

2015-10-01

The extraction of true terrain points from unstructured laser point cloud data is an important process in order to produce an accurate digital terrain model (DTM). However, most of these spatial filtering methods just utilizing the geometrical data to discriminate the terrain points from nonterrain points. The point cloud filtering method also can be improved by using the spectral information available with some scanners. Therefore, the objective of this study is to investigate the effectiveness of using the three-channel (red, green and blue) of the colour image captured from built-in digital camera which is available in some Terrestrial Laser Scanner (TLS) for terrain extraction. In this study, the data acquisition was conducted at a mini replica landscape in Universiti Teknologi Malaysia (UTM), Skudai campus using Leica ScanStation C10. The spectral information of the coloured point clouds from selected sample classes are extracted for spectral analysis. The coloured point clouds which within the corresponding preset spectral threshold are identified as that specific feature point from the dataset. This process of terrain extraction is done through using developed Matlab coding. Result demonstrates that a higher spectral resolution passive image is required in order to improve the output. This is because low quality of the colour images captured by the sensor contributes to the low separability in spectral reflectance. In conclusion, this study shows that, spectral information is capable to be used as a parameter for terrain extraction.

Comparison of 3D point clouds obtained by photogrammetric UAVs and TLS to determine the attitude of dolerite outcrops discontinuities.

NASA Astrophysics Data System (ADS)

Duarte, João; Gonçalves, Gil; Duarte, Diogo; Figueiredo, Fernando; Mira, Maria

2015-04-01

Photogrammetric Unmanned Aerial Vehicles (UAVs) and Terrestrial Laser Scanners (TLS) are two emerging technologies that allows the production of dense 3D point clouds of the sensed topographic surfaces. Although image-based stereo-photogrammetric point clouds could not, in general, compete on geometric quality over TLS point clouds, fully automated mapping solutions based on ultra-light UAVs (or drones) have recently become commercially available at very reasonable accuracy and cost for engineering and geological applications. The purpose of this paper is to compare the two point clouds generated by these two technologies, in order to automatize the manual process tasks commonly used to detect and represent the attitude of discontinuities (Stereographic projection: Schmidt net - Equal area). To avoid the difficulties of access and guarantee the data survey security conditions, this fundamental step in all geological/geotechnical studies, applied to the extractive industry and engineering works, has to be replaced by a more expeditious and reliable methodology. This methodology will allow, in a more actuated clear way, give answers to the needs of evaluation of rock masses, by mapping the structures present, which will reduce considerably the associated risks (investment, structures dimensioning, security, etc.). A case study of a dolerite outcrop locate in the center of Portugal (the dolerite outcrop is situated in the volcanic complex of Serra de Todo-o-Mundo, Casais Gaiola, intruded in Jurassic sandstones) will be used to assess this methodology. The results obtained show that the 3D point cloud produced by the Photogrammetric UAV platform has the appropriate geometric quality for extracting the parameters that define the discontinuities of the dolerite outcrops. Although, they are comparable to the manual extracted parameters, their quality is inferior to parameters extracted from the TLS point cloud.

Combination of dispersive liquid-liquid microextraction with flame atomic absorption spectrometry using microsample introduction for determination of lead in water samples.

PubMed

Naseri, Mohammad Taghi; Hemmatkhah, Payam; Hosseini, Mohammad Reza Milani; Assadi, Yaghoub

2008-03-03

The dispersive liquid-liquid microextraction (DLLME) was combined with the flame atomic absorption spectrometry (FAAS) for determination of lead in the water samples. Diethyldithiophosphoric acid (DDTP), carbon tetrachloride and methanol were used as chelating agent, extraction solvent and disperser solvent, respectively. A new FAAS sample introduction system was employed for the microvolume nebulization of the non-flammable chlorinated organic extracts. Injection of 20 microL volumes of the organic extract into an air-acetylene flame provided very sensitive spike-like and reproducible signals. Some effective parameters on the microextraction and the complex formation were selected and optimized. These parameters include extraction and disperser solvent type as well as their volume, extraction time, salt effect, pH and amount of the chelating agent. Under the optimized conditions, the enrichment factor of 450 was obtained from a sample volume of 25.0 mL. The enhancement factor, calculated as the ratio of the slopes of the calibration graphs with and without preconcentration, which was about 1000. The calibration graph was linear in the range of 1-70 microgL(-1) with a detection limit of 0.5 microgL(-1). The relative standard deviation (R.S.D.) for seven replicate measurements of 5.0 and 50 microgL(-1) of lead were 3.8 and 2.0%, respectively. The relative recoveries of lead in tap, well, river and seawater samples at the spiking level of 20 microgL(-1) ranged from 93.8 to 106.2%. The characteristics of the proposed method were compared with those of the liquid-liquid extraction (LLE), cloud point extraction (CPE), on-line and off-line solid-phase extraction (SPE) as well as co-precipitation, based on bibliographic data. Operation simplicity, rapidity, low cost, high enrichment factor, good repeatability, and low consumption of the extraction solvent at a microliter level are the main advantages of the proposed method.

Optimal Information Extraction of Laser Scanning Dataset by Scale-Adaptive Reduction

NASA Astrophysics Data System (ADS)

Zang, Y.; Yang, B.

2018-04-01

3D laser technology is widely used to collocate the surface information of object. For various applications, we need to extract a good perceptual quality point cloud from the scanned points. To solve the problem, most of existing methods extract important points based on a fixed scale. However, geometric features of 3D object come from various geometric scales. We propose a multi-scale construction method based on radial basis function. For each scale, important points are extracted from the point cloud based on their importance. We apply a perception metric Just-Noticeable-Difference to measure degradation of each geometric scale. Finally, scale-adaptive optimal information extraction is realized. Experiments are undertaken to evaluate the effective of the proposed method, suggesting a reliable solution for optimal information extraction of object.

Effect of Dark Chocolate Extracts on Phorbol 12-Myristate 13-Acetate-Induced Oxidative Burst in Leukocytes Isolated by Normo-Weight and Overweight/Obese Subjects

PubMed Central

Ioannone, Francesca; Sacchetti, Giampiero; Serafini, Mauro

2017-01-01

Oxidative and inflammatory stress represents a major risk factor for cardiovascular disease (CVD) in overweight and obese subjects. Between the different plant foods, chocolate has been shown to decrease CVD risk due to its antioxidant and anti-inflammatory properties. However, as we recently showed in epidemiological studies, meta-analyses, and human trials, dietary antioxidants resulted more effective in subjects characterized by an ongoing oxidative stress, than in healthy people. Aim of this work was to investigate the effect of different concentrations of chocolate phenolic extract (CPE) on in vitro free radical production, stimulated by phorbol 12-myristate 13-acetate (PMA), in leukocytes extracted from blood of normo-weight and overweight/obese subjects. Neutrophils from overweight/obese group had a significantly higher free radical production compared to the normo-weight group. In neutrophils, the lowest CPE concentration significantly reduced free radical production in overweight/obese group only, and higher CPE concentrations were effective in both groups. In monocytes, the CPE concentration that was significantly effective in reducing free radical production was lower in overweight/obese subjects than in normo-weight subjects. Chocolate polyphenol extracts inhibit oxidative burst in human neutrophils and monocytes with a higher efficiency in subjects characterized by an unphysiological oxidative/inflammatory stress, such as overweight and obese. Results of this study provide further evidence about a differential role of dietary antioxidant strictly related to the “stress” condition of the subjects. PMID:28649567

Effect of Dark Chocolate Extracts on Phorbol 12-Myristate 13-Acetate-Induced Oxidative Burst in Leukocytes Isolated by Normo-Weight and Overweight/Obese Subjects.

PubMed

Ioannone, Francesca; Sacchetti, Giampiero; Serafini, Mauro

2017-01-01

Oxidative and inflammatory stress represents a major risk factor for cardiovascular disease (CVD) in overweight and obese subjects. Between the different plant foods, chocolate has been shown to decrease CVD risk due to its antioxidant and anti-inflammatory properties. However, as we recently showed in epidemiological studies, meta-analyses, and human trials, dietary antioxidants resulted more effective in subjects characterized by an ongoing oxidative stress, than in healthy people. Aim of this work was to investigate the effect of different concentrations of chocolate phenolic extract (CPE) on in vitro free radical production, stimulated by phorbol 12-myristate 13-acetate (PMA), in leukocytes extracted from blood of normo-weight and overweight/obese subjects. Neutrophils from overweight/obese group had a significantly higher free radical production compared to the normo-weight group. In neutrophils, the lowest CPE concentration significantly reduced free radical production in overweight/obese group only, and higher CPE concentrations were effective in both groups. In monocytes, the CPE concentration that was significantly effective in reducing free radical production was lower in overweight/obese subjects than in normo-weight subjects. Chocolate polyphenol extracts inhibit oxidative burst in human neutrophils and monocytes with a higher efficiency in subjects characterized by an unphysiological oxidative/inflammatory stress, such as overweight and obese. Results of this study provide further evidence about a differential role of dietary antioxidant strictly related to the "stress" condition of the subjects.

Hierarchical extraction of urban objects from mobile laser scanning data

NASA Astrophysics Data System (ADS)

Yang, Bisheng; Dong, Zhen; Zhao, Gang; Dai, Wenxia

2015-01-01

Point clouds collected in urban scenes contain a huge number of points (e.g., billions), numerous objects with significant size variability, complex and incomplete structures, and variable point densities, raising great challenges for the automated extraction of urban objects in the field of photogrammetry, computer vision, and robotics. This paper addresses these challenges by proposing an automated method to extract urban objects robustly and efficiently. The proposed method generates multi-scale supervoxels from 3D point clouds using the point attributes (e.g., colors, intensities) and spatial distances between points, and then segments the supervoxels rather than individual points by combining graph based segmentation with multiple cues (e.g., principal direction, colors) of the supervoxels. The proposed method defines a set of rules for merging segments into meaningful units according to types of urban objects and forms the semantic knowledge of urban objects for the classification of objects. Finally, the proposed method extracts and classifies urban objects in a hierarchical order ranked by the saliency of the segments. Experiments show that the proposed method is efficient and robust for extracting buildings, streetlamps, trees, telegraph poles, traffic signs, cars, and enclosures from mobile laser scanning (MLS) point clouds, with an overall accuracy of 92.3%.

Scan Line Based Road Marking Extraction from Mobile LiDAR Point Clouds†

PubMed Central

Yan, Li; Liu, Hua; Tan, Junxiang; Li, Zan; Xie, Hong; Chen, Changjun

2016-01-01

Mobile Mapping Technology (MMT) is one of the most important 3D spatial data acquisition technologies. The state-of-the-art mobile mapping systems, equipped with laser scanners and named Mobile LiDAR Scanning (MLS) systems, have been widely used in a variety of areas, especially in road mapping and road inventory. With the commercialization of Advanced Driving Assistance Systems (ADASs) and self-driving technology, there will be a great demand for lane-level detailed 3D maps, and MLS is the most promising technology to generate such lane-level detailed 3D maps. Road markings and road edges are necessary information in creating such lane-level detailed 3D maps. This paper proposes a scan line based method to extract road markings from mobile LiDAR point clouds in three steps: (1) preprocessing; (2) road points extraction; (3) road markings extraction and refinement. In preprocessing step, the isolated LiDAR points in the air are removed from the LiDAR point clouds and the point clouds are organized into scan lines. In the road points extraction step, seed road points are first extracted by Height Difference (HD) between trajectory data and road surface, then full road points are extracted from the point clouds by moving least squares line fitting. In the road markings extraction and refinement step, the intensity values of road points in a scan line are first smoothed by a dynamic window median filter to suppress intensity noises, then road markings are extracted by Edge Detection and Edge Constraint (EDEC) method, and the Fake Road Marking Points (FRMPs) are eliminated from the detected road markings by segment and dimensionality feature-based refinement. The performance of the proposed method is evaluated by three data samples and the experiment results indicate that road points are well extracted from MLS data and road markings are well extracted from road points by the applied method. A quantitative study shows that the proposed method achieves an average completeness, correctness, and F-measure of 0.96, 0.93, and 0.94, respectively. The time complexity analysis shows that the scan line based road markings extraction method proposed in this paper provides a promising alternative for offline road markings extraction from MLS data. PMID:27322279

Triton X-114 based cloud point extraction: a thermoreversible approach for separation/concentration and dispersion of nanomaterials in the aqueous phase.

PubMed

Liu, Jing-fu; Liu, Rui; Yin, Yong-guang; Jiang, Gui-bin

2009-03-28

Capable of preserving the sizes and shapes of nanomaterials during the phase transferring, Triton X-114 based cloud point extraction provides a general, simple, and cost-effective route for reversible concentration/separation or dispersion of various nanomaterials in the aqueous phase.

Automatic Extraction of Road Markings from Mobile Laser-Point Cloud Using Intensity Data

NASA Astrophysics Data System (ADS)

Yao, L.; Chen, Q.; Qin, C.; Wu, H.; Zhang, S.

2018-04-01

With the development of intelligent transportation, road's high precision information data has been widely applied in many fields. This paper proposes a concise and practical way to extract road marking information from point cloud data collected by mobile mapping system (MMS). The method contains three steps. Firstly, road surface is segmented through edge detection from scan lines. Then the intensity image is generated by inverse distance weighted (IDW) interpolation and the road marking is extracted by using adaptive threshold segmentation based on integral image without intensity calibration. Moreover, the noise is reduced by removing a small number of plaque pixels from binary image. Finally, point cloud mapped from binary image is clustered into marking objects according to Euclidean distance, and using a series of algorithms including template matching and feature attribute filtering for the classification of linear markings, arrow markings and guidelines. Through processing the point cloud data collected by RIEGL VUX-1 in case area, the results show that the F-score of marking extraction is 0.83, and the average classification rate is 0.9.

In vivo efficiency of the collagen coated nanofibrous scaffold and their effect on growth factors and pro-inflammatory cytokines in wound healing.

PubMed

Ramanathan, Giriprasath; Muthukumar, Thangavelu; Tirichurapalli Sivagnanam, Uma

2017-11-05

Exploring the importance of nanofibrous scaffold with traditionally important medicine as a wound dressing material prevents infection and aids in faster healing of wounds. In the present study, the Collagen (COL) from the marine fish skin was extracted and employed for coating the Poly(3-hydroxybutyric acid) (P)-Gelatin (G) nanofibrous scaffold with a bioactive Coccinia grandis extract (CPE) fabricated through electrospinning. Further, the fabricated collagen coated nanofibrous scaffold (PG-CPE-COL) applied to the experimental wound of rats and the wound healing was analyzed with by physiochemical and biological techniques. The increased level of hydroxyproline, hexosamine and uronic acid was observed in PG-CPE-COL treated than the other groups. The CPE and collagen in the nanofibrous scaffold accelerates the wound healing and thereby reduced the inflammation caused by the cyclooxygenase-2 (COX-2) and inducible nitric oxide synthases (iNOS) in wound healing. The nanofibrous scaffold has influenced the expression of various growth factors such as vascular endothelial growth factor (VEGF), epidermal growth factor (EGF) and transforming growth factor (TGF-β). In addition, the PG-CPE-COL nanofibrous scaffold increases the deposition of collagen synthesis and accelerates reepithelialization. Thus, the results suggest that the collagen coated nanofibrous scaffold with bioactive traditional medicine enhanced the faster healing of wound. Copyright © 2017 Elsevier B.V. All rights reserved.

Impact of Surface Active Ionic Liquids on the Cloud Points of Nonionic Surfactants and the Formation of Aqueous Micellar Two-Phase Systems.

PubMed

Vicente, Filipa A; Cardoso, Inês S; Sintra, Tânia E; Lemus, Jesus; Marques, Eduardo F; Ventura, Sónia P M; Coutinho, João A P

2017-09-21

Aqueous micellar two-phase systems (AMTPS) hold a large potential for cloud point extraction of biomolecules but are yet poorly studied and characterized, with few phase diagrams reported for these systems, hence limiting their use in extraction processes. This work reports a systematic investigation of the effect of different surface-active ionic liquids (SAILs)-covering a wide range of molecular properties-upon the clouding behavior of three nonionic Tergitol surfactants. Two different effects of the SAILs on the cloud points and mixed micelle size have been observed: ILs with a more hydrophilic character and lower critical packing parameter (CPP < 1 / 2 ) lead to the formation of smaller micelles and concomitantly increase the cloud points; in contrast, ILs with a more hydrophobic character and higher CPP (CPP ≥ 1) induce significant micellar growth and a decrease in the cloud points. The latter effect is particularly interesting and unusual for it was accepted that cloud point reduction is only induced by inorganic salts. The effects of nonionic surfactant concentration, SAIL concentration, pH, and micelle ζ potential are also studied and rationalized.

The registration of non-cooperative moving targets laser point cloud in different view point

NASA Astrophysics Data System (ADS)

Wang, Shuai; Sun, Huayan; Guo, Huichao

2018-01-01

Non-cooperative moving target multi-view cloud registration is the key technology of 3D reconstruction of laser threedimension imaging. The main problem is that the density changes greatly and noise exists under different acquisition conditions of point cloud. In this paper, firstly, the feature descriptor is used to find the most similar point cloud, and then based on the registration algorithm of region segmentation, the geometric structure of the point is extracted by the geometric similarity between point and point, The point cloud is divided into regions based on spectral clustering, feature descriptors are created for each region, searching to find the most similar regions in the most similar point of view cloud, and then aligning the pair of point clouds by aligning their minimum bounding boxes. Repeat the above steps again until registration of all point clouds is completed. Experiments show that this method is insensitive to the density of point clouds and performs well on the noise of laser three-dimension imaging.

Applications of 3D-EDGE Detection for ALS Point Cloud

NASA Astrophysics Data System (ADS)

Ni, H.; Lin, X. G.; Zhang, J. X.

2017-09-01

Edge detection has been one of the major issues in the field of remote sensing and photogrammetry. With the fast development of sensor technology of laser scanning system, dense point clouds have become increasingly common. Precious 3D-edges are able to be detected from these point clouds and a great deal of edge or feature line extraction methods have been proposed. Among these methods, an easy-to-use 3D-edge detection method, AGPN (Analyzing Geometric Properties of Neighborhoods), has been proposed. The AGPN method detects edges based on the analysis of geometric properties of a query point's neighbourhood. The AGPN method detects two kinds of 3D-edges, including boundary elements and fold edges, and it has many applications. This paper presents three applications of AGPN, i.e., 3D line segment extraction, ground points filtering, and ground breakline extraction. Experiments show that the utilization of AGPN method gives a straightforward solution to these applications.

Speciation and Determination of Low Concentration of Iron in Beer Samples by Cloud Point Extraction

ERIC Educational Resources Information Center

Khalafi, Lida; Doolittle, Pamela; Wright, John

2018-01-01

A laboratory experiment is described in which students determine the concentration and speciation of iron in beer samples using cloud point extraction and absorbance spectroscopy. The basis of determination is the complexation between iron and 2-(5-bromo-2- pyridylazo)-5-diethylaminophenol (5-Br-PADAP) as a colorimetric reagent in an aqueous…

Immunogenic activity of the fish tapeworm Pterobothrium heteracanthum (Trypanorhyncha: Pterobothriidae) in BALB/c mice.

PubMed

Mattos, D P B G; Verícimo, M A; Lopes, L M S; São Clemente, S C

2015-03-01

The aim of this study was to verify the immunogenicity of Pterobothrium heteracanthum (Cestoda: Trypanorhyncha) crude protein extract (PH-CPE) in BALB/c mice. The parasites were obtained from Micropogonias furnieri (Osteichthyes: Sciaenidae). Groups of six mice were each immunized with 10, 50 or 100 μg of PH-CPE, on days 0 and 35. Both specific IgG and IgE responses were developed after immunization. The immunoblot assay revealed that specific IgG recognizes PH-CPE proteins with two molecular weight ranges, 60-75 and 30-40 kDa, and that IgE recognizes larger proteins over 120 kDa. This appears to be the first report on the immunogenicity of metacestodes within the Pterobothriidae and that PH-CPE is a potential inducer of a specific IgE response.

Characterization of Piezoresistive PEDOT:PSS Pressure Sensors with Inter-Digitated and Cross-Point Electrode Structures

PubMed Central

Wang, Jer-Chyi; Karmakar, Rajat Subhra; Lu, Yu-Jen; Huang, Chiung-Yin; Wei, Kuo-Chen

2015-01-01

The piezoresistive characteristics of poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS) pressure sensors with inter-digitated (IDE) and cross-point electrode (CPE) structures have been investigated. A small variation of the resistance of the pressure sensors with IDE without bottom indium-tin-oxide (b-ITO) film and with CPE structures was observed owing to the single carrier-conducting pathway. For the IDE pressure sensors with b-ITO, the piezoresistive characteristics at low and high pressure were similar to those of the pressure sensors with IDE without b-ITO and with CPE structures, respectively, leading to increased piezoresistive pressure sensitivity as the PEDOT:PSS film thickness decreased. A maximum sensitivity of more than 42 kΩ/Pa was achieved. When the normal pressure was applied, the increased number of conducting points or the reduced distance between the PEDOT oligomers within the PEDOT:PSS film resulted in a decrease of the resistance. The piezoresistive pressure sensors with a single carrier-conducting pathway, i.e., IDE without b-ITO and CPE structures, exhibited a small relaxation time and a superior reversible operation, which can be advantageous for fast piezoresistive response applications. PMID:25569756

Characterization of piezoresistive PEDOT:PSS pressure sensors with inter-digitated and cross-point electrode structures.

PubMed

Wang, Jer-Chyi; Karmakar, Rajat Subhra; Lu, Yu-Jen; Huang, Chiung-Yin; Wei, Kuo-Chen

2015-01-05

The piezoresistive characteristics of poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS) pressure sensors with inter-digitated (IDE) and cross-point electrode (CPE) structures have been investigated. A small variation of the resistance of the pressure sensors with IDE without bottom indium-tin-oxide (b-ITO) film and with CPE structures was observed owing to the single carrier-conducting pathway. For the IDE pressure sensors with b-ITO, the piezoresistive characteristics at low and high pressure were similar to those of the pressure sensors with IDE without b-ITO and with CPE structures, respectively, leading to increased piezoresistive pressure sensitivity as the PEDOT:PSS film thickness decreased. A maximum sensitivity of more than 42 kΩ/Pa was achieved. When the normal pressure was applied, the increased number of conducting points or the reduced distance between the PEDOT oligomers within the PEDOT:PSS film resulted in a decrease of the resistance. The piezoresistive pressure sensors with a single carrier-conducting pathway, i.e., IDE without b-ITO and CPE structures, exhibited a small relaxation time and a superior reversible operation, which can be advantageous for fast piezoresistive response applications.

Clostridium perfringens Enterotoxin Interacts with Claudins via Electrostatic Attraction*

PubMed Central

Kimura, Jun; Abe, Hiroyuki; Kamitani, Shigeki; Toshima, Hirono; Fukui, Aya; Miyake, Masami; Kamata, Yoichi; Sugita-Konishi, Yoshiko; Yamamoto, Shigeki; Horiguchi, Yasuhiko

2010-01-01

Clostridium perfringens enterotoxin (CPE), a causative agent of food poisoning, is a pore-forming toxin disrupting the selective permeability of the plasma membrane of target cells, resulting in cell death. We previously identified claudin as the cell surface receptor for CPE. Claudin, a component of tight junctions, is a tetratransmembrane protein and constitutes a large family of more than 20 members, not all of which serve as the receptor for CPE. The mechanism by which the toxin distinguishes the sensitive claudins is unknown. In this study, we localized the region of claudin responsible for interaction with CPE to the C-terminal part of the second extracellular loop and found that the isoelectric point of this region in sensitive claudins was higher than insensitive claudins. Amino acid substitutions to lower the pI resulted in reduced sensitivity to CPE among sensitive claudins, whereas substitutions to raise the pI endowed CPE-insensitive claudins with sensitivity. The steric structure of the claudin-binding domain of CPE reveals an acidic cleft surrounded by Tyr306, Tyr310, Tyr312, and Leu315, which were reported to be essential for interaction with the sensitive claudins. These results imply that an electrostatic attraction between the basic claudin region and the acidic CPE cleft is involved in their interaction. PMID:19903817

Contextual Classification of Point Cloud Data by Exploiting Individual 3d Neigbourhoods

NASA Astrophysics Data System (ADS)

Weinmann, M.; Schmidt, A.; Mallet, C.; Hinz, S.; Rottensteiner, F.; Jutzi, B.

2015-03-01

The fully automated analysis of 3D point clouds is of great importance in photogrammetry, remote sensing and computer vision. For reliably extracting objects such as buildings, road inventory or vegetation, many approaches rely on the results of a point cloud classification, where each 3D point is assigned a respective semantic class label. Such an assignment, in turn, typically involves statistical methods for feature extraction and machine learning. Whereas the different components in the processing workflow have extensively, but separately been investigated in recent years, the respective connection by sharing the results of crucial tasks across all components has not yet been addressed. This connection not only encapsulates the interrelated issues of neighborhood selection and feature extraction, but also the issue of how to involve spatial context in the classification step. In this paper, we present a novel and generic approach for 3D scene analysis which relies on (i) individually optimized 3D neighborhoods for (ii) the extraction of distinctive geometric features and (iii) the contextual classification of point cloud data. For a labeled benchmark dataset, we demonstrate the beneficial impact of involving contextual information in the classification process and that using individual 3D neighborhoods of optimal size significantly increases the quality of the results for both pointwise and contextual classification.

Automatic extraction of discontinuity orientation from rock mass surface 3D point cloud

NASA Astrophysics Data System (ADS)

Chen, Jianqin; Zhu, Hehua; Li, Xiaojun

2016-10-01

This paper presents a new method for extracting discontinuity orientation automatically from rock mass surface 3D point cloud. The proposed method consists of four steps: (1) automatic grouping of discontinuity sets using an improved K-means clustering method, (2) discontinuity segmentation and optimization, (3) discontinuity plane fitting using Random Sample Consensus (RANSAC) method, and (4) coordinate transformation of discontinuity plane. The method is first validated by the point cloud of a small piece of a rock slope acquired by photogrammetry. The extracted discontinuity orientations are compared with measured ones in the field. Then it is applied to a publicly available LiDAR data of a road cut rock slope at Rockbench repository. The extracted discontinuity orientations are compared with the method proposed by Riquelme et al. (2014). The results show that the presented method is reliable and of high accuracy, and can meet the engineering needs.

Extractive biodegradation and bioavailability assessment of phenanthrene in the cloud point system by Sphingomonas polyaromaticivorans.

PubMed

Pan, Tao; Deng, Tao; Zeng, Xinying; Dong, Wei; Yu, Shuijing

2016-01-01

The biological treatment of polycyclic aromatic hydrocarbons is an important issue. Most microbes have limited practical applications because of the poor bioavailability of polycyclic aromatic hydrocarbons. In this study, the extractive biodegradation of phenanthrene by Sphingomonas polyaromaticivorans was conducted by introducing the cloud point system. The cloud point system is composed of a mixture of (40 g/L) Brij 30 and Tergitol TMN-3, which are nonionic surfactants, in equal proportions. After phenanthrene degradation, a higher wet cell weight and lower phenanthrene residue were obtained in the cloud point system than that in the control system. According to the results of high-performance liquid chromatography, the residual phenanthrene preferred to partition from the dilute phase into the coacervate phase. The concentration of residual phenanthrene in the dilute phase (below 0.001 mg/L) is lower than its solubility in water (1.18 mg/L) after extractive biodegradation. Therefore, dilute phase detoxification was achieved, thus indicating that the dilute phase could be discharged without causing phenanthrene pollution. Bioavailability was assessed by introducing the apparent logP in the cloud point system. Apparent logP decreased significantly, thus indicating that the bioavailability of phenanthrene increased remarkably in the system. This study provides a potential application of biological treatment in water and soil contaminated by phenanthrene.

Extracting cross sections and water levels of vegetated ditches from LiDAR point clouds

NASA Astrophysics Data System (ADS)

Roelens, Jennifer; Dondeyne, Stefaan; Van Orshoven, Jos; Diels, Jan

2016-12-01

The hydrologic response of a catchment is sensitive to the morphology of the drainage network. Dimensions of bigger channels are usually well known, however, geometrical data for man-made ditches is often missing as there are many and small. Aerial LiDAR data offers the possibility to extract these small geometrical features. Analysing the three-dimensional point clouds directly will maintain the highest degree of information. A longitudinal and cross-sectional buffer were used to extract the cross-sectional profile points from the LiDAR point cloud. The profile was represented by spline functions fitted through the minimum envelop of the extracted points. The cross-sectional ditch profiles were classified for the presence of water and vegetation based on the normalized difference water index and the spatial characteristics of the points along the profile. The normalized difference water index was created using the RGB and intensity data coupled to the LiDAR points. The mean vertical deviation of 0.14 m found between the extracted and reference cross sections could mainly be attributed to the occurrence of water and partly to vegetation on the banks. In contrast to the cross-sectional area, the extracted width was not influenced by the environment (coefficient of determination R2 = 0.87). Water and vegetation influenced the extracted ditch characteristics, but the proposed method is still robust and therefore facilitates input data acquisition and improves accuracy of spatially explicit hydrological models.

Cocoa flavonoids protect hepatic cells against high-glucose-induced oxidative stress: relevance of MAPKs.

PubMed

Cordero-Herrera, Isabel; Martín, María Angeles; Goya, Luis; Ramos, Sonia

2015-04-01

Oxidative stress plays a main role in the pathogenesis of type 2 diabetes mellitus. Cocoa and (-)-epicatechin (EC), a main cocoa flavanol, have been suggested to exert beneficial effects in type 2 diabetes mellitus because of their protective effects against oxidative stress and insulin-like properties. In this study, the protective effect of EC and a cocoa phenolic extract (CPE) against oxidative stress induced by a high-glucose challenge, which causes insulin resistance, was investigated on hepatic HepG2 cells. Oxidative status, phosphorylated mitogen-activated protein kinases (MAPKs), nuclear factor E2 related factor 2 (Nrf2) and p-(Ser)-IRS-1 expression, and glucose uptake were evaluated. EC and CPE regulated antioxidant enzymes and activated extracellular-regulated kinase and Nrf2. EC and CPE pre-treatment prevented high-glucose-induced antioxidant defences and p-MAPKs, and maintained Nrf2 stimulation. The presence of selective MAPK inhibitors induced changes in redox status, glucose uptake, p-(Ser)- and total IRS-1 levels that were observed in CPE-mediated protection. EC and CPE recovered redox status of insulin-resistant HepG2 cells, suggesting that the functionality in EC- and CPE-treated cells was protected against high-glucose-induced oxidative insult. CPE beneficial effects on redox balance and insulin resistance were mediated by targeting MAPKs. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Largely improved the low temperature toughness of acrylonitrile-styrene-acrylate (ASA) resin: Fabricated a core-shell structure of two elastomers through the differences of interfacial tensions

NASA Astrophysics Data System (ADS)

Mao, Zepeng; Zhang, Jun

2018-06-01

The phase morphology of two elastomers (i.e., chlorinated polyethylene (CPE) and polybutadiene rubber (BR)) were devised to be a core-shell structure in acrylonitrile-styrene-acrylate (ASA) resin matrix, via the interfacial tension differences of polymer pairs. Selective extraction test and scanning electron microscopy (SEM) were utilized to verify this special phase morphology. The results demonstrated that the core-shell structure, BR core and CPE shell, significantly contributed to improve the low temperature toughness of ASA/CPE/BR ternary blends, which may be because the nonpolar BR core was segregated from polar ASA by the CPE shell. The CPE shell served dual functions: Not only did it play compatibilizing effect in the interface between BR and ASA matrix, but it also toughened the blends at 25 and 0 °C. The blends of ASA/CPE/BR (100/27/3, w/w/w) and ASA/CPE/BR (100/22/8, w/w/w) showed the peak impact strengths at about 28 and 9 kJ/m2 at 0 and -30 °C, respectively, which were higher than both that of ASA/CPE/BR (100/30/0, w/w/w) and ASA/CPE/BR (100/0/30, w/w/w). Moreover, the impact strength of ternary blends at room temperature kept at 40 kJ/m2 when BR content was lower than 10 phr. Other characterizations including contact angle measurement, dynamic mechanical thermal analysis (DMTA), morphology of impact-fractured surfaces, tensile properties, flexural properties, and Fourier transform infrared spectroscopy (FTIR) were measured as well.

Extracting valley-ridge lines from point-cloud-based 3D fingerprint models.

PubMed

Pang, Xufang; Song, Zhan; Xie, Wuyuan

2013-01-01

3D fingerprinting is an emerging technology with the distinct advantage of touchless operation. More important, 3D fingerprint models contain more biometric information than traditional 2D fingerprint images. However, current approaches to fingerprint feature detection usually must transform the 3D models to a 2D space through unwrapping or other methods, which might introduce distortions. A new approach directly extracts valley-ridge features from point-cloud-based 3D fingerprint models. It first applies the moving least-squares method to fit a local paraboloid surface and represent the local point cloud area. It then computes the local surface's curvatures and curvature tensors to facilitate detection of the potential valley and ridge points. The approach projects those points to the most likely valley-ridge lines, using statistical means such as covariance analysis and cross correlation. To finally extract the valley-ridge lines, it grows the polylines that approximate the projected feature points and removes the perturbations between the sampled points. Experiments with different 3D fingerprint models demonstrate this approach's feasibility and performance.

Point Cloud Oriented Shoulder Line Extraction in Loess Hilly Area

NASA Astrophysics Data System (ADS)

Min, Li; Xin, Yang; Liyang, Xiong

2016-06-01

Shoulder line is the significant line in hilly area of Loess Plateau in China, dividing the surface into positive and negative terrain (P-N terrains). Due to the point cloud vegetation removal methods of P-N terrains are different, there is an imperative need for shoulder line extraction. In this paper, we proposed an automatic shoulder line extraction method based on point cloud. The workflow is as below: (i) ground points were selected by using a grid filter in order to remove most of noisy points. (ii) Based on DEM interpolated by those ground points, slope was mapped and classified into two classes (P-N terrains), using Natural Break Classified method. (iii) The common boundary between two slopes is extracted as shoulder line candidate. (iv) Adjust the filter gird size and repeat step i-iii until the shoulder line candidate matches its real location. (v) Generate shoulder line of the whole area. Test area locates in Madigou, Jingbian County of Shaanxi Province, China. A total of 600 million points are acquired in the test area of 0.23km2, using Riegl VZ400 3D Laser Scanner in August 2014. Due to the limit Granted computing performance, the test area is divided into 60 blocks and 13 of them around the shoulder line were selected for filter grid size optimizing. The experiment result shows that the optimal filter grid size varies in diverse sample area, and a power function relation exists between filter grid size and point density. The optimal grid size was determined by above relation and shoulder lines of 60 blocks were then extracted. Comparing with the manual interpretation results, the accuracy of the whole result reaches 85%. This method can be applied to shoulder line extraction in hilly area, which is crucial for point cloud denoising and high accuracy DEM generation.

Standardization of RP-HPLC methods for the detection of the major peanut allergens Ara h 1, Ara h 2 and Ara h 3

USDA-ARS?s Scientific Manuscript database

Crude peanut extract (CPE) was analyzed for three major allergens (Ara h 1, h 2, and h 3) using a C12 and a C18 column at two wavelengths (280 and 220 nm) and under different solvent conditions. HPLC profiles were compared for retention time, resolution, and peak heights. CPE samples were spiked wit...

Automatic Rail Extraction and Celarance Check with a Point Cloud Captured by Mls in a Railway

NASA Astrophysics Data System (ADS)

Niina, Y.; Honma, R.; Honma, Y.; Kondo, K.; Tsuji, K.; Hiramatsu, T.; Oketani, E.

2018-05-01

Recently, MLS (Mobile Laser Scanning) has been successfully used in a road maintenance. In this paper, we present the application of MLS for the inspection of clearance along railway tracks of West Japan Railway Company. Point clouds around the track are captured by MLS mounted on a bogie and rail position can be determined by matching the shape of the ideal rail head with respect to the point cloud by ICP algorithm. A clearance check is executed automatically with virtual clearance model laid along the extracted rail. As a result of evaluation, the accuracy of extracting rail positions is less than 3 mm. With respect to the automatic clearance check, the objects inside the clearance and the ones related to a contact line is successfully detected by visual confirmation.

A preconcentration method for indirect determination of acrylamide from chips, crackers and cereal-based baby foods using flame atomic absorption spectrometry.

PubMed

Altunay, Nail; Gürkan, Ramazan; Orhan, Ulaş

2016-12-01

Acrylamide is a toxic species for human health, and is a Maillard reaction product which forms spontaneously in heat treatment process of foods. Therefore, a simple, fast and cost-effective method was developed for the indirect determination of acrylamide in processed foods particularly consumed by children. The method is based on ion-pairing of acrylamide with fluorescein (F 2- ) in presence of Ni(II) ions at pH 9.0, and then extraction of the formed ternary complex into micellar phase of poly(ethyleneglycol-mono-p-nonylphenylether) (PONPE 7.5) before analysis by flame atomic absorption spectrometry (FAAS). The ultrasonic-assisted cloud point extraction (UA-CPE) has been used for the preconcentration of acrylamide in the samples prior to its FAAS detection. The matrix matched calibration curve is linear in range of 0.3-150µgkg -1 under optimal reagent conditions (1.75mL of 0.1molL -1 ammonia buffer at pH 9.0, 2.2mgL -1 Ni(II), 4.0×10 -4 molL -1 F 2- , 0.4% (w/v) NH 4 Cl and 0.7% (v/v) PONPE 7.5) with sensitivity enhancement of 160-fold. The proposed method has been validated by assessment of the following parameters; the limits of detection (LOD) and quantification (LOQ) (0.08µgkg -1 and 0.28µgkg -1 , respectively) with a relative standard deviation (RSD%) lower than 6.3%, and extractive recovery higher than 95% for acrylamide spiked at levels of 5 and 25µgkg -1 . The method was successfully applied to the indirect determination of acrylamide in the processed foods and two CRMs with satisfactory results. Copyright © 2016 Elsevier B.V. All rights reserved.

Automatic extraction of pavement markings on streets from point cloud data of mobile LiDAR

NASA Astrophysics Data System (ADS)

Gao, Yang; Zhong, Ruofei; Tang, Tao; Wang, Liuzhao; Liu, Xianlin

2017-08-01

Pavement markings provide an important foundation as they help to keep roads users safe. Accurate and comprehensive information about pavement markings assists the road regulators and is useful in developing driverless technology. Mobile light detection and ranging (LiDAR) systems offer new opportunities to collect and process accurate pavement markings’ information. Mobile LiDAR systems can directly obtain the three-dimensional (3D) coordinates of an object, thus defining spatial data and the intensity of (3D) objects in a fast and efficient way. The RGB attribute information of data points can be obtained based on the panoramic camera in the system. In this paper, we present a novel method process to automatically extract pavement markings using multiple attribute information of the laser scanning point cloud from the mobile LiDAR data. This method process utilizes a differential grayscale of RGB color, laser pulse reflection intensity, and the differential intensity to identify and extract pavement markings. We utilized point cloud density to remove the noise and used morphological operations to eliminate the errors. In the application, we tested our method process on different sections of roads in Beijing, China, and Buffalo, NY, USA. The results indicated that both correctness (p) and completeness (r) were higher than 90%. The method process of this research can be applied to extract pavement markings from huge point cloud data produced by mobile LiDAR.

Synergistic cloud point extraction behavior of aluminum(III) with 2-methyl-8-quinolinol and 3,5-dichlorophenol.

PubMed

Ohashi, Akira; Tsuguchi, Akira; Imura, Hisanori; Ohashi, Kousaburo

2004-07-01

The cloud point extraction behavior of aluminum(III) with 8-quinolinol (HQ) or 2-methyl-8-quinolinol (HMQ) and Triton X-100 was investigated in the absence and presence of 3,5-dichlorophenol (Hdcp). Aluminum(III) was almost extracted with HQ and 4(v/v)% Triton X-100 above pH 5.0, but was not extracted with HMQ-Triton X-100. However, in the presence of Hdcp, it was almost quantitatively extracted with HMQ-Triton X-100. The synergistic effect of Hdcp on the extraction of aluminum(III) with HMQ and Triton X-100 may be caused by the formation of a mixed-ligand complex, Al(dcp)(MQ)2.

Temporal Analysis and Automatic Calibration of the Velodyne HDL-32E LiDAR System

NASA Astrophysics Data System (ADS)

Chan, T. O.; Lichti, D. D.; Belton, D.

2013-10-01

At the end of the first quarter of 2012, more than 600 Velodyne LiDAR systems had been sold worldwide for various robotic and high-accuracy survey applications. The ultra-compact Velodyne HDL-32E LiDAR has become a predominant sensor for many applications that require lower sensor size/weight and cost. For high accuracy applications, cost-effective calibration methods with minimal manual intervention are always desired by users. However, the calibrations are complicated by the Velodyne LiDAR's narrow vertical field of view and the very highly time-variant nature of its measurements. In the paper, the temporal stability of the HDL-32E is first analysed as the motivation for developing a new, automated calibration method. This is followed by a detailed description of the calibration method that is driven by a novel segmentation method for extracting vertical cylindrical features from the Velodyne point clouds. The proposed segmentation method utilizes the Velodyne point cloud's slice-like nature and first decomposes the point clouds into 2D layers. Then the layers are treated as 2D images and are processed with the Generalized Hough Transform which extracts the points distributed in circular patterns from the point cloud layers. Subsequently, the vertical cylindrical features can be readily extracted from the whole point clouds based on the previously extracted points. The points are passed to the calibration that estimates the cylinder parameters and the LiDAR's additional parameters simultaneously by constraining the segmented points to fit to the cylindrical geometric model in such a way the weighted sum of the adjustment residuals are minimized. The proposed calibration is highly automatic and this allows end users to obtain the time-variant additional parameters instantly and frequently whenever there are vertical cylindrical features presenting in scenes. The methods were verified with two different real datasets, and the results suggest that up to 78.43% accuracy improvement for the HDL-32E can be achieved using the proposed calibration method.

Vertical Optical Scanning with Panoramic Vision for Tree Trunk Reconstruction

PubMed Central

Berveglieri, Adilson; Liang, Xinlian; Honkavaara, Eija

2017-01-01

This paper presents a practical application of a technique that uses a vertical optical flow with a fisheye camera to generate dense point clouds from a single planimetric station. Accurate data can be extracted to enable the measurement of tree trunks or branches. The images that are collected with this technique can be oriented in photogrammetric software (using fisheye models) and used to generate dense point clouds, provided that some constraints on the camera positions are adopted. A set of images was captured in a forest plot in the experiments. Weighted geometric constraints were imposed in the photogrammetric software to calculate the image orientation, perform dense image matching, and accurately generate a 3D point cloud. The tree trunks in the scenes were reconstructed and mapped in a local reference system. The accuracy assessment was based on differences between measured and estimated trunk diameters at different heights. Trunk sections from an image-based point cloud were also compared to the corresponding sections that were extracted from a dense terrestrial laser scanning (TLS) point cloud. Cylindrical fitting of the trunk sections allowed the assessment of the accuracies of the trunk geometric shapes in both clouds. The average difference between the cylinders that were fitted to the photogrammetric cloud and those to the TLS cloud was less than 1 cm, which indicates the potential of the proposed technique. The point densities that were obtained with vertical optical scanning were 1/3 less than those that were obtained with TLS. However, the point density can be improved by using higher resolution cameras. PMID:29207468

Vertical Optical Scanning with Panoramic Vision for Tree Trunk Reconstruction.

PubMed

Berveglieri, Adilson; Tommaselli, Antonio M G; Liang, Xinlian; Honkavaara, Eija

2017-12-02

This paper presents a practical application of a technique that uses a vertical optical flow with a fisheye camera to generate dense point clouds from a single planimetric station. Accurate data can be extracted to enable the measurement of tree trunks or branches. The images that are collected with this technique can be oriented in photogrammetric software (using fisheye models) and used to generate dense point clouds, provided that some constraints on the camera positions are adopted. A set of images was captured in a forest plot in the experiments. Weighted geometric constraints were imposed in the photogrammetric software to calculate the image orientation, perform dense image matching, and accurately generate a 3D point cloud. The tree trunks in the scenes were reconstructed and mapped in a local reference system. The accuracy assessment was based on differences between measured and estimated trunk diameters at different heights. Trunk sections from an image-based point cloud were also compared to the corresponding sections that were extracted from a dense terrestrial laser scanning (TLS) point cloud. Cylindrical fitting of the trunk sections allowed the assessment of the accuracies of the trunk geometric shapes in both clouds. The average difference between the cylinders that were fitted to the photogrammetric cloud and those to the TLS cloud was less than 1 cm, which indicates the potential of the proposed technique. The point densities that were obtained with vertical optical scanning were 1/3 less than those that were obtained with TLS. However, the point density can be improved by using higher resolution cameras.

Strong ion exchange in centrifugal partition extraction (SIX-CPE): effect of partition cell design and dimensions on purification process efficiency.

PubMed

Hamzaoui, Mahmoud; Hubert, Jane; Reynaud, Romain; Marchal, Luc; Foucault, Alain; Renault, Jean-Hugues

2012-07-20

The aim of this article was to evaluate the influence of the column design of a hydrostatic support-free liquid-liquid chromatography device on the process efficiency when the strong ion-exchange (SIX) development mode is used. The purification of p-hydroxybenzylglucosinolate (sinalbin) from a crude aqueous extract of white mustard seeds (Sinapis alba L.) was achieved on two types of devices: a centrifugal partition chromatograph (CPC) and a centrifugal partition extractor (CPE). They differ in the number, volume and geometry of their partition cells. The SIX-CPE process was evaluated in terms of productivity and sinalbin purification capability as compared to previously optimized SIX-CPC protocols that were carried out on columns of 200 mL and 5700 mL inner volume, respectively. The objective was to determine whether the decrease in partition cell number, the increase in their volume and the use of a "twin cell" design would induce a significant increase in productivity by applying higher mobile phase flow rate while maintaining a constant separation quality. 4.6g of sinalbin (92% recovery) were isolated from 25 g of a crude white mustard seed extract, in only 32 min and with a purity of 94.7%, thus corresponding to a productivity of 28 g per hour and per liter of column volume (g/h/LV(c)). Therefore, the SIX-CPE process demonstrates promising industrial technology transfer perspectives for the large-scale isolation of ionized natural products. Copyright © 2012 Elsevier B.V. All rights reserved.

Change Analysis in Structural Laser Scanning Point Clouds: The Baseline Method

PubMed Central

Shen, Yueqian; Lindenbergh, Roderik; Wang, Jinhu

2016-01-01

A method is introduced for detecting changes from point clouds that avoids registration. For many applications, changes are detected between two scans of the same scene obtained at different times. Traditionally, these scans are aligned to a common coordinate system having the disadvantage that this registration step introduces additional errors. In addition, registration requires stable targets or features. To avoid these issues, we propose a change detection method based on so-called baselines. Baselines connect feature points within one scan. To analyze changes, baselines connecting corresponding points in two scans are compared. As feature points either targets or virtual points corresponding to some reconstructable feature in the scene are used. The new method is implemented on two scans sampling a masonry laboratory building before and after seismic testing, that resulted in damages in the order of several centimeters. The centres of the bricks of the laboratory building are automatically extracted to serve as virtual points. Baselines connecting virtual points and/or target points are extracted and compared with respect to a suitable structural coordinate system. Changes detected from the baseline analysis are compared to a traditional cloud to cloud change analysis demonstrating the potential of the new method for structural analysis. PMID:28029121

Change Analysis in Structural Laser Scanning Point Clouds: The Baseline Method.

PubMed

Shen, Yueqian; Lindenbergh, Roderik; Wang, Jinhu

2016-12-24

A method is introduced for detecting changes from point clouds that avoids registration. For many applications, changes are detected between two scans of the same scene obtained at different times. Traditionally, these scans are aligned to a common coordinate system having the disadvantage that this registration step introduces additional errors. In addition, registration requires stable targets or features. To avoid these issues, we propose a change detection method based on so-called baselines. Baselines connect feature points within one scan. To analyze changes, baselines connecting corresponding points in two scans are compared. As feature points either targets or virtual points corresponding to some reconstructable feature in the scene are used. The new method is implemented on two scans sampling a masonry laboratory building before and after seismic testing, that resulted in damages in the order of several centimeters. The centres of the bricks of the laboratory building are automatically extracted to serve as virtual points. Baselines connecting virtual points and/or target points are extracted and compared with respect to a suitable structural coordinate system. Changes detected from the baseline analysis are compared to a traditional cloud to cloud change analysis demonstrating the potential of the new method for structural analysis.

Performance Evaluation of sUAS Equipped with Velodyne HDL-32E LiDAR Sensor

NASA Astrophysics Data System (ADS)

Jozkow, G.; Wieczorek, P.; Karpina, M.; Walicka, A.; Borkowski, A.

2017-08-01

The Velodyne HDL-32E laser scanner is used more frequently as main mapping sensor in small commercial UASs. However, there is still little information about the actual accuracy of point clouds collected with such UASs. This work evaluates empirically the accuracy of the point cloud collected with such UAS. Accuracy assessment was conducted in four aspects: impact of sensors on theoretical point cloud accuracy, trajectory reconstruction quality, and internal and absolute point cloud accuracies. Theoretical point cloud accuracy was evaluated by calculating 3D position error knowing errors of used sensors. The quality of trajectory reconstruction was assessed by comparing position and attitude differences from forward and reverse EKF solution. Internal and absolute accuracies were evaluated by fitting planes to 8 point cloud samples extracted for planar surfaces. In addition, the absolute accuracy was also determined by calculating point 3D distances between LiDAR UAS and reference TLS point clouds. Test data consisted of point clouds collected in two separate flights performed over the same area. Executed experiments showed that in tested UAS, the trajectory reconstruction, especially attitude, has significant impact on point cloud accuracy. Estimated absolute accuracy of point clouds collected during both test flights was better than 10 cm, thus investigated UAS fits mapping-grade category.

Three-dimensional reconstruction of indoor whole elements based on mobile LiDAR point cloud data

NASA Astrophysics Data System (ADS)

Gong, Yuejian; Mao, Wenbo; Bi, Jiantao; Ji, Wei; He, Zhanjun

2014-11-01

Ground-based LiDAR is one of the most effective city modeling tools at present, which has been widely used for three-dimensional reconstruction of outdoor objects. However, as for indoor objects, there are some technical bottlenecks due to lack of GPS signal. In this paper, based on the high-precision indoor point cloud data which was obtained by LiDAR, an international advanced indoor mobile measuring equipment, high -precision model was fulfilled for all indoor ancillary facilities. The point cloud data we employed also contain color feature, which is extracted by fusion with CCD images. Thus, it has both space geometric feature and spectral information which can be used for constructing objects' surface and restoring color and texture of the geometric model. Based on Autodesk CAD platform and with help of PointSence plug, three-dimensional reconstruction of indoor whole elements was realized. Specifically, Pointools Edit Pro was adopted to edit the point cloud, then different types of indoor point cloud data was processed, including data format conversion, outline extracting and texture mapping of the point cloud model. Finally, three-dimensional visualization of the real-world indoor was completed. Experiment results showed that high-precision 3D point cloud data obtained by indoor mobile measuring equipment can be used for indoor whole elements' 3-d reconstruction and that methods proposed in this paper can efficiently realize the 3 -d construction of indoor whole elements. Moreover, the modeling precision could be controlled within 5 cm, which was proved to be a satisfactory result.

Community College Student Transfer: Understanding Community College Students' Decisions about Transfer in Southeastern Kentucky

ERIC Educational Resources Information Center

Mobelini, Deronda Collier

2012-01-01

The Kentucky Council on Postsecondary Education's (CPE) "Stronger by Degrees" 2011-2015 Strategic Agenda points to additional causes for concern in the slower than projected increase in the rate of transfer from KCTCS colleges to four-year institutions (CPE, 2010). Therefore, it is important for KCTCS to develop a better understanding of…

Model for Semantically Rich Point Cloud Data

NASA Astrophysics Data System (ADS)

Poux, F.; Neuville, R.; Hallot, P.; Billen, R.

2017-10-01

This paper proposes an interoperable model for managing high dimensional point clouds while integrating semantics. Point clouds from sensors are a direct source of information physically describing a 3D state of the recorded environment. As such, they are an exhaustive representation of the real world at every scale: 3D reality-based spatial data. Their generation is increasingly fast but processing routines and data models lack of knowledge to reason from information extraction rather than interpretation. The enhanced smart point cloud developed model allows to bring intelligence to point clouds via 3 connected meta-models while linking available knowledge and classification procedures that permits semantic injection. Interoperability drives the model adaptation to potentially many applications through specialized domain ontologies. A first prototype is implemented in Python and PostgreSQL database and allows to combine semantic and spatial concepts for basic hybrid queries on different point clouds.

The protective effects of aqueous extract of Carica papaya seeds in paracetamol induced nephrotoxicity in male wistar rats.

PubMed

Naggayi, Madinah; Mukiibi, Nozmo; Iliya, Ezekiel

2015-06-01

Oxidative stress plays a crucial role in the development of drug induced nephrotoxicity. The study aimed to determine the nephroprotective and ameliorative effects of Carica papaya seed extract in paracetamol-induced nephrotoxicity in rats. To carry out phytochemical screening of Carica papaya, measure serum urea, creatinine and uric acid and describe the histopathological status of the kidneys in the treated and untreated groups. Phytochemical screening of the extract was done. Thirty two adult male Wistar rats were divided into four groups (n= 8 in each group). Group A (control) animals received normal saline for seven days, group B (paracetamol group) received normal saline, and paracetamol single dose on the 8th day. Group C received Carica papaya extract (CPE) 500 mg/kg, and paracetamol on the 8th day, while group D, rats were pretreated with CPE 750 mg/kg/day,and paracetamol administration on the 8th day. Samples of kidney tissue were removed for histopathological examination. Screening of Carica papaya showed presence of nephroprotective pytochemicals. Paracetamol administration resulted in significant elevation of renal function markers. CPE ameliorated the effect of paracetamol by reducing the markers as well as reversing the paracetamol-induced changes in kidney architecture. Carica papaya contains nephroprotective phytochemicals and may be useful in preventing kidney damage induced by paracetamol.

Mapping Urban Tree Canopy Cover Using Fused Airborne LIDAR and Satellite Imagery Data

NASA Astrophysics Data System (ADS)

Parmehr, Ebadat G.; Amati, Marco; Fraser, Clive S.

2016-06-01

Urban green spaces, particularly urban trees, play a key role in enhancing the liveability of cities. The availability of accurate and up-to-date maps of tree canopy cover is important for sustainable development of urban green spaces. LiDAR point clouds are widely used for the mapping of buildings and trees, and several LiDAR point cloud classification techniques have been proposed for automatic mapping. However, the effectiveness of point cloud classification techniques for automated tree extraction from LiDAR data can be impacted to the point of failure by the complexity of tree canopy shapes in urban areas. Multispectral imagery, which provides complementary information to LiDAR data, can improve point cloud classification quality. This paper proposes a reliable method for the extraction of tree canopy cover from fused LiDAR point cloud and multispectral satellite imagery data. The proposed method initially associates each LiDAR point with spectral information from the co-registered satellite imagery data. It calculates the normalised difference vegetation index (NDVI) value for each LiDAR point and corrects tree points which have been misclassified as buildings. Then, region growing of tree points, taking the NDVI value into account, is applied. Finally, the LiDAR points classified as tree points are utilised to generate a canopy cover map. The performance of the proposed tree canopy cover mapping method is experimentally evaluated on a data set of airborne LiDAR and WorldView 2 imagery covering a suburb in Melbourne, Australia.

Emergence of anxiety-like behaviours in depressive-like Cpe(fat/fat) mice.

PubMed

Rodriguiz, Ramona M; Wilkins, John J; Creson, Thomas K; Biswas, Reeta; Berezniuk, Iryna; Fricker, Arun D; Fricker, Lloyd D; Wetsel, William C

2013-08-01

Cpe(fat/fat) mice have a point mutation in carboxypeptidase E (Cpe), an exopeptidase that removes C-terminal basic amino acids from intermediates to produce bioactive peptides. The mutation renders the enzyme inactive and unstable. The absence of Cpe activity in these mutants leads to abnormal processing of many peptides, with elevated levels of intermediates and greatly reduced levels of the mature peptides. Cpe(fat/fat) mice develop obesity, diabetes and infertility in adulthood. We examined whether anxiety- and/or depressive-like behaviours are also present. Anxiety-like responses are not evident in young Cpe(fat/fat) mice (∼60 d), but appear in older animals (>90 d). These behaviours are reversed by acute treatment with diazepam or fluoxetine. In contrast, increased immobilities in forced swim and tail suspension are evident in all age groups examined. These behaviours are reversed by acute administration of reboxetine. In comparison acute treatments with fluoxetine or bupropion are ineffective; however, immobility times are normalized with 2 wk treatment. These data demonstrate that Cpe(fat/fat) mice display depressive-like responses aged ∼60 d, whereas anxiety-like behaviours emerge ∼1 month later. In tail suspension, the reboxetine findings show that noradrenergic actions of antidepressants are intact in Cpe(fat/fat) mice. The ability of acute fluoxetine treatment to rescue anxiety-like while leaving depressive-like responses unaffected suggests that serotonin mechanisms underlying these behaviours are different. Since depressive-like responses in the Cpe(fat/fat) mice are rescued by 2 wk, but not acute, treatment with fluoxetine or bupropion, these mice may serve as a useful model that resembles human depression.

[Determination of biphenyl ether herbicides in water using HPLC with cloud-point extraction].

PubMed

He, Cheng-Yan; Li, Yuan-Qian; Wang, Shen-Jiao; Ouyang, Hua-Xue; Zheng, Bo

2010-01-01

To determine residues of multiple biphenyl ether herbicides simultaneously in water using high performance liquid chromatography (HPLC) with cloud-point extraction. The residues of eight biphenyl ether herbicides (including bentazone, fomesafen, acifluorfen, aclonifen, bifenox, fluoroglycofenethy, nitrofen, oxyfluorfen) in water samples were extracted with cloud-point extraction of Triton X-114. The analytes were separated and determined using reverse phase HPLC with ultraviolet detector at 300 nm. Optimized conditions for the pretreatment of water samples and the parameters of chromatographic separation applied. There was a good linear correlation between the concentration and the peak area of the analytes in the range of 0.05-2.00 mg/L (r = 0.9991-0.9998). Except bentazone, the spiked recoveries of the biphenyl ether herbicides in the water samples ranged from 80.1% to 100.9%, with relative standard deviations ranging from 2.70% to 6.40%. The detection limit of the method ranged from 0.10 microg/L to 0.50 microg/L. The proposed method is simple, rapid and sensitive, and can meet the requirements of determination of multiple biphenyl ether herbicides simultaneously in natural waters.

Automatic Extraction of Road Markings from Mobile Laser Scanning Data

NASA Astrophysics Data System (ADS)

Ma, H.; Pei, Z.; Wei, Z.; Zhong, R.

2017-09-01

Road markings as critical feature in high-defination maps, which are Advanced Driver Assistance System (ADAS) and self-driving technology required, have important functions in providing guidance and information to moving cars. Mobile laser scanning (MLS) system is an effective way to obtain the 3D information of the road surface, including road markings, at highway speeds and at less than traditional survey costs. This paper presents a novel method to automatically extract road markings from MLS point clouds. Ground points are first filtered from raw input point clouds using neighborhood elevation consistency method. The basic assumption of the method is that the road surface is smooth. Points with small elevation-difference between neighborhood are considered to be ground points. Then ground points are partitioned into a set of profiles according to trajectory data. The intensity histogram of points in each profile is generated to find intensity jumps in certain threshold which inversely to laser distance. The separated points are used as seed points to region grow based on intensity so as to obtain road mark of integrity. We use the point cloud template-matching method to refine the road marking candidates via removing the noise clusters with low correlation coefficient. During experiment with a MLS point set of about 2 kilometres in a city center, our method provides a promising solution to the road markings extraction from MLS data.

The potential of cloud point system as a novel two-phase partitioning system for biotransformation.

PubMed

Wang, Zhilong

2007-05-01

Although the extractive biotransformation in two-phase partitioning systems have been studied extensively, such as the water-organic solvent two-phase system, the aqueous two-phase system, the reverse micelle system, and the room temperature ionic liquid, etc., this has not yet resulted in a widespread industrial application. Based on the discussion of the main obstacles, an exploitation of a cloud point system, which has already been applied in a separation field known as a cloud point extraction, as a novel two-phase partitioning system for biotransformation, is reviewed by analysis of some topical examples. At the end of the review, the process control and downstream processing in the application of the novel two-phase partitioning system for biotransformation are also briefly discussed.

Datum Feature Extraction and Deformation Analysis Method Based on Normal Vector of Point Cloud

NASA Astrophysics Data System (ADS)

Sun, W.; Wang, J.; Jin, F.; Liang, Z.; Yang, Y.

2018-04-01

In order to solve the problem lacking applicable analysis method in the application of three-dimensional laser scanning technology to the field of deformation monitoring, an efficient method extracting datum feature and analysing deformation based on normal vector of point cloud was proposed. Firstly, the kd-tree is used to establish the topological relation. Datum points are detected by tracking the normal vector of point cloud determined by the normal vector of local planar. Then, the cubic B-spline curve fitting is performed on the datum points. Finally, datum elevation and the inclination angle of the radial point are calculated according to the fitted curve and then the deformation information was analyzed. The proposed approach was verified on real large-scale tank data set captured with terrestrial laser scanner in a chemical plant. The results show that the method could obtain the entire information of the monitor object quickly and comprehensively, and reflect accurately the datum feature deformation.

Extractive biodecolorization of triphenylmethane dyes in cloud point system by Aeromonas hydrophila DN322p.

PubMed

Pan, Tao; Ren, Suizhou; Xu, Meiying; Sun, Guoping; Guo, Jun

2013-07-01

The biological treatment of triphenylmethane dyes is an important issue. Most microbes have limited practical application because they cannot completely detoxicate these dyes. In this study, the extractive biodecolorization of triphenylmethane dyes by Aeromonas hydrophila DN322p was carried out by introducing the cloud point system. The cloud point system is composed of a mixture of nonionic surfactants (20 g/L) Brij 30 and Tergitol TMN-3 in equal proportions. After the decolorization of crystal violet, a higher wet cell weight was obtained in the cloud point system than that of the control system. Based on the results of thin-layer chromatography, the residual crystal violet and its decolorized product, leuco crystal violet, preferred to partition into the coacervate phase. Therefore, the detoxification of the dilute phase was achieved, which indicated that the dilute phase could be discharged without causing dye pollution. The extractive biodecolorization of three other triphenylmethane dyes was also examined in this system. The decolorization of malachite green and brilliant green was similar to that of crystal violet. Only ethyl violet achieved a poor decolorization rate because DN322p decolorized it via adsorption but did not convert it into its leuco form. This study provides potential application of biological treatment in triphenylmethane dye wastewater.

D Modeling of Components of a Garden by Using Point Cloud Data

NASA Astrophysics Data System (ADS)

Kumazakia, R.; Kunii, Y.

2016-06-01

Laser measurement is currently applied to several tasks such as plumbing management, road investigation through mobile mapping systems, and elevation model utilization through airborne LiDAR. Effective laser measurement methods have been well-documented in civil engineering, but few attempts have been made to establish equally effective methods in landscape engineering. By using point cloud data acquired through laser measurement, the aesthetic landscaping of Japanese gardens can be enhanced. This study focuses on simple landscape simulations for pruning and rearranging trees as well as rearranging rocks, lanterns, and other garden features by using point cloud data. However, such simulations lack concreteness. Therefore, this study considers the construction of a library of garden features extracted from point cloud data. The library would serve as a resource for creating new gardens and simulating gardens prior to conducting repairs. Extracted garden features are imported as 3ds Max objects, and realistic 3D models are generated by using a material editor system. As further work toward the publication of a 3D model library, file formats for tree crowns and trunks should be adjusted. Moreover, reducing the size of created models is necessary. Models created using point cloud data are informative because simply shaped garden features such as trees are often seen in the 3D industry.

Quantitative evaluation for small surface damage based on iterative difference and triangulation of 3D point cloud

NASA Astrophysics Data System (ADS)

Zhang, Yuyan; Guo, Quanli; Wang, Zhenchun; Yang, Degong

2018-03-01

This paper proposes a non-contact, non-destructive evaluation method for the surface damage of high-speed sliding electrical contact rails. The proposed method establishes a model of damage identification and calculation. A laser scanning system is built to obtain the 3D point cloud data of the rail surface. In order to extract the damage region of the rail surface, the 3D point cloud data are processed using iterative difference, nearest neighbours search and a data registration algorithm. The curvature of the point cloud data in the damage region is mapped to RGB color information, which can directly reflect the change trend of the curvature of the point cloud data in the damage region. The extracted damage region is divided into three prism elements by a method of triangulation. The volume and mass of a single element are calculated by the method of geometric segmentation. Finally, the total volume and mass of the damage region are obtained by the principle of superposition. The proposed method is applied to several typical injuries and the results are discussed. The experimental results show that the algorithm can identify damage shapes and calculate damage mass with milligram precision, which are useful for evaluating the damage in a further research stage.

Automatic pole-like object modeling via 3D part-based analysis of point cloud

NASA Astrophysics Data System (ADS)

He, Liu; Yang, Haoxiang; Huang, Yuchun

2016-10-01

Pole-like objects, including trees, lampposts and traffic signs, are indispensable part of urban infrastructure. With the advance of vehicle-based laser scanning (VLS), massive point cloud of roadside urban areas becomes applied in 3D digital city modeling. Based on the property that different pole-like objects have various canopy parts and similar trunk parts, this paper proposed the 3D part-based shape analysis to robustly extract, identify and model the pole-like objects. The proposed method includes: 3D clustering and recognition of trunks, voxel growing and part-based 3D modeling. After preprocessing, the trunk center is identified as the point that has local density peak and the largest minimum inter-cluster distance. Starting from the trunk centers, the remaining points are iteratively clustered to the same centers of their nearest point with higher density. To eliminate the noisy points, cluster border is refined by trimming boundary outliers. Then, candidate trunks are extracted based on the clustering results in three orthogonal planes by shape analysis. Voxel growing obtains the completed pole-like objects regardless of overlaying. Finally, entire trunk, branch and crown part are analyzed to obtain seven feature parameters. These parameters are utilized to model three parts respectively and get signal part-assembled 3D model. The proposed method is tested using the VLS-based point cloud of Wuhan University, China. The point cloud includes many kinds of trees, lampposts and other pole-like posters under different occlusions and overlaying. Experimental results show that the proposed method can extract the exact attributes and model the roadside pole-like objects efficiently.

Application of Micro-cloud point extraction for spectrophotometric determination of Malachite green, Crystal violet and Rhodamine B in aqueous samples

NASA Astrophysics Data System (ADS)

Ghasemi, Elham; Kaykhaii, Massoud

2016-07-01

A novel, green, simple and fast method was developed for spectrophotometric determination of Malachite green, Crystal violet, and Rhodamine B in water samples based on Micro-cloud Point extraction (MCPE) at room temperature. This is the first report on the application of MCPE on dyes. In this method, to reach the cloud point at room temperature, the MCPE procedure was carried out in brine using Triton X-114 as a non-ionic surfactant. The factors influencing the extraction efficiency were investigated and optimized. Under the optimized condition, calibration curves were found to be linear in the concentration range of 0.06-0.60 mg/L, 0.10-0.80 mg/L, and 0.03-0.30 mg/L with the enrichment factors of 29.26, 85.47 and 28.36, respectively for Malachite green, Crystal violet, and Rhodamine B. Limit of detections were between 2.2 and 5.1 μg/L.

Application of Micro-cloud point extraction for spectrophotometric determination of Malachite green, Crystal violet and Rhodamine B in aqueous samples.

PubMed

Ghasemi, Elham; Kaykhaii, Massoud

2016-07-05

A novel, green, simple and fast method was developed for spectrophotometric determination of Malachite green, Crystal violet, and Rhodamine B in water samples based on Micro-cloud Point extraction (MCPE) at room temperature. This is the first report on the application of MCPE on dyes. In this method, to reach the cloud point at room temperature, the MCPE procedure was carried out in brine using Triton X-114 as a non-ionic surfactant. The factors influencing the extraction efficiency were investigated and optimized. Under the optimized condition, calibration curves were found to be linear in the concentration range of 0.06-0.60mg/L, 0.10-0.80mg/L, and 0.03-0.30mg/L with the enrichment factors of 29.26, 85.47 and 28.36, respectively for Malachite green, Crystal violet, and Rhodamine B. Limit of detections were between 2.2 and 5.1μg/L. Copyright © 2016 Elsevier B.V. All rights reserved.

Space Subdivision in Indoor Mobile Laser Scanning Point Clouds Based on Scanline Analysis.

PubMed

Zheng, Yi; Peter, Michael; Zhong, Ruofei; Oude Elberink, Sander; Zhou, Quan

2018-06-05

Indoor space subdivision is an important aspect of scene analysis that provides essential information for many applications, such as indoor navigation and evacuation route planning. Until now, most proposed scene understanding algorithms have been based on whole point clouds, which has led to complicated operations, high computational loads and low processing speed. This paper presents novel methods to efficiently extract the location of openings (e.g., doors and windows) and to subdivide space by analyzing scanlines. An opening detection method is demonstrated that analyses the local geometric regularity in scanlines to refine the extracted opening. Moreover, a space subdivision method based on the extracted openings and the scanning system trajectory is described. Finally, the opening detection and space subdivision results are saved as point cloud labels which will be used for further investigations. The method has been tested on a real dataset collected by ZEB-REVO. The experimental results validate the completeness and correctness of the proposed method for different indoor environment and scanning paths.

Smart Point Cloud: Definition and Remaining Challenges

NASA Astrophysics Data System (ADS)

Poux, F.; Hallot, P.; Neuville, R.; Billen, R.

2016-10-01

Dealing with coloured point cloud acquired from terrestrial laser scanner, this paper identifies remaining challenges for a new data structure: the smart point cloud. This concept arises with the statement that massive and discretized spatial information from active remote sensing technology is often underused due to data mining limitations. The generalisation of point cloud data associated with the heterogeneity and temporality of such datasets is the main issue regarding structure, segmentation, classification, and interaction for an immediate understanding. We propose to use both point cloud properties and human knowledge through machine learning to rapidly extract pertinent information, using user-centered information (smart data) rather than raw data. A review of feature detection, machine learning frameworks and database systems indexed both for mining queries and data visualisation is studied. Based on existing approaches, we propose a new 3-block flexible framework around device expertise, analytic expertise and domain base reflexion. This contribution serves as the first step for the realisation of a comprehensive smart point cloud data structure.

Physicochemical and Antioxidant Properties of Rice Bran Oils Produced from Colored Rice Using Different Extraction Methods.

PubMed

Mingyai, Sukanya; Kettawan, Aikkarach; Srikaeo, Khongsak; Singanusong, Riantong

2017-06-01

This study investigated the physicochemical and antioxidant properties of rice bran oil (RBO) produced from the bran of three rice varities; Khao Dawk Mali 105 (white rice), Red Jasmine rice (red rice) and Hom-nin rice (black rice) using three extraction methods including cold-press extraction (CPE), solvent extraction (SE) and supercritical CO 2 extraction (SC-CO 2 ). Yields, color, acid value (AV), free fatty acid (FFA), peroxide value (PV), iodine value (IV), total phenolic compound (TPC), γ-oryzanol, α-tocopherol and fatty acid profile were analyzed. It was found that the yields obtained from SE, SC-CO 2 and CPE extractions were 17.35-20.19%, 14.76-18.16% and 3.22-6.22%, respectively. The RBO from the bran of red and black rice samples exhibited high antioxidant activities. They also contained higher amount of γ-oryzanol and α-tocopherol than those of white rice sample. In terms of extraction methods, SC-CO 2 provided better qualities of RBO as evidenced by their physicochemical and antioxidant properties. This study found that RBO produced from the bran of black rice samples using SC-CO 2 extraction method showed the best physicochemical and antioxidant properties.

A building extraction approach for Airborne Laser Scanner data utilizing the Object Based Image Analysis paradigm

NASA Astrophysics Data System (ADS)

Tomljenovic, Ivan; Tiede, Dirk; Blaschke, Thomas

2016-10-01

In the past two decades Object-Based Image Analysis (OBIA) established itself as an efficient approach for the classification and extraction of information from remote sensing imagery and, increasingly, from non-image based sources such as Airborne Laser Scanner (ALS) point clouds. ALS data is represented in the form of a point cloud with recorded multiple returns and intensities. In our work, we combined OBIA with ALS point cloud data in order to identify and extract buildings as 2D polygons representing roof outlines in a top down mapping approach. We performed rasterization of the ALS data into a height raster for the purpose of the generation of a Digital Surface Model (DSM) and a derived Digital Elevation Model (DEM). Further objects were generated in conjunction with point statistics from the linked point cloud. With the use of class modelling methods, we generated the final target class of objects representing buildings. The approach was developed for a test area in Biberach an der Riß (Germany). In order to point out the possibilities of the adaptation-free transferability to another data set, the algorithm has been applied ;as is; to the ISPRS Benchmarking data set of Toronto (Canada). The obtained results show high accuracies for the initial study area (thematic accuracies of around 98%, geometric accuracy of above 80%). The very high performance within the ISPRS Benchmark without any modification of the algorithm and without any adaptation of parameters is particularly noteworthy.

Cinnamon polyphenol extract regulates tristetraprolin and related gene expression in mouse adipocytes

USDA-ARS?s Scientific Manuscript database

Cinnamon (Cinnamomum verum) has been widely used in spices, flavoring agents, and preservatives. Cinnamon polyphenol extract (CPE) may be important in the alleviation of chronic diseases, but the molecular evidence is not substantial. Tristetraprolin (TTP) family proteins have anti-inflammatory ef...

Lack of evidence for contact sensitization by Pfiesteria extract.

PubMed

Patterson, Rachel M; Noga, Edward; Germolec, Dori

2007-07-01

Members of the estuarine dinoflagellate genus Pfiesteria are reported to have been responsible for massive fish kills in the southeastern United States. Some reports suggest that exposure to waters having Pfiesteria blooms or occupation-related exposure might result in Pfiesteria-induced dermal irritation and inflammation. Although the toxin has not been isolated and purified, the original data suggested both hydrophilic and hydrophobic toxic components. Some investigators propose that dermonecrotic properties are associated with a hydrophobic fraction. A bioactive C18-bound putative toxin (CPE) extracted from Pfiesteria-laden aquarium water during active fish-killing conditions was examined in the present study to evaluate its potential to produce inflammation and dermal sensitization and to determine whether the inflammation and dermatitis reported in early human exposure studies were allergic or irritant in nature. This fraction was cytotoxic to mouse Neuro-2A cells and primary human epidermal keratinocytes (NHEK) at a concentration of 1 mg/mL. Balb/C mice exposed to 50-200% CPE by skin painting exhibited a 6-10% increase in ear swelling relative to vehicle-treated mice in a primary irritancy assay. There was no increase in lymph node cell proliferation as measured using the local lymph node assay. Exposure to CPE in culture up-regulated interleukin-8 in NHEK, whereas granulocyte macrophage-colony-stimulating factor and tumor necrosis factor alpha were only minimally altered. This study suggests that CPE is cytotoxic to keratinocytes in culture at high concentrations and that it induces mild, localized irritation but not dermal sensitization.

Drawing and Landscape Simulation for Japanese Garden by Using Terrestrial Laser Scanner

NASA Astrophysics Data System (ADS)

Kumazaki, R.; Kunii, Y.

2015-05-01

Recently, many laser scanners are applied for various measurement fields. This paper investigates that it was useful to use the terrestrial laser scanner in the field of landscape architecture and examined a usage in Japanese garden. As for the use of 3D point cloud data in the Japanese garden, it is the visual use such as the animations. Therefore, some applications of the 3D point cloud data was investigated that are as follows. Firstly, ortho image of the Japanese garden could be outputted for the 3D point cloud data. Secondly, contour lines of the Japanese garden also could be extracted, and drawing was became possible. Consequently, drawing of Japanese garden was realized more efficiency due to achievement of laborsaving. Moreover, operation of the measurement and drawing could be performed without technical skills, and any observers can be operated. Furthermore, 3D point cloud data could be edited, and some landscape simulations that extraction and placement of tree or some objects were became possible. As a result, it can be said that the terrestrial laser scanner will be applied in landscape architecture field more widely.

Facets : a Cloudcompare Plugin to Extract Geological Planes from Unstructured 3d Point Clouds

NASA Astrophysics Data System (ADS)

Dewez, T. J. B.; Girardeau-Montaut, D.; Allanic, C.; Rohmer, J.

2016-06-01

Geological planar facets (stratification, fault, joint…) are key features to unravel the tectonic history of rock outcrop or appreciate the stability of a hazardous rock cliff. Measuring their spatial attitude (dip and strike) is generally performed by hand with a compass/clinometer, which is time consuming, requires some degree of censoring (i.e. refusing to measure some features judged unimportant at the time), is not always possible for fractures higher up on the outcrop and is somewhat hazardous. 3D virtual geological outcrop hold the potential to alleviate these issues. Efficiently segmenting massive 3D point clouds into individual planar facets, inside a convenient software environment was lacking. FACETS is a dedicated plugin within CloudCompare v2.6.2 (http://cloudcompare.org/ ) implemented to perform planar facet extraction, calculate their dip and dip direction (i.e. azimuth of steepest decent) and report the extracted data in interactive stereograms. Two algorithms perform the segmentation: Kd-Tree and Fast Marching. Both divide the point cloud into sub-cells, then compute elementary planar objects and aggregate them progressively according to a planeity threshold into polygons. The boundaries of the polygons are adjusted around segmented points with a tension parameter, and the facet polygons can be exported as 3D polygon shapefiles towards third party GIS software or simply as ASCII comma separated files. One of the great features of FACETS is the capability to explore planar objects but also 3D points with normals with the stereogram tool. Poles can be readily displayed, queried and manually segmented interactively. The plugin blends seamlessly into CloudCompare to leverage all its other 3D point cloud manipulation features. A demonstration of the tool is presented to illustrate these different features. While designed for geological applications, FACETS could be more widely applied to any planar objects.

Instantaneous Coastline Extraction from LIDAR Point Cloud and High Resolution Remote Sensing Imagery

NASA Astrophysics Data System (ADS)

Li, Y.; Zhoing, L.; Lai, Z.; Gan, Z.

2018-04-01

A new method was proposed for instantaneous waterline extraction in this paper, which combines point cloud geometry features and image spectral characteristics of the coastal zone. The proposed method consists of follow steps: Mean Shift algorithm is used to segment the coastal zone of high resolution remote sensing images into small regions containing semantic information;Region features are extracted by integrating LiDAR data and the surface area of the image; initial waterlines are extracted by α-shape algorithm; a region growing algorithm with is taking into coastline refinement, with a growth rule integrating the intensity and topography of LiDAR data; moothing the coastline. Experiments are conducted to demonstrate the efficiency of the proposed method.

Hierarchical Regularization of Polygons for Photogrammetric Point Clouds of Oblique Images

NASA Astrophysics Data System (ADS)

Xie, L.; Hu, H.; Zhu, Q.; Wu, B.; Zhang, Y.

2017-05-01

Despite the success of multi-view stereo (MVS) reconstruction from massive oblique images in city scale, only point clouds and triangulated meshes are available from existing MVS pipelines, which are topologically defect laden, free of semantical information and hard to edit and manipulate interactively in further applications. On the other hand, 2D polygons and polygonal models are still the industrial standard. However, extraction of the 2D polygons from MVS point clouds is still a non-trivial task, given the fact that the boundaries of the detected planes are zigzagged and regularities, such as parallel and orthogonal, cannot preserve. Aiming to solve these issues, this paper proposes a hierarchical polygon regularization method for the photogrammetric point clouds from existing MVS pipelines, which comprises of local and global levels. After boundary points extraction, e.g. using alpha shapes, the local level is used to consolidate the original points, by refining the orientation and position of the points using linear priors. The points are then grouped into local segments by forward searching. In the global level, regularities are enforced through a labeling process, which encourage the segments share the same label and the same label represents segments are parallel or orthogonal. This is formulated as Markov Random Field and solved efficiently. Preliminary results are made with point clouds from aerial oblique images and compared with two classical regularization methods, which have revealed that the proposed method are more powerful in abstracting a single building and is promising for further 3D polygonal model reconstruction and GIS applications.

Scan-To Output Validation: Towards a Standardized Geometric Quality Assessment of Building Information Models Based on Point Clouds

NASA Astrophysics Data System (ADS)

Bonduel, M.; Bassier, M.; Vergauwen, M.; Pauwels, P.; Klein, R.

2017-11-01

The use of Building Information Modeling (BIM) for existing buildings based on point clouds is increasing. Standardized geometric quality assessment of the BIMs is needed to make them more reliable and thus reusable for future users. First, available literature on the subject is studied. Next, an initial proposal for a standardized geometric quality assessment is presented. Finally, this method is tested and evaluated with a case study. The number of specifications on BIM relating to existing buildings is limited. The Levels of Accuracy (LOA) specification of the USIBD provides definitions and suggestions regarding geometric model accuracy, but lacks a standardized assessment method. A deviation analysis is found to be dependent on (1) the used mathematical model, (2) the density of the point clouds and (3) the order of comparison. Results of the analysis can be graphical and numerical. An analysis on macro (building) and micro (BIM object) scale is necessary. On macro scale, the complete model is compared to the original point cloud and vice versa to get an overview of the general model quality. The graphical results show occluded zones and non-modeled objects respectively. Colored point clouds are derived from this analysis and integrated in the BIM. On micro scale, the relevant surface parts are extracted per BIM object and compared to the complete point cloud. Occluded zones are extracted based on a maximum deviation. What remains is classified according to the LOA specification. The numerical results are integrated in the BIM with the use of object parameters.

Detection and Classification of Pole-Like Objects from Mobile Mapping Data

NASA Astrophysics Data System (ADS)

Fukano, K.; Masuda, H.

2015-08-01

Laser scanners on a vehicle-based mobile mapping system can capture 3D point-clouds of roads and roadside objects. Since roadside objects have to be maintained periodically, their 3D models are useful for planning maintenance tasks. In our previous work, we proposed a method for detecting cylindrical poles and planar plates in a point-cloud. However, it is often required to further classify pole-like objects into utility poles, streetlights, traffic signals and signs, which are managed by different organizations. In addition, our previous method may fail to extract low pole-like objects, which are often observed in urban residential areas. In this paper, we propose new methods for extracting and classifying pole-like objects. In our method, we robustly extract a wide variety of poles by converting point-clouds into wireframe models and calculating cross-sections between wireframe models and horizontal cutting planes. For classifying pole-like objects, we subdivide a pole-like object into five subsets by extracting poles and planes, and calculate feature values of each subset. Then we apply a supervised machine learning method using feature variables of subsets. In our experiments, our method could achieve excellent results for detection and classification of pole-like objects.

Highly Cross-Linked Polyethylene Reduces Osteolysis Incidence and Wear-Related Reoperation Rate in Cementless Total Hip Arthroplasty Compared With Conventional Polyethylene at a Mean 12-Year Follow-Up.

PubMed

Tsukamoto, Manabu; Mori, Toshiharu; Ohnishi, Hideo; Uchida, Soshi; Sakai, Akinori

2017-12-01

A number of studies on total hip arthroplasty have compared highly cross-linked polyethylene (HXLPE) with conventional polyethylene (CPE) liners beyond 10 years. However, the impact of HXLPE on the wear-related reoperation rate is unclear. The purpose of this study was to evaluate the clinical advantage of using a single manufacturer's HXLPE in terms of reducing the reoperation rate. The study was a follow-up retrospective cohort study over a mean of 12 years that examined patients aged 45-70 years with cementless total hip arthroplasty using a 26-mm-diameter cobalt-chromium head. Sixty-seven patients (79 hips; HXLPE group = 41 hips, CPE group = 38 hips) were evaluated for a minimum 10-year follow-up. Kaplan-Meier survival analysis was performed, with wear-related reoperations and radiographic osteolysis serving as the end points. The polyethylene wear rate was also assessed. The mean 12-year follow-up rates of survivorship that were evaluated using wear-related reoperations as the end point were 100% and 91.4% in the HXLPE and CPE groups, respectively (P = .007), and the mean 12-year follow-up rates of survivorship with osteolysis as the end point were 100% and 36.2%, respectively (P < .001). Compared with the CPE group, the HXLPE group presented a significantly reduced wear rate (HXLPE group, 0.035 mm/y; CPE group, 0.118 mm/y). A unique strength of this study is that we assessed a single manufacturer's HXLPE while keeping most other implant parameters uniform. This study reveals the clinical advantage of using a single manufacturer's HXLPE in terms of a reduced wear-related reoperation rate at a mean 12-year follow-up. Copyright © 2017 Elsevier Inc. All rights reserved.

Outcrop-scale fracture trace identification using surface roughness derived from a high-density point cloud

NASA Astrophysics Data System (ADS)

Okyay, U.; Glennie, C. L.; Khan, S.

2017-12-01

Owing to the advent of terrestrial laser scanners (TLS), high-density point cloud data has become increasingly available to the geoscience research community. Research groups have started producing their own point clouds for various applications, gradually shifting their emphasis from obtaining the data towards extracting more and meaningful information from the point clouds. Extracting fracture properties from three-dimensional data in a (semi-)automated manner has been an active area of research in geosciences. Several studies have developed various processing algorithms for extracting only planar surfaces. In comparison, (semi-)automated identification of fracture traces at the outcrop scale, which could be used for mapping fracture distribution have not been investigated frequently. Understanding the spatial distribution and configuration of natural fractures is of particular importance, as they directly influence fluid-flow through the host rock. Surface roughness, typically defined as the deviation of a natural surface from a reference datum, has become an important metric in geoscience research, especially with the increasing density and accuracy of point clouds. In the study presented herein, a surface roughness model was employed to identify fracture traces and their distribution on an ophiolite outcrop in Oman. Surface roughness calculations were performed using orthogonal distance regression over various grid intervals. The results demonstrated that surface roughness could identify outcrop-scale fracture traces from which fracture distribution and density maps can be generated. However, considering outcrop conditions and properties and the purpose of the application, the definition of an adequate grid interval for surface roughness model and selection of threshold values for distribution maps are not straightforward and require user intervention and interpretation.

Ion-pair cloud-point extraction: a new method for the determination of water-soluble vitamins in plasma and urine.

PubMed

Heydari, Rouhollah; Elyasi, Najmeh S

2014-10-01

A novel, simple, and effective ion-pair cloud-point extraction coupled with a gradient high-performance liquid chromatography method was developed for determination of thiamine (vitamin B1 ), niacinamide (vitamin B3 ), pyridoxine (vitamin B6 ), and riboflavin (vitamin B2 ) in plasma and urine samples. The extraction and separation of vitamins were achieved based on an ion-pair formation approach between these ionizable analytes and 1-heptanesulfonic acid sodium salt as an ion-pairing agent. Influential variables on the ion-pair cloud-point extraction efficiency, such as the ion-pairing agent concentration, ionic strength, pH, volume of Triton X-100, extraction temperature, and incubation time have been fully evaluated and optimized. Water-soluble vitamins were successfully extracted by 1-heptanesulfonic acid sodium salt (0.2% w/v) as ion-pairing agent with Triton X-100 (4% w/v) as surfactant phase at 50°C for 10 min. The calibration curves showed good linearity (r(2) > 0.9916) and precision in the concentration ranges of 1-50 μg/mL for thiamine and niacinamide, 5-100 μg/mL for pyridoxine, and 0.5-20 μg/mL for riboflavin. The recoveries were in the range of 78.0-88.0% with relative standard deviations ranging from 6.2 to 8.2%. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Automatic Recognition of Indoor Navigation Elements from Kinect Point Clouds

NASA Astrophysics Data System (ADS)

Zeng, L.; Kang, Z.

2017-09-01

This paper realizes automatically the navigating elements defined by indoorGML data standard - door, stairway and wall. The data used is indoor 3D point cloud collected by Kinect v2 launched in 2011 through the means of ORB-SLAM. By contrast, it is cheaper and more convenient than lidar, but the point clouds also have the problem of noise, registration error and large data volume. Hence, we adopt a shape descriptor - histogram of distances between two randomly chosen points, proposed by Osada and merges with other descriptor - in conjunction with random forest classifier to recognize the navigation elements (door, stairway and wall) from Kinect point clouds. This research acquires navigation elements and their 3-d location information from each single data frame through segmentation of point clouds, boundary extraction, feature calculation and classification. Finally, this paper utilizes the acquired navigation elements and their information to generate the state data of the indoor navigation module automatically. The experimental results demonstrate a high recognition accuracy of the proposed method.

Cloud point extraction of Δ9-tetrahydrocannabinol from cannabis resin.

PubMed

Ameur, S; Haddou, B; Derriche, Z; Canselier, J P; Gourdon, C

2013-04-01

A cloud point extraction coupled with high performance liquid chromatography (HPLC/UV) method was developed for the determination of Δ(9)-tetrahydrocannabinol (THC) in micellar phase. The nonionic surfactant "Dowfax 20B102" was used to extract and pre-concentrate THC from cannabis resin, prior to its determination with a HPLC-UV system (diode array detector) with isocratic elution. The parameters and variables affecting the extraction were investigated. Under optimum conditions (1 wt.% Dowfax 20B102, 1 wt.% Na2SO4, T = 318 K, t = 30 min), this method yielded a quite satisfactory recovery rate (~81 %). The limit of detection was 0.04 μg mL(-1), and the relative standard deviation was less than 2 %. Compared with conventional solid-liquid extraction, this new method avoids the use of volatile organic solvents, therefore is environmentally safer.

Towards semi-automatic rock mass discontinuity orientation and set analysis from 3D point clouds

NASA Astrophysics Data System (ADS)

Guo, Jiateng; Liu, Shanjun; Zhang, Peina; Wu, Lixin; Zhou, Wenhui; Yu, Yinan

2017-06-01

Obtaining accurate information on rock mass discontinuities for deformation analysis and the evaluation of rock mass stability is important. Obtaining measurements for high and steep zones with the traditional compass method is difficult. Photogrammetry, three-dimensional (3D) laser scanning and other remote sensing methods have gradually become mainstream methods. In this study, a method that is based on a 3D point cloud is proposed to semi-automatically extract rock mass structural plane information. The original data are pre-treated prior to segmentation by removing outlier points. The next step is to segment the point cloud into different point subsets. Various parameters, such as the normal, dip/direction and dip, can be calculated for each point subset after obtaining the equation of the best fit plane for the relevant point subset. A cluster analysis (a point subset that satisfies some conditions and thus forms a cluster) is performed based on the normal vectors by introducing the firefly algorithm (FA) and the fuzzy c-means (FCM) algorithm. Finally, clusters that belong to the same discontinuity sets are merged and coloured for visualization purposes. A prototype system is developed based on this method to extract the points of the rock discontinuity from a 3D point cloud. A comparison with existing software shows that this method is feasible. This method can provide a reference for rock mechanics, 3D geological modelling and other related fields.

Lack of Evidence for Contact Sensitization by Pfiesteria Extract

PubMed Central

Patterson, Rachel M.; Noga, Edward; Germolec, Dori

2007-01-01

Background Members of the estuarine dinoflagellate genus Pfiesteria are reported to have been responsible for massive fish kills in the southeastern United States. Some reports suggest that exposure to waters having Pfiesteria blooms or occupation-related exposure might result in Pfiesteria-induced dermal irritation and inflammation. Although the toxin has not been isolated and purified, the original data suggested both hydrophilic and hydrophobic toxic components. Some investigators propose that dermonecrotic properties are associated with a hydrophobic fraction. Objectives A bioactive C18-bound putative toxin (CPE) extracted from Pfiesteria-laden aquarium water during active fish-killing conditions was examined in the present study to evaluate its potential to produce inflammation and dermal sensitization and to determine whether the inflammation and dermatitis reported in early human exposure studies were allergic or irritant in nature. Results This fraction was cytotoxic to mouse Neuro-2A cells and primary human epidermal keratinocytes (NHEK) at a concentration of 1 mg/mL. Balb/C mice exposed to 50–200% CPE by skin painting exhibited a 6–10% increase in ear swelling relative to vehicle-treated mice in a primary irritancy assay. There was no increase in lymph node cell proliferation as measured using the local lymph node assay. Exposure to CPE in culture up-regulated interleukin-8 in NHEK, whereas granulocyte macrophage–colony-stimulating factor and tumor necrosis factor α were only minimally altered. Conclusions This study suggests that CPE is cytotoxic to keratinocytes in culture at high concentrations and that it induces mild, localized irritation but not dermal sensitization. PMID:17637917

a Voxel-Based Filtering Algorithm for Mobile LIDAR Data

NASA Astrophysics Data System (ADS)

Qin, H.; Guan, G.; Yu, Y.; Zhong, L.

2018-04-01

This paper presents a stepwise voxel-based filtering algorithm for mobile LiDAR data. In the first step, to improve computational efficiency, mobile LiDAR points, in xy-plane, are first partitioned into a set of two-dimensional (2-D) blocks with a given block size, in each of which all laser points are further organized into an octree partition structure with a set of three-dimensional (3-D) voxels. Then, a voxel-based upward growing processing is performed to roughly separate terrain from non-terrain points with global and local terrain thresholds. In the second step, the extracted terrain points are refined by computing voxel curvatures. This voxel-based filtering algorithm is comprehensively discussed in the analyses of parameter sensitivity and overall performance. An experimental study performed on multiple point cloud samples, collected by different commercial mobile LiDAR systems, showed that the proposed algorithm provides a promising solution to terrain point extraction from mobile point clouds.

Determination of Cd in urine by cloud point extraction-tungsten coil atomic absorption spectrometry.

PubMed

Donati, George L; Pharr, Kathryn E; Calloway, Clifton P; Nóbrega, Joaquim A; Jones, Bradley T

2008-09-15

Cadmium concentrations in human urine are typically at or below the 1 microgL(-1) level, so only a handful of techniques may be appropriate for this application. These include sophisticated methods such as graphite furnace atomic absorption spectrometry and inductively coupled plasma mass spectrometry. While tungsten coil atomic absorption spectrometry is a simpler and less expensive technique, its practical detection limits often prohibit the detection of Cd in normal urine samples. In addition, the nature of the urine matrix often necessitates accurate background correction techniques, which would add expense and complexity to the tungsten coil instrument. This manuscript describes a cloud point extraction method that reduces matrix interference while preconcentrating Cd by a factor of 15. Ammonium pyrrolidinedithiocarbamate and Triton X-114 are used as complexing agent and surfactant, respectively, in the extraction procedure. Triton X-114 forms an extractant coacervate surfactant-rich phase that is denser than water, so the aqueous supernatant is easily removed leaving the metal-containing surfactant layer intact. A 25 microL aliquot of this preconcentrated sample is placed directly onto the tungsten coil for analysis. The cloud point extraction procedure allows for simple background correction based either on the measurement of absorption at a nearby wavelength, or measurement of absorption at a time in the atomization step immediately prior to the onset of the Cd signal. Seven human urine samples are analyzed by this technique and the results are compared to those found by the inductively coupled plasma mass spectrometry analysis of the same samples performed at a different institution. The limit of detection for Cd in urine is 5 ngL(-1) for cloud point extraction tungsten coil atomic absorption spectrometry. The accuracy of the method is determined with a standard reference material (toxic metals in freeze-dried urine) and the determined values agree with the reported levels at the 95% confidence level.

Traffic sign detection in MLS acquired point clouds for geometric and image-based semantic inventory

NASA Astrophysics Data System (ADS)

Soilán, Mario; Riveiro, Belén; Martínez-Sánchez, Joaquín; Arias, Pedro

2016-04-01

Nowadays, mobile laser scanning has become a valid technology for infrastructure inspection. This technology permits collecting accurate 3D point clouds of urban and road environments and the geometric and semantic analysis of data became an active research topic in the last years. This paper focuses on the detection of vertical traffic signs in 3D point clouds acquired by a LYNX Mobile Mapper system, comprised of laser scanning and RGB cameras. Each traffic sign is automatically detected in the LiDAR point cloud, and its main geometric parameters can be automatically extracted, therefore aiding the inventory process. Furthermore, the 3D position of traffic signs are reprojected on the 2D images, which are spatially and temporally synced with the point cloud. Image analysis allows for recognizing the traffic sign semantics using machine learning approaches. The presented method was tested in road and urban scenarios in Galicia (Spain). The recall results for traffic sign detection are close to 98%, and existing false positives can be easily filtered after point cloud projection. Finally, the lack of a large, publicly available Spanish traffic sign database is pointed out.

Semantic Segmentation of Building Elements Using Point Cloud Hashing

NASA Astrophysics Data System (ADS)

Chizhova, M.; Gurianov, A.; Hess, M.; Luhmann, T.; Brunn, A.; Stilla, U.

2018-05-01

For the interpretation of point clouds, the semantic definition of extracted segments from point clouds or images is a common problem. Usually, the semantic of geometrical pre-segmented point cloud elements are determined using probabilistic networks and scene databases. The proposed semantic segmentation method is based on the psychological human interpretation of geometric objects, especially on fundamental rules of primary comprehension. Starting from these rules the buildings could be quite well and simply classified by a human operator (e.g. architect) into different building types and structural elements (dome, nave, transept etc.), including particular building parts which are visually detected. The key part of the procedure is a novel method based on hashing where point cloud projections are transformed into binary pixel representations. A segmentation approach released on the example of classical Orthodox churches is suitable for other buildings and objects characterized through a particular typology in its construction (e.g. industrial objects in standardized enviroments with strict component design allowing clear semantic modelling).

Image-Based Airborne LiDAR Point Cloud Encoding for 3d Building Model Retrieval

NASA Astrophysics Data System (ADS)

Chen, Yi-Chen; Lin, Chao-Hung

2016-06-01

With the development of Web 2.0 and cyber city modeling, an increasing number of 3D models have been available on web-based model-sharing platforms with many applications such as navigation, urban planning, and virtual reality. Based on the concept of data reuse, a 3D model retrieval system is proposed to retrieve building models similar to a user-specified query. The basic idea behind this system is to reuse these existing 3D building models instead of reconstruction from point clouds. To efficiently retrieve models, the models in databases are compactly encoded by using a shape descriptor generally. However, most of the geometric descriptors in related works are applied to polygonal models. In this study, the input query of the model retrieval system is a point cloud acquired by Light Detection and Ranging (LiDAR) systems because of the efficient scene scanning and spatial information collection. Using Point clouds with sparse, noisy, and incomplete sampling as input queries is more difficult than that by using 3D models. Because that the building roof is more informative than other parts in the airborne LiDAR point cloud, an image-based approach is proposed to encode both point clouds from input queries and 3D models in databases. The main goal of data encoding is that the models in the database and input point clouds can be consistently encoded. Firstly, top-view depth images of buildings are generated to represent the geometry surface of a building roof. Secondly, geometric features are extracted from depth images based on height, edge and plane of building. Finally, descriptors can be extracted by spatial histograms and used in 3D model retrieval system. For data retrieval, the models are retrieved by matching the encoding coefficients of point clouds and building models. In experiments, a database including about 900,000 3D models collected from the Internet is used for evaluation of data retrieval. The results of the proposed method show a clear superiority over related methods.

In vivo evaluation of the antiviral activity of Cajanus cajan on measles virus.

PubMed

Nwodo, U U; Ngene, A A; Iroegbu, C U; Onyedikachi, O A L; Chigor, V N; Okoh, A I

2011-09-01

Cajanus cajan, a tropical shrub, serves as source of food and traditional medicines. The evaluation of aqueous and ethanol extracts for activity against measles virus and toxicity to embryonated chicken eggs was carried out in this study. In vivo and in vitro assay techniques using embryonated chicken eggs and tissue culture (Hep-2 cell lines) as media for both virus cultivation and anti-virus assay showed that a hot-water extract yielded higher activity against measles virus. The hot-water extract of the stem yielded a Log(2) titre of 0.1 for the in vivo assay and an inhibition of cytopathic effect (CPE) in Hep-2 cells by 100% for the in vitro assay. At all concentrations of the extracts, there was a lowering of virus concentration (p = 0.05), indicated by hemagglutination (HA) titration, which is the advantage of HA titration over the tissue culture technique using CPE. This study validates embryonated chicken eggs as suitable media for anti-virus assay and the use of C. cajan in the treatment of some diseases of viral origin.

Tunnel Point Cloud Filtering Method Based on Elliptic Cylindrical Model

NASA Astrophysics Data System (ADS)

Zhua, Ningning; Jiaa, Yonghong; Luo, Lun

2016-06-01

The large number of bolts and screws that attached to the subway shield ring plates, along with the great amount of accessories of metal stents and electrical equipments mounted on the tunnel walls, make the laser point cloud data include lots of non-tunnel section points (hereinafter referred to as non-points), therefore affecting the accuracy for modeling and deformation monitoring. This paper proposed a filtering method for the point cloud based on the elliptic cylindrical model. The original laser point cloud data was firstly projected onto a horizontal plane, and a searching algorithm was given to extract the edging points of both sides, which were used further to fit the tunnel central axis. Along the axis the point cloud was segmented regionally, and then fitted as smooth elliptic cylindrical surface by means of iteration. This processing enabled the automatic filtering of those inner wall non-points. Experiments of two groups showed coincident results, that the elliptic cylindrical model based method could effectively filter out the non-points, and meet the accuracy requirements for subway deformation monitoring. The method provides a new mode for the periodic monitoring of tunnel sections all-around deformation in subways routine operation and maintenance.

Rapid, semi-automatic fracture and contact mapping for point clouds, images and geophysical data

NASA Astrophysics Data System (ADS)

Thiele, Samuel T.; Grose, Lachlan; Samsu, Anindita; Micklethwaite, Steven; Vollgger, Stefan A.; Cruden, Alexander R.

2017-12-01

The advent of large digital datasets from unmanned aerial vehicle (UAV) and satellite platforms now challenges our ability to extract information across multiple scales in a timely manner, often meaning that the full value of the data is not realised. Here we adapt a least-cost-path solver and specially tailored cost functions to rapidly interpolate structural features between manually defined control points in point cloud and raster datasets. We implement the method in the geographic information system QGIS and the point cloud and mesh processing software CloudCompare. Using these implementations, the method can be applied to a variety of three-dimensional (3-D) and two-dimensional (2-D) datasets, including high-resolution aerial imagery, digital outcrop models, digital elevation models (DEMs) and geophysical grids. We demonstrate the algorithm with four diverse applications in which we extract (1) joint and contact patterns in high-resolution orthophotographs, (2) fracture patterns in a dense 3-D point cloud, (3) earthquake surface ruptures of the Greendale Fault associated with the Mw7.1 Darfield earthquake (New Zealand) from high-resolution light detection and ranging (lidar) data, and (4) oceanic fracture zones from bathymetric data of the North Atlantic. The approach improves the consistency of the interpretation process while retaining expert guidance and achieves significant improvements (35-65 %) in digitisation time compared to traditional methods. Furthermore, it opens up new possibilities for data synthesis and can quantify the agreement between datasets and an interpretation.

Classification of Aerial Photogrammetric 3d Point Clouds

NASA Astrophysics Data System (ADS)

Becker, C.; Häni, N.; Rosinskaya, E.; d'Angelo, E.; Strecha, C.

2017-05-01

We present a powerful method to extract per-point semantic class labels from aerial photogrammetry data. Labelling this kind of data is important for tasks such as environmental modelling, object classification and scene understanding. Unlike previous point cloud classification methods that rely exclusively on geometric features, we show that incorporating color information yields a significant increase in accuracy in detecting semantic classes. We test our classification method on three real-world photogrammetry datasets that were generated with Pix4Dmapper Pro, and with varying point densities. We show that off-the-shelf machine learning techniques coupled with our new features allow us to train highly accurate classifiers that generalize well to unseen data, processing point clouds containing 10 million points in less than 3 minutes on a desktop computer.

Continuously Deformation Monitoring of Subway Tunnel Based on Terrestrial Point Clouds

NASA Astrophysics Data System (ADS)

Kang, Z.; Tuo, L.; Zlatanova, S.

2012-07-01

The deformation monitoring of subway tunnel is of extraordinary necessity. Therefore, a method for deformation monitoring based on terrestrial point clouds is proposed in this paper. First, the traditional adjacent stations registration is replaced by sectioncontrolled registration, so that the common control points can be used by each station and thus the error accumulation avoided within a section. Afterwards, the central axis of the subway tunnel is determined through RANSAC (Random Sample Consensus) algorithm and curve fitting. Although with very high resolution, laser points are still discrete and thus the vertical section is computed via the quadric fitting of the vicinity of interest, instead of the fitting of the whole model of a subway tunnel, which is determined by the intersection line rotated about the central axis of tunnel within a vertical plane. The extraction of the vertical section is then optimized using RANSAC for the purpose of filtering out noises. Based on the extracted vertical sections, the volume of tunnel deformation is estimated by the comparison between vertical sections extracted at the same position from different epochs of point clouds. Furthermore, the continuously extracted vertical sections are deployed to evaluate the convergent tendency of the tunnel. The proposed algorithms are verified using real datasets in terms of accuracy and computation efficiency. The experimental result of fitting accuracy analysis shows the maximum deviation between interpolated point and real point is 1.5 mm, and the minimum one is 0.1 mm; the convergent tendency of the tunnel was detected by the comparison of adjacent fitting radius. The maximum error is 6 mm, while the minimum one is 1 mm. The computation cost of vertical section abstraction is within 3 seconds/section, which proves high efficiency..

Automated extraction and analysis of rock discontinuity characteristics from 3D point clouds

NASA Astrophysics Data System (ADS)

Bianchetti, Matteo; Villa, Alberto; Agliardi, Federico; Crosta, Giovanni B.

2016-04-01

A reliable characterization of fractured rock masses requires an exhaustive geometrical description of discontinuities, including orientation, spacing, and size. These are required to describe discontinuum rock mass structure, perform Discrete Fracture Network and DEM modelling, or provide input for rock mass classification or equivalent continuum estimate of rock mass properties. Although several advanced methodologies have been developed in the last decades, a complete characterization of discontinuity geometry in practice is still challenging, due to scale-dependent variability of fracture patterns and difficult accessibility to large outcrops. Recent advances in remote survey techniques, such as terrestrial laser scanning and digital photogrammetry, allow a fast and accurate acquisition of dense 3D point clouds, which promoted the development of several semi-automatic approaches to extract discontinuity features. Nevertheless, these often need user supervision on algorithm parameters which can be difficult to assess. To overcome this problem, we developed an original Matlab tool, allowing fast, fully automatic extraction and analysis of discontinuity features with no requirements on point cloud accuracy, density and homogeneity. The tool consists of a set of algorithms which: (i) process raw 3D point clouds, (ii) automatically characterize discontinuity sets, (iii) identify individual discontinuity surfaces, and (iv) analyse their spacing and persistence. The tool operates in either a supervised or unsupervised mode, starting from an automatic preliminary exploration data analysis. The identification and geometrical characterization of discontinuity features is divided in steps. First, coplanar surfaces are identified in the whole point cloud using K-Nearest Neighbor and Principal Component Analysis algorithms optimized on point cloud accuracy and specified typical facet size. Then, discontinuity set orientation is calculated using Kernel Density Estimation and principal vector similarity criteria. Poles to points are assigned to individual discontinuity objects using easy custom vector clustering and Jaccard distance approaches, and each object is segmented into planar clusters using an improved version of the DBSCAN algorithm. Modal set orientations are then recomputed by cluster-based orientation statistics to avoid the effects of biases related to cluster size and density heterogeneity of the point cloud. Finally, spacing values are measured between individual discontinuity clusters along scanlines parallel to modal pole vectors, whereas individual feature size (persistence) is measured using 3D convex hull bounding boxes. Spacing and size are provided both as raw population data and as summary statistics. The tool is optimized for parallel computing on 64bit systems, and a Graphic User Interface (GUI) has been developed to manage data processing, provide several outputs, including reclassified point clouds, tables, plots, derived fracture intensity parameters, and export to modelling software tools. We present test applications performed both on synthetic 3D data (simple 3D solids) and real case studies, validating the results with existing geomechanical datasets.

Georeferencing UAS Derivatives Through Point Cloud Registration with Archived Lidar Datasets

NASA Astrophysics Data System (ADS)

Magtalas, M. S. L. Y.; Aves, J. C. L.; Blanco, A. C.

2016-10-01

Georeferencing gathered images is a common step before performing spatial analysis and other processes on acquired datasets using unmanned aerial systems (UAS). Methods of applying spatial information to aerial images or their derivatives is through onboard GPS (Global Positioning Systems) geotagging, or through tying of models through GCPs (Ground Control Points) acquired in the field. Currently, UAS (Unmanned Aerial System) derivatives are limited to meter-levels of accuracy when their generation is unaided with points of known position on the ground. The use of ground control points established using survey-grade GPS or GNSS receivers can greatly reduce model errors to centimeter levels. However, this comes with additional costs not only with instrument acquisition and survey operations, but also in actual time spent in the field. This study uses a workflow for cloud-based post-processing of UAS data in combination with already existing LiDAR data. The georeferencing of the UAV point cloud is executed using the Iterative Closest Point algorithm (ICP). It is applied through the open-source CloudCompare software (Girardeau-Montaut, 2006) on a `skeleton point cloud'. This skeleton point cloud consists of manually extracted features consistent on both LiDAR and UAV data. For this cloud, roads and buildings with minimal deviations given their differing dates of acquisition are considered consistent. Transformation parameters are computed for the skeleton cloud which could then be applied to the whole UAS dataset. In addition, a separate cloud consisting of non-vegetation features automatically derived using CANUPO classification algorithm (Brodu and Lague, 2012) was used to generate a separate set of parameters. Ground survey is done to validate the transformed cloud. An RMSE value of around 16 centimeters was found when comparing validation data to the models georeferenced using the CANUPO cloud and the manual skeleton cloud. Cloud-to-cloud distance computations of CANUPO and manual skeleton clouds were obtained with values for both equal to around 0.67 meters at 1.73 standard deviation.

Cloud point extraction of iron(III) and vanadium(V) using 8-quinolinol derivatives and Triton X-100 and determination of 10(-7)moldm(-3) level iron(III) in riverine water reference by a graphite furnace atomic absorption spectroscopy.

PubMed

Ohashi, Akira; Ito, Hiromi; Kanai, Chikako; Imura, Hisanori; Ohashi, Kousaburo

2005-01-30

The cloud point extraction behavior of iron(III) and vanadium(V) using 8-quinolinol derivatives (HA) such as 8-quinolinol (HQ), 2-methyl-8-quinolinol (HMQ), 5-butyloxymethyl-8-quinolinol (HO(4)Q), 5-hexyloxymethyl-8-quinolinol (HO(6)Q), and 2-methyl-5-octyloxymethyl-8-quinolinol (HMO(8)Q) and Triton X-100 solution was investigated. Iron(III) was extracted with HA and 4% (v/v) Triton X-100 in the pH range of 1.70-5.44. Above pH 4.0, more than 95% of iron(III) was extracted with HQ, HMQ, and HMO(8)Q. Vanadium(V) was also extracted with HA and 4% (v/v) Triton X-100 in the pH range of 2.07-5.00, and the extractability increased in the following order of HMQ < HQ < HO(4)Q < HO(6)Q. The cloud point extraction was applied to the determination of iron(III) in the riverine water reference by a graphite furnace atomic absorption spectroscopy. When 1.25 x 10(-3)M HMQ and 1% (v/v) Triton X-100 were used, the found values showed a good agreement with the certified ones within the 2% of the R.S.D. Moreover, the effect of an alkyl group on the solubility of 5-alkyloxymethyl-8-quinolinol and 2-methyl-5-alkyloxymethyl-8-quinolinol in 4% (v/v) Triton X-100 at 25 degrees C was also investigated.

A Lidar Point Cloud Based Procedure for Vertical Canopy Structure Analysis And 3D Single Tree Modelling in Forest

PubMed Central

Wang, Yunsheng; Weinacker, Holger; Koch, Barbara

2008-01-01

A procedure for both vertical canopy structure analysis and 3D single tree modelling based on Lidar point cloud is presented in this paper. The whole area of research is segmented into small study cells by a raster net. For each cell, a normalized point cloud whose point heights represent the absolute heights of the ground objects is generated from the original Lidar raw point cloud. The main tree canopy layers and the height ranges of the layers are detected according to a statistical analysis of the height distribution probability of the normalized raw points. For the 3D modelling of individual trees, individual trees are detected and delineated not only from the top canopy layer but also from the sub canopy layer. The normalized points are resampled into a local voxel space. A series of horizontal 2D projection images at the different height levels are then generated respect to the voxel space. Tree crown regions are detected from the projection images. Individual trees are then extracted by means of a pre-order forest traversal process through all the tree crown regions at the different height levels. Finally, 3D tree crown models of the extracted individual trees are reconstructed. With further analyses on the 3D models of individual tree crowns, important parameters such as crown height range, crown volume and crown contours at the different height levels can be derived. PMID:27879916

The Potential Therapeutic Agent Mepacrine Protects Caco-2 Cells against Clostridium perfringens Enterotoxin Action.

PubMed

Freedman, John C; Hendricks, Matthew R; McClane, Bruce A

2017-01-01

Clostridium perfringens enterotoxin (CPE) causes the diarrhea associated with a common bacterial food poisoning and many antibiotic-associated diarrhea cases. The severity of some CPE-mediated disease cases warrants the development of potential therapeutics. A previous study showed that the presence of mepacrine inhibited CPE-induced electrophysiology effects in artificial lipid bilayers lacking CPE receptors. However, that study did not assess whether mepacrine inactivates CPE or, instead, inhibits a step in CPE action. Furthermore, CPE action in host cells is complex, involving the toxin binding to receptors, receptor-bound CPE oligomerizing into a prepore on the membrane surface, and β-hairpins in the CPE prepore inserting into the membrane to form a pore that induces cell death. Therefore, the current study evaluated the ability of mepacrine to protect cells from CPE. This drug was found to reduce CPE-induced cytotoxicity in Caco-2 cells. This protection did not involve mepacrine inactivation of CPE, indicating that mepacrine affects one or more steps in CPE action. Western blotting then demonstrated that mepacrine decreases CPE pore levels in Caco-2 cells. This mepacrine-induced reduction in CPE pore levels did not involve CPE binding inhibition but rather an increase in CPE monomer dissociation due to mepacrine interactions with Caco-2 membranes. In addition, mepacrine was also shown to inhibit CPE pores when already present in Caco-2 cells. These in vitro studies, which identified two mepacrine-sensitive steps in CPE-induced cytotoxicity, add support to further testing of the therapeutic potential of mepacrine against CPE-mediated disease. IMPORTANCE Clostridium perfringens enterotoxin (CPE) causes the gastrointestinal (GI) symptoms of a common bacterial food poisoning and several nonfoodborne human GI diseases. A previous study showed that, via an undetermined mechanism, the presence of mepacrine blocks CPE-induced electrophysiologic activity in artificial membranes. The current study now demonstrates that mepacrine also inhibits CPE-induced cytotoxicity in human enterocyte-like Caco-2 cells and that mepacrine does not directly inactivate CPE. Instead, this drug reduces both CPE pore formation and CPE pore activity in Caco-2 cells. These results suggest mepacrine as a therapeutic candidate for treating CPE-mediated GI diseases.

Carboxypeptidase E modulates intestinal immune homeostasis and protects against experimental colitis in mice.

PubMed

Bär, Florian; Föh, Bandik; Pagel, René; Schröder, Torsten; Schlichting, Heidi; Hirose, Misa; Lemcke, Susanne; Klinger, Antje; König, Peter; Karsten, Christian M; Büning, Jürgen; Lehnert, Hendrik; Fellermann, Klaus; Ibrahim, Saleh M; Sina, Christian

2014-01-01

Enteroendocrine cells (EEC) produce neuropeptides, which are crucially involved in the maintenance of the intestinal barrier. Hence, EEC dysfunction is suggested to be involved in the complex pathophysiology of inflammatory bowel disease (IBD), which is characterized by decreased intestinal barrier function. However, the underlying mechanisms for EEC dysfunction are not clear and suitable models for a better understanding are lacking. Here, we demonstrate that Carboxypeptidase E (CPE) is specifically expressed in EEC of the murine colon and ileum and that its deficiency is associated with reduced intestinal levels of Neuropeptide Y (NPY) and Peptide YY (PYY), which are both produced by EEC. Moreover, cpe-/- mice exhibit an aggravated course of DSS-induced chronic colitis compared to wildtype littermates. In addition, we observed elevated mucosal IL-6 and KC transcript levels already at baseline conditions in cpe-/- mice. Moreover, supernatants obtained from isolated intestinal crypts of cpe-/- mice lead to increased IL-6 and KC expression in MODE-K cells in the presence of LPS. This effect was reversible by co-administration of recombinant NPY, suggesting a CPE mediated immunosuppressive effect in the intestines by influencing the processing of specific neuropeptides. In this context, the chemotaxis of bone marrow derived macrophages towards respective supernatants was enhanced. In conclusion, our data point to an anti-inflammatory role of CPE in the intestine by influencing local cytokine levels and thus regulating the migration of myeloid immune cells into the mucosa. These findings highlight the importance of EEC for intestinal homeostasis and propose EEC as potential therapeutic targets in IBD.

Cloud point extraction and flame atomic absorption spectrometric determination of cadmium and nickel in drinking and wastewater samples.

PubMed

Naeemullah; Kazi, Tasneem G; Shah, Faheem; Afridi, Hassan I; Baig, Jameel Ahmed; Soomro, Abdul Sattar

2013-01-01

A simple method for the preconcentration of cadmium (Cd) and nickel (Ni) in drinking and wastewater samples was developed. Cloud point extraction has been used for the preconcentration of both metals, after formation of complexes with 8-hydroxyquinoline (8-HQ) and extraction with the surfactant octylphenoxypolyethoxyethanol (Triton X-114). Dilution of the surfactant-rich phase with acidified ethanol was performed after phase separation, and the Cd and Ni contents were measured by flame atomic absorption spectrometry. The experimental variables, such as pH, amounts of reagents (8-HQ and Triton X-114), temperature, incubation time, and sample volume, were optimized. After optimization of the complexation and extraction conditions, enhancement factors of 80 and 61, with LOD values of 0.22 and 0.52 microg/L, were obtained for Cd and Ni, respectively. The proposed method was applied satisfactorily for the determination of both elements in drinking and wastewater samples.

Automatic extraction of blocks from 3D point clouds of fractured rock

NASA Astrophysics Data System (ADS)

Chen, Na; Kemeny, John; Jiang, Qinghui; Pan, Zhiwen

2017-12-01

This paper presents a new method for extracting blocks and calculating block size automatically from rock surface 3D point clouds. Block size is an important rock mass characteristic and forms the basis for several rock mass classification schemes. The proposed method consists of four steps: 1) the automatic extraction of discontinuities using an improved Ransac Shape Detection method, 2) the calculation of discontinuity intersections based on plane geometry, 3) the extraction of block candidates based on three discontinuities intersecting one another to form corners, and 4) the identification of "true" blocks using an improved Floodfill algorithm. The calculated block sizes were compared with manual measurements in two case studies, one with fabricated cardboard blocks and the other from an actual rock mass outcrop. The results demonstrate that the proposed method is accurate and overcomes the inaccuracies, safety hazards, and biases of traditional techniques.

Feature-constrained surface reconstruction approach for point cloud data acquired with 3D laser scanner

NASA Astrophysics Data System (ADS)

Wang, Yongbo; Sheng, Yehua; Lu, Guonian; Tian, Peng; Zhang, Kai

2008-04-01

Surface reconstruction is an important task in the field of 3d-GIS, computer aided design and computer graphics (CAD & CG), virtual simulation and so on. Based on available incremental surface reconstruction methods, a feature-constrained surface reconstruction approach for point cloud is presented. Firstly features are extracted from point cloud under the rules of curvature extremes and minimum spanning tree. By projecting local sample points to the fitted tangent planes and using extracted features to guide and constrain the process of local triangulation and surface propagation, topological relationship among sample points can be achieved. For the constructed models, a process named consistent normal adjustment and regularization is adopted to adjust normal of each face so that the correct surface model is achieved. Experiments show that the presented approach inherits the convenient implementation and high efficiency of traditional incremental surface reconstruction method, meanwhile, it avoids improper propagation of normal across sharp edges, which means the applicability of incremental surface reconstruction is greatly improved. Above all, appropriate k-neighborhood can help to recognize un-sufficient sampled areas and boundary parts, the presented approach can be used to reconstruct both open and close surfaces without additional interference.

The Feasibility of 3d Point Cloud Generation from Smartphones

NASA Astrophysics Data System (ADS)

Alsubaie, N.; El-Sheimy, N.

2016-06-01

This paper proposes a new technique for increasing the accuracy of direct geo-referenced image-based 3D point cloud generated from low-cost sensors in smartphones. The smartphone's motion sensors are used to directly acquire the Exterior Orientation Parameters (EOPs) of the captured images. These EOPs, along with the Interior Orientation Parameters (IOPs) of the camera/ phone, are used to reconstruct the image-based 3D point cloud. However, because smartphone motion sensors suffer from poor GPS accuracy, accumulated drift and high signal noise, inaccurate 3D mapping solutions often result. Therefore, horizontal and vertical linear features, visible in each image, are extracted and used as constraints in the bundle adjustment procedure. These constraints correct the relative position and orientation of the 3D mapping solution. Once the enhanced EOPs are estimated, the semi-global matching algorithm (SGM) is used to generate the image-based dense 3D point cloud. Statistical analysis and assessment are implemented herein, in order to demonstrate the feasibility of 3D point cloud generation from the consumer-grade sensors in smartphones.

Assessing and Correcting Topographic Effects on Forest Canopy Height Retrieval Using Airborne LiDAR Data

PubMed Central

Duan, Zhugeng; Zhao, Dan; Zeng, Yuan; Zhao, Yujin; Wu, Bingfang; Zhu, Jianjun

2015-01-01

Topography affects forest canopy height retrieval based on airborne Light Detection and Ranging (LiDAR) data a lot. This paper proposes a method for correcting deviations caused by topography based on individual tree crown segmentation. The point cloud of an individual tree was extracted according to crown boundaries of isolated individual trees from digital orthophoto maps (DOMs). Normalized canopy height was calculated by subtracting the elevation of centres of gravity from the elevation of point cloud. First, individual tree crown boundaries are obtained by carrying out segmentation on the DOM. Second, point clouds of the individual trees are extracted based on the boundaries. Third, precise DEM is derived from the point cloud which is classified by a multi-scale curvature classification algorithm. Finally, a height weighted correction method is applied to correct the topological effects. The method is applied to LiDAR data acquired in South China, and its effectiveness is tested using 41 field survey plots. The results show that the terrain impacts the canopy height of individual trees in that the downslope side of the tree trunk is elevated and the upslope side is depressed. This further affects the extraction of the location and crown of individual trees. A strong correlation was detected between the slope gradient and the proportions of returns with height differences more than 0.3, 0.5 and 0.8 m in the total returns, with coefficient of determination R2 of 0.83, 0.76, and 0.60 (n = 41), respectively. PMID:26016907

Automatic registration of terrestrial point clouds based on panoramic reflectance images and efficient BaySAC

NASA Astrophysics Data System (ADS)

Kang, Zhizhong

2013-10-01

This paper presents a new approach to automatic registration of terrestrial laser scanning (TLS) point clouds utilizing a novel robust estimation method by an efficient BaySAC (BAYes SAmpling Consensus). The proposed method directly generates reflectance images from 3D point clouds, and then using SIFT algorithm extracts keypoints to identify corresponding image points. The 3D corresponding points, from which transformation parameters between point clouds are computed, are acquired by mapping the 2D ones onto the point cloud. To remove false accepted correspondences, we implement a conditional sampling method to select the n data points with the highest inlier probabilities as a hypothesis set and update the inlier probabilities of each data point using simplified Bayes' rule for the purpose of improving the computation efficiency. The prior probability is estimated by the verification of the distance invariance between correspondences. The proposed approach is tested on four data sets acquired by three different scanners. The results show that, comparing with the performance of RANSAC, BaySAC leads to less iterations and cheaper computation cost when the hypothesis set is contaminated with more outliers. The registration results also indicate that, the proposed algorithm can achieve high registration accuracy on all experimental datasets.

Potentiometric determination of antihistaminic diphenhydramine hydrochloride in pharmaceutical preparations and biological fluids using screen-printed electrode.

PubMed

Frag, Eman Y Z; Mohamed, Gehad G; El-Sayed, Wael G

2011-10-01

The performance characteristic of sensitive screen-printed (SPE) and carbon paste (CPE) electrodes was investigated for the determination of diphenhydramine hydrochloride (DPH) drug in pure, pharmaceutical preparations and biological fluids. Different experimental conditions namely types of materials used to prepare the working electrode (plasticizer), titrant, pH, temperature and life time were studied. Under these conditions, the SPE shows the best performance than CPE with respect to total potential change and potential break at the end point. The SPE and CPE exhibit suitable response to DPH in a concentration range of 1.0.10(-2) to 1.0.10(-6) mol/L with a limit of detection 9.70.10(-7) and 9.80.10(-7) mol/L, respectively. The slope of the system was 55.2±1.0 and 54.7±1.0 mV/decade over pH range 3.0-8.0 and 3-7 for SPE and CPE, respectively. Selectivity coefficients for DPH relative to a numbers of potential interfering substances were investigated. The SPE and CPE show a fast response time of 10 and 16s and were used over a period of 2 months with a good reproducibility. The sensors were applied successfully to determine DPH in pharmaceutical preparations and biological fluids. The results are compared with the official method. Copyright © 2011 Elsevier B.V. All rights reserved.

Cpe1786/IscR of Clostridium perfringens represses expression of genes involved in Fe-S cluster biogenesis.

PubMed

André, Gaelle; Haudecoeur, Elise; Courtois, Emmanuelle; Monot, Marc; Dupuy, Bruno; Rodionov, Dmitry A; Martin-Verstraete, Isabelle

2017-05-01

Cpe1786 of Clostridium perfringens is an Rrf2-type regulator containing the three-cysteine residues coordinating a Fe-S in IscR, the repressor controlling Fe-S homeostasis in enterobacteria. The cpe1786 gene formed an operon with iscSU involved in Fe-S biogenesis and tmrU. This operon was transcribed from a σ A -dependent promoter. We showed that in the heterologous host Bacillus subtilis, Cpe1786, renamed IscR Cp , negatively controlled its own transcription. We constructed an iscR mutant in C. perfringens. We then compared the expression profile of strain 13 and of the iscR mutant. IscR Cp controlled expression of genes involved in Fe-S biogenesis, in amino acid or sugar metabolisms, in fermentation pathways and in host compound utilization. We then demonstrated, using a ChIP-PCR experiment, that IscR Cp interacted with its promoter region in vivo in C. perfringens and with the promoter of cpe2093 encoding an amino acid ABC transporter. We utilized a comparative genomic approach to infer a candidate IscR binding motif and reconstruct IscR regulons in clostridia. We showed that point mutations in the conserved motif of 29 bp identified upstream of iscR decreased the cysteine-dependent repression of iscR mediated by IscR Cp . Copyright © 2016 Institut Pasteur. All rights reserved.

Determination of carcinogenic herbicides in milk samples using green non-ionic silicone surfactant of cloud point extraction and spectrophotometry.

PubMed

Mohd, N I; Zain, N N M; Raoov, M; Mohamad, S

2018-04-01

A new cloud point methodology was successfully used for the extraction of carcinogenic pesticides in milk samples as a prior step to their determination by spectrophotometry. In this work, non-ionic silicone surfactant, also known as 3-(3-hydroxypropyl-heptatrimethylxyloxane), was chosen as a green extraction solvent because of its structure and properties. The effect of different parameters, such as the type of surfactant, concentration and volume of surfactant, pH, salt, temperature, incubation time and water content on the cloud point extraction of carcinogenic pesticides such as atrazine and propazine, was studied in detail and a set of optimum conditions was established. A good correlation coefficient ( R 2 ) in the range of 0.991-0.997 for all calibration curves was obtained. The limit of detection was 1.06 µg l -1 (atrazine) and 1.22 µg l -1 (propazine), and the limit of quantitation was 3.54 µg l -1 (atrazine) and 4.07 µg l -1 (propazine). Satisfactory recoveries in the range of 81-108% were determined in milk samples at 5 and 1000 µg l -1 , respectively, with low relative standard deviation, n  = 3 of 0.301-7.45% in milk matrices. The proposed method is very convenient, rapid, cost-effective and environmentally friendly for food analysis.

Classification of Mls Point Clouds in Urban Scenes Using Detrended Geometric Features from Supervoxel-Based Local Contexts

NASA Astrophysics Data System (ADS)

Sun, Z.; Xu, Y.; Hoegner, L.; Stilla, U.

2018-05-01

In this work, we propose a classification method designed for the labeling of MLS point clouds, with detrended geometric features extracted from the points of the supervoxel-based local context. To achieve the analysis of complex 3D urban scenes, acquired points of the scene should be tagged with individual labels of different classes. Thus, assigning a unique label to the points of an object that belong to the same category plays an essential role in the entire 3D scene analysis workflow. Although plenty of studies in this field have been reported, this work is still a challenging task. Specifically, in this work: 1) A novel geometric feature extraction method, detrending the redundant and in-salient information in the local context, is proposed, which is proved to be effective for extracting local geometric features from the 3D scene. 2) Instead of using individual point as basic element, the supervoxel-based local context is designed to encapsulate geometric characteristics of points, providing a flexible and robust solution for feature extraction. 3) Experiments using complex urban scene with manually labeled ground truth are conducted, and the performance of proposed method with respect to different methods is analyzed. With the testing dataset, we have obtained a result of 0.92 for overall accuracy for assigning eight semantic classes.

Assessment of different models for computing the probability of a clear line of sight

NASA Astrophysics Data System (ADS)

Bojin, Sorin; Paulescu, Marius; Badescu, Viorel

2017-12-01

This paper is focused on modeling the morphological properties of the cloud fields in terms of the probability of a clear line of sight (PCLOS). PCLOS is defined as the probability that a line of sight between observer and a given point of the celestial vault goes freely without intersecting a cloud. A variety of PCLOS models assuming the cloud shape hemisphere, semi-ellipsoid and ellipsoid are tested. The effective parameters (cloud aspect ratio and absolute cloud fraction) are extracted from high-resolution series of sunshine number measurements. The performance of the PCLOS models is evaluated from the perspective of their ability in retrieving the point cloudiness. The advantages and disadvantages of the tested models are discussed, aiming to a simplified parameterization of PCLOS models.

Exploiting the Complementarity between Dereplication and Computer-Assisted Structure Elucidation for the Chemical Profiling of Natural Cosmetic Ingredients: Tephrosia purpurea as a Case Study.

PubMed

Hubert, Jane; Chollet, Sébastien; Purson, Sylvain; Reynaud, Romain; Harakat, Dominique; Martinez, Agathe; Nuzillard, Jean-Marc; Renault, Jean-Hugues

2015-07-24

The aqueous-ethanolic extract of Tephrosia purpurea seeds is currently exploited in the cosmetic industry as a natural ingredient of skin lotions. The aim of this study was to chemically characterize this ingredient by combining centrifugal partition extraction (CPE) as a fractionation tool with two complementary identification approaches involving dereplication and computer-assisted structure elucidation. Following two rapid fractionations of the crude extract (2 g), seven major compounds namely, caffeic acid, quercetin-3-O-rutinoside, ethyl galactoside, ciceritol, stachyose, saccharose, and citric acid, were unambiguously identified within the CPE-generated simplified mixtures by a recently developed (13)C NMR-based dereplication method. The structures of four additional compounds, patuletin-3-O-rutinoside, kaempferol-3-O-rutinoside, guaiacylglycerol 8-vanillic acid ether, and 2-methyl-2-glucopyranosyloxypropanoic acid, were automatically elucidated by using the Logic for Structure Determination program based on the interpretation of 2D NMR (HSQC, HMBC, and COSY) connectivity data. As more than 80% of the crude extract mass was characterized without need for tedious and labor-intensive multistep purification procedures, the identification tools involved in this work constitute a promising strategy for an efficient and time-saving chemical profiling of natural extracts.

A portable foot-parameter-extracting system

NASA Astrophysics Data System (ADS)

Zhang, MingKai; Liang, Jin; Li, Wenpan; Liu, Shifan

2016-03-01

In order to solve the problem of automatic foot measurement in garment customization, a new automatic footparameter- extracting system based on stereo vision, photogrammetry and heterodyne multiple frequency phase shift technology is proposed and implemented. The key technologies applied in the system are studied, including calibration of projector, alignment of point clouds, and foot measurement. Firstly, a new projector calibration algorithm based on plane model has been put forward to get the initial calibration parameters and a feature point detection scheme of calibration board image is developed. Then, an almost perfect match of two clouds is achieved by performing a first alignment using the Sampled Consensus - Initial Alignment algorithm (SAC-IA) and refining the alignment using the Iterative Closest Point algorithm (ICP). Finally, the approaches used for foot-parameterextracting and the system scheme are presented in detail. Experimental results show that the RMS error of the calibration result is 0.03 pixel and the foot parameter extracting experiment shows the feasibility of the extracting algorithm. Compared with the traditional measurement method, the system can be more portable, accurate and robust.

Accurate facade feature extraction method for buildings from three-dimensional point cloud data considering structural information

NASA Astrophysics Data System (ADS)

Wang, Yongzhi; Ma, Yuqing; Zhu, A.-xing; Zhao, Hui; Liao, Lixia

2018-05-01

Facade features represent segmentations of building surfaces and can serve as a building framework. Extracting facade features from three-dimensional (3D) point cloud data (3D PCD) is an efficient method for 3D building modeling. By combining the advantages of 3D PCD and two-dimensional optical images, this study describes the creation of a highly accurate building facade feature extraction method from 3D PCD with a focus on structural information. The new extraction method involves three major steps: image feature extraction, exploration of the mapping method between the image features and 3D PCD, and optimization of the initial 3D PCD facade features considering structural information. Results show that the new method can extract the 3D PCD facade features of buildings more accurately and continuously. The new method is validated using a case study. In addition, the effectiveness of the new method is demonstrated by comparing it with the range image-extraction method and the optical image-extraction method in the absence of structural information. The 3D PCD facade features extracted by the new method can be applied in many fields, such as 3D building modeling and building information modeling.

Photogrammetric Recording and Reconstruction of Town Scale Models - the Case of the Plan-Relief of Strasbourg

NASA Astrophysics Data System (ADS)

Macher, H.; Grussenmeyer, P.; Landes, T.; Halin, G.; Chevrier, C.; Huyghe, O.

2017-08-01

The French collection of Plan-Reliefs, scale models of fortified towns, constitutes a precious testimony of the history of France. The aim of the URBANIA project is the valorisation and the diffusion of this Heritage through the creation of virtual models. The town scale model of Strasbourg at 1/600 currently exhibited in the Historical Museum of Strasbourg was selected as a case study. In this paper, the photogrammetric recording of this scale model is first presented. The acquisition protocol as well as the data post-processing are detailed. Then, the modelling of the city and more specially building blocks is investigated. Based on point clouds of the scale model, the extraction of roof elements is considered. It deals first with the segmentation of the point cloud into building blocks. Then, for each block, points belonging to roofs are identified and the extraction of chimney point clouds as well as roof ridges and roof planes is performed. Finally, the 3D parametric modelling of the building blocks is studied by considering roof polygons and polylines describing chimneys as input. In a future works section, the semantically enrichment and the potential usage scenarios of the scale model are envisaged.

A hierarchical methodology for urban facade parsing from TLS point clouds

NASA Astrophysics Data System (ADS)

Li, Zhuqiang; Zhang, Liqiang; Mathiopoulos, P. Takis; Liu, Fangyu; Zhang, Liang; Li, Shuaipeng; Liu, Hao

2017-01-01

The effective and automated parsing of building facades from terrestrial laser scanning (TLS) point clouds of urban environments is an important research topic in the GIS and remote sensing fields. It is also challenging because of the complexity and great variety of the available 3D building facade layouts as well as the noise and data missing of the input TLS point clouds. In this paper, we introduce a novel methodology for the accurate and computationally efficient parsing of urban building facades from TLS point clouds. The main novelty of the proposed methodology is that it is a systematic and hierarchical approach that considers, in an adaptive way, the semantic and underlying structures of the urban facades for segmentation and subsequent accurate modeling. Firstly, the available input point cloud is decomposed into depth planes based on a data-driven method; such layer decomposition enables similarity detection in each depth plane layer. Secondly, the labeling of the facade elements is performed using the SVM classifier in combination with our proposed BieS-ScSPM algorithm. The labeling outcome is then augmented with weak architectural knowledge. Thirdly, least-squares fitted normalized gray accumulative curves are applied to detect regular structures, and a binarization dilation extraction algorithm is used to partition facade elements. A dynamic line-by-line division is further applied to extract the boundaries of the elements. The 3D geometrical façade models are then reconstructed by optimizing facade elements across depth plane layers. We have evaluated the performance of the proposed method using several TLS facade datasets. Qualitative and quantitative performance comparisons with several other state-of-the-art methods dealing with the same facade parsing problem have demonstrated its superiority in performance and its effectiveness in improving segmentation accuracy.

[Study on extracting and separating curcuminoids from Curcuma longa rhizome using ultrasound strengthen by microemulsion].

PubMed

Yue, Chun-Hua; Zheng, Li-Tao; Guo, Qi-Ming; Li, Kun-Ping

2014-05-01

To establish a new method for the extraction and separation of curcuminoids from Curcuma longa rhizome by cloud-point preconcentration using microemulsions as solvent. The spectrophotometry was used to detect the solubility of curcumin in different oil phase, emulsifier and auxiliary emulsifier, and the microemulsion prescription was used for false three-phase figure optimization. The extraction process was optimized by uniform experiment design. The curcuminoids were separated from microemulsion extract by cloud-point preconcentration. Oil phase was oleic acid ethyl ester; Emulsifier was OP emulsifier; Auxiliary emulsifier was polyethylene glycol(peg) 400; The quantity of emulsifier to auxiliary emulsifier was the ratio of 5: 1; Microemulsion prescription was water-oleic acid ethyl ester-mixed emulsifier (0.45:0.1:0.45). The optimum extraction process was: time for 12.5 min, temperature of 52 degrees C, power of 360 W, frequency of 400 kHz, and the liquid-solid ratio of 40:1. The extraction rate of curcuminoids was 92.17% and 86.85% in microemulsion and oil phase, respectively. Curcuminoids is soluble in this microemulsion prescription with good extraction rate. This method is simple and suitable for curcuminoids extraction from Curcuma longa rhizome.

Section Curve Reconstruction and Mean-Camber Curve Extraction of a Point-Sampled Blade Surface

PubMed Central

Li, Wen-long; Xie, He; Li, Qi-dong; Zhou, Li-ping; Yin, Zhou-ping

2014-01-01

The blade is one of the most critical parts of an aviation engine, and a small change in the blade geometry may significantly affect the dynamics performance of the aviation engine. Rapid advancements in 3D scanning techniques have enabled the inspection of the blade shape using a dense and accurate point cloud. This paper proposes a new method to achieving two common tasks in blade inspection: section curve reconstruction and mean-camber curve extraction with the representation of a point cloud. The mathematical morphology is expanded and applied to restrain the effect of the measuring defects and generate an ordered sequence of 2D measured points in the section plane. Then, the energy and distance are minimized to iteratively smoothen the measured points, approximate the section curve and extract the mean-camber curve. In addition, a turbine blade is machined and scanned to observe the curvature variation, energy variation and approximation error, which demonstrates the availability of the proposed method. The proposed method is simple to implement and can be applied in aviation casting-blade finish inspection, large forging-blade allowance inspection and visual-guided robot grinding localization. PMID:25551467

Section curve reconstruction and mean-camber curve extraction of a point-sampled blade surface.

PubMed

Li, Wen-long; Xie, He; Li, Qi-dong; Zhou, Li-ping; Yin, Zhou-ping

2014-01-01

The blade is one of the most critical parts of an aviation engine, and a small change in the blade geometry may significantly affect the dynamics performance of the aviation engine. Rapid advancements in 3D scanning techniques have enabled the inspection of the blade shape using a dense and accurate point cloud. This paper proposes a new method to achieving two common tasks in blade inspection: section curve reconstruction and mean-camber curve extraction with the representation of a point cloud. The mathematical morphology is expanded and applied to restrain the effect of the measuring defects and generate an ordered sequence of 2D measured points in the section plane. Then, the energy and distance are minimized to iteratively smoothen the measured points, approximate the section curve and extract the mean-camber curve. In addition, a turbine blade is machined and scanned to observe the curvature variation, energy variation and approximation error, which demonstrates the availability of the proposed method. The proposed method is simple to implement and can be applied in aviation casting-blade finish inspection, large forging-blade allowance inspection and visual-guided robot grinding localization.

Image Capture with Synchronized Multiple-Cameras for Extraction of Accurate Geometries

NASA Astrophysics Data System (ADS)

Koehl, M.; Delacourt, T.; Boutry, C.

2016-06-01

This paper presents a project of recording and modelling tunnels, traffic circles and roads from multiple sensors. The aim is the representation and the accurate 3D modelling of a selection of road infrastructures as dense point clouds in order to extract profiles and metrics from it. Indeed, these models will be used for the sizing of infrastructures in order to simulate exceptional convoy truck routes. The objective is to extract directly from the point clouds the heights, widths and lengths of bridges and tunnels, the diameter of gyrating and to highlight potential obstacles for a convoy. Light, mobile and fast acquisition approaches based on images and videos from a set of synchronized sensors have been tested in order to obtain useable point clouds. The presented solution is based on a combination of multiple low-cost cameras designed on an on-boarded device allowing dynamic captures. The experimental device containing GoPro Hero4 cameras has been set up and used for tests in static or mobile acquisitions. That way, various configurations have been tested by using multiple synchronized cameras. These configurations are discussed in order to highlight the best operational configuration according to the shape of the acquired objects. As the precise calibration of each sensor and its optics are major factors in the process of creation of accurate dense point clouds, and in order to reach the best quality available from such cameras, the estimation of the internal parameters of fisheye lenses of the cameras has been processed. Reference measures were also realized by using a 3D TLS (Faro Focus 3D) to allow the accuracy assessment.

Feature Relevance Assessment of Multispectral Airborne LIDAR Data for Tree Species Classification

NASA Astrophysics Data System (ADS)

Amiri, N.; Heurich, M.; Krzystek, P.; Skidmore, A. K.

2018-04-01

The presented experiment investigates the potential of Multispectral Laser Scanning (MLS) point clouds for single tree species classification. The basic idea is to simulate a MLS sensor by combining two different Lidar sensors providing three different wavelngthes. The available data were acquired in the summer 2016 at the same date in a leaf-on condition with an average point density of 37 points/m2. For the purpose of classification, we segmented the combined 3D point clouds consisiting of three different spectral channels into 3D clusters using Normalized Cut segmentation approach. Then, we extracted four group of features from the 3D point cloud space. Once a varity of features has been extracted, we applied forward stepwise feature selection in order to reduce the number of irrelevant or redundant features. For the classification, we used multinomial logestic regression with L1 regularization. Our study is conducted using 586 ground measured single trees from 20 sample plots in the Bavarian Forest National Park, in Germany. Due to lack of reference data for some rare species, we focused on four classes of species. The results show an improvement between 4-10 pp for the tree species classification by using MLS data in comparison to a single wavelength based approach. A cross validated (15-fold) accuracy of 0.75 can be achieved when all feature sets from three different spectral channels are used. Our results cleary indicates that the use of MLS point clouds has great potential to improve detailed forest species mapping.

Evaluation of Methods for Coregistration and Fusion of Rpas-Based 3d Point Clouds and Thermal Infrared Images

NASA Astrophysics Data System (ADS)

Hoegner, L.; Tuttas, S.; Xu, Y.; Eder, K.; Stilla, U.

2016-06-01

This paper discusses the automatic coregistration and fusion of 3d point clouds generated from aerial image sequences and corresponding thermal infrared (TIR) images. Both RGB and TIR images have been taken from a RPAS platform with a predefined flight path where every RGB image has a corresponding TIR image taken from the same position and with the same orientation with respect to the accuracy of the RPAS system and the inertial measurement unit. To remove remaining differences in the exterior orientation, different strategies for coregistering RGB and TIR images are discussed: (i) coregistration based on 2D line segments for every single TIR image and the corresponding RGB image. This method implies a mainly planar scene to avoid mismatches; (ii) coregistration of both the dense 3D point clouds from RGB images and from TIR images by coregistering 2D image projections of both point clouds; (iii) coregistration based on 2D line segments in every single TIR image and 3D line segments extracted from intersections of planes fitted in the segmented dense 3D point cloud; (iv) coregistration of both the dense 3D point clouds from RGB images and from TIR images using both ICP and an adapted version based on corresponding segmented planes; (v) coregistration of both image sets based on point features. The quality is measured by comparing the differences of the back projection of homologous points in both corrected RGB and TIR images.

Building Facade Modeling Under Line Feature Constraint Based on Close-Range Images

NASA Astrophysics Data System (ADS)

Liang, Y.; Sheng, Y. H.

2018-04-01

To solve existing problems in modeling facade of building merely with point feature based on close-range images , a new method for modeling building facade under line feature constraint is proposed in this paper. Firstly, Camera parameters and sparse spatial point clouds data were restored using the SFM , and 3D dense point clouds were generated with MVS; Secondly, the line features were detected based on the gradient direction , those detected line features were fit considering directions and lengths , then line features were matched under multiple types of constraints and extracted from multi-image sequence. At last, final facade mesh of a building was triangulated with point cloud and line features. The experiment shows that this method can effectively reconstruct the geometric facade of buildings using the advantages of combining point and line features of the close - range image sequence, especially in restoring the contour information of the facade of buildings.

A Registration Method Based on Contour Point Cloud for 3D Whole-Body PET and CT Images

PubMed Central

Yang, Qiyao; Wang, Zhiguo; Zhang, Guoxu

2017-01-01

The PET and CT fusion image, combining the anatomical and functional information, has important clinical meaning. An effective registration of PET and CT images is the basis of image fusion. This paper presents a multithread registration method based on contour point cloud for 3D whole-body PET and CT images. Firstly, a geometric feature-based segmentation (GFS) method and a dynamic threshold denoising (DTD) method are creatively proposed to preprocess CT and PET images, respectively. Next, a new automated trunk slices extraction method is presented for extracting feature point clouds. Finally, the multithread Iterative Closet Point is adopted to drive an affine transform. We compare our method with a multiresolution registration method based on Mattes Mutual Information on 13 pairs (246~286 slices per pair) of 3D whole-body PET and CT data. Experimental results demonstrate the registration effectiveness of our method with lower negative normalization correlation (NC = −0.933) on feature images and less Euclidean distance error (ED = 2.826) on landmark points, outperforming the source data (NC = −0.496, ED = 25.847) and the compared method (NC = −0.614, ED = 16.085). Moreover, our method is about ten times faster than the compared one. PMID:28316979

Low cost digital photogrammetry: From the extraction of point clouds by SFM technique to 3D mathematical modeling

NASA Astrophysics Data System (ADS)

Michele, Mangiameli; Giuseppe, Mussumeci; Salvatore, Zito

2017-07-01

The Structure From Motion (SFM) is a technique applied to a series of photographs of an object that returns a 3D reconstruction made up by points in the space (point clouds). This research aims at comparing the results of the SFM approach with the results of a 3D laser scanning in terms of density and accuracy of the model. The experience was conducted by detecting several architectural elements (walls and portals of historical buildings) both with a 3D laser scanner of the latest generation and an amateur photographic camera. The point clouds acquired by laser scanner and those acquired by the photo camera have been systematically compared. In particular we present the experience carried out on the "Don Diego Pappalardo Palace" site in Pedara (Catania, Sicily).

Csf Based Non-Ground Points Extraction from LIDAR Data

NASA Astrophysics Data System (ADS)

Shen, A.; Zhang, W.; Shi, H.

2017-09-01

Region growing is a classical method of point cloud segmentation. Based on the idea of collecting the pixels with similar properties to form regions, region growing is widely used in many fields such as medicine, forestry and remote sensing. In this algorithm, there are two core problems. One is the selection of seed points, the other is the setting of the growth constraints, in which the selection of the seed points is the foundation. In this paper, we propose a CSF (Cloth Simulation Filtering) based method to extract the non-ground seed points effectively. The experiments have shown that this method can obtain a group of seed spots compared with the traditional methods. It is a new attempt to extract seed points

Extraction of convective cloud parameters from Doppler Weather Radar MAX(Z) product using Image Processing Technique

NASA Astrophysics Data System (ADS)

Arunachalam, M. S.; Puli, Anil; Anuradha, B.

2016-07-01

In the present work continuous extraction of convective cloud optical information and reflectivity (MAX(Z) in dBZ) using online retrieval technique for time series data production from Doppler Weather Radar (DWR) located at Indian Meteorological Department, Chennai has been developed in MATLAB. Reflectivity measurements for different locations within the DWR range of 250 Km radii of circular disc area can be retrieved using this technique. It gives both time series reflectivity of point location and also Range Time Intensity (RTI) maps of reflectivity for the corresponding location. The Graphical User Interface (GUI) developed for the cloud reflectivity is user friendly; it also provides the convective cloud optical information such as cloud base height (CBH), cloud top height (CTH) and cloud optical depth (COD). This technique is also applicable for retrieving other DWR products such as Plan Position Indicator (Z, in dBZ), Plan Position Indicator (Z, in dBZ)-Close Range, Volume Velocity Processing (V, in knots), Plan Position Indicator (V, in m/s), Surface Rainfall Intensity (SRI, mm/hr), Precipitation Accumulation (PAC) 24 hrs at 0300UTC. Keywords: Reflectivity, cloud top height, cloud base, cloud optical depth

Determination of trace inorganic mercury species in water samples by cloud point extraction and UV-vis spectrophotometry.

PubMed

Ulusoy, Halil Ibrahim

2014-01-01

A new micelle-mediated extraction method was developed for preconcentration of ultratrace Hg(II) ions prior to spectrophotometric determination. 2-(2'-Thiazolylazo)-p-cresol (TAC) and Ponpe 7.5 were used as the chelating agent and nonionic surfactant, respectively. Hg(II) ions form a hydrophobic complex with TAC in a micelle medium. The main factors affecting cloud point extraction efficiency, such as pH of the medium, concentrations of TAC and Ponpe 7.5, and equilibration temperature and time, were investigated in detail. An overall preconcentration factor of 33.3 was obtained upon preconcentration of a 50 mL sample. The LOD obtained under the optimal conditions was 0.86 microg/L, and the RSD for five replicate measurements of 100 microg/L Hg(II) was 3.12%. The method was successfully applied to the determination of Hg in environmental water samples.

Speciation of organic and inorganic selenium in selenium-enriched rice by graphite furnace atomic absorption spectrometry after cloud point extraction.

PubMed

Sun, Mei; Liu, Guijian; Wu, Qianghua

2013-11-01

A new method was developed for the determination of organic and inorganic selenium in selenium-enriched rice by graphite furnace atomic absorption spectrometry detection after cloud point extraction. Effective separation of organic and inorganic selenium in selenium-enriched rice was achieved by sequentially extracting with water and cyclohexane. Under the optimised conditions, the limit of detection (LOD) was 0.08 μg L(-1), the relative standard deviation (RSD) was 2.1% (c=10.0 μg L(-1), n=11), and the enrichment factor for selenium was 82. Recoveries of inorganic selenium in the selenium-enriched rice samples were between 90.3% and 106.0%. The proposed method was successfully applied for the determination of organic and inorganic selenium as well as total selenium in selenium-enriched rice. Copyright © 2013 Elsevier Ltd. All rights reserved.

Localization of Pathology on Complex Architecture Building Surfaces

NASA Astrophysics Data System (ADS)

Sidiropoulos, A. A.; Lakakis, K. N.; Mouza, V. K.

2017-02-01

The technology of 3D laser scanning is considered as one of the most common methods for heritage documentation. The point clouds that are being produced provide information of high detail, both geometric and thematic. There are various studies that examine techniques of the best exploitation of this information. In this study, an algorithm of pathology localization, such as cracks and fissures, on complex building surfaces is being tested. The algorithm makes use of the points' position in the point cloud and tries to distinguish them in two groups-patterns; pathology and non-pathology. The extraction of the geometric information that is being used for recognizing the pattern of the points is being accomplished via Principal Component Analysis (PCA) in user-specified neighborhoods in the whole point cloud. The implementation of PCA leads to the definition of the normal vector at each point of the cloud. Two tests that operate separately examine both local and global geometric criteria among the points and conclude which of them should be categorized as pathology. The proposed algorithm was tested on parts of the Gazi Evrenos Baths masonry, which are located at the city of Giannitsa at Northern Greece.

Robust Segmentation of Planar and Linear Features of Terrestrial Laser Scanner Point Clouds Acquired from Construction Sites.

PubMed

Maalek, Reza; Lichti, Derek D; Ruwanpura, Janaka Y

2018-03-08

Automated segmentation of planar and linear features of point clouds acquired from construction sites is essential for the automatic extraction of building construction elements such as columns, beams and slabs. However, many planar and linear segmentation methods use scene-dependent similarity thresholds that may not provide generalizable solutions for all environments. In addition, outliers exist in construction site point clouds due to data artefacts caused by moving objects, occlusions and dust. To address these concerns, a novel method for robust classification and segmentation of planar and linear features is proposed. First, coplanar and collinear points are classified through a robust principal components analysis procedure. The classified points are then grouped using a new robust clustering method, the robust complete linkage method. A robust method is also proposed to extract the points of flat-slab floors and/or ceilings independent of the aforementioned stages to improve computational efficiency. The applicability of the proposed method is evaluated in eight datasets acquired from a complex laboratory environment and two construction sites at the University of Calgary. The precision, recall, and accuracy of the segmentation at both construction sites were 96.8%, 97.7% and 95%, respectively. These results demonstrate the suitability of the proposed method for robust segmentation of planar and linear features of contaminated datasets, such as those collected from construction sites.

Robust Segmentation of Planar and Linear Features of Terrestrial Laser Scanner Point Clouds Acquired from Construction Sites

PubMed Central

Maalek, Reza; Lichti, Derek D; Ruwanpura, Janaka Y

2018-01-01

Automated segmentation of planar and linear features of point clouds acquired from construction sites is essential for the automatic extraction of building construction elements such as columns, beams and slabs. However, many planar and linear segmentation methods use scene-dependent similarity thresholds that may not provide generalizable solutions for all environments. In addition, outliers exist in construction site point clouds due to data artefacts caused by moving objects, occlusions and dust. To address these concerns, a novel method for robust classification and segmentation of planar and linear features is proposed. First, coplanar and collinear points are classified through a robust principal components analysis procedure. The classified points are then grouped using a new robust clustering method, the robust complete linkage method. A robust method is also proposed to extract the points of flat-slab floors and/or ceilings independent of the aforementioned stages to improve computational efficiency. The applicability of the proposed method is evaluated in eight datasets acquired from a complex laboratory environment and two construction sites at the University of Calgary. The precision, recall, and accuracy of the segmentation at both construction sites were 96.8%, 97.7% and 95%, respectively. These results demonstrate the suitability of the proposed method for robust segmentation of planar and linear features of contaminated datasets, such as those collected from construction sites. PMID:29518062

Detection of vitamin b1 (thiamine) using modified carbon paste electrodes with polypyrrole

NASA Astrophysics Data System (ADS)

Muppariqoh, N. M.; Wahyuni, W. T.; Putra, B. R.

2017-03-01

Vitamin B1 (thiamine) is oxidized in alkaline medium and can be detected by cyclic voltammetry technique using carbon paste electrode (CPE) as a working electrode. polypyrrole-modified CPE were used in this study to increase sensitivity and selectivity measurement of thiamine. Molecularly imprinted polymers (MIP) of the modified CPE was prepared through electrodeposition of pyrrole. Measurement of thiamine performed in KCl 0.05 M (pH 10, tris buffer) using CPE and the modified CPE gave an optimum condition anodic current of thiamine at 0.3 V, potential range (-1.6_1 V), and scan rate of 100 mV/s. Measurement of thiamine using polypyrrole modified CPE (CPE-MIPpy) showed better result than CPE itself with detection limit of 6.9×10-5 M and quantitation limit 2.1×10-4 M. CPE-MIPpy is selective to vita min B1. In conclusion, CPE-MIPpy as a working electrode showed better performance of thiamine measurement than that of CPE.

Automated Point Cloud Correspondence Detection for Underwater Mapping Using AUVs

NASA Technical Reports Server (NTRS)

Hammond, Marcus; Clark, Ashley; Mahajan, Aditya; Sharma, Sumant; Rock, Stephen

2015-01-01

An algorithm for automating correspondence detection between point clouds composed of multibeam sonar data is presented. This allows accurate initialization for point cloud alignment techniques even in cases where accurate inertial navigation is not available, such as iceberg profiling or vehicles with low-grade inertial navigation systems. Techniques from computer vision literature are used to extract, label, and match keypoints between "pseudo-images" generated from these point clouds. Image matches are refined using RANSAC and information about the vehicle trajectory. The resulting correspondences can be used to initialize an iterative closest point (ICP) registration algorithm to estimate accumulated navigation error and aid in the creation of accurate, self-consistent maps. The results presented use multibeam sonar data obtained from multiple overlapping passes of an underwater canyon in Monterey Bay, California. Using strict matching criteria, the method detects 23 between-swath correspondence events in a set of 155 pseudo-images with zero false positives. Using less conservative matching criteria doubles the number of matches but introduces several false positive matches as well. Heuristics based on known vehicle trajectory information are used to eliminate these.

Registration of Vehicle-Borne Point Clouds and Panoramic Images Based on Sensor Constellations.

PubMed

Yao, Lianbi; Wu, Hangbin; Li, Yayun; Meng, Bin; Qian, Jinfei; Liu, Chun; Fan, Hongchao

2017-04-11

A mobile mapping system (MMS) is usually utilized to collect environmental data on and around urban roads. Laser scanners and panoramic cameras are the main sensors of an MMS. This paper presents a new method for the registration of the point clouds and panoramic images based on sensor constellation. After the sensor constellation was analyzed, a feature point, the intersection of the connecting line between the global positioning system (GPS) antenna and the panoramic camera with a horizontal plane, was utilized to separate the point clouds into blocks. The blocks for the central and sideward laser scanners were extracted with the segmentation feature points. Then, the point clouds located in the blocks were separated from the original point clouds. Each point in the blocks was used to find the accurate corresponding pixel in the relative panoramic images via a collinear function, and the position and orientation relationship amongst different sensors. A search strategy is proposed for the correspondence of laser scanners and lenses of panoramic cameras to reduce calculation complexity and improve efficiency. Four cases of different urban road types were selected to verify the efficiency and accuracy of the proposed method. Results indicate that most of the point clouds (with an average of 99.7%) were successfully registered with the panoramic images with great efficiency. Geometric evaluation results indicate that horizontal accuracy was approximately 0.10-0.20 m, and vertical accuracy was approximately 0.01-0.02 m for all cases. Finally, the main factors that affect registration accuracy, including time synchronization amongst different sensors, system positioning and vehicle speed, are discussed.

Clostridium perfringens Type A Strains Carrying a Plasmid-Borne Enterotoxin Gene (Genotype IS1151-cpe or IS1470-like-cpe) as a Common Cause of Food Poisoning▿

PubMed Central

Lahti, Päivi; Heikinheimo, Annamari; Johansson, Tuula; Korkeala, Hannu

2008-01-01

The prevalences of various genotypes of enterotoxin gene-carrying (cpe-positive) Clostridium perfringens type A in 24 different food poisoning outbreaks were 75% (chromosomal IS1470-cpe), 21% (plasmid-borne IS1470-like-cpe), and 4% (plasmid-borne IS1151-cpe). These results show that C. perfringens type A carrying the plasmid-borne cpe is a common cause of food poisoning. PMID:18003798

2.5D multi-view gait recognition based on point cloud registration.

PubMed

Tang, Jin; Luo, Jian; Tjahjadi, Tardi; Gao, Yan

2014-03-28

This paper presents a method for modeling a 2.5-dimensional (2.5D) human body and extracting the gait features for identifying the human subject. To achieve view-invariant gait recognition, a multi-view synthesizing method based on point cloud registration (MVSM) to generate multi-view training galleries is proposed. The concept of a density and curvature-based Color Gait Curvature Image is introduced to map 2.5D data onto a 2D space to enable data dimension reduction by discrete cosine transform and 2D principle component analysis. Gait recognition is achieved via a 2.5D view-invariant gait recognition method based on point cloud registration. Experimental results on the in-house database captured by a Microsoft Kinect camera show a significant performance gain when using MVSM.

An integrated process for the recovery of high added-value compounds from olive oil using solid support free liquid-liquid extraction and chromatography techniques.

PubMed

Angelis, Apostolis; Hamzaoui, Mahmoud; Aligiannis, Nektarios; Nikou, Theodora; Michailidis, Dimitris; Gerolimatos, Panagiotis; Termentzi, Aikaterini; Hubert, Jane; Halabalaki, Maria; Renault, Jean-Hugues; Skaltsounis, Alexios-Léandros

2017-03-31

An integrated extraction and purification process for the direct recovery of high added value compounds from extra virgin olive oil (EVOO) is proposed by using solid support free liquid-liquid extraction and chromatography techniques. Two different extraction methods were developed on a laboratory-scale Centrifugal Partition Extractor (CPE): a sequential strategy consisting of several "extraction-recovery" cycles and a continuous strategy based on stationary phase co-current elution. In both cases, EVOO was used as mobile phase diluted in food grade n-hexane (feed mobile phase) and the required biphasic system was obtained by adding ethanol and water as polar solvents. For the sequential process, 17.5L of feed EVOO containing organic phase (i.e. 7L of EVOO treated) were extracted yielding 9.5g of total phenolic fraction corresponding to a productivity of 5.8g/h/L of CPE column. Regarding the second approach, the co-current process, 2L of the feed oil phase (containing to 0.8L of EVOO) were treated at 100mL/min yielding 1.03g of total phenolic fraction corresponding to a productivity of 8.9g/h/L of CPE column. The total phenolic fraction was then fractionated by using stepwise gradient elution Centrifugal Partition Chromatography (CPC). The biphasic solvent systems were composed of n-hexane, ethyl acetate, ethanol and water in different proportions (X/Y/2/3, v/v). In a single run of 4h on a column with a capacity of 1L, 910mg of oleocanthal, 882mg of oleacein, 104mg of hydroxytyrosol were successfully recovered from 5g of phenolic extract with purities of 85%, 92% and 90%, respectively. CPC fractions were then submitted to orthogonal chromatographic steps (adsorption on silica gel or size exclusion chromatography) leading to the isolation of additional eleven compounds belonging to triterpens, phenolic compounds and secoiridoids. Among them, elenolic acid ethylester was found to be new compound. Thin Layer Chromatography (TLC), Nuclear magnetic Resonance (NMR) and High Performance Liquid Chromatography - Diode Array Detector (HPLC-DAD) were used for monitoring and evaluation purposes throughout the entire procedure. Copyright © 2017 Elsevier B.V. All rights reserved.

Automated estimation of leaf distribution for individual trees based on TLS point clouds

NASA Astrophysics Data System (ADS)

Koma, Zsófia; Rutzinger, Martin; Bremer, Magnus

2017-04-01

Light Detection and Ranging (LiDAR) especially the ground based LiDAR (Terrestrial Laser Scanning - TLS) is an operational used and widely available measurement tool supporting forest inventory updating and research in forest ecology. High resolution point clouds from TLS already represent single leaves which can be used for a more precise estimation of Leaf Area Index (LAI) and for higher accurate biomass estimation. However, currently the methodology for extracting single leafs from the unclassified point clouds for individual trees is still missing. The aim of this study is to present a novel segmentation approach in order to extract single leaves and derive features related to leaf morphology (such as area, slope, length and width) of each single leaf from TLS point cloud data. For the study two exemplary single trees were scanned in leaf-on condition on the university campus of Innsbruck during calm wind conditions. A northern red oak (Quercus rubra) was scanned by a discrete return recording Optech ILRIS-3D TLS scanner and a tulip tree (Liliodendron tulpifera) with Riegl VZ-6000 scanner. During the scanning campaign a reference dataset was measured parallel to scanning. In this case 230 leaves were randomly collected around the lower branches of the tree and photos were taken. The developed workflow steps were the following: in the first step normal vectors and eigenvalues were calculated based on the user specified neighborhood. Then using the direction of the largest eigenvalue outliers i.e. ghost points were removed. After that region growing segmentation based on the curvature and angles between normal vectors was applied on the filtered point cloud. On each segment a RANSAC plane fitting algorithm was applied in order to extract the segment based normal vectors. Using the related features of the calculated segments the stem and branches were labeled as non-leaf and other segments were classified as leaf. The validation of the different segmentation parameters was evaluated as the following: i) the sum area of the collected leaves and the point cloud, ii) the segmented leaf length-width ratio iii) the distribution of the leaf area for the segmented and the reference-ones were compared and the ideal parameter-set was found. The results show that the leaves can be captured with the developed workflow and the slope can be determined robustly for the segmented leaves. However, area, length and width values are systematically depending on the angle and the distance from the scanner. For correction of the systematic underestimation, more systematic measurement or LiDAR simulation is required for further detailed analysis. The results of leaf segmentation algorithm show high potential in generating more precise tree models with correctly located leaves in order to extract more precise input model for biological modeling of LAI or atmospheric corrections studies. The presented workflow also can be used in monitoring the change of angle of the leaves due to sun irradiation, water balance, and day-night rhythm.

On charged particle equilibrium violation in external photon fields.

PubMed

Bouchard, Hugo; Seuntjens, Jan; Palmans, Hugo

2012-03-01

In a recent paper by Bouchard et al. [Med. Phys. 36(10), 4654-4663 (2009)], a theoretical model of quality correction factors for idealistic so-called plan-class specific reference (PCSR) fields was proposed. The reasoning was founded on the definition of PCSR fields made earlier by Alfonso et al. [Med. Phys. 35(11), 5179-5186 (2008)], requiring the beam to achieve charged particle equilibrium (CPE), in a time-averaged sense, in the reference medium. The relation obtained by Bouchard et al. was derived using Fano's theorem (1954) which states that if CPE is established in a given medium, the dose is independent of point-to-point density variations. A potential misconception on the achievability of the condition required by Fano (1954) might be responsible for false practical conclusions, both in the definition of PCSR fields as well as the theoretical model of quality correction factor. In this paper, the practical achievability of CPE in external beams is treated in detail. The fact that this condition is not achievable in single or composite deliveries is illustrated by an intuitive method and is also formally demonstrated. Fano's theorem is not applicable in external beam radiation dosimetry without (virtually) removing attenuation effects, and therefore, the relation conditionally defined by Bouchard et al. (2009) cannot be valid in practice. A definition of PCSR fields in the recent formalism for nonstandard beams proposed by Alfonso et al. (2008) should be modified, revising the criterion of CPE condition. The authors propose reconsidering the terminology used to describe standard and nonstandard beams. The authors argue that quality correction factors of intensity modulated radiation therapy PCSR fields (i.e., k(Q(pcsr),Q) (f(pcsr),f(ref) )) could be unity under ideal conditions, but it is concluded that further investigation is necessary to confirm that hypothesis.

UAS-SfM for coastal research: Geomorphic feature extraction and land cover classification from high-resolution elevation and optical imagery

USGS Publications Warehouse

Sturdivant, Emily; Lentz, Erika; Thieler, E. Robert; Farris, Amy; Weber, Kathryn; Remsen, David P.; Miner, Simon; Henderson, Rachel

2017-01-01

The vulnerability of coastal systems to hazards such as storms and sea-level rise is typically characterized using a combination of ground and manned airborne systems that have limited spatial or temporal scales. Structure-from-motion (SfM) photogrammetry applied to imagery acquired by unmanned aerial systems (UAS) offers a rapid and inexpensive means to produce high-resolution topographic and visual reflectance datasets that rival existing lidar and imagery standards. Here, we use SfM to produce an elevation point cloud, an orthomosaic, and a digital elevation model (DEM) from data collected by UAS at a beach and wetland site in Massachusetts, USA. We apply existing methods to (a) determine the position of shorelines and foredunes using a feature extraction routine developed for lidar point clouds and (b) map land cover from the rasterized surfaces using a supervised classification routine. In both analyses, we experimentally vary the input datasets to understand the benefits and limitations of UAS-SfM for coastal vulnerability assessment. We find that (a) geomorphic features are extracted from the SfM point cloud with near-continuous coverage and sub-meter precision, better than was possible from a recent lidar dataset covering the same area; and (b) land cover classification is greatly improved by including topographic data with visual reflectance, but changes to resolution (when <50 cm) have little influence on the classification accuracy.

Multi-Scale Voxel Segmentation for Terrestrial Lidar Data within Marshes

NASA Astrophysics Data System (ADS)

Nguyen, C. T.; Starek, M. J.; Tissot, P.; Gibeaut, J. C.

2016-12-01

The resilience of marshes to a rising sea is dependent on their elevation response. Terrestrial laser scanning (TLS) is a detailed topographic approach for accurate, dense surface measurement with high potential for monitoring of marsh surface elevation response. The dense point cloud provides a 3D representation of the surface, which includes both terrain and non-terrain objects. Extraction of topographic information requires filtering of the data into like-groups or classes, therefore, methods must be incorporated to identify structure in the data prior to creation of an end product. A voxel representation of three-dimensional space provides quantitative visualization and analysis for pattern recognition. The objectives of this study are threefold: 1) apply a multi-scale voxel approach to effectively extract geometric features from the TLS point cloud data, 2) investigate the utility of K-means and Self Organizing Map (SOM) clustering algorithms for segmentation, and 3) utilize a variety of validity indices to measure the quality of the result. TLS data were collected at a marsh site along the central Texas Gulf Coast using a Riegl VZ 400 TLS. The site consists of both exposed and vegetated surface regions. To characterize structure of the point cloud, octree segmentation is applied to create a tree data structure of voxels containing the points. The flexibility of voxels in size and point density makes this algorithm a promising candidate to locally extract statistical and geometric features of the terrain including surface normal and curvature. The characteristics of the voxel itself such as the volume and point density are also computed and assigned to each point as are laser pulse characteristics. The features extracted from the voxelization are then used as input for clustering of the points using the K-means and SOM clustering algorithms. Optimal number of clusters are then determined based on evaluation of cluster separability criterions. Results for different combinations of the feature space vector and differences between K-means and SOM clustering will be presented. The developed method provides a novel approach for compressing TLS scene complexity in marshes, such as for vegetation biomass studies or erosion monitoring.

Point Cloud Based Change Detection - an Automated Approach for Cloud-based Services

NASA Astrophysics Data System (ADS)

Collins, Patrick; Bahr, Thomas

2016-04-01

The fusion of stereo photogrammetric point clouds with LiDAR data or terrain information derived from SAR interferometry has a significant potential for 3D topographic change detection. In the present case study latest point cloud generation and analysis capabilities are used to examine a landslide that occurred in the village of Malin in Maharashtra, India, on 30 July 2014, and affected an area of ca. 44.000 m2. It focuses on Pléiades high resolution satellite imagery and the Airbus DS WorldDEMTM as a product of the TanDEM-X mission. This case study was performed using the COTS software package ENVI 5.3. Integration of custom processes and automation is supported by IDL (Interactive Data Language). Thus, ENVI analytics is running via the object-oriented and IDL-based ENVITask API. The pre-event topography is represented by the WorldDEMTM product, delivered with a raster of 12 m x 12 m and based on the EGM2008 geoid (called pre-DEM). For the post-event situation a Pléiades 1B stereo image pair of the AOI affected was obtained. The ENVITask "GeneratePointCloudsByDenseImageMatching" was implemented to extract passive point clouds in LAS format from the panchromatic stereo datasets: • A dense image-matching algorithm is used to identify corresponding points in the two images. • A block adjustment is applied to refine the 3D coordinates that describe the scene geometry. • Additionally, the WorldDEMTM was input to constrain the range of heights in the matching area, and subsequently the length of the epipolar line. The "PointCloudFeatureExtraction" task was executed to generate the post-event digital surface model from the photogrammetric point clouds (called post-DEM). Post-processing consisted of the following steps: • Adding the geoid component (EGM 2008) to the post-DEM. • Pre-DEM reprojection to the UTM Zone 43N (WGS-84) coordinate system and resizing. • Subtraction of the pre-DEM from the post-DEM. • Filtering and threshold based classification of the DEM difference to analyze the surface changes in 3D. The automated point cloud generation and analysis introduced here can be embedded in virtually any existing geospatial workflow for operational applications. Three integration options were implemented in this case study: • Integration within any ArcGIS environment whether deployed on the desktop, in the cloud, or online. Execution uses a customized ArcGIS script tool. A Python script file retrieves the parameters from the user interface and runs the precompiled IDL code. That IDL code is used to interface between the Python script and the relevant ENVITasks. • Publishing the point cloud processing tasks as services via the ENVI Services Engine (ESE). ESE is a cloud-based image analysis solution to publish and deploy advanced ENVI image and data analytics to existing enterprise infrastructures. For this purpose the entire IDL code can be capsuled in a single ENVITask. • Integration in an existing geospatial workflow using the Python-to-IDL Bridge. This mechanism allows calling IDL code within Python on a user-defined platform. The results of this case study allow a 3D estimation of the topographic changes within the tectonically active and anthropogenically invaded Malin area after the landslide event. Accordingly, the point cloud analysis was correlated successfully with modelled displacement contours of the slope. Based on optical satellite imagery, such point clouds of high precision and density distribution can be obtained in a few minutes to support the operational monitoring of landslide processes.

Automatic registration of panoramic image sequence and mobile laser scanning data using semantic features

NASA Astrophysics Data System (ADS)

Li, Jianping; Yang, Bisheng; Chen, Chi; Huang, Ronggang; Dong, Zhen; Xiao, Wen

2018-02-01

Inaccurate exterior orientation parameters (EoPs) between sensors obtained by pre-calibration leads to failure of registration between panoramic image sequence and mobile laser scanning data. To address this challenge, this paper proposes an automatic registration method based on semantic features extracted from panoramic images and point clouds. Firstly, accurate rotation parameters between the panoramic camera and the laser scanner are estimated using GPS and IMU aided structure from motion (SfM). The initial EoPs of panoramic images are obtained at the same time. Secondly, vehicles in panoramic images are extracted by the Faster-RCNN as candidate primitives to be matched with potential corresponding primitives in point clouds according to the initial EoPs. Finally, translation between the panoramic camera and the laser scanner is refined by maximizing the overlapping area of corresponding primitive pairs based on the Particle Swarm Optimization (PSO), resulting in a finer registration between panoramic image sequences and point clouds. Two challenging urban scenes were experimented to assess the proposed method, and the final registration errors of these two scenes were both less than three pixels, which demonstrates a high level of automation, robustness and accuracy.

In vitro cytotoxicity induced by Clostridium perfringens isolate carrying a chromosomal cpe gene is exclusively dependent on sporulation and enterotoxin production.

PubMed

Yasugi, Mayo; Sugahara, Yuki; Hoshi, Hidenobu; Kondo, Kaori; Talukdar, Prabhat K; Sarker, Mahfuzur R; Yamamoto, Shigeki; Kamata, Yoichi; Miyake, Masami

2015-08-01

Clostridium perfringens type A is a common source of food poisoning (FP) and non-food-borne (NFB) gastrointestinal diseases in humans. In the intestinal tract, the vegetative cells sporulate and produce a major pathogenic factor, C. perfringens enterotoxin (CPE). Most type A FP isolates carry a chromosomal cpe gene, whereas NFB type A isolates typically carry a plasmid-encoded cpe. In vitro, the purified CPE protein binds to a receptor and forms pores, exerting a cytotoxic activity in epithelial cells. However, it remains unclear if CPE is indispensable for C. perfringens cytotoxicity. In this study, we examined the cytotoxicity of cpe-harboring C. perfringens isolates co-cultured with human intestinal epithelial Caco-2 cells. The FP strains showed severe cytotoxicity during sporulation and CPE production, but not during vegetative cell growth. While Caco-2 cells were intact during co-culturing with cpe-null mutant derivative of strain SM101 (a FP strain carrying a chromosomal cpe gene), the wild-type level cytotoxicity was observed with cpe-complemented strain. In contrast, both wild-type and cpe-null mutant derivative of the NFB strain F4969 induced Caco-2 cell death during both vegetative and sporulation growth. Collectively, the Caco-2 cell cytotoxicity caused by C. perfringens strain SM101 is considered to be exclusively dependent on CPE production, whereas some additional toxins should be involved in F4969-mediated in vitro cytotoxicity. Copyright © 2015 Elsevier Ltd. All rights reserved.

Registration of Vehicle-Borne Point Clouds and Panoramic Images Based on Sensor Constellations

PubMed Central

Yao, Lianbi; Wu, Hangbin; Li, Yayun; Meng, Bin; Qian, Jinfei; Liu, Chun; Fan, Hongchao

2017-01-01

A mobile mapping system (MMS) is usually utilized to collect environmental data on and around urban roads. Laser scanners and panoramic cameras are the main sensors of an MMS. This paper presents a new method for the registration of the point clouds and panoramic images based on sensor constellation. After the sensor constellation was analyzed, a feature point, the intersection of the connecting line between the global positioning system (GPS) antenna and the panoramic camera with a horizontal plane, was utilized to separate the point clouds into blocks. The blocks for the central and sideward laser scanners were extracted with the segmentation feature points. Then, the point clouds located in the blocks were separated from the original point clouds. Each point in the blocks was used to find the accurate corresponding pixel in the relative panoramic images via a collinear function, and the position and orientation relationship amongst different sensors. A search strategy is proposed for the correspondence of laser scanners and lenses of panoramic cameras to reduce calculation complexity and improve efficiency. Four cases of different urban road types were selected to verify the efficiency and accuracy of the proposed method. Results indicate that most of the point clouds (with an average of 99.7%) were successfully registered with the panoramic images with great efficiency. Geometric evaluation results indicate that horizontal accuracy was approximately 0.10–0.20 m, and vertical accuracy was approximately 0.01–0.02 m for all cases. Finally, the main factors that affect registration accuracy, including time synchronization amongst different sensors, system positioning and vehicle speed, are discussed. PMID:28398256

Point Cloud Based Approach to Stem Width Extraction of Sorghum

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

Jin, Jihui; Zakhor, Avideh

A revolution in the field of genomics has produced vast amounts of data and furthered our understanding of the genotypephenotype map, but is currently constrained by manually intensive or limited phenotype data collection. We propose an algorithm to estimate stem width, a key characteristic used for biomass potential evaluation, from 3D point cloud data collected by a robot equipped with a depth sensor in a single pass in a standard field. The algorithm applies a two step alignment to register point clouds in different frames, a Frangi filter to identify stemlike objects in the point cloud and an orientation basedmore » filter to segment out and refine individual stems for width estimation. Individually, detected stems which are split due to occlusions are merged and then registered with previously found stems in previous camera frames in order to track temporally. We then refine the estimates to produce an accurate histogram of width estimates per plot. Since the plants in each plot are genetically identical, distributions of the stem width per plot can be useful in identifying genetically superior sorghum for biofuels.« less

Airborne LIDAR point cloud tower inclination judgment

NASA Astrophysics Data System (ADS)

liang, Chen; zhengjun, Liu; jianguo, Qian

2016-11-01

Inclined transmission line towers for the safe operation of the line caused a great threat, how to effectively, quickly and accurately perform inclined judgment tower of power supply company safety and security of supply has played a key role. In recent years, with the development of unmanned aerial vehicles, unmanned aerial vehicles equipped with a laser scanner, GPS, inertial navigation is one of the high-precision 3D Remote Sensing System in the electricity sector more and more. By airborne radar scan point cloud to visually show the whole picture of the three-dimensional spatial information of the power line corridors, such as the line facilities and equipment, terrain and trees. Currently, LIDAR point cloud research in the field has not yet formed an algorithm to determine tower inclination, the paper through the existing power line corridor on the tower base extraction, through their own tower shape characteristic analysis, a vertical stratification the method of combining convex hull algorithm for point cloud tower scarce two cases using two different methods for the tower was Inclined to judge, and the results with high reliability.

Digital Investigations of AN Archaeological Smart Point Cloud: a Real Time Web-Based Platform to Manage the Visualisation of Semantical Queries

NASA Astrophysics Data System (ADS)

Poux, F.; Neuville, R.; Hallot, P.; Van Wersch, L.; Luczfalvy Jancsó, A.; Billen, R.

2017-05-01

While virtual copies of the real world tend to be created faster than ever through point clouds and derivatives, their working proficiency by all professionals' demands adapted tools to facilitate knowledge dissemination. Digital investigations are changing the way cultural heritage researchers, archaeologists, and curators work and collaborate to progressively aggregate expertise through one common platform. In this paper, we present a web application in a WebGL framework accessible on any HTML5-compatible browser. It allows real time point cloud exploration of the mosaics in the Oratory of Germigny-des-Prés, and emphasises the ease of use as well as performances. Our reasoning engine is constructed over a semantically rich point cloud data structure, where metadata has been injected a priori. We developed a tool that directly allows semantic extraction and visualisation of pertinent information for the end users. It leads to efficient communication between actors by proposing optimal 3D viewpoints as a basis on which interactions can grow.

Point Cloud Based Approach to Stem Width Extraction of Sorghum

DOE PAGES

Jin, Jihui; Zakhor, Avideh

2017-01-29

A revolution in the field of genomics has produced vast amounts of data and furthered our understanding of the genotypephenotype map, but is currently constrained by manually intensive or limited phenotype data collection. We propose an algorithm to estimate stem width, a key characteristic used for biomass potential evaluation, from 3D point cloud data collected by a robot equipped with a depth sensor in a single pass in a standard field. The algorithm applies a two step alignment to register point clouds in different frames, a Frangi filter to identify stemlike objects in the point cloud and an orientation basedmore » filter to segment out and refine individual stems for width estimation. Individually, detected stems which are split due to occlusions are merged and then registered with previously found stems in previous camera frames in order to track temporally. We then refine the estimates to produce an accurate histogram of width estimates per plot. Since the plants in each plot are genetically identical, distributions of the stem width per plot can be useful in identifying genetically superior sorghum for biofuels.« less

a Method for the Registration of Hemispherical Photographs and Tls Intensity Images

NASA Astrophysics Data System (ADS)

Schmidt, A.; Schilling, A.; Maas, H.-G.

2012-07-01

Terrestrial laser scanners generate dense and accurate 3D point clouds with minimal effort, which represent the geometry of real objects, while image data contains texture information of object surfaces. Based on the complementary characteristics of both data sets, a combination is very appealing for many applications, including forest-related tasks. In the scope of our research project, independent data sets of a plain birch stand have been taken by a full-spherical laser scanner and a hemispherical digital camera. Previously, both kinds of data sets have been considered separately: Individual trees were successfully extracted from large 3D point clouds, and so-called forest inventory parameters could be determined. Additionally, a simplified tree topology representation was retrieved. From hemispherical images, leaf area index (LAI) values, as a very relevant parameter for describing a stand, have been computed. The objective of our approach is to merge a 3D point cloud with image data in a way that RGB values are assigned to each 3D point. So far, segmentation and classification of TLS point clouds in forestry applications was mainly based on geometrical aspects of the data set. However, a 3D point cloud with colour information provides valuable cues exceeding simple statistical evaluation of geometrical object features and thus may facilitate the analysis of the scan data significantly.

2.5D Multi-View Gait Recognition Based on Point Cloud Registration

PubMed Central

Tang, Jin; Luo, Jian; Tjahjadi, Tardi; Gao, Yan

2014-01-01

This paper presents a method for modeling a 2.5-dimensional (2.5D) human body and extracting the gait features for identifying the human subject. To achieve view-invariant gait recognition, a multi-view synthesizing method based on point cloud registration (MVSM) to generate multi-view training galleries is proposed. The concept of a density and curvature-based Color Gait Curvature Image is introduced to map 2.5D data onto a 2D space to enable data dimension reduction by discrete cosine transform and 2D principle component analysis. Gait recognition is achieved via a 2.5D view-invariant gait recognition method based on point cloud registration. Experimental results on the in-house database captured by a Microsoft Kinect camera show a significant performance gain when using MVSM. PMID:24686727

Design of relative motion and attitude profiles for three-dimensional resident space object imaging with a laser rangefinder

NASA Astrophysics Data System (ADS)

Nayak, M.; Beck, J.; Udrea, B.

This paper focuses on the aerospace application of a single beam laser rangefinder (LRF) for 3D imaging, shape detection, and reconstruction in the context of a space-based space situational awareness (SSA) mission scenario. The primary limitation to 3D imaging from LRF point clouds is the one-dimensional nature of the single beam measurements. A method that combines relative orbital motion and scanning attitude motion to generate point clouds has been developed and the design and characterization of multiple relative motion and attitude maneuver profiles are presented. The target resident space object (RSO) has the shape of a generic telecommunications satellite. The shape and attitude of the RSO are unknown to the chaser satellite however, it is assumed that the RSO is un-cooperative and has fixed inertial pointing. All sensors in the metrology chain are assumed ideal. A previous study by the authors used pure Keplerian motion to perform a similar 3D imaging mission at an asteroid. A new baseline for proximity operations maneuvers for LRF scanning, based on a waypoint adaptation of the Hill-Clohessy-Wiltshire (HCW) equations is examined. Propellant expenditure for each waypoint profile is discussed and combinations of relative motion and attitude maneuvers that minimize the propellant used to achieve a minimum required point cloud density are studied. Both LRF strike-point coverage and point cloud density are maximized; the capability for 3D shape registration and reconstruction from point clouds generated with a single beam LRF without catalog comparison is proven. Next, a method of using edge detection algorithms to process a point cloud into a 3D modeled image containing reconstructed shapes is presented. Weighted accuracy of edge reconstruction with respect to the true model is used to calculate a qualitative “ metric” that evaluates effectiveness of coverage. Both edge recognition algorithms and the metric are independent of point cloud densit- , therefore they are utilized to compare the quality of point clouds generated by various attitude and waypoint command profiles. The RSO model incorporates diverse irregular protruding shapes, such as open sensor covers, instrument pods and solar arrays, to test the limits of the algorithms. This analysis is used to mathematically prove that point clouds generated by a single-beam LRF can achieve sufficient edge recognition accuracy for SSA applications, with meaningful shape information extractable even from sparse point clouds. For all command profiles, reconstruction of RSO shapes from the point clouds generated with the proposed method are compared to the truth model and conclusions are drawn regarding their fidelity.

Functional characterization of enzymes catalyzing ceramide phosphoethanolamine biosynthesis in mice.

PubMed

Bickert, Andreas; Ginkel, Christina; Kol, Matthijs; vom Dorp, Katharina; Jastrow, Holger; Degen, Joachim; Jacobs, René L; Vance, Dennis E; Winterhager, Elke; Jiang, Xian-Cheng; Dörmann, Peter; Somerharju, Pentti; Holthuis, Joost C M; Willecke, Klaus

2015-04-01

Besides bulk amounts of SM, mammalian cells produce small quantities of the SM analog ceramide phosphoethanolamine (CPE). Little is known about the biological role of CPE or enzymes responsible for CPE production. Heterologous expression studies revealed that SM synthase (SMS)2 is a bifunctional enzyme producing both SM and CPE, whereas SMS-related protein (SMSr) serves as monofunctional CPE synthase. Acute disruption of SMSr catalytic activity in cultured cells causes a rise in endoplasmic reticulum (ER) ceramides, fragmentation of ER exit sites, and induction of mitochondrial apoptosis. To address the relevance of CPE biosynthesis in vivo, we analyzed the tissue-specific distribution of CPE in mice and generated mouse lines lacking SMSr and SMS2 catalytic activity. We found that CPE levels were >300-fold lower than SM in all tissues examined. Unexpectedly, combined inactivation of SMSr and SMS2 significantly reduced, but did not eliminate, tissue-specific CPE pools and had no obvious impact on mouse development or fertility. While SMSr is widely expressed and serves as the principal CPE synthase in the brain, blocking its catalytic activity did not affect ceramide levels or secretory pathway integrity in the brain or any other tissue. Our data provide a first inventory of CPE species and CPE-biosynthetic enzymes in mammals. Copyright © 2015 by the American Society for Biochemistry and Molecular Biology, Inc.

Invariant-feature-based adaptive automatic target recognition in obscured 3D point clouds

NASA Astrophysics Data System (ADS)

Khuon, Timothy; Kershner, Charles; Mattei, Enrico; Alverio, Arnel; Rand, Robert

2014-06-01

Target recognition and classification in a 3D point cloud is a non-trivial process due to the nature of the data collected from a sensor system. The signal can be corrupted by noise from the environment, electronic system, A/D converter, etc. Therefore, an adaptive system with a desired tolerance is required to perform classification and recognition optimally. The feature-based pattern recognition algorithm architecture as described below is particularly devised for solving a single-sensor classification non-parametrically. Feature set is extracted from an input point cloud, normalized, and classifier a neural network classifier. For instance, automatic target recognition in an urban area would require different feature sets from one in a dense foliage area. The figure above (see manuscript) illustrates the architecture of the feature based adaptive signature extraction of 3D point cloud including LIDAR, RADAR, and electro-optical data. This network takes a 3D cluster and classifies it into a specific class. The algorithm is a supervised and adaptive classifier with two modes: the training mode and the performing mode. For the training mode, a number of novel patterns are selected from actual or artificial data. A particular 3D cluster is input to the network as shown above for the decision class output. The network consists of three sequential functional modules. The first module is for feature extraction that extracts the input cluster into a set of singular value features or feature vector. Then the feature vector is input into the feature normalization module to normalize and balance it before being fed to the neural net classifier for the classification. The neural net can be trained by actual or artificial novel data until each trained output reaches the declared output within the defined tolerance. In case new novel data is added after the neural net has been learned, the training is then resumed until the neural net has incrementally learned with the new novel data. The associative memory capability of the neural net enables the incremental learning. The back propagation algorithm or support vector machine can be utilized for the classification and recognition.

Application of mixed cloud point extraction for the analysis of six flavonoids in Apocynum venetum leaf samples by high performance liquid chromatography.

PubMed

Zhou, Jun; Sun, Jiang Bing; Xu, Xin Yu; Cheng, Zhao Hui; Zeng, Ping; Wang, Feng Qiao; Zhang, Qiong

2015-03-25

A simple, inexpensive and efficient method based on the mixed cloud point extraction (MCPE) combined with high performance liquid chromatography was developed for the simultaneous separation and determination of six flavonoids (rutin, hyperoside, quercetin-3-O-sophoroside, isoquercitrin, astragalin and quercetin) in Apocynum venetum leaf samples. The non-ionic surfactant Genapol X-080 and cetyl-trimethyl ammonium bromide (CTAB) was chosen as the mixed extracting solvent. Parameters that affect the MCPE processes, such as the content of Genapol X-080 and CTAB, pH, salt content, extraction temperature and time were investigated and optimized. Under the optimized conditions, the calibration curve for six flavonoids were all linear with the correlation coefficients greater than 0.9994. The intra-day and inter-day precision (RSD) were below 8.1% and the limits of detection (LOD) for the six flavonoids were 1.2-5.0 ng mL(-1) (S/N=3). The proposed method was successfully used to separate and determine the six flavonoids in A. venetum leaf samples. Copyright © 2015 Elsevier B.V. All rights reserved.

Computing multiple aggregation levels and contextual features for road facilities recognition using mobile laser scanning data

NASA Astrophysics Data System (ADS)

Yang, Bisheng; Dong, Zhen; Liu, Yuan; Liang, Fuxun; Wang, Yongjun

2017-04-01

In recent years, updating the inventory of road infrastructures based on field work is labor intensive, time consuming, and costly. Fortunately, vehicle-based mobile laser scanning (MLS) systems provide an efficient solution to rapidly capture three-dimensional (3D) point clouds of road environments with high flexibility and precision. However, robust recognition of road facilities from huge volumes of 3D point clouds is still a challenging issue because of complicated and incomplete structures, occlusions and varied point densities. Most existing methods utilize point or object based features to recognize object candidates, and can only extract limited types of objects with a relatively low recognition rate, especially for incomplete and small objects. To overcome these drawbacks, this paper proposes a semantic labeling framework by combing multiple aggregation levels (point-segment-object) of features and contextual features to recognize road facilities, such as road surfaces, road boundaries, buildings, guardrails, street lamps, traffic signs, roadside-trees, power lines, and cars, for highway infrastructure inventory. The proposed method first identifies ground and non-ground points, and extracts road surfaces facilities from ground points. Non-ground points are segmented into individual candidate objects based on the proposed multi-rule region growing method. Then, the multiple aggregation levels of features and the contextual features (relative positions, relative directions, and spatial patterns) associated with each candidate object are calculated and fed into a SVM classifier to label the corresponding candidate object. The recognition performance of combining multiple aggregation levels and contextual features was compared with single level (point, segment, or object) based features using large-scale highway scene point clouds. Comparative studies demonstrated that the proposed semantic labeling framework significantly improves road facilities recognition precision (90.6%) and recall (91.2%), particularly for incomplete and small objects.

Clostridium Perfringens Enterotoxin (CPE) and CPE-Binding Domain (c-CPE) for the Detection and Treatment of Gynecologic Cancers

PubMed Central

Black, Jonathan D.; Lopez, Salvatore; Cocco, Emiliano; Schwab, Carlton L.; English, Diana P.; Santin, Alessandro D.

2015-01-01

Clostridium perfringens enterotoxin (CPE) is a three-domain polypeptide, which binds to Claudin-3 and Claudin-4 with high affinity. Because these receptors are highly differentially expressed in many human tumors, claudin-3 and claudin-4 may provide an efficient molecular tool to specifically identify and target biologically aggressive human cancer cells for CPE-specific binding and cytolysis. In this review we will discuss these surface proteins as targets for the detection and treatment of chemotherapy-resistant gynecologic malignancies overexpressing claudin-3 and -4 using CPE-based theranostic agents. We will also discuss the use of fluorescent c-CPE peptide in the operative setting for real time detection of micro-metastatic tumors during surgery and review the potential role of CPE in other medical applications. PMID:25835384

3D micro-mapping: Towards assessing the quality of crowdsourcing to support 3D point cloud analysis

NASA Astrophysics Data System (ADS)

Herfort, Benjamin; Höfle, Bernhard; Klonner, Carolin

2018-03-01

In this paper, we propose a method to crowdsource the task of complex three-dimensional information extraction from 3D point clouds. We design web-based 3D micro tasks tailored to assess segmented LiDAR point clouds of urban trees and investigate the quality of the approach in an empirical user study. Our results for three different experiments with increasing complexity indicate that a single crowdsourcing task can be solved in a very short time of less than five seconds on average. Furthermore, the results of our empirical case study reveal that the accuracy, sensitivity and precision of 3D crowdsourcing are high for most information extraction problems. For our first experiment (binary classification with single answer) we obtain an accuracy of 91%, a sensitivity of 95% and a precision of 92%. For the more complex tasks of the second Experiment 2 (multiple answer classification) the accuracy ranges from 65% to 99% depending on the label class. Regarding the third experiment - the determination of the crown base height of individual trees - our study highlights that crowdsourcing can be a tool to obtain values with even higher accuracy in comparison to an automated computer-based approach. Finally, we found out that the accuracy of the crowdsourced results for all experiments is hardly influenced by characteristics of the input point cloud data and of the users. Importantly, the results' accuracy can be estimated using agreement among volunteers as an intrinsic indicator, which makes a broad application of 3D micro-mapping very promising.

Clostridium perfringens enterotoxin as a potential drug for intravesical treatment of bladder cancer.

PubMed

Gabig, Theodore G; Waltzer, Wayne C; Whyard, Terry; Romanov, Victor

2016-09-16

The current intravesical treatment of bladder cancer (BC) is limited to a few chemotherapeutics that show imperfect effectiveness and are associated with some serious complications. Thus, there is an urgent need for alternative therapies, especially for patients with high-risk non-muscle invasive (NMIBC). Clostridium perfringens enterotoxin (CPE), cytolytic protein binds to its receptors: claudin 3 and 4 that are expressed in epithelial cells. This binding is followed by rapid cell death. Claudin 4 is present in several epithelial tissue including bladder urothelium and its expression is elevated in some forms of BC. In addition to directly targeting BC cells, binding of CPE to claudins increases urothelium permeability that creates conditions for better accession of the tumor. Therefore, we evaluated CPE as a candidate for intravesical treatment of BC using a cellular model. We examined cytotoxicity of CPE against BC cells lines and 3D cultures of cells derived from surgical samples. To better elucidate cellular mechanisms, activated by CPE and to consider the use of CPE non-toxic fragment (C-CPE) for combination treatment with other drugs we synthesized C-CPE, compared its cytotoxic activity with CPE and examined claudin 4 expression and intracellular localization after C-CPE treatment. CPE induced cell death after 1 h in low aggressive RT4 cells, in moderately aggressive 5637 cells and in the primary 3D cultures of BC cells derived from NMIBC. Conversely, non-transformed urothelial cells and cells derived from highly aggressive tumor (T24) survived this treatment. The reason for this resistance to CPE might be the lower expression of CLDNs or their inaccessibility for CPE in these cells. C-CPE treatment for 48 h did not affect cell viability in tested cells, but declined expression of CLDN4 in RT4 cells. C-CPE increased sensitivity of RT4 cells to Mitommycin C and Dasatinib. To better understand mechanisms of this effect we examined expression and phosphorylation status of EphA2 and Src after C-CPE treatment and found changes in expression and phosphorylated status of these regulatory molecules. These observations show that after additional preclinical studies CPE and C-CPE in combinations with other drugs can be considered as a potential modalities for intravesical treatment of BC because of its ability to effectively destroy BC cells expressing claudin 4 and low toxicity against normal urothelium. Copyright © 2016 Elsevier Inc. All rights reserved.

Self-Similar Spin Images for Point Cloud Matching

NASA Astrophysics Data System (ADS)

Pulido, Daniel

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

An evaluation of a toolkit for the early detection, management, and control of carbapenemase-producing Enterobacteriaceae: a survey of acute hospital trusts in England.

PubMed

Coope, C M; Verlander, N Q; Schneider, A; Hopkins, S; Welfare, W; Johnson, A P; Patel, B; Oliver, I

2018-03-09

Following hospital outbreaks of carbapenemase-producing Enterobacteriaceae (CPE), Public Health England published a toolkit in December 2013 to promote the early detection, management, and control of CPE colonization and infection in acute hospital settings. To examine awareness, uptake, implementation and usefulness of the CPE toolkit and identify potential barriers and facilitators to its adoption in order to inform future guidance. A cross-sectional survey of National Health Service (NHS) acute trusts was conducted in May 2016. Descriptive analysis and multivariable regression models were conducted, and narrative responses were analysed thematically and informed using behaviour change theory. Most (92%) acute trusts had a written CPE plan. Fewer (75%) reported consistent compliance with screening and isolation of CPE risk patients. Lower prioritization and weaker senior management support for CPE prevention were associated with poorer compliance. Awareness of the CPE toolkit was high and all trusts with patients infected or colonized with CPE had used the toolkit either as provided (32%), or to inform (65%) their own local CPE plan. Despite this, many respondents (80%) did not believe that the CPE toolkit guidance offered an effective means to prevent CPE or was practical to follow. CPE prevention and control requires robust IPC measures. Successful implementation can be hindered by a complex set of factors related to their practical execution, insufficient resources and a lack of confidence in the effectiveness of the guidance. Future CPE guidance would benefit from substantive user involvement, processes for ongoing feedback, and regular guidance updates. Copyright © 2018 The Healthcare Infection Society. All rights reserved.

Sex determination based on amelogenin DNA by modified electrode with gold nanoparticle.

PubMed

Mazloum-Ardakani, Mohammad; Rajabzadeh, Nooshin; Benvidi, Ali; Heidari, Mohammad Mehdi

2013-12-15

We have developed a simple and renewable electrochemical biosensor based on carbon paste electrode (CPE) for the detection of DNA synthesis and hybridization. CPE was modified with gold nanoparticles (AuNPs), which are helpful for immobilization of thiolated bioreceptors. AuNPs were characterized by scanning electron microscopy (SEM). Self-assembled monolayers (SAMs) of thiolated single-stranded DNA (SH-ssDNA) of the amelogenin gene was formed on CPE. The immobilization of the probe and its hybridization with the target DNA was optimized using different experimental conditions. The modified electrode was characterized by electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV). The electrochemical response of ssDNA hybridization and DNA synthesis was measured using differential pulse voltammetry (DPV) with methylene blue (MB) as an electroactive indicator. The new biosensor can distinguish between complementary and non-complementary strands of amelogenin ssDNA. Genomic DNA was extracted from blood and was detected based on changes in the MB reduction signal. These results demonstrated that the new biosensor could be used for sex determination. The proposed biosensor in this study could be used for detection and discrimination of polymerase chain reaction (PCR) products of amelogenin DNA. Copyright © 2013 Elsevier Inc. All rights reserved.

Forest understory trees can be segmented accurately within sufficiently dense airborne laser scanning point clouds.

PubMed

Hamraz, Hamid; Contreras, Marco A; Zhang, Jun

2017-07-28

Airborne laser scanning (LiDAR) point clouds over large forested areas can be processed to segment individual trees and subsequently extract tree-level information. Existing segmentation procedures typically detect more than 90% of overstory trees, yet they barely detect 60% of understory trees because of the occlusion effect of higher canopy layers. Although understory trees provide limited financial value, they are an essential component of ecosystem functioning by offering habitat for numerous wildlife species and influencing stand development. Here we model the occlusion effect in terms of point density. We estimate the fractions of points representing different canopy layers (one overstory and multiple understory) and also pinpoint the required density for reasonable tree segmentation (where accuracy plateaus). We show that at a density of ~170 pt/m² understory trees can likely be segmented as accurately as overstory trees. Given the advancements of LiDAR sensor technology, point clouds will affordably reach this required density. Using modern computational approaches for big data, the denser point clouds can efficiently be processed to ultimately allow accurate remote quantification of forest resources. The methodology can also be adopted for other similar remote sensing or advanced imaging applications such as geological subsurface modelling or biomedical tissue analysis.

The Iqmulus Urban Showcase: Automatic Tree Classification and Identification in Huge Mobile Mapping Point Clouds

NASA Astrophysics Data System (ADS)

Böhm, J.; Bredif, M.; Gierlinger, T.; Krämer, M.; Lindenberg, R.; Liu, K.; Michel, F.; Sirmacek, B.

2016-06-01

Current 3D data capturing as implemented on for example airborne or mobile laser scanning systems is able to efficiently sample the surface of a city by billions of unselective points during one working day. What is still difficult is to extract and visualize meaningful information hidden in these point clouds with the same efficiency. This is where the FP7 IQmulus project enters the scene. IQmulus is an interactive facility for processing and visualizing big spatial data. In this study the potential of IQmulus is demonstrated on a laser mobile mapping point cloud of 1 billion points sampling ~ 10 km of street environment in Toulouse, France. After the data is uploaded to the IQmulus Hadoop Distributed File System, a workflow is defined by the user consisting of retiling the data followed by a PCA driven local dimensionality analysis, which runs efficiently on the IQmulus cloud facility using a Spark implementation. Points scattering in 3 directions are clustered in the tree class, and are separated next into individual trees. Five hours of processing at the 12 node computing cluster results in the automatic identification of 4000+ urban trees. Visualization of the results in the IQmulus fat client helps users to appreciate the results, and developers to identify remaining flaws in the processing workflow.

Cytotoxicity and antiviral activity of electrochemical - synthesized silver nanoparticles against poliovirus.

PubMed

Huy, Tran Quang; Hien Thanh, Nguyen Thi; Thuy, Nguyen Thanh; Chung, Pham Van; Hung, Pham Ngoc; Le, Anh-Tuan; Hong Hanh, Nguyen Thi

2017-03-01

Silver nanoparticles (AgNPs) have been proven to have noticeable cytotoxicity in vitro and antiviral activity against some types of enveloped viruses. This paper presents the cytotoxicity and antiviral activity of pure AgNPs synthesized by the electrochemical method, towards cell culture and poliovirus (a non-enveloped virus). Prepared AgNPs were characterized by ultraviolet-visible spectroscopy, energy-dispersive X-ray spectroscopy and transmission electron microscopy. Before incubation with poliovirus, different concentrations of AgNPs were added to human rhabdomyosarcoma (RD) cell monolayers seeded in 96 well plates for testing their cytotoxicity. The in vitro cytotoxicity and anti-poliovirus activity of AgNPs were daily assessed for cytopathic effect (CPE) through inverted light microscopy. CPE in the tested wells was determined in comparison with those in wells of negative and positive control. Structure analysis showed that AgNPs were formed with a quasi-spherical shape with mean size about 7.1nm and high purity. No CPE of RD cells was seen in wells at the time point of 48h post-incubation with AgNPs at concentration up to 100ppm. The anti-poliovirus activity of AgNPs was determined at 3.13ppm corresponding to the viral concentration of 1TCID 50 (Tissue Culture Infective Dose) after 30min, and 10TCID 50 after 60min, the cell viability was found up to 98% at 48h post-infection, with no CPE found. Whereas, a strong CPE of RD cells was found at 48h post-infection with the mixture of AgNPs and poliovirus at concentration of 100TCID 50 , and in wells of positive controls. With mentioned advantages, electrochemical-synthesized AgNPs are promising candidate for advanced biomedical and disinfection applications. Copyright © 2016 Elsevier B.V. All rights reserved.

Automatic registration of Iphone images to LASER point clouds of the urban structures using shape features

NASA Astrophysics Data System (ADS)

Sirmacek, B.; Lindenbergh, R. C.; Menenti, M.

2013-10-01

Fusion of 3D airborne laser (LIDAR) data and terrestrial optical imagery can be applied in 3D urban modeling and model up-dating. The most challenging aspect of the fusion procedure is registering the terrestrial optical images on the LIDAR point clouds. In this article, we propose an approach for registering these two different data from different sensor sources. As we use iPhone camera images which are taken in front of the interested urban structure by the application user and the high resolution LIDAR point clouds of the acquired by an airborne laser sensor. After finding the photo capturing position and orientation from the iPhone photograph metafile, we automatically select the area of interest in the point cloud and transform it into a range image which has only grayscale intensity levels according to the distance from the image acquisition position. We benefit from local features for registering the iPhone image to the generated range image. In this article, we have applied the registration process based on local feature extraction and graph matching. Finally, the registration result is used for facade texture mapping on the 3D building surface mesh which is generated from the LIDAR point cloud. Our experimental results indicate possible usage of the proposed algorithm framework for 3D urban map updating and enhancing purposes.

Bicarbonate and amino acids are co-germinants for spores of Clostridium perfringens type A isolates carrying plasmid-borne enterotoxin gene.

PubMed

Alnoman, Maryam; Udompijitkul, Pathima; Banawas, Saeed; Sarker, Mahfuzur R

2018-02-01

Clostridium perfringens type A isolates carrying a chromosomal enterotoxin (cpe) gene (C-cpe) are generally linked to food poisoning, while isolates carrying cpe on a plasmid (P-cpe) are associated with non-food-borne gastrointestinal diseases. Both C-cpe and P-cpe isolates can form metabolically dormant spores, which through germination process return to actively growing cells to cause diseases. In our previous study, we showed that only 3 out of 20 amino acids (aa) in phosphate buffer (pH 7.0) triggered germination of spores of P-cpe isolates (P-cpe spores). We now found that 14 out of 20 individual aa tested induced germination of P-cpe spores in the presence of bicarbonate buffer (pH 7.0). However, no significant spore germination was observed with bicarbonate (pH 7.0) alone, indicating that aa and bicarbonate are co-germinants for P-cpe spores. P-cpe strain F4969 gerKC spores did not germinate, and gerAA spores germinated extremely poorly as compared to wild-type and gerKA spores with aa-bicarbonate (pH 7.0) co-germinants. The germination defects in gerKC and gerAA spores were partially restored by complementing gerKC or gerAA spores with wild-type gerKC or gerAA, respectively. Collectively, this study identified aa-bicarbonate as a novel nutrient germinant for P-cpe spores and provided evidence that GerKC and GerAA play major roles in aa-bicarbonate induced germination. Copyright © 2017 Elsevier Ltd. All rights reserved.

Proanthocyanidins Modulate MicroRNA Expression in Human HepG2 Cells

PubMed Central

Arola-Arnal, Anna; Bladé, Cinta

2011-01-01

Mi(cro)RNAs are small non-coding RNAs of 18-25 nucleotides in length that modulate gene expression at the post-transcriptional level. These RNAs have been shown to be involved in a several biological processes, human diseases and metabolic disorders. Proanthocyanidins, which are the most abundant polyphenol class in the human diet, have positive health effects on a variety of metabolic disorders such as inflammation, obesity, diabetes and insulin resistance. The present study aimed to evaluate whether proanthocyanidin-rich natural extracts modulate miRNA expression. Using microarray analysis and Q-PCR, we investigated miRNA expression in HepG2 cells treated with proanthocyanidins. Our results showed that when HepG2 cells were treated with grape seed proanthocyanidin extract (GSPE), cocoa proanthocyanidin extract (CPE) or pure epigallocatechin gallate isolated from green tea (EGCG), fifteen, six and five differentially expressed miRNAs, respectively, were identified out of 904 mRNAs. Specifically, miR-30b* was downregulated by the three treatments, and treatment with GSPE or CPE upregulated miR-1224-3p, miR-197 and miR-532-3p. Therefore, these results provide evidence of the capacity of dietary proanthocyanidins to influence microRNA expression, suggesting a new mechanism of action of proanthocyanidins. PMID:21998738

Reduction of Aspergillus niger Virulence in Apple Fruits by Deletion of the Catalase Gene cpeB.

PubMed

Zhang, Meng-Ke; Tang, Jun; Huang, Zhong-Qin; Hu, Kang-Di; Li, Yan-Hong; Han, Zhuo; Chen, Xiao-Yan; Hu, Lan-Ying; Yao, Gai-Fang; Zhang, Hua

2018-05-30

Aspergillus niger, a common saprophytic fungus, causes rot in many fruits. We studied the role of a putative catalase-peroxidase-encoding gene, cpeB, in oxidative stress and virulence in fruit. The cpeB gene was deleted in A. niger by homologous recombination, and the Δ cpeB mutant showed decreased CAT activity compared with that of the wild type. The cpeB gene deletion caused increased sensitivity to H 2 O 2 stress, and spore germination was significantly reduced; in addition, the reactive-oxygen-species (ROS) metabolites superoxide anions (·O 2 - ), hydrogen peroxide (H 2 O 2 ), and malondialdehyde (MDA) accumulated in the Δ cpeB mutant during H 2 O 2 stress. Furthermore, ROS metabolism in A. niger infected apples was determined, and our results showed that the Δ cpeB mutant induced an attenuated response in apple fruit during the fruit-pathogen interaction; the cpeB gene deletion significantly reduced the development of lesions, suggesting that the cpeB gene in A. niger is essential for full virulence in apples.

A new dispersive liquid-liquid microextraction using ionic liquid based microemulsion coupled with cloud point extraction for determination of copper in serum and water samples.

PubMed

Arain, Salma Aslam; Kazi, Tasneem Gul; Afridi, Hassan Imran; Arain, Mariam Shahzadi; Panhwar, Abdul Haleem; Khan, Naeemullah; Baig, Jameel Ahmed; Shah, Faheem

2016-04-01

A simple and rapid dispersive liquid-liquid microextraction procedure based on ionic liquid assisted microemulsion (IL-µE-DLLME) combined with cloud point extraction has been developed for preconcentration copper (Cu(2+)) in drinking water and serum samples of adolescent female hepatitits C (HCV) patients. In this method a ternary system was developed to form microemulsion (µE) by phase inversion method (PIM), using ionic liquid, 1-butyl-3-methylimidazolium hexafluorophosphate ([C4mim][PF6]) and nonionic surfactant, TX-100 (as a stabilizer in aqueous media). The Ionic liquid microemulsion (IL-µE) was evaluated through visual assessment, optical light microscope and spectrophotometrically. The Cu(2+) in real water and aqueous acid digested serum samples were complexed with 8-hydroxyquinoline (oxine) and extracted into IL-µE medium. The phase separation of stable IL-µE was carried out by the micellar cloud point extraction approach. The influence of of different parameters such as pH, oxine concentration, centrifugation time and rate were investigated. At optimized experimental conditions, the limit of detection and enhancement factor were found to be 0.132 µg/L and 70 respectively, with relative standard deviation <5%. In order to validate the developed method, certified reference materials (SLRS-4 Riverine water) and human serum (Sero-M10181) were analyzed. The resulting data indicated a non-significant difference in obtained and certified values of Cu(2+). The developed procedure was successfully applied for the preconcentration and determination of trace levels of Cu(2+) in environmental and biological samples. Copyright © 2015 Elsevier Inc. All rights reserved.

Alternative Methods for Estimating Plane Parameters Based on a Point Cloud

NASA Astrophysics Data System (ADS)

Stryczek, Roman

2017-12-01

Non-contact measurement techniques carried out using triangulation optical sensors are increasingly popular in measurements with the use of industrial robots directly on production lines. The result of such measurements is often a cloud of measurement points that is characterized by considerable measuring noise, presence of a number of points that differ from the reference model, and excessive errors that must be eliminated from the analysis. To obtain vector information points contained in the cloud that describe reference models, the data obtained during a measurement should be subjected to appropriate processing operations. The present paperwork presents an analysis of suitability of methods known as RANdom Sample Consensus (RANSAC), Monte Carlo Method (MCM), and Particle Swarm Optimization (PSO) for the extraction of the reference model. The effectiveness of the tested methods is illustrated by examples of measurement of the height of an object and the angle of a plane, which were made on the basis of experiments carried out at workshop conditions.

Automatic Monitoring of Tunnel Deformation Based on High Density Point Clouds Data

NASA Astrophysics Data System (ADS)

Du, L.; Zhong, R.; Sun, H.; Wu, Q.

2017-09-01

An automated method for tunnel deformation monitoring using high density point clouds data is presented. Firstly, the 3D point clouds data are converted to two-dimensional surface by projection on the XOY plane, the projection point set of central axis on XOY plane named Uxoy is calculated by combining the Alpha Shape algorithm with RANSAC (Random Sampling Consistency) algorithm, and then the projection point set of central axis on YOZ plane named Uyoz is obtained by highest and lowest points which are extracted by intersecting straight lines that through each point of Uxoy and perpendicular to the two -dimensional surface with the tunnel point clouds, Uxoy and Uyoz together form the 3D center axis finally. Secondly, the buffer of each cross section is calculated by K-Nearest neighbor algorithm, and the initial cross-sectional point set is quickly constructed by projection method. Finally, the cross sections are denoised and the section lines are fitted using the method of iterative ellipse fitting. In order to improve the accuracy of the cross section, a fine adjustment method is proposed to rotate the initial sectional plane around the intercept point in the horizontal and vertical direction within the buffer. The proposed method is used in Shanghai subway tunnel, and the deformation of each section in the direction of 0 to 360 degrees is calculated. The result shows that the cross sections becomes flat circles from regular circles due to the great pressure at the top of the tunnel

Voltammetric Determination of Anethole on La2O3/CPE and BDDE

PubMed Central

Dziubaniuk, Małgorzata

2018-01-01

In this work, DPV determination of anethole was presented using various carbon, two-diameter (1.5 and 3 mm) electrodes, that is, BDD, GC, CP, and CP doped by La2O3 and CeO2 nanoparticles. La2O3/CPE to our best knowledge was proposed first time. Cyclic voltammograms confirmed totally irreversible electrode electrooxidation process, controlled by diffusion, in which two electrons take part. The most satisfactory sensitivity 0.885 ± 0.016 µA/mg L−1 in 0.1 mol L−1 acetate buffer was obtained for La2O3/CPE with the correlation coefficient r of 0.9993, while for BDDE it was 0.135 ± 0.003 µA/mg L−1 with r of 0.9990. The lowest detection limit of 0.004 mg L−1 was reached on La2O3/CPE (3 mm), what may be compared with the most sensitive conjugate methods, but in the proposed approach, no sample preparation and analyte separation was needed. Anethole was successfully determined in specially prepared ethanol extracts of herbal mixtures of various compositions, which imitated real products. The proposed procedure was verified in analysis of commercial products, that is, anise essential oil, which contains a large concentration of anethole, and in alcohol drinks like Metaxa, Ouzo, and Rakija, in which the considered analyte occurs on trace levels. Structure and properties of the considered nanopowders and graphite pastes were investigated by EDX, SEM, and EIS. PMID:29675284

Alberta CancerBridges development of a care plan evaluation measure

PubMed Central

Giese-Davis, J.; Sisler, J.; Zhong, L.; Brandelli, Y.; McCormick, J.L.; Railton, C.; Shirt, L.; Lau, H.; Hao, D.; Chobanuk, J.; Walley, B.; Joy, A.A.; Taylor, A.; Carlson, L.

2018-01-01

Background No standardized measures specifically assess cancer survivors’ and healthcare providers’ experience of Survivor Care Plans (scps). We sought to develop two care plan evaluation (cpe) measures, one for survivors (cpe-s) and one for healthcare providers (cpe-p), examine initial psychometric qualities in Alberta, and assess generalizability in Manitoba, Canada. Methods We developed the initial measures using convenience samples of breast (n = 35) and head and neck (n = 18) survivors who received scps at the end of active cancer-centre treatment. After assessing Alberta’s scp concordance with Institute of Medicine (iom) recommendations using a published coding scheme, we examined psychometric qualities for the cpe-s and cpe-p. We examined generalizability in Manitoba, Canada, with colorectal survivors discharged to primary care providers for follow-up (n = 75). Results We demonstrated acceptable internal consistency for the cpe-s and cpe-p subscales and total score after eliminating one item per subscale for cpe-s, two for cpe-p, resulting in revised scales with four 7-item and 6-item subscales, respectively. Subscale scores correlated highly indicating that for each measure the total score may be the most reliable and valid. We provide initial cpe-s discriminant, convergent, and predictive validity using the total score. Using the Manitoba sample, initial psychometrics similarly indicated good generalizability across differences in tumour groups, scp, and location. Conclusions We recommend the revised cpe-s and cpe-p for further use and development. Studies documenting the creation and standardization of scp evaluations are few, and we recommend further development of patient experience measures to improve both clinical practice and the specificity of research questions. PMID:29507497

Antiretroviral neuropenetration scores better correlate with cognitive performance of HIV-infected patients after accounting for drug susceptibility.

PubMed

Fabbiani, Massimiliano; Grima, Pierfrancesco; Milanini, Benedetta; Mondi, Annalisa; Baldonero, Eleonora; Ciccarelli, Nicoletta; Cauda, Roberto; Silveri, Maria C; De Luca, Andrea; Di Giambenedetto, Simona

2015-01-01

The aim of the study was to explore how viral resistance and antiretroviral central nervous system (CNS) penetration could impact on cognitive performance of HIV-infected patients. We performed a multicentre cross-sectional study enrolling HIV-infected patients undergoing neuropsychological testing, with a previous genotypic resistance test on plasma samples. CNS penetration-effectiveness (CPE) scores and genotypic susceptibility scores (GSS) were calculated for each regimen. A composite score (CPE-GSS) was then constructed. Factors associated with cognitive impairment were investigated by logistic regression analysis. A total of 215 patients were included. Mean CPE was 7.1 (95% CI 6.9, 7.3) with 206 (95.8%) patients showing a CPE≥6. GSS correction decreased the CPE value in 21.4% (mean 6.5, 95% CI 6.3, 6.7), 26.5% (mean 6.4, 95% CI 6.1, 6.6) and 24.2% (mean 6.4, 95% CI 6.2, 6.6) of subjects using ANRS, HIVDB and REGA rules, respectively. Overall, 66 (30.7%) patients were considered cognitively impaired. No significant association could be demonstrated between CPE and cognitive impairment. However, higher GSS-CPE was associated with a lower risk of cognitive impairment (CPE-GSSANRS odds ratio 0.75, P=0.022; CPE-GSSHIVDB odds ratio 0.77, P=0.038; CPE-GSSREGA odds ratio 0.78, P=0.038). Overall, a cutoff of CPE-GSS≥5 seemed the most discriminatory according to each different interpretation system. GSS-corrected CPE score showed a better correlation with neurocognitive performance than the standard CPE score. These results suggest that antiretroviral drug susceptibility, besides drug CNS penetration, can play a role in the control of HIV-associated neurocognitive disorders.

Chrysin and its phosphate ester inhibit cell proliferation and induce apoptosis in Hela cells.

PubMed

Zhang, Ting; Chen, Xiaolan; Qu, Lingbo; Wu, Jinglan; Cui, Ran; Zhao, Yufen

2004-12-01

To improve the biological activities of chrysin (CR), we synthesize Diethyl Chysin-7-yl phosphate (CPE: C(19)H(19)O(7)P) and tetraethyl bis-phosphoric ester of chrysin (CP: C(23)H(28)O(10)P(2)) through a simplified Atheron-Todd reaction. The interactions of the CR and CPE with lysozyme were explored by electrospray ionization mass spectrometry (ESI) and fluorescence spectrometry method. Experimental results indicate that CPE could form the noncovalent compound with lysozyme, while the interaction of the CR with lysozyme was not detected. In addition, whether and how the compounds CPE and CP affect proliferation and apoptosis in human cervical cancer Hela cells were investigated. Moreover, the effects of CPE and CP in Hela cells were compared with that of the nonmodified CR compound. The Hela cells were co-cultured with CR, CP, and CPE as experimental groups, respectively, and corresponding control groups treated without CR, CP, and CPE. The proliferation and apoptosis were detected using MTT assay, HCl denatured-methyl green-pyronin staining, PCNA immunohistochemistry and TUNEL techniques. The cell growth IC(50), relative absorbance (RA), proliferating index (PI), PCNA-IR (immunoreactivity IR) integration value (IV), and apoptosis index (AI) were calculated and their correlation was analyzed in each group. The results show that all CR, CP, and CPE could inhibit proliferation and induce apoptosis in Hela cells. Moreover, the effects of CP and CPE were more potent than that of CR. The CP and CPE were proved to be a kind of stronger apoptosis inducers than nonphosphated CR. There was a negative correlation between proliferation and apoptosis. In conclusion, the CR, CP, and CPE could effectively inhibit growth by down-regulated expression of PCNA, and induce apoptosis in Hela cells. The efficiency of the modified CP and CPE preceded nonmodified CR compounds. The CP and CPE may be a new potential anti-cancer drug for therapy of human cervical carcinoma.

Mandatory continuing professional education in pharmacy: the Singapore experience.

PubMed

Ang, Hui-Gek; Pua, Yong-Hao; Subari, Nur Azah

2013-08-01

Mandatory Continuing Professional Education (CPE) for the renewal of pharmacists' practising certificate was implemented in Singapore in 2008 OBJECTIVE: To study pharmacists' perceptions and attitudes about the impact of mandatory CPE in Singapore. Singapore. Internet-based questionnaire survey, conducted between May and June 2011. Pharmacists' perceptions and attitudes toward mandatory CPE and the perceived difficulty in fulfilling the CPE requirements. The overall survey response rate was 52 % (840/1,609). Of the respondents, 32 % were non-practising, 49 % were practising in patient care areas, and 19 % were practising in non-patient care areas. More than half the pharmacists agreed that mandatory CPE (1) enhanced or increased their knowledge base and skills (70 %; 95 % CI 67-73 %), (2) motivated them to continually learn (64 %; 95 % CI, 60-67 %), and (3) motivated them to reflect on their professional practice or work (58 %; 95 % CI, 54-61 %). Mandatory CPE was not perceived to enhance or increase employability. Non-practising pharmacists appeared to have the greatest difficulty meeting the CPE requirements. In general, pharmacists value mandatory CPE more for positive professional reasons than for employability reasons. The survey results may serve as useful baseline data for future studies of pharmacists' perceptions and attitudes toward CPE in Singapore.

Clostridium perfringens Enterotoxin: Action, Genetics, and Translational Applications

PubMed Central

Freedman, John C.; Shrestha, Archana; McClane, Bruce A.

2016-01-01

Clostridium perfringens enterotoxin (CPE) is responsible for causing the gastrointestinal symptoms of several C. perfringens food- and nonfood-borne human gastrointestinal diseases. The enterotoxin gene (cpe) is located on either the chromosome (for most C. perfringens type A food poisoning strains) or large conjugative plasmids (for the remaining type A food poisoning and most, if not all, other CPE-producing strains). In all CPE-positive strains, the cpe gene is strongly associated with insertion sequences that may help to assist its mobilization and spread. During disease, CPE is produced when C. perfringens sporulates in the intestines, a process involving several sporulation-specific alternative sigma factors. The action of CPE starts with its binding to claudin receptors to form a small complex; those small complexes then oligomerize to create a hexameric prepore on the membrane surface. Beta hairpin loops from the CPE molecules in the prepore assemble into a beta barrel that inserts into the membrane to form an active pore that enhances calcium influx, causing cell death. This cell death results in intestinal damage that causes fluid and electrolyte loss. CPE is now being explored for translational applications including cancer therapy/diagnosis, drug delivery, and vaccination. PMID:26999202

Feature relevance assessment for the semantic interpretation of 3D point cloud data

NASA Astrophysics Data System (ADS)

Weinmann, M.; Jutzi, B.; Mallet, C.

2013-10-01

The automatic analysis of large 3D point clouds represents a crucial task in photogrammetry, remote sensing and computer vision. In this paper, we propose a new methodology for the semantic interpretation of such point clouds which involves feature relevance assessment in order to reduce both processing time and memory consumption. Given a standard benchmark dataset with 1.3 million 3D points, we first extract a set of 21 geometric 3D and 2D features. Subsequently, we apply a classifier-independent ranking procedure which involves a general relevance metric in order to derive compact and robust subsets of versatile features which are generally applicable for a large variety of subsequent tasks. This metric is based on 7 different feature selection strategies and thus addresses different intrinsic properties of the given data. For the example of semantically interpreting 3D point cloud data, we demonstrate the great potential of smaller subsets consisting of only the most relevant features with 4 different state-of-the-art classifiers. The results reveal that, instead of including as many features as possible in order to compensate for lack of knowledge, a crucial task such as scene interpretation can be carried out with only few versatile features and even improved accuracy.

- and Graph-Based Point Cloud Segmentation of 3d Scenes Using Perceptual Grouping Laws

NASA Astrophysics Data System (ADS)

Xu, Y.; Hoegner, L.; Tuttas, S.; Stilla, U.

2017-05-01

Segmentation is the fundamental step for recognizing and extracting objects from point clouds of 3D scene. In this paper, we present a strategy for point cloud segmentation using voxel structure and graph-based clustering with perceptual grouping laws, which allows a learning-free and completely automatic but parametric solution for segmenting 3D point cloud. To speak precisely, two segmentation methods utilizing voxel and supervoxel structures are reported and tested. The voxel-based data structure can increase efficiency and robustness of the segmentation process, suppressing the negative effect of noise, outliers, and uneven points densities. The clustering of voxels and supervoxel is carried out using graph theory on the basis of the local contextual information, which commonly conducted utilizing merely pairwise information in conventional clustering algorithms. By the use of perceptual laws, our method conducts the segmentation in a pure geometric way avoiding the use of RGB color and intensity information, so that it can be applied to more general applications. Experiments using different datasets have demonstrated that our proposed methods can achieve good results, especially for complex scenes and nonplanar surfaces of objects. Quantitative comparisons between our methods and other representative segmentation methods also confirms the effectiveness and efficiency of our proposals.

Didactic Lecture Versus Interactive Workshop for Continuing Pharmacy Education on Reproductive Health: A Randomized Controlled Trial.

PubMed

Javadi, Mohammadreza; Kargar, Alireza; Gholami, Kheirollah; Hadjibabaie, Molouk; Rashidian, Arash; Torkamandi, Hassan; Sarayani, Amir

2015-09-01

Pharmacists are routinely providing reproductive health counseling in community pharmacies, but studies have revealed significant deficits in their competencies. Therefore, continuing pharmacy education (CPE) could be utilized as a valuable modality to upgrade pharmacists' capabilities. A randomized controlled trial was designed to compare the efficacy of CPE meetings (lecture based vs. workshop based) on contraception and male sexual dysfunctions. Sixty pharmacists were recruited for each CPE meeting. Small group training using simulated patients was employed in the workshop-based CPE. Study outcomes were declarative/procedural knowledge, attitudes, and satisfaction of the participants. Data were collected pre-CPE, post-CPE, and 2 months afterward and were analyzed using repeated measure analysis of variance and Mann-Whitney U test. Results showed that lecture-based CPE was more successful in improving pharmacists' knowledge post-CPE (p < .001). In contrast, a significant decrease was observed in the lecture-based group at follow-up (p = .002), whereas the workshop-based group maintained their knowledge over time (p = 1.00). Knowledge scores of both groups were significantly higher at follow-up in comparison with pre-CPE (p < .01). No significant differences were observed regarding satisfaction and attitudes scores between groups. In conclusion, an interactive workshop might not be superior to lecture-based training for improving pharmacists' knowledge and attitudes in a 1-day CPE meeting. © The Author(s) 2013.

Street curb recognition in 3d point cloud data using morphological operations

NASA Astrophysics Data System (ADS)

Rodríguez-Cuenca, Borja; Concepción Alonso-Rodríguez, María; García-Cortés, Silverio; Ordóñez, Celestino

2015-04-01

Accurate and automatic detection of cartographic-entities saves a great deal of time and money when creating and updating cartographic databases. The current trend in remote sensing feature extraction is to develop methods that are as automatic as possible. The aim is to develop algorithms that can obtain accurate results with the least possible human intervention in the process. Non-manual curb detection is an important issue in road maintenance, 3D urban modeling, and autonomous navigation fields. This paper is focused on the semi-automatic recognition of curbs and street boundaries using a 3D point cloud registered by a mobile laser scanner (MLS) system. This work is divided into four steps. First, a coordinate system transformation is carried out, moving from a global coordinate system to a local one. After that and in order to simplify the calculations involved in the procedure, a rasterization based on the projection of the measured point cloud on the XY plane was carried out, passing from the 3D original data to a 2D image. To determine the location of curbs in the image, different image processing techniques such as thresholding and morphological operations were applied. Finally, the upper and lower edges of curbs are detected by an unsupervised classification algorithm on the curvature and roughness of the points that represent curbs. The proposed method is valid in both straight and curved road sections and applicable both to laser scanner and stereo vision 3D data due to the independence of its scanning geometry. This method has been successfully tested with two datasets measured by different sensors. The first dataset corresponds to a point cloud measured by a TOPCON sensor in the Spanish town of Cudillero. That point cloud comprises more than 6,000,000 points and covers a 400-meter street. The second dataset corresponds to a point cloud measured by a RIEGL sensor in the Austrian town of Horn. That point cloud comprises 8,000,000 points and represents a 160-meter street. The proposed method provides success rates in curb recognition of over 85% in both datasets.

Infection due to travel-related carbapenemase-producing Enterobacteriaceae, a largely underestimated phenomenon in Belgium.

PubMed

Jans, B; D Huang, T-D; Bauraing, C; Berhin, C; Bogaerts, P; Deplano, A; Denis, O; Catry, B; Glupczynski, Y

2015-06-01

Carbapenemase-producing Enterobacteriaceae (CPE) are emerging worldwide, representing a major threat for public health. Early CPE detection is crucial in order to prevent infections and the development of reservoirs/outbreaks in hospitals. In 2008, most of the CPE strains reported in Belgium were imported from patients repatriated from abroad. Actually, this is no longer the case. A surveillance was set up in Belgian hospitals (2012) in order to explore the epidemiology and determinants of CPE, including the link with international travel/hospitalization. The present article describes travel-related CPE reported in Belgium. Different other potential sources for importation of CPE are discussed. Only 12% of all CPE cases reported in Belgium (2012-2013) were travel related (with/without hospitalization). This is undoubtedly an underestimation (missing travel data: 36%), considering the increasing tourism, the immigration from endemic countries, the growing number of foreign patients using scheduled medical care in Belgium, and the medical repatriations from foreign hospitals. The free movement of persons and services (European Union) contributes to an increase in foreign healthcare workers (HCW) in Belgian hospitals. Residents from nursing homes located at the country borders can be another potential source of dissemination of CPE between countries. Moreover, the high population density in Belgium can increase the risk for CPE-dissemination. Urban areas in Belgium may cumulate these potential risk factors for import/dissemination of CPE. Ideally, travel history data should be obtained from hospital hygiene teams, not from the microbiological laboratory. Patients who received medical care abroad (whatever the country) should be screened for CPE at admission.

Deficiencies in pro-thyrotropin-releasing hormone processing and abnormalities in thermoregulation in Cpefat/fat mice.

PubMed

Nillni, Eduardo A; Xie, Weihua; Mulcahy, Lawrence; Sanchez, Vanesa C; Wetsel, William C

2002-12-13

Cpe(fat/fat) mice are obese, diabetic, and infertile. They have a mutation in carboxypeptidase E (CPE), an enzyme that converts prohormone intermediates to bioactive peptides. The Cpe(fat) mutation leads to rapid degradation of the enzyme. To test whether pro-thyrotropin-releasing hormone (TRH) conversion to TRH involves CPE, processing was examined in the Cpe(fat/fat) mouse. Hypothalamic TRH is depressed by at least 75% compared with wild-type controls. Concentrations of pro-TRH forms are increased in homozygotes. TRH-[Gly(4)-Lys(5)-Arg(6)] and TRH-[Gly(4)-Lys(5)] represent approximately 45% of the total TRH-like immunoreactivity in Cpe(fat/fat) mice; they constitute approximately 1% in controls. Levels of TRH-[Gly(4)] were depressed in homozygotes. Because the hypothalamus contains some TRH, another carboxypeptidase must be responsible for processing. Immunocytochemical studies indicate that TRH neurons contain CPE- and carboxypeptidase D-like immunoreactivity. Recombinant CPE or carboxypeptidase D can convert synthetic TRH-[Gly(4)-Lys(5)] and TRH-[Gly(4)-Lys(5)-Arg(6)] to TRH-[Gly(4)]. When Cpe(fat/fat) mice are exposed to cold, they cannot maintain their body temperatures, and this loss is associated with hypothalamic TRH depletion and reduction in thyroid hormone. These findings demonstrate that the Cpe(fat) mutation can affect not only carboxypeptidase activity but also endoproteolysis. Because Cpe(fat/fat) mice cannot sustain a cold challenge, and because alterations in the hypothalamic-pituitary-thyroid axis can affect metabolism, deficits in pro-TRH processing may contribute to the obese and diabetic phenotype in these mice.

Nootropic, anxiolytic and CNS-depressant studies on different plant sources of shankhpushpi.

PubMed

Malik, Jai; Karan, Maninder; Vasisht, Karan

2011-12-01

Shankhpushpi, a well-known drug in Ayurveda, is extensively used for different central nervous system (CNS) effects especially memory enhancement. Different plants are used under the name shankhpushpi in different regions of India, leading to an uncertainty regarding its true source. Plants commonly used under the name shankhpushpi are: Convolvulus pluricaulis Chois., Evolvulus alsinoides Linn., both from Convolvulaceae, and Clitoria ternatea Linn. (Leguminosae). To find out the true source of shankhpushpi by evaluating and comparing memory-enhancing activity of the three above mentioned plants. Anxiolytic, antidepressant and CNS-depressant activities of these three plants were also compared and evaluated. The nootropic activity of the aqueous methanol extract of each plant was tested using elevated plus-maze (EPM) and step-down models. Anxiolytic, antidepressant and CNS-depressant studies were evaluated using EPM, Porsolt?s swim despair and actophotometer models, respectively. C. pluricaulis extract (CPE) at a dose of 100 mg/kg, p.o. showed maximum nootropic and anxiolytic activity (p < 0.001). E. alsinoides extract (EAE) and C. ternatea extract (CTE) showed maximum memory-enhancing and anxiolytic activity (p < 0.001) at 200 and 100?mg/kg, respectively. Amongst the three plants, EAE and CTE showed significant (p < 0.05), while CPE did not exhibit any antidepressant activity. All the three plants showed CNS-depressant action at higher dose levels. The above results showed all the three plants possess nootropic, anxiolytic and CNS-depressant activity. The results of memory-enhancing activity suggest C. pluricaulis to be used as true source of shankhpushpi.

D Building Reconstruction by Multiview Images and the Integrated Application with Augmented Reality

NASA Astrophysics Data System (ADS)

Hwang, Jin-Tsong; Chu, Ting-Chen

2016-10-01

This study presents an approach wherein photographs with a high degree of overlap are clicked using a digital camera and used to generate three-dimensional (3D) point clouds via feature point extraction and matching. To reconstruct a building model, an unmanned aerial vehicle (UAV) is used to click photographs from vertical shooting angles above the building. Multiview images are taken from the ground to eliminate the shielding effect on UAV images caused by trees. Point clouds from the UAV and multiview images are generated via Pix4Dmapper. By merging two sets of point clouds via tie points, the complete building model is reconstructed. The 3D models are reconstructed using AutoCAD 2016 to generate vectors from the point clouds; SketchUp Make 2016 is used to rebuild a complete building model with textures. To apply 3D building models in urban planning and design, a modern approach is to rebuild the digital models; however, replacing the landscape design and building distribution in real time is difficult as the frequency of building replacement increases. One potential solution to these problems is augmented reality (AR). Using Unity3D and Vuforia to design and implement the smartphone application service, a markerless AR of the building model can be built. This study is aimed at providing technical and design skills related to urban planning, urban designing, and building information retrieval using AR.

Results from the Canadian Nosocomial Infection Surveillance Program on Carbapenemase-Producing Enterobacteriaceae, 2010 to 2014

PubMed Central

Mataseje, Laura F.; Abdesselam, Kahina; Vachon, Julie; Mitchel, Robyn; Bryce, Elizabeth; Roscoe, Diane; Boyd, David A.; Embree, Joanne; Katz, Kevin; Kibsey, Pamela; Simor, Andrew E.; Taylor, Geoffrey; Turgeon, Nathalie; Langley, Joanne; Gravel, Denise; Amaratunga, Kanchana

2016-01-01

Carbapenemase-producing Enterobacteriaceae (CPE) are increasing globally; here we report on the investigation of CPE in Canada over a 5-year period. Participating acute care facilities across Canada submitted carbapenem-nonsusceptible Enterobacteriaceae from 1 January 2010 to 31 December 2014 to the National Microbiology Laboratory. All CPE were characterized by antimicrobial susceptibilities, pulsed-field gel electrophoresis, multilocus sequence typing, and plasmid restriction fragment length polymorphism analysis and had patient data collected using a standard questionnaire. The 5-year incidence rate of CPE was 0.09 per 10,000 patient days and 0.07 per 1,000 admissions. There were a total of 261 CPE isolated from 238 patients in 58 hospitals during the study period. blaKPC-3 (64.8%) and blaNDM-1 (17.6%) represented the highest proportion of carbapenemase genes detected in Canadian isolates. Patients who had a history of medical attention during international travel accounted for 21% of CPE cases. The hospital 30-day all-cause mortality rate for the 5-year surveillance period was 17.1 per 100 CPE cases. No significant increase in the occurrence of CPE was observed from 2010 to 2014. Nosocomial transmission of CPE, as well as international health care, is driving its persistence within Canada. PMID:27600052

Results from the Canadian Nosocomial Infection Surveillance Program on Carbapenemase-Producing Enterobacteriaceae, 2010 to 2014.

PubMed

Mataseje, Laura F; Abdesselam, Kahina; Vachon, Julie; Mitchel, Robyn; Bryce, Elizabeth; Roscoe, Diane; Boyd, David A; Embree, Joanne; Katz, Kevin; Kibsey, Pamela; Simor, Andrew E; Taylor, Geoffrey; Turgeon, Nathalie; Langley, Joanne; Gravel, Denise; Amaratunga, Kanchana; Mulvey, Michael R

2016-11-01

Carbapenemase-producing Enterobacteriaceae (CPE) are increasing globally; here we report on the investigation of CPE in Canada over a 5-year period. Participating acute care facilities across Canada submitted carbapenem-nonsusceptible Enterobacteriaceae from 1 January 2010 to 31 December 2014 to the National Microbiology Laboratory. All CPE were characterized by antimicrobial susceptibilities, pulsed-field gel electrophoresis, multilocus sequence typing, and plasmid restriction fragment length polymorphism analysis and had patient data collected using a standard questionnaire. The 5-year incidence rate of CPE was 0.09 per 10,000 patient days and 0.07 per 1,000 admissions. There were a total of 261 CPE isolated from 238 patients in 58 hospitals during the study period. bla KPC-3 (64.8%) and bla NDM-1 (17.6%) represented the highest proportion of carbapenemase genes detected in Canadian isolates. Patients who had a history of medical attention during international travel accounted for 21% of CPE cases. The hospital 30-day all-cause mortality rate for the 5-year surveillance period was 17.1 per 100 CPE cases. No significant increase in the occurrence of CPE was observed from 2010 to 2014. Nosocomial transmission of CPE, as well as international health care, is driving its persistence within Canada. © Crown copyright 2016.

Audit of the management of patients at high risk of carbapenemase-producing enterobacteriaceae (CPE): Are we ready?

PubMed

Ratnayake, Lasantha; Harris, Amy; Ko, Doreen; Hawtin, Linda

2017-11-01

Incidence of carbapenemase-producing enterobacteriaceae (CPE) in the UK is increasing. In 2013, Public Health England (PHE) published a toolkit to control spread of CPE within healthcare settings. To assess compliance to hospital CPE policy (adapted from PHE) in the identification, isolation and screening of suspected CPE patients. Admission booklets of 150 patients were evaluated to see whether the relevant section had been completed to identify high-risk CPE patients. Where necessary, patients were interviewed or their GPs were contacted to assess their CPE risk. Additionally, 28 patients screened for CPE were audited to assess compliance to screening and isolation. Only 23 patients out of 147 (15.6%) were risk assessed on admission. Risk status of 27 (18.4%) patients could not be assessed due to lack of data. Fifteen patients out of 28 (54%) screened for CPE were identified and isolated on admission. Ten out of 19 patients (53%) had three screens 48 h apart. This audit highlights difficulties in screening based on individual risk factors as the majority of patients were not screened on admission and documentation on isolation and screening was poor. More needs to be done to raise awareness of the requirements for routine assessment, isolation and screening.

Enhanced electrochemiluminescence sensor from tris(2,2'-bipyridyl)ruthenium(II) incorporated into MCM-41 and an ionic liquid-based carbon paste electrode.

PubMed

Li, Jing; Huang, Minghua; Liu, Xiaoqing; Wei, Hui; Xu, Yuanhong; Xu, Guobao; Wang, Erkang

2007-07-01

The electrochemiluminescence (ECL) of tris(2,2'-bipyridyl)ruthenium(II) [Ru(bpy)(3)(2+)] ion-exchanged in the sulfonic-functionalized MCM-41 silicas was developed with tripropylamine (TPrA) as a co-reactant in a carbon paste electrode (CPE) using a room temperature ionic liquid (IL) as a binder. The sulfonic-functionalized silicas MCM-41 were used for preparing an ECL sensor by the electrostatic interactions between Ru(bpy)(3)(2+) cations and sulfonic acid groups. We used the IL as a binder to construct the CPE (IL-CPE) to replace the traditional binder of the CPE (T-CPE)--silicone oil. The results indicated that the MCM-41-modified IL-CPE had more open structures to allow faster diffusion of Ru(bpy)(3)(2+) and that the ionic liquid also acted as a conducting bridge to connect TPrA with Ru(bpy)(3)(2+) sites immobilized in the electrode, resulting in a higher ECL intensity compared with the MCM-41-modified T-CPE. Herein, the detection limit for TPrA of the MCM-41-modified IL-CPE was 7.2 nM, which was two orders of magnitude lower than that observed at the T-CPE. When this new sensor was used in flow injection analysis (FIA), the MCM-41-modified IL-CPE ECL sensor also showed good reproducibility. Furthermore, the sensor could also be renewed easily by mechanical polishing whenever needed.

Active case finding for carbapenemase-producing Enterobacteriaceae in a teaching hospital: prevalence and risk factors for colonization.

PubMed

Poole, K; George, R; Decraene, V; Shankar, K; Cawthorne, J; Savage, N; Welfare, W; Dodgson, A

2016-10-01

Over the past decade, the prevalence of carbapenemase-producing Enterobacteriaceae (CPE) has increased. Whilst basic infection prevention and control practices reduce the risk of transmission, cases of unrecognized carriage pose a potential risk of transmission. To estimate the prevalence of CPE and explore risk factors associated with colonization within a large teaching hospital with an established CPE outbreak. All inpatients that had not previously tested positive for CPE were offered testing. Demographic and hospital episode data were also collected, together with antibiotic and proton pump inhibitor (PPI) use in the preceding 24h. This study identified 70 CPE-positive cases (26 newly identified and 44 previously known) and 592 CPE-negative cases, giving a combined prevalence of 11% [95% confidence interval (CI) 8-13]. Medication (antibiotic and PPI use), previous admission, ethnicity and length of stay were assessed as risk factors for colonization, and none were found to be independently associated with CPE colonization. Using logistic regression, age [odds ratio (OR) 1.03, 95% CI 1.01-1.07] and antibiotic use (OR 2.55, 95% CI 1.08-6.03) were the only risk factors significantly associated with CPE colonization. This study has added to the evidence base by estimating the prevalence of CPE among inpatients in an acute hospital with an established CPE outbreak. A case-finding exercise was feasible and identified a number of new cases. Despite a small sample size, increasing age and prescription of an antibiotic on the day of testing were significantly associated with CPE colonization. Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

Immunohistochemical expression and colocalization of somatostatin, carboxypeptidase-E and prohormone convertases 1 and 2 in rat brain.

PubMed

Billova, S; Galanopoulou, A S; Seidah, N G; Qiu, X; Kumar, U

2007-06-29

The processing of many peptides for their maturation in target tissue depends upon the presence of sorting receptor. Several previous studies have predicted that carboxypeptidase-E (CPE), prohormone convertase 1 (PC1) and prohormone convertase 2 (PC2) may function as sorting elements for somatostatin (SST) for its maturation and processing to appropriate targets. However, nothing is currently known about whether brain, neuronal culture or even endocrine cells express SST, CPE, PC1 and PC2 and exhibit colocalization. Accordingly, in the present study using peroxidase immunohistochemistry, double-labeled indirect immunofluorescence immunohistochemistry and Western blot analysis, we mapped the distributional pattern of SST, CPE, PC1 and PC2 in different rat brain regions. Additionally, we also determined the colocalization of SST with CPE, PC1 and PC2 as well as colocalization of CPE with PC1 and PC2. The localization of SST, CPE, PC1 and PC2 reveals a distinct and region specific distribution pattern in the rat brain. Using an indirect double-label immunofluorescence method we observed selective neuron specific colocalization in a region specific manner in cortex, striatum and hippocampus. These studies provide the first evidence for colocalization between SST, CPE, PC1 and PC2 as well as CPE with PC1 and PC2. SST in cerebral cortex colocalized in pyramidal and non-pyramidal neurons with CPE, PC1 and PC2. Most importantly, in striatum and hippocampus colocalization was mostly observed selectively and preferentially in interneurons. CPE is also colocalized with PC1 and PC2 in a region specific manner. The data presented here provide a new insight into the distribution and colocalization of SST, CPE, PC1 and PC2 in rat brain. Taken together, our data anticipate the possibility that CPE, PC1 and PC2 might be potential target for the maturation of SST.

Critical Point Facility (CPE) Group in the Spacelab Payload Operations Control Center (SL POCC)

NASA Technical Reports Server (NTRS)

1992-01-01

The primary payload for Space Shuttle Mission STS-42, launched January 22, 1992, was the International Microgravity Laboratory-1 (IML-1), a pressurized manned Spacelab module. The goal of IML-1 was to explore in depth the complex effects of weightlessness of living organisms and materials processing. Around-the-clock research was performed on the human nervous system's adaptation to low gravity and effects of microgravity on other life forms such as shrimp eggs, lentil seedlings, fruit fly eggs, and bacteria. Materials processing experiments were also conducted, including crystal growth from a variety of substances such as enzymes, mercury iodide, and a virus. The Huntsville Operations Support Center (HOSC) Spacelab Payload Operations Control Center (SL POCC) at the Marshall Space Flight Center (MSFC) was the air/ground communication channel used between the astronauts and ground control teams during the Spacelab missions. Featured is the Critical Point Facility (CPE) group in the SL POCC during STS-42, IML-1 mission.

Automatic Detection and Classification of Pole-Like Objects for Urban Cartography Using Mobile Laser Scanning Data

PubMed Central

Ordóñez, Celestino; Cabo, Carlos; Sanz-Ablanedo, Enoc

2017-01-01

Mobile laser scanning (MLS) is a modern and powerful technology capable of obtaining massive point clouds of objects in a short period of time. Although this technology is nowadays being widely applied in urban cartography and 3D city modelling, it has some drawbacks that need to be avoided in order to strengthen it. One of the most important shortcomings of MLS data is concerned with the fact that it provides an unstructured dataset whose processing is very time-consuming. Consequently, there is a growing interest in developing algorithms for the automatic extraction of useful information from MLS point clouds. This work is focused on establishing a methodology and developing an algorithm to detect pole-like objects and classify them into several categories using MLS datasets. The developed procedure starts with the discretization of the point cloud by means of a voxelization, in order to simplify and reduce the processing time in the segmentation process. In turn, a heuristic segmentation algorithm was developed to detect pole-like objects in the MLS point cloud. Finally, two supervised classification algorithms, linear discriminant analysis and support vector machines, were used to distinguish between the different types of poles in the point cloud. The predictors are the principal component eigenvalues obtained from the Cartesian coordinates of the laser points, the range of the Z coordinate, and some shape-related indexes. The performance of the method was tested in an urban area with 123 poles of different categories. Very encouraging results were obtained, since the accuracy rate was over 90%. PMID:28640189

Faecal carriage of extended-spectrum β-lactamase-producing enterobacteria among soldiers at admission in a French military hospital after aeromedical evacuation from overseas.

PubMed

Janvier, F; Delacour, H; Tessé, S; Larréché, S; Sanmartin, N; Ollat, D; Rapp, C; Mérens, A

2014-10-01

The aim of this study was to assess the faecal carriage of carbapenemase-producing enterobacteria (CPE) and extended-spectrum β-lactamase (ESBL)-producing enterobacteria among soldiers at admission in a French military hospital after aeromedical evacuation from overseas. During a period of 1 year, 83 rectal swabs collected in French soldiers at admission were screened for multidrug-resistant enterobacteria with a chromogenic medium. ESBL detection was performed with the double-disc synergy test in the absence or presence of cloxacillin. The genotypic characterisation of resistance mechanisms, sequence typing and phylotyping was performed by polymerase chain reaction (PCR) and sequencing with bacterial DNA extracted from isolates. No CPE was detected. Eleven ESBL Escherichia coli isolates belonging to four phylogenetic groups were detected, including ten CTX-M-15 and one CTX-M-14. The overall gut colonisation with ESBL-producing bacteria (13.25 %) was 6-fold higher than that reported in soldiers in the suburbs of Paris in 2009. ESBL faecal carriage was particularly high (34.48 %) in soldiers repatriated from Afghanistan (risk ratio = 18.62; p = 0.0001). This study highlights the importance of systematic additional contact precautions and CPE/ESBL screening in soldiers repatriated from overseas in French hospitals.

Extracting Topological Relations Between Indoor Spaces from Point Clouds

NASA Astrophysics Data System (ADS)

Tran, H.; Khoshelham, K.; Kealy, A.; Díaz-Vilariño, L.

2017-09-01

3D models of indoor environments are essential for many application domains such as navigation guidance, emergency management and a range of indoor location-based services. The principal components defined in different BIM standards contain not only building elements, such as floors, walls and doors, but also navigable spaces and their topological relations, which are essential for path planning and navigation. We present an approach to automatically reconstruct topological relations between navigable spaces from point clouds. Three types of topological relations, namely containment, adjacency and connectivity of the spaces are modelled. The results of initial experiments demonstrate the potential of the method in supporting indoor navigation.

Exploring point-cloud features from partial body views for gender classification

NASA Astrophysics Data System (ADS)

Fouts, Aaron; McCoppin, Ryan; Rizki, Mateen; Tamburino, Louis; Mendoza-Schrock, Olga

2012-06-01

In this paper we extend a previous exploration of histogram features extracted from 3D point cloud images of human subjects for gender discrimination. Feature extraction used a collection of concentric cylinders to define volumes for counting 3D points. The histogram features are characterized by a rotational axis and a selected set of volumes derived from the concentric cylinders. The point cloud images are drawn from the CAESAR anthropometric database provided by the Air Force Research Laboratory (AFRL) Human Effectiveness Directorate and SAE International. This database contains approximately 4400 high resolution LIDAR whole body scans of carefully posed human subjects. Success from our previous investigation was based on extracting features from full body coverage which required integration of multiple camera images. With the full body coverage, the central vertical body axis and orientation are readily obtainable; however, this is not the case with a one camera view providing less than one half body coverage. Assuming that the subjects are upright, we need to determine or estimate the position of the vertical axis and the orientation of the body about this axis relative to the camera. In past experiments the vertical axis was located through the center of mass of torso points projected on the ground plane and the body orientation derived using principle component analysis. In a natural extension of our previous work to partial body views, the absence of rotational invariance about the cylindrical axis greatly increases the difficulty for gender classification. Even the problem of estimating the axis is no longer simple. We describe some simple feasibility experiments that use partial image histograms. Here, the cylindrical axis is assumed to be known. We also discuss experiments with full body images that explore the sensitivity of classification accuracy relative to displacements of the cylindrical axis. Our initial results provide the basis for further investigation of more complex partial body viewing problems and new methods for estimating the two position coordinates for the axis location and the unknown body orientation angle.

Extraction of Features from High-resolution 3D LiDaR Point-cloud Data

NASA Astrophysics Data System (ADS)

Keller, P.; Kreylos, O.; Hamann, B.; Kellogg, L. H.; Cowgill, E. S.; Yikilmaz, M. B.; Hering-Bertram, M.; Hagen, H.

2008-12-01

Airborne and tripod-based LiDaR scans are capable of producing new insight into geologic features by providing high-quality 3D measurements of the landscape. High-resolution LiDaR is a promising method for studying slip on faults, erosion, and other landscape-altering processes. LiDaR scans can produce up to several billion individual point returns associated with the reflection of a laser from natural and engineered surfaces; these point clouds are typically used to derive a high-resolution digital elevation model (DEM). Currently, there exist only few methods that can support the analysis of the data at full resolution and in the natural 3D perspective in which it was collected by working directly with the points. We are developing new algorithms for extracting features from LiDaR scans, and present method for determining the local curvature of a LiDaR data set, working directly with the individual point returns of a scan. Computing the curvature enables us to rapidly and automatically identify key features such as ridge-lines, stream beds, and edges of terraces. We fit polynomial surface patches via a moving least squares (MLS) approach to local point neighborhoods, determining curvature values for each point. The size of the local point neighborhood is defined by a user. Since both terrestrial and airborne LiDaR scans suffer from high noise, we apply additional pre- and post-processing smoothing steps to eliminate unwanted features. LiDaR data also captures objects like buildings and trees complicating greatly the task of extracting reliable curvature values. Hence, we use a stochastic approach to determine whether a point can be reliably used to estimate curvature or not. Additionally, we have developed a graph-based approach to establish connectivities among points that correspond to regions of high curvature. The result is an explicit description of ridge-lines, for example. We have applied our method to the raw point cloud data collected as part of the GeoEarthScope B-4 project on a section of the San Andreas Fault (Segment SA09). This section provides an excellent test site for our method as it exposes the fault clearly, contains few extraneous structures, and exhibits multiple dry stream-beds that have been off-set by motion on the fault.

Porphyran-capped gold nanoparticles modified carbon paste electrode: a simple and efficient electrochemical sensor for the sensitive determination of 5-fluorouracil

NASA Astrophysics Data System (ADS)

Lima, Dhésmon; Calaça, Giselle Nathaly; Viana, Adriano Gonçalves; Pessôa, Christiana Andrade

2018-01-01

The application of carbon paste electrodes modified with porphyran-capped gold nanoparticles (CPE/AuNps-PFR) to detect an important anticancer drug, 5-fluorouracil (5-FU), is described. Gold nanoparticles (AuNps) were synthesized through a green one-pot route, by using porphyran (PFR) (a sulfated polysaccharide extracted from red seaweed) as reducing and stabilizing agent. The reaction temperature and the concentrations of AuCl4- and PFR for AuNps-PFR synthesis were optimized by using a 23 full factorial design with central point assayed in triplicate. The smallest particle size (128.7 nm, obtained by DLS) was achieved by employing a temperature of 70 °C and AuCl4- and PFR concentrations equal to 2.5 mmol L-1 and 0.25 mg mL-1, respectively. The AuNps-PFR nanocomposite was characterized by UV-vis spectroscopy, FTIR, DLS, TEM, XRD and zeta potential, which proved that PFR was effective at reducing and capping the AuNps. Cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) experiments showed that the nanocomposite could enhance the electrochemical performance of the electrodes, as a consequence of the high conductivity and large surface area presented by the AuNps. The CPE/AuNps-PFR was able to electrocatalyze the oxidation of 5-FU by CV and differential pulse voltammetry (DPV). A linear relationship between the DPV peak currents and 5-FU concentration was verified in the range from 29.9 to 234 μmol L-1 in 0.04 mol L-1 BR buffer solution pH 8.0. Detection and quantification limits were found to be 0.66 and 2.22 μmol L-1, respectively. Besides the good sensitivity, CPE/AuNps-PFR showed reproducibility and did not suffer significant interference from potentially electroative biological compounds. The good analytical performance of the modified electrode was confirmed for determining 5-FU in pharmaceutical formulations, with good percent recoveries (ranging from 96.6 to 101.4%) and an acceptable relative standard deviation (RSD = 2.80%).

Cinnamon polyphenols attenuate cell swelling and mitochondrial dysfunction following oxygen-glucose deprivation in glial cells.

PubMed

Panickar, Kiran S; Polansky, Marilyn M; Anderson, Richard A

2009-04-01

Astrocyte swelling is an integral component of cytotoxic brain edema in ischemic injury. While mechanisms underlying astrocyte swelling are likely multifactorial, oxidative stress and mitochondrial dysfunction are hypothesized to contribute to such swelling. We investigated the protective effects of cinnamon polyphenol extract (CPE) that has anti-oxidant and insulin-potentiating effects on cell swelling and depolarization of the inner mitochondrial membrane potential (DeltaPsi(m)) in ischemic injury. C6 glial cells were subjected to oxygen-glucose deprivation (OGD) and cell volume determined using the 3-O-methyl-[3H]-glucose method at 90 min after the end of OGD. When compared with controls, OGD increased cell volume by 34%. This increase was blocked by CPE or insulin but not by blockers of oxidative/nitrosative stress including vitamin E, resveratrol, N-nitro-L-arginine methyl ester (L-NAME) or uric acid. Mitochondrial dysfunction, a key component of ischemic injury, contributes to cell swelling. Changes in DeltaPsi(m) were assessed at the end of OGD with tetramethylrhodamine ethyl ester (TMRE), a potentiometric dye. OGD induced a 39% decline in DeltaPsi(m) and this decline was blocked by CPE as well as insulin. To test the involvement of the mitochondrial permeability transition (mPT), we used Cyclosporin A (CsA), an immunosuppressant and a blocker of the mPT pore. CsA blocked cell swelling and the decline in DeltaPsi(m) but FK506, an immunosuppressant that does not block the mPT, did not. Our results show that CPE reduces OGD-induced cell swelling as well as the decline in DeltaPsi(m) in cultures and some of its protective effects may be through inhibiting the mPT.

Indoor Navigation from Point Clouds: 3d Modelling and Obstacle Detection

NASA Astrophysics Data System (ADS)

Díaz-Vilariño, L.; Boguslawski, P.; Khoshelham, K.; Lorenzo, H.; Mahdjoubi, L.

2016-06-01

In the recent years, indoor modelling and navigation has become a research of interest because many stakeholders require navigation assistance in various application scenarios. The navigational assistance for blind or wheelchair people, building crisis management such as fire protection, augmented reality for gaming, tourism or training emergency assistance units are just some of the direct applications of indoor modelling and navigation. Navigational information is traditionally extracted from 2D drawings or layouts. Real state of indoors, including opening position and geometry for both windows and doors, and the presence of obstacles is commonly ignored. In this work, a real indoor-path planning methodology based on 3D point clouds is developed. The value and originality of the approach consist on considering point clouds not only for reconstructing semantically-rich 3D indoor models, but also for detecting potential obstacles in the route planning and using these for readapting the routes according to the real state of the indoor depictured by the laser scanner.

Comparative Analysis of Data Structures for Storing Massive Tins in a Dbms

NASA Astrophysics Data System (ADS)

Kumar, K.; Ledoux, H.; Stoter, J.

2016-06-01

Point cloud data are an important source for 3D geoinformation. Modern day 3D data acquisition and processing techniques such as airborne laser scanning and multi-beam echosounding generate billions of 3D points for simply an area of few square kilometers. With the size of the point clouds exceeding the billion mark for even a small area, there is a need for their efficient storage and management. These point clouds are sometimes associated with attributes and constraints as well. Storing billions of 3D points is currently possible which is confirmed by the initial implementations in Oracle Spatial SDO PC and the PostgreSQL Point Cloud extension. But to be able to analyse and extract useful information from point clouds, we need more than just points i.e. we require the surface defined by these points in space. There are different ways to represent surfaces in GIS including grids, TINs, boundary representations, etc. In this study, we investigate the database solutions for the storage and management of massive TINs. The classical (face and edge based) and compact (star based) data structures are discussed at length with reference to their structure, advantages and limitations in handling massive triangulations and are compared with the current solution of PostGIS Simple Feature. The main test dataset is the TIN generated from third national elevation model of the Netherlands (AHN3) with a point density of over 10 points/m2. PostgreSQL/PostGIS DBMS is used for storing the generated TIN. The data structures are tested with the generated TIN models to account for their geometry, topology, storage, indexing, and loading time in a database. Our study is useful in identifying what are the limitations of the existing data structures for storing massive TINs and what is required to optimise these structures for managing massive triangulations in a database.

Point Cloud Analysis for Uav-Borne Laser Scanning with Horizontally and Vertically Oriented Line Scanners - Concept and First Results

NASA Astrophysics Data System (ADS)

Weinmann, M.; Müller, M. S.; Hillemann, M.; Reydel, N.; Hinz, S.; Jutzi, B.

2017-08-01

In this paper, we focus on UAV-borne laser scanning with the objective of densely sampling object surfaces in the local surrounding of the UAV. In this regard, using a line scanner which scans along the vertical direction and perpendicular to the flight direction results in a point cloud with low point density if the UAV moves fast. Using a line scanner which scans along the horizontal direction only delivers data corresponding to the altitude of the UAV and thus a low scene coverage. For these reasons, we present a concept and a system for UAV-borne laser scanning using multiple line scanners. Our system consists of a quadcopter equipped with horizontally and vertically oriented line scanners. We demonstrate the capabilities of our system by presenting first results obtained for a flight within an outdoor scene. Thereby, we use a downsampling of the original point cloud and different neighborhood types to extract fundamental geometric features which in turn can be used for scene interpretation with respect to linear, planar or volumetric structures.

Water Leakage Diagnosis in Metro Tunnels by Intergration of Laser Point Cloud and Infrared Thermal Imaging

NASA Astrophysics Data System (ADS)

Yu, P.; Wu, H.; Liu, C.; Xu, Z.

2018-04-01

Diagnosis of water leakage in metro tunnels is of great significance to the metro tunnel construction and the safety of metro operation. A method that integrates laser scanning and infrared thermal imaging is proposed for the diagnosis of water leakage. The diagnosis of water leakage in this paper is mainly divided into two parts: extraction of water leakage geometry information and extraction of water leakage attribute information. Firstly, the suspected water leakage is obtained by threshold segmentation based on the point cloud of tunnel. And the real water leakage is obtained by the auxiliary interpretation of infrared thermal images. Then, the characteristic of isotherm outline is expressed by solving Centroid Distance Function to determine the type of water leakage. Similarly, the location of leakage silt and the direction of crack are calculated by finding coordinates of feature points on Centroid Distance Function. Finally, a metro tunnel part in Shanghai was selected as the case area to make experiment and the result shown that the proposed method in this paper can be used to diagnosis water leakage disease completely and accurately.

Semantic Segmentation of Indoor Point Clouds Using Convolutional Neural Network

NASA Astrophysics Data System (ADS)

Babacan, K.; Chen, L.; Sohn, G.

2017-11-01

As Building Information Modelling (BIM) thrives, geometry becomes no longer sufficient; an ever increasing variety of semantic information is needed to express an indoor model adequately. On the other hand, for the existing buildings, automatically generating semantically enriched BIM from point cloud data is in its infancy. The previous research to enhance the semantic content rely on frameworks in which some specific rules and/or features that are hand coded by specialists. These methods immanently lack generalization and easily break in different circumstances. On this account, a generalized framework is urgently needed to automatically and accurately generate semantic information. Therefore we propose to employ deep learning techniques for the semantic segmentation of point clouds into meaningful parts. More specifically, we build a volumetric data representation in order to efficiently generate the high number of training samples needed to initiate a convolutional neural network architecture. The feedforward propagation is used in such a way to perform the classification in voxel level for achieving semantic segmentation. The method is tested both for a mobile laser scanner point cloud, and a larger scale synthetically generated data. We also demonstrate a case study, in which our method can be effectively used to leverage the extraction of planar surfaces in challenging cluttered indoor environments.

Prolonged carriage and potential onward transmission of carbapenemase-producing Enterobacteriaceae in Dutch travelers.

PubMed

van Hattem, Jarne M; Arcilla, Maris S; Bootsma, Martin Cj; van Genderen, Perry J; Goorhuis, Abraham; Grobusch, Martin P; Molhoek, Nicky; Oude Lashof, Astrid Ml; Schultsz, Constance; Stobberingh, Ellen E; Verbrugh, Henri A; de Jong, Menno D; Melles, Damian C; Penders, John

2016-07-01

The aim was to study acquisition and persistence of carbapenemase-producing Enterobacteriaceae (CPE) among travelers. Stools from 2001 travelers and 215 nontraveling household members, collected before and immediately post-travel as well as 1, 3, 6 and 12 months upon return, were screened for CPE. Five travelers, all visiting Asia outside the Indian subcontinent, acquired CPE. One traveler persistently carried the same OXA-244 CPE up to 6 months post-travel. Three months after travel, her co-traveling spouse also became positive for this OXA-244 CPE strain, suggesting clonal transmission within this household. Acquisition of CPE is not restricted to travelers to the Indian subcontinent and/or to travelers seeking healthcare during travel and can persist up to at least 6 months post-travel.

Systemic Vulnerabilities in Customer-Premises Equipment (CPE) Routers

DTIC Science & Technology

2017-07-01

equipment (CPE),1 specifically small office/home office (SOHO) routers, has become ubiquitous. CPE routers are notorious for their web interface...and enabling remote management, although all settings controllable over the web -management interface can be manipulated. • 85% (11 of 13) of...specifically small office/home office (SOHO) routers— has become ubiquitous. CPE routers are notorious for their web interface vulnerabilities, old ver- sions

The Carnian (Late Triassic) carbon isotope excursion: new insights from the terrestrial realm

NASA Astrophysics Data System (ADS)

Miller, Charlotte; Kürschner, Wolfram; Peterse, Francien; Baranyi, Viktoria; Reichart, Gert-Jan

2016-04-01

The geological record contains evidence for numerous pronounced perturbations in the global carbon cycle, some of which are associated with eruptions from large igneous provinces (LIP), and consequently, ocean acidification and mass extinction. In the Carnian (Late Triassic), evidence from sedimentology and fossil pollen points to a significant change in climate, resulting in biotic turnover: during a period termed the 'Carnian Pluvial Event' (CPE). Additionally, during the Carnian, large volumes of flood basalts were erupted from the Wrangellia LIP (western North America). Evidence from the marine realm suggests a fundamental relationship between the CPE, a global 'wet' period, and the injection of light carbon into the atmosphere from the LIP. Here we provide the first evidence from the terrestrial realm of a significant negative δ13C excursion through the CPE recorded in the sedimentary archive of the Wiscombe Park Borehole, Devon (UK). Both total organic matter and plant leaf waxes reflect a gradual carbon isotope excursion of ~-5‰ during this time interval. Our data provides evidence for the global nature of this isotope excursion, supporting the hypothesis that the excursion was likely the result of an injection of light carbon into the atmosphere from the Wrangellia LIP.

Specific binding of Clostridium perfringens enterotoxin fragment to Claudin-b and modulation of zebrafish epidermal barrier.

PubMed

Zhang, Jingjing; Ni, Chen; Yang, Zhenguo; Piontek, Anna; Chen, Huapu; Wang, Sijie; Fan, Yiming; Qin, Zhihai; Piontek, Joerg

2015-08-01

Claudins (Cldn) are the major components of tight junctions (TJs) sealing the paracellular cleft in tissue barriers of various organs. Zebrafish Cldnb, the homolog of mammalian Cldn4, is expressed at epithelial cell-cell contacts and is important for regulating epidermal permeability. The bacterial toxin Clostridium perfringens enterotoxin (CPE) has been shown to bind to a subset of mammalian Cldns. In this study, we used the Cldn-binding C-terminal domain of CPE (194-319 amino acids, cCPE 194-319 ) to investigate its functional role in modulating zebrafish larval epidermal barriers. In vitro analyses show that cCPE 194-319 removed Cldn4 from epithelial cells and disrupted the monolayer tightness, which could be rescued by the removal of cCPE 194-319. Incubation of zebrafish larvae with cCPE 194-319 removed Cldnb specifically from the epidermal cell membrane. Dye diffusion analysis with 4-kDa fluorescent dextran indicated that the permeability of the epidermal barrier increased due to cCPE 194-319 incubation. Electron microscopic investigation revealed reversible loss of TJ integrity by Cldnb removal. Collectively, these results suggest that cCPE 194-319 could be used as a Cldnb modulator to transiently open the epidermal barrier in zebrafish. In addition, zebrafish might be used as an in vivo system to investigate the capability of cCPE to enhance drug delivery across tissue barriers. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Identification of natural metabolites in mixture: a pattern recognition strategy based on (13)C NMR.

PubMed

Hubert, Jane; Nuzillard, Jean-Marc; Purson, Sylvain; Hamzaoui, Mahmoud; Borie, Nicolas; Reynaud, Romain; Renault, Jean-Hugues

2014-03-18

Because of their highly complex metabolite profile, the chemical characterization of bioactive natural extracts usually requires time-consuming multistep purification procedures to achieve the structural elucidation of pure individual metabolites. The aim of the present work was to develop a dereplication strategy for the identification of natural metabolites directly within mixtures. Exploiting the polarity range of metabolites, the principle was to rapidly fractionate a multigram quantity of a crude extract by centrifugal partition extraction (CPE). The obtained fractions of simplified chemical composition were subsequently analyzed by (13)C NMR. After automatic collection and alignment of (13)C signals across spectra, hierarchical clustering analysis (HCA) was performed for pattern recognition. As a result, strong correlations between (13)C signals of a single structure within the mixtures of the fraction series were visualized as chemical shift clusters. Each cluster was finally assigned to a molecular structure with the help of a locally built (13)C NMR chemical shift database. The proof of principle of this strategy was achieved on a simple model mixture of commercially available plant secondary metabolites and then applied to a bark extract of the African tree Anogeissus leiocarpus Guill. & Perr. (Combretaceae). Starting from 5 g of this genuine extract, the fraction series was generated by CPE in only 95 min. (13)C NMR analyses of all fractions followed by pattern recognition of (13)C chemical shifts resulted in the unambiguous identification of seven major compounds, namely, sericoside, trachelosperogenin E, ellagic acid, an epimer mixture of (+)-gallocatechin and (-)-epigallocatechin, 3,3'-di-O-methylellagic acid 4'-O-xylopyranoside, and 3,4,3'-tri-O-methylflavellagic acid 4'-O-glucopyranoside.

Supervised Outlier Detection in Large-Scale Mvs Point Clouds for 3d City Modeling Applications

NASA Astrophysics Data System (ADS)

Stucker, C.; Richard, A.; Wegner, J. D.; Schindler, K.

2018-05-01

We propose to use a discriminative classifier for outlier detection in large-scale point clouds of cities generated via multi-view stereo (MVS) from densely acquired images. What makes outlier removal hard are varying distributions of inliers and outliers across a scene. Heuristic outlier removal using a specific feature that encodes point distribution often delivers unsatisfying results. Although most outliers can be identified correctly (high recall), many inliers are erroneously removed (low precision), too. This aggravates object 3D reconstruction due to missing data. We thus propose to discriminatively learn class-specific distributions directly from the data to achieve high precision. We apply a standard Random Forest classifier that infers a binary label (inlier or outlier) for each 3D point in the raw, unfiltered point cloud and test two approaches for training. In the first, non-semantic approach, features are extracted without considering the semantic interpretation of the 3D points. The trained model approximates the average distribution of inliers and outliers across all semantic classes. Second, semantic interpretation is incorporated into the learning process, i.e. we train separate inlieroutlier classifiers per semantic class (building facades, roof, ground, vegetation, fields, and water). Performance of learned filtering is evaluated on several large SfM point clouds of cities. We find that results confirm our underlying assumption that discriminatively learning inlier-outlier distributions does improve precision over global heuristics by up to ≍ 12 percent points. Moreover, semantically informed filtering that models class-specific distributions further improves precision by up to ≍ 10 percent points, being able to remove very isolated building, roof, and water points while preserving inliers on building facades and vegetation.

What influences malaysian nurses to participate in continuing professional education activities?

PubMed

Chong, Mei Chan; Sellick, Kenneth; Francis, Karen; Abdullah, Khatijah Lim

2011-03-01

A cross sectional descriptive study, which involved government hospitals and health clinics from Peninsular Malaysia sought to identify the continuing professional education (CPE) needs and their readiness for E-learning. This paper focuses on the first phase of that study that aimed to determine the factors that influence nurses' participation in CPE. Multistage cluster sampling was used to recruit 1,000 nurses randomly from 12 hospitals and 24 health clinics from four states in Peninsular Malaysia who agreed to be involved. The respondent rate was 792 (79.2%), of which 562 (80%) had participated in CPE in the last 12 months. Findings suggested that updating knowledge and providing quality care are the most important factors that motivate participation in CPE, with respective means of 4.34 and 4.39. All the mean scores for educational opportunity were less than 3.0. Chi-square tests were used to test the association of demographic data and CPE participation. All demographical data were significantly associated with CPE participation, except marital status. Implementation of mandatory CPE is considered an important measure to increase nurse's participation in CPE. However, effective planning that takes into consideration the learning needs of nurses is recommended. Copyright © 2011 Korean Society of Nursing Science. Published by Elsevier B.V. All rights reserved.

NIa-Pro of Papaya ringspot virus interacts with Carica papaya eukaryotic translation initiation factor 3 subunit G (CpeIF3G).

PubMed

Gao, Le; Tuo, Decai; Shen, Wentao; Yan, Pu; Li, Xiaoying; Zhou, Peng

2015-02-01

The interaction of papaya eukaryotic translation initiation factor 3 subunit G (CpeIF3G) with Papaya ringspot virus (PRSV) NIa-Pro was validated using a bimolecular fluorescence complementation assay in papaya protoplasts based on the previous yeast two-hybrid assay results. The C-terminal (residues 133-239) fragment of PRSV NIa-Pro and the central domain (residues 59-167) of CpeIF3G were required for effective interaction between NIa-Pro and CpeIF3G as shown by a Sos recruitment yeast two-hybrid system with several deletion mutants of NIa-Pro and CpeIF3G. The central domain of CpeIF3G, which contains a C2HC-type zinc finger motif, is required to bind to other eIFs of the translational machinery. In addition, quantitative real-time reverse transcription PCR assay confirmed that PRSV infection leads to a 2- to 4.5-fold up-regulation of CpeIF3G mRNA in papaya. Plant eIF3G is involved in various stress response by enhancing the translation of resistance-related proteins. It is proposed that the NIa-Pro-CpeIF3G interaction may impair translation preinitiation complex assembly of defense proteins and interfere with host defense.

Lost in Virtual Reality: Pathfinding Algorithms Detect Rock Fractures and Contacts in Point Clouds

NASA Astrophysics Data System (ADS)

Thiele, S.; Grose, L.; Micklethwaite, S.

2016-12-01

UAV-based photogrammetric and LiDAR techniques provide high resolution 3D point clouds and ortho-rectified photomontages that can capture surface geology in outstanding detail over wide areas. Automated and semi-automated methods are vital to extract full value from these data in practical time periods, though the nuances of geological structures and materials (natural variability in colour and geometry, soft and hard linkage, shadows and multiscale properties) make this a challenging task. We present a novel method for computer assisted trace detection in dense point clouds, using a lowest cost path solver to "follow" fracture traces and lithological contacts between user defined end points. This is achieved by defining a local neighbourhood network where each point in the cloud is linked to its neighbours, and then using a least-cost path algorithm to search this network and estimate the trace of the fracture or contact. A variety of different algorithms can then be applied to calculate the best fit plane, produce a fracture network, or map properties such as roughness, curvature and fracture intensity. Our prototype of this method (Fig. 1) suggests the technique is feasible and remarkably good at following traces under non-optimal conditions such as variable-shadow, partial occlusion and complex fracturing. Furthermore, if a fracture is initially mapped incorrectly, the user can easily provide further guidance by defining intermediate waypoints. Future development will include optimization of the algorithm to perform well on large point clouds and modifications that permit the detection of features such as step-overs. We also plan on implementing this approach in an interactive graphical user environment.

Applications of UAS-SfM for coastal vulnerability assessment: Geomorphic feature extraction and land cover classification from fine-scale elevation and imagery data

NASA Astrophysics Data System (ADS)

Sturdivant, E. J.; Lentz, E. E.; Thieler, E. R.; Remsen, D.; Miner, S.

2016-12-01

Characterizing the vulnerability of coastal systems to storm events, chronic change and sea-level rise can be improved with high-resolution data that capture timely snapshots of biogeomorphology. Imagery acquired with unmanned aerial systems (UAS) coupled with structure from motion (SfM) photogrammetry can produce high-resolution topographic and visual reflectance datasets that rival or exceed lidar and orthoimagery. Here we compare SfM-derived data to lidar and visual imagery for their utility in a) geomorphic feature extraction and b) land cover classification for coastal habitat assessment. At a beach and wetland site on Cape Cod, Massachusetts, we used UAS to capture photographs over a 15-hectare coastal area with a resulting pixel resolution of 2.5 cm. We used standard SfM processing in Agisoft PhotoScan to produce an elevation point cloud, an orthomosaic, and a digital elevation model (DEM). The SfM-derived products have a horizontal uncertainty of +/- 2.8 cm. Using the point cloud in an extraction routine developed for lidar data, we determined the position of shorelines, dune crests, and dune toes. We used the output imagery and DEM to map land cover with a pixel-based supervised classification. The dense and highly precise SfM point cloud enabled extraction of geomorphic features with greater detail than with lidar. The feature positions are reported with near-continuous coverage and sub-meter accuracy. The orthomosaic image produced with SfM provides visual reflectance with higher resolution than those available from aerial flight surveys, which enables visual identification of small features and thus aids the training and validation of the automated classification. We find that the high-resolution and correspondingly high density of UAS data requires some simple modifications to existing measurement techniques and processing workflows, and that the types of data and the quality provided is equivalent to, and in some cases surpasses, that of data collected using other methods.

Automatic 3D Extraction of Buildings, Vegetation and Roads from LIDAR Data

NASA Astrophysics Data System (ADS)

Bellakaout, A.; Cherkaoui, M.; Ettarid, M.; Touzani, A.

2016-06-01

Aerial topographic surveys using Light Detection and Ranging (LiDAR) technology collect dense and accurate information from the surface or terrain; it is becoming one of the important tools in the geosciences for studying objects and earth surface. Classification of Lidar data for extracting ground, vegetation, and buildings is a very important step needed in numerous applications such as 3D city modelling, extraction of different derived data for geographical information systems (GIS), mapping, navigation, etc... Regardless of what the scan data will be used for, an automatic process is greatly required to handle the large amount of data collected because the manual process is time consuming and very expensive. This paper is presenting an approach for automatic classification of aerial Lidar data into five groups of items: buildings, trees, roads, linear object and soil using single return Lidar and processing the point cloud without generating DEM. Topological relationship and height variation analysis is adopted to segment, preliminary, the entire point cloud preliminarily into upper and lower contours, uniform and non-uniform surface, non-uniform surfaces, linear objects, and others. This primary classification is used on the one hand to know the upper and lower part of each building in an urban scene, needed to model buildings façades; and on the other hand to extract point cloud of uniform surfaces which contain roofs, roads and ground used in the second phase of classification. A second algorithm is developed to segment the uniform surface into buildings roofs, roads and ground, the second phase of classification based on the topological relationship and height variation analysis, The proposed approach has been tested using two areas : the first is a housing complex and the second is a primary school. The proposed approach led to successful classification results of buildings, vegetation and road classes.

Low frequency sonic waves assisted cloud point extraction of polyhydroxyalkanoate from Cupriavidus necator.

PubMed

Murugesan, Sivananth; Iyyaswami, Regupathi

2017-08-15

Low frequency sonic waves, less than 10kHz were introduced to assist cloud point extraction of polyhydroxyalkanoate from Cupriavidus necator present within the crude broth. Process parameters including surfactant system variables and sonication parameters were studied for their effect on extraction efficiency. Introduction of low frequency sonic waves assists in the dissolution of microbial cell wall by the surfactant micelles and release of cellular content, polyhydroxyalkanoate granules released were encapsulated by the micelle core which was confirmed by crotonic acid assay. In addition, sonic waves resulted in the separation of homogeneous surfactant and broth mixture into two distinct phases, top aqueous phase and polyhydroxyalkanoate enriched bottom surfactant rich phase. Mixed surfactant systems showed higher extraction efficiency compared to that of individual Triton X-100 concentrations, owing to increase in the hydrophobicity of the micellar core and its interaction with polyhydroxyalkanoate. Addition of salts to the mixed surfactant system induces screening of charged surfactant head groups and reduces inter-micellar repulsion, presence of ammonium ions lead to electrostatic repulsion and weaker cation sodium enhances the formation of micellar network. Addition of polyethylene glycol 8000 resulted in increasing interaction with the surfactant tails of the micelle core there by reducing the purity of polyhydroxyalkanoate. Copyright © 2017 Elsevier B.V. All rights reserved.

The interaction of Clostridium perfringens enterotoxin with receptor claudins

PubMed Central

Shrestha, Archana; Uzal, Francisco A.; McClane, Bruce A.

2016-01-01

Clostridium perfringens enterotoxin (CPE) has significant medical importance due to its involvement in several common human gastrointestinal diseases. This 35 kDa single polypeptide toxin consists of two domains: a C-terminal domain involved in receptor binding and an N-terminal domain involved in oligomerization, membrane insertion and pore formation. The action of CPE starts with its binding to receptors, which include certain members of the claudin tight junction protein family; bound CPE then forms a series of complexes, one of which is a pore that causes the calcium influx responsible for host cell death. Recent studies have revealed that CPE binding to claudin receptors involves interactions between the C-terminal CPE domain and both the 1st and 2nd extracellular loops (ECL-1 and ECL-2) of claudin receptors. Of particular importance for this binding is the docking of ECL-2 into a pocket present in the C-terminal domain of the toxin. This increased understanding of CPE interactions with claudin receptors is now fostering the development of receptor decoy therapeutics for CPE-mediated gastrointestinal disease, reagents for cancer therapy/diagnoses and enhancers of drug delivery. PMID:27090847

Stairs and Doors Recognition as Natural Landmarks Based on Clouds of 3D Edge-Points from RGB-D Sensors for Mobile Robot Localization.

PubMed

Souto, Leonardo A V; Castro, André; Gonçalves, Luiz Marcos Garcia; Nascimento, Tiago P

2017-08-08

Natural landmarks are the main features in the next step of the research in localization of mobile robot platforms. The identification and recognition of these landmarks are crucial to better localize a robot. To help solving this problem, this work proposes an approach for the identification and recognition of natural marks included in the environment using images from RGB-D (Red, Green, Blue, Depth) sensors. In the identification step, a structural analysis of the natural landmarks that are present in the environment is performed. The extraction of edge points of these landmarks is done using the 3D point cloud obtained from the RGB-D sensor. These edge points are smoothed through the S l 0 algorithm, which minimizes the standard deviation of the normals at each point. Then, the second step of the proposed algorithm begins, which is the proper recognition of the natural landmarks. This recognition step is done as a real-time algorithm that extracts the points referring to the filtered edges and determines to which structure they belong to in the current scenario: stairs or doors. Finally, the geometrical characteristics that are intrinsic to the doors and stairs are identified. The approach proposed here has been validated with real robot experiments. The performed tests verify the efficacy of our proposed approach.

Stairs and Doors Recognition as Natural Landmarks Based on Clouds of 3D Edge-Points from RGB-D Sensors for Mobile Robot Localization†

PubMed Central

Castro, André; Nascimento, Tiago P.

2017-01-01

Natural landmarks are the main features in the next step of the research in localization of mobile robot platforms. The identification and recognition of these landmarks are crucial to better localize a robot. To help solving this problem, this work proposes an approach for the identification and recognition of natural marks included in the environment using images from RGB-D (Red, Green, Blue, Depth) sensors. In the identification step, a structural analysis of the natural landmarks that are present in the environment is performed. The extraction of edge points of these landmarks is done using the 3D point cloud obtained from the RGB-D sensor. These edge points are smoothed through the Sl0 algorithm, which minimizes the standard deviation of the normals at each point. Then, the second step of the proposed algorithm begins, which is the proper recognition of the natural landmarks. This recognition step is done as a real-time algorithm that extracts the points referring to the filtered edges and determines to which structure they belong to in the current scenario: stairs or doors. Finally, the geometrical characteristics that are intrinsic to the doors and stairs are identified. The approach proposed here has been validated with real robot experiments. The performed tests verify the efficacy of our proposed approach. PMID:28786925

DECONTAMINATION OF DDT-POLLUTED SOIL BY SOIL WASHING/CLOUD POINT EXTRACTION (R822832)

EPA Science Inventory

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

Environmental monitoring of phenolic pollutants in water by cloud point extraction prior to micellar electrokinetic chromatography.

PubMed

Stege, Patricia W; Sombra, Lorena L; Messina, Germán A; Martinez, Luis D; Silva, María F

2009-05-01

Many aromatic compounds can be found in the environment as a result of anthropogenic activities and some of them are highly toxic. The need to determine low concentrations of pollutants requires analytical methods with high sensitivity, selectivity, and resolution for application to soil, sediment, water, and other environmental samples. Complex sample preparation involving analyte isolation and enrichment is generally necessary before the final analysis. The present paper outlines a novel, simple, low-cost, and environmentally friendly method for the simultaneous determination of p-nitrophenol (PNP), p-aminophenol (PAP), and hydroquinone (HQ) by micellar electrokinetic capillary chromatography after preconcentration by cloud point extraction. Enrichment factors of 180 to 200 were achieved. The limits of detection of the analytes for the preconcentration of 50-ml sample volume were 0.10 microg L(-1) for PNP, 0.20 microg L(-1) for PAP, and 0.16 microg L(-1) for HQ. The optimized procedure was applied to the determination of phenolic pollutants in natural waters from San Luis, Argentina.

Monitoring Aircraft Motion at Airports by LIDAR

NASA Astrophysics Data System (ADS)

Toth, C.; Jozkow, G.; Koppanyi, Z.; Young, S.; Grejner-Brzezinska, D.

2016-06-01

Improving sensor performance, combined with better affordability, provides better object space observability, resulting in new applications. Remote sensing systems are primarily concerned with acquiring data of the static components of our environment, such as the topographic surface of the earth, transportation infrastructure, city models, etc. Observing the dynamic component of the object space is still rather rare in the geospatial application field; vehicle extraction and traffic flow monitoring are a few examples of using remote sensing to detect and model moving objects. Deploying a network of inexpensive LiDAR sensors along taxiways and runways can provide both geometrically and temporally rich geospatial data that aircraft body can be extracted from the point cloud, and then, based on consecutive point clouds motion parameters can be estimated. Acquiring accurate aircraft trajectory data is essential to improve aviation safety at airports. This paper reports about the initial experiences obtained by using a network of four Velodyne VLP- 16 sensors to acquire data along a runway segment.

Antiretroviral therapy CNS penetration and HIV-1-associated CNS disease.

PubMed

Garvey, L; Winston, A; Walsh, J; Post, F; Porter, K; Gazzard, B; Fisher, M; Leen, C; Pillay, D; Hill, T; Johnson, M; Gilson, R; Anderson, J; Easterbrook, P; Bansi, L; Orkin, C; Ainsworth, J; Palfreeman, A; Gompels, M; Phillips, A N; Sabin, C A

2011-02-22

The impact of different antiretroviral agents on the risk of developing or surviving CNS disease remains unknown. The aim of this study was to investigate whether using antiretroviral regimens with higher CNS penetration effectiveness (CPE) scores was associated with reduced incidence of CNS disease and improved survival in the UK Collaborative HIV Cohort (CHIC) Study. Adults without previous CNS disease, who commenced combination antiretroviral therapy (cART) between 1996 and 2008, were included (n = 22,356). Initial and most recent cART CPE scores were calculated. CNS diseases were HIV encephalopathy (HIVe), progressive multifocal leukoencephalopathy (PML), cerebral toxoplasmosis (TOXO), and cryptococcal meningitis (CRYPTO). Incidence rates and overall survival were stratified by CPE score. A multivariable Poisson regression model was used to identify independent associations. The median (interquartile range) CPE score for initial cART regimen increased from 7 (5-8) in 1996-1997 to 9 (8-10) in 2000-2001 and subsequently declined to 6 (7-8) in 2006-2008. Differences in gender, HIV acquisition risk group, and ethnicity existed between CPE score strata. A total of 251 subjects were diagnosed with a CNS disease (HIVe 80; TOXO 59; CRYPTO 56; PML 54). CNS diseases occurred more frequently in subjects prescribed regimens with CPE scores ≤ 4, and less frequently in those with scores ≥ 10; however, these differences were nonsignificant. Initial and most recent cART CPE scores ≤ 4 were independently associated with increased risk of death. Clinical status at time of commencing cART influences antiretroviral selection and CPE score. This information should be considered when utilizing CPE scores for retrospective analyses.

An Efficient Method for Automatic Road Extraction Based on Multiple Features from LiDAR Data

NASA Astrophysics Data System (ADS)

Li, Y.; Hu, X.; Guan, H.; Liu, P.

2016-06-01

The road extraction in urban areas is difficult task due to the complicated patterns and many contextual objects. LiDAR data directly provides three dimensional (3D) points with less occlusions and smaller shadows. The elevation information and surface roughness are distinguishing features to separate roads. However, LiDAR data has some disadvantages are not beneficial to object extraction, such as the irregular distribution of point clouds and lack of clear edges of roads. For these problems, this paper proposes an automatic road centerlines extraction method which has three major steps: (1) road center point detection based on multiple feature spatial clustering for separating road points from ground points, (2) local principal component analysis with least squares fitting for extracting the primitives of road centerlines, and (3) hierarchical grouping for connecting primitives into complete roads network. Compared with MTH (consist of Mean shift algorithm, Tensor voting, and Hough transform) proposed in our previous article, this method greatly reduced the computational cost. To evaluate the proposed method, the Vaihingen data set, a benchmark testing data provided by ISPRS for "Urban Classification and 3D Building Reconstruction" project, was selected. The experimental results show that our method achieve the same performance by less time in road extraction using LiDAR data.

Development of selective medium for IMP-type carbapenemase-producing Enterobacteriaceae in stool specimens.

PubMed

Yamamoto, Norihisa; Kawahara, Ryuji; Akeda, Yukihiro; Shanmugakani, Rathina Kumar; Yoshida, Hisao; Hagiya, Hideharu; Hara, Naohiro; Nishi, Isao; Yukawa, Satomi; Asada, Rumiko; Sasaki, Yumi; Maeda, Kazuhiro; Sakamoto, Noriko; Hamada, Shigeyuki; Tomono, Kazunori

2017-03-24

Identification of carbapenemase-producing Enterobacteriaceae (CPE) in faecal specimens is challenging. This fact is particularly critical because low-level carbapenem-resistant organisms such as IMP-producing CPE are most prevalent in Japan. We developed a modified selective medium more suitable for IMP-type CPE. Fifteen reference CPE strains producing different types of β-lactamases were used to evaluate the commercially available CHROMagar KPC and chromID CARBA as well as the newly prepared MC-ECC medium (CHROMagar ECC supplemented with meropenem, cloxacillin, and ZnSO 4 ) and M-ECC medium (CHROMagar ECC supplemented with meropenem and ZnSO 4 ). A total of 1035 clinical samples were then examined to detect CPE using chromID CARBA and M-ECC medium. All tested strains producing NDM-, KPC-, and OXA-48-carbapenemases were successfully cultured in the media employed. Although most of the IMP-positive strains did not grow in CHROMagar KPC, chromID CARBA, or MC-ECC, all tested strains grew on M-ECC. When faecal samples were applied to the media, M-ECC medium allowed the best growth of IMP-type CPE with a significantly higher sensitivity (99.3%) than that of chromID CARBA (13.9%). M-ECC medium was determined as the most favourable selective medium for the detection of IMP-type CPE as well as other types of CPE.

Detailed Hydrographic Feature Extraction from High-Resolution LiDAR Data

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

Danny L. Anderson

Detailed hydrographic feature extraction from high-resolution light detection and ranging (LiDAR) data is investigated. Methods for quantitatively evaluating and comparing such extractions are presented, including the use of sinuosity and longitudinal root-mean-square-error (LRMSE). These metrics are then used to quantitatively compare stream networks in two studies. The first study examines the effect of raster cell size on watershed boundaries and stream networks delineated from LiDAR-derived digital elevation models (DEMs). The study confirmed that, with the greatly increased resolution of LiDAR data, smaller cell sizes generally yielded better stream network delineations, based on sinuosity and LRMSE. The second study demonstrates amore » new method of delineating a stream directly from LiDAR point clouds, without the intermediate step of deriving a DEM. Direct use of LiDAR point clouds could improve efficiency and accuracy of hydrographic feature extractions. The direct delineation method developed herein and termed “mDn”, is an extension of the D8 method that has been used for several decades with gridded raster data. The method divides the region around a starting point into sectors, using the LiDAR data points within each sector to determine an average slope, and selecting the sector with the greatest downward slope to determine the direction of flow. An mDn delineation was compared with a traditional grid-based delineation, using TauDEM, and other readily available, common stream data sets. Although, the TauDEM delineation yielded a sinuosity that more closely matches the reference, the mDn delineation yielded a sinuosity that was higher than either the TauDEM method or the existing published stream delineations. Furthermore, stream delineation using the mDn method yielded the smallest LRMSE.« less

Electrochemical detection of dopamine based on pre-concentration by graphene nanosheets.

PubMed

Bagherzadeh, Mojtaba; Heydari, Maryam

2013-10-21

Herein, graphene nanosheets (GNS) were synthesized, by a green and facile method based on reduction by glucose, and characterized. Afterwards, a carbon paste electrode (CPE) was modified with GNS by casting and drying GNS on top of the CPE (CPE/GNS). The behavior of the CPE/GNS towards dopamine (DA) and ascorbic acid (AA) was investigated by electrochemical methods and the obtained results showed that the CPE/GNS had adsorbed only DA. Based on this behavior, the DA molecules were pre-concentrated on top of the CPE/GNS, followed by stripping in DA free solution. Subsequent to experimental and instrumental optimization, a calibration curve from 2.0 × 10(-6) to 1.0 × 10(-3) M DA, r(2) = 0.99 (±0.01), with detection limit (DL) = 8.5 × 10(-7) M DA, sensitivity = 15.4 (±0.94) μA, and RSD = 6.1 was observed in the presence of 1.0 × 10(-3) M AA. Finally, the performance of the CPE/GNS was successfully tested in a pharmaceutical sample. This work provides a promising strategy for DA detection in the presence of biological interferences, e.g. AA, with high sensitivity and simple characteristics.

Accuracy Analysis of a Dam Model from Drone Surveys

PubMed Central

Buffi, Giulia; Venturi, Sara

2017-01-01

This paper investigates the accuracy of models obtained by drone surveys. To this end, this work analyzes how the placement of ground control points (GCPs) used to georeference the dense point cloud of a dam affects the resulting three-dimensional (3D) model. Images of a double arch masonry dam upstream face are acquired from drone survey and used to build the 3D model of the dam for vulnerability analysis purposes. However, there still remained the issue of understanding the real impact of a correct GCPs location choice to properly georeference the images and thus, the model. To this end, a high number of GCPs configurations were investigated, building a series of dense point clouds. The accuracy of these resulting dense clouds was estimated comparing the coordinates of check points extracted from the model and their true coordinates measured via traditional topography. The paper aims at providing information about the optimal choice of GCPs placement not only for dams but also for all surveys of high-rise structures. The knowledge a priori of the effect of the GCPs number and location on the model accuracy can increase survey reliability and accuracy and speed up the survey set-up operations. PMID:28771185

Accuracy Analysis of a Dam Model from Drone Surveys.

PubMed

Ridolfi, Elena; Buffi, Giulia; Venturi, Sara; Manciola, Piergiorgio

2017-08-03

This paper investigates the accuracy of models obtained by drone surveys. To this end, this work analyzes how the placement of ground control points (GCPs) used to georeference the dense point cloud of a dam affects the resulting three-dimensional (3D) model. Images of a double arch masonry dam upstream face are acquired from drone survey and used to build the 3D model of the dam for vulnerability analysis purposes. However, there still remained the issue of understanding the real impact of a correct GCPs location choice to properly georeference the images and thus, the model. To this end, a high number of GCPs configurations were investigated, building a series of dense point clouds. The accuracy of these resulting dense clouds was estimated comparing the coordinates of check points extracted from the model and their true coordinates measured via traditional topography. The paper aims at providing information about the optimal choice of GCPs placement not only for dams but also for all surveys of high-rise structures. The knowledge a priori of the effect of the GCPs number and location on the model accuracy can increase survey reliability and accuracy and speed up the survey set-up operations.

Antiretroviral therapy CNS penetration and HIV-1–associated CNS disease

PubMed Central

Winston, A.; Walsh, J.; Post, F.; Porter, K.; Gazzard, B.; Fisher, M.; Leen, C.; Pillay, D.; Hill, T.; Johnson, M.; Gilson, R.; Anderson, J.; Easterbrook, P.; Bansi, L.; Orkin, C.; Ainsworth, J.; Palfreeman, A.; Gompels, M.; Phillips, A.N.; Sabin, C.A.

2011-01-01

Objective: The impact of different antiretroviral agents on the risk of developing or surviving CNS disease remains unknown. The aim of this study was to investigate whether using antiretroviral regimens with higher CNS penetration effectiveness (CPE) scores was associated with reduced incidence of CNS disease and improved survival in the UK Collaborative HIV Cohort (CHIC) Study. Methods: Adults without previous CNS disease, who commenced combination antiretroviral therapy (cART) between 1996 and 2008, were included (n = 22,356). Initial and most recent cART CPE scores were calculated. CNS diseases were HIV encephalopathy (HIVe), progressive multifocal leukoencephalopathy (PML), cerebral toxoplasmosis (TOXO), and cryptococcal meningitis (CRYPTO). Incidence rates and overall survival were stratified by CPE score. A multivariable Poisson regression model was used to identify independent associations. Results: The median (interquartile range) CPE score for initial cART regimen increased from 7 (5–8) in 1996–1997 to 9 (8–10) in 2000–2001 and subsequently declined to 6 (7–8) in 2006–2008. Differences in gender, HIV acquisition risk group, and ethnicity existed between CPE score strata. A total of 251 subjects were diagnosed with a CNS disease (HIVe 80; TOXO 59; CRYPTO 56; PML 54). CNS diseases occurred more frequently in subjects prescribed regimens with CPE scores ≤4, and less frequently in those with scores ≥10; however, these differences were nonsignificant. Initial and most recent cART CPE scores ≤4 were independently associated with increased risk of death. Conclusion: Clinical status at time of commencing cART influences antiretroviral selection and CPE score. This information should be considered when utilizing CPE scores for retrospective analyses. PMID:21339496

Increasing proportion of carbapenemase-producing Enterobacteriaceae and emergence of a MCR-1 producer through a multicentric study among hospital-based and private laboratories in Belgium from September to November 2015.

PubMed

Huang, Te Din; Bogaerts, Pierre; Berhin, Catherine; Hoebeke, Martin; Bauraing, Caroline; Glupczynski, Youri

2017-05-11

Carbapenemase-producing Enterobacteriaceae (CPE) strains have been increasingly reported in Belgium. We aimed to determine the proportion of CPE among Enterobacteriaceae isolated from hospitalised patients and community outpatients in Belgium in 2015. For the hospitalised patients, the results were compared to a previous similar survey performed in the same hospitals in 2012. Twenty-four hospital-based and 10 private laboratories collected prospectively 200 non-duplicated Enterobacteriaceae isolates from clinical specimens. All isolates were screened locally by carbapenem disk diffusion using European Committee on Antimicrobial Susceptibility Testing methodology. Putative CPE strains with inhibition zone diameters below the screening breakpoints were referred centrally for confirmation of carbapenemase production. From September to November 2015, we found a proportion of clinical CPE of 0.55% (26/4,705) and of 0.60% (12/1,991) among hospitalised patients and among ambulatory outpatients respectively. Klebsiella pneumoniae (26/38) and OXA-48-like carbapenemase (28/38) were the predominant species and enzyme among CPE. One OXA-48-producing Escherichia coli isolated from a hospital was found carrying plasmid-mediated MCR-1 colistin resistance. Compared with the 2012 survey, we found a significant increased proportion of clinical CPE (0.55% in 2015 vs 0.25% in 2012; p = 0.02) and an increased proportion of hospitals (13/24 in 2015 vs 8/24 in 2012) with at least one CPE detected. The study results confirmed the concerning spread of CPE including a colistin-resistant MCR-1 producer in hospitals and the establishment of CPE in the community in Belgium. This article is copyright of The Authors, 2017.

Analysis, Thematic Maps and Data Mining from Point Cloud to Ontology for Software Development

NASA Astrophysics Data System (ADS)

Nespeca, R.; De Luca, L.

2016-06-01

The primary purpose of the survey for the restoration of Cultural Heritage is the interpretation of the state of building preservation. For this, the advantages of the remote sensing systems that generate dense point cloud (range-based or image-based) are not limited only to the acquired data. The paper shows that it is possible to extrapolate very useful information in diagnostics using spatial annotation, with the use of algorithms already implemented in open-source software. Generally, the drawing of degradation maps is the result of manual work, so dependent on the subjectivity of the operator. This paper describes a method of extraction and visualization of information, obtained by mathematical procedures, quantitative, repeatable and verifiable. The case study is a part of the east facade of the Eglise collégiale Saint-Maurice also called Notre Dame des Grâces, in Caromb, in southern France. The work was conducted on the matrix of information contained in the point cloud asci format. The first result is the extrapolation of new geometric descriptors. First, we create the digital maps with the calculated quantities. Subsequently, we have moved to semi-quantitative analyses that transform new data into useful information. We have written the algorithms for accurate selection, for the segmentation of point cloud, for automatic calculation of the real surface and the volume. Furthermore, we have created the graph of spatial distribution of the descriptors. This work shows that if we work during the data processing we can transform the point cloud into an enriched database: the use, the management and the data mining is easy, fast and effective for everyone involved in the restoration process.

Single shot laser speckle based 3D acquisition system for medical applications

NASA Astrophysics Data System (ADS)

Khan, Danish; Shirazi, Muhammad Ayaz; Kim, Min Young

2018-06-01

The state of the art techniques used by medical practitioners to extract the three-dimensional (3D) geometry of different body parts requires a series of images/frames such as laser line profiling or structured light scanning. Movement of the patients during scanning process often leads to inaccurate measurements due to sequential image acquisition. Single shot structured techniques are robust to motion but the prevalent challenges in single shot structured light methods are the low density and algorithm complexity. In this research, a single shot 3D measurement system is presented that extracts the 3D point cloud of human skin by projecting a laser speckle pattern using a single pair of images captured by two synchronized cameras. In contrast to conventional laser speckle 3D measurement systems that realize stereo correspondence by digital correlation of projected speckle patterns, the proposed system employs KLT tracking method to locate the corresponding points. The 3D point cloud contains no outliers and sufficient quality of 3D reconstruction is achieved. The 3D shape acquisition of human body parts validates the potential application of the proposed system in the medical industry.

New Roles of Carboxypeptidase E in Endocrine and Neural Function and Cancer

PubMed Central

Cawley, Niamh X.; Wetsel, William C.; Murthy, Saravana R. K.; Park, Joshua J.; Pacak, Karel

2012-01-01

Carboxypeptidase E (CPE) or carboxypeptidase H was first discovered in 1982 as an enkephalin-convertase that cleaved a C-terminal basic residue from enkephalin precursors to generate enkephalin. Since then, CPE has been shown to be a multifunctional protein that subserves many essential nonenzymatic roles in the endocrine and nervous systems. Here, we review the phylogeny, structure, and function of CPE in hormone and neuropeptide sorting and vesicle transport for secretion, alternative splicing of the CPE transcript, and single nucleotide polymorphisms in humans. With this and the analysis of mutant and knockout mice, the data collectively support important roles for CPE in the modulation of metabolic and glucose homeostasis, bone remodeling, obesity, fertility, neuroprotection, stress, sexual behavior, mood and emotional responses, learning, and memory. Recently, a splice variant form of CPE has been found to be an inducer of tumor growth and metastasis and a prognostic biomarker for metastasis in endocrine and nonendocrine tumors. PMID:22402194

Min-Cut Based Segmentation of Airborne LIDAR Point Clouds

NASA Astrophysics Data System (ADS)

Ural, S.; Shan, J.

2012-07-01

Introducing an organization to the unstructured point cloud before extracting information from airborne lidar data is common in many applications. Aggregating the points with similar features into segments in 3-D which comply with the nature of actual objects is affected by the neighborhood, scale, features and noise among other aspects. In this study, we present a min-cut based method for segmenting the point cloud. We first assess the neighborhood of each point in 3-D by investigating the local geometric and statistical properties of the candidates. Neighborhood selection is essential since point features are calculated within their local neighborhood. Following neighborhood determination, we calculate point features and determine the clusters in the feature space. We adapt a graph representation from image processing which is especially used in pixel labeling problems and establish it for the unstructured 3-D point clouds. The edges of the graph that are connecting the points with each other and nodes representing feature clusters hold the smoothness costs in the spatial domain and data costs in the feature domain. Smoothness costs ensure spatial coherence, while data costs control the consistency with the representative feature clusters. This graph representation formalizes the segmentation task as an energy minimization problem. It allows the implementation of an approximate solution by min-cuts for a global minimum of this NP hard minimization problem in low order polynomial time. We test our method with airborne lidar point cloud acquired with maximum planned post spacing of 1.4 m and a vertical accuracy 10.5 cm as RMSE. We present the effects of neighborhood and feature determination in the segmentation results and assess the accuracy and efficiency of the implemented min-cut algorithm as well as its sensitivity to the parameters of the smoothness and data cost functions. We find that smoothness cost that only considers simple distance parameter does not strongly conform to the natural structure of the points. Including shape information within the energy function by assigning costs based on the local properties may help to achieve a better representation for segmentation.

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2017-10-18

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

Geometric identification and damage detection of structural elements by terrestrial laser scanner

NASA Astrophysics Data System (ADS)

Hou, Tsung-Chin; Liu, Yu-Wei; Su, Yu-Min

2016-04-01

In recent years, three-dimensional (3D) terrestrial laser scanning technologies with higher precision and higher capability are developing rapidly. The growing maturity of laser scanning has gradually approached the required precision as those have been provided by traditional structural monitoring technologies. Together with widely available fast computation for massive point cloud data processing, 3D laser scanning can serve as an efficient structural monitoring alternative for civil engineering communities. Currently most research efforts have focused on integrating/calculating the measured multi-station point cloud data, as well as modeling/establishing the 3D meshes of the scanned objects. Very little attention has been spent on extracting the information related to health conditions and mechanical states of structures. In this study, an automated numerical approach that integrates various existing algorithms for geometric identification and damage detection of structural elements were established. Specifically, adaptive meshes were employed for classifying the point cloud data of the structural elements, and detecting the associated damages from the calculated eigenvalues in each area of the structural element. Furthermore, kd-tree was used to enhance the searching efficiency of plane fitting which were later used for identifying the boundaries of structural elements. The results of geometric identification were compared with M3C2 algorithm provided by CloudCompare, as well as validated by LVDT measurements of full-scale reinforced concrete beams tested in laboratory. It shows that 3D laser scanning, through the established processing approaches of the point cloud data, can offer a rapid, nondestructive, remote, and accurate solution for geometric identification and damage detection of structural elements.

Clostridium perfringens enterotoxin and Clostridium difficile toxin A/B do not play a role in acute haemorrhagic diarrhoea syndrome in dogs.

PubMed

Busch, K; Suchodolski, J S; Kühner, K A; Minamoto, Y; Steiner, J M; Mueller, R S; Hartmann, K; Unterer, S

2015-03-07

Although an association between clostridial pathogens and canine idiopathic acute haemorrhagic diarrhoea syndrome (AHDS) has been described, the relevance of those bacteria and their toxins remains unclear. The aim of this study was to evaluate the association between severity of clinical signs and presence of Clostridium perfringens enterotoxin (CPE) and Clostridium difficile toxin A/B (CDT A/B) in faeces of dogs with AHDS. Faecal samples of 54 dogs with idiopathic AHDS were tested by qualitative CPE and CDT A/B ELISA, and PCR was performed to detect enterotoxin genes of C. perfringens (cpe) and toxin B genes of C. difficile (cdt b). Prevalence of cdt b and CDT A/B in dogs with AHDS was 10/54 and 2/54 versus 3/23 and 0/23 in control dogs. Prevalence of cpe was 35/54 in affected versus 9/23 in control dogs. Prevalence of CPE in dogs with AHDS (13/54) was higher compared with control dogs (0/23). No significant difference was detected between CPE-positive and -negative and between cpe-positive and -negative dogs in severity of clinical signs, duration of hospitalisation, mortality rate and selected laboratory parameters. This study suggests that CPE and CDT A/B do not play a role in idiopathic AHDS, are not associated with clinical parameters in affected dogs and cannot be used to predict disease outcome. British Veterinary Association.

Building Facade Reconstruction by Fusing Terrestrial Laser Points and Images

PubMed Central

Pu, Shi; Vosselman, George

2009-01-01

Laser data and optical data have a complementary nature for three dimensional feature extraction. Efficient integration of the two data sources will lead to a more reliable and automated extraction of three dimensional features. This paper presents a semiautomatic building facade reconstruction approach, which efficiently combines information from terrestrial laser point clouds and close range images. A building facade's general structure is discovered and established using the planar features from laser data. Then strong lines in images are extracted using Canny extractor and Hough transformation, and compared with current model edges for necessary improvement. Finally, textures with optimal visibility are selected and applied according to accurate image orientations. Solutions to several challenge problems throughout the collaborated reconstruction, such as referencing between laser points and multiple images and automated texturing, are described. The limitations and remaining works of this approach are also discussed. PMID:22408539

Extraction of Urban Trees from Integrated Airborne Based Digital Image and LIDAR Point Cloud Datasets - Initial Results

NASA Astrophysics Data System (ADS)

Dogon-yaro, M. A.; Kumar, P.; Rahman, A. Abdul; Buyuksalih, G.

2016-10-01

Timely and accurate acquisition of information on the condition and structural changes of urban trees serves as a tool for decision makers to better appreciate urban ecosystems and their numerous values which are critical to building up strategies for sustainable development. The conventional techniques used for extracting tree features include; ground surveying and interpretation of the aerial photography. However, these techniques are associated with some constraint, such as labour intensive field work, a lot of financial requirement, influences by weather condition and topographical covers which can be overcome by means of integrated airborne based LiDAR and very high resolution digital image datasets. This study presented a semi-automated approach for extracting urban trees from integrated airborne based LIDAR and multispectral digital image datasets over Istanbul city of Turkey. The above scheme includes detection and extraction of shadow free vegetation features based on spectral properties of digital images using shadow index and NDVI techniques and automated extraction of 3D information about vegetation features from the integrated processing of shadow free vegetation image and LiDAR point cloud datasets. The ability of the developed algorithms shows a promising result as an automated and cost effective approach to estimating and delineated 3D information of urban trees. The research also proved that integrated datasets is a suitable technology and a viable source of information for city managers to be used in urban trees management.

Practice and research in Australian massage therapy: a national workforce survey

PubMed Central

Wardle, Jonathan L.; Barnett, Rebecca; Adams, Jon

2015-01-01

Background Massage is the largest complementary medicine profession in Australia, in terms of public utilisation, practitioner distribution, and number of practitioners, and is being increasingly integrated into the Australian health care system. However, despite the increasing importance of massage therapists in Australian health care delivery, or the increased practice and education obligations this may entail, there has been little exploration of practice, research, and education characteristics of the Australian massage therapist workforce. Purpose To identify practice, research, and education characteristics among the Australian massage therapist workforce. Settings The Australian massage therapy profession. Participants 301 randomly selected members of the Association of Massage Therapists (Australia). Research Design A 15-item, cross-sectional telephone survey. Main Outcomes Measures Massage therapists’ demographic information, practice characteristics, and education and research characteristics. Results Most respondents (73.8%) worked 20 hours per week or less practising massage, nearly half of all respondents (46.8%) treated fewer than 10 massage clients per week, and over three-quarters (81.7%) of respondents were self-employed. Massage therapy was the sole source of income for just over half (55.0%) of the study respondents. Only 5.7% of respondents earned over the average wage ($50,000) through their massage activities. Nearly half of all respondents (43.3%) reported regularly exceeding their continuing professional education (CPE) quota mandated by their professional association. However, 21.1% reported struggling to achieve their CPE quota each year. Over one-third of respondents (35.6%) were not interested in acquiring further CPE points beyond minimum requirements. Respondents were significantly more likely to have an active approach to research if they had higher income (p = .015). Multivariate analysis showed factors associated with access to CPE to be the only significant predictors for increased CPE. Conclusions The massage profession in Australia remains largely part-time and practitioners earn less than the average Australian wage. The factors that underlie research and education involvement appear to be highly individualised and, therefore, policies targeting specific groups may be arbitrary and ineffective. PMID:26082824

Valorisation of urban elements through 3D models generated from image matching point clouds and augmented reality visualization based in mobile platforms

NASA Astrophysics Data System (ADS)

Marques, Luís.; Roca Cladera, Josep; Tenedório, José António

2017-10-01

The use of multiple sets of images with high level of overlapping to extract 3D point clouds has increased progressively in recent years. There are two main fundamental factors in the origin of this progress. In first, the image matching algorithms has been optimised and the software available that supports the progress of these techniques has been constantly developed. In second, because of the emergent paradigm of smart cities which has been promoting the virtualization of urban spaces and their elements. The creation of 3D models for urban elements is extremely relevant for urbanists to constitute digital archives of urban elements and being especially useful for enrich maps and databases or reconstruct and analyse objects/areas through time, building and recreating scenarios and implementing intuitive methods of interaction. These characteristics assist, for example, higher public participation creating a completely collaborative solution system, envisioning processes, simulations and results. This paper is organized in two main topics. The first deals with technical data modelling obtained by terrestrial photographs: planning criteria for obtaining photographs, approving or rejecting photos based on their quality, editing photos, creating masks, aligning photos, generating tie points, extracting point clouds, generating meshes, building textures and exporting results. The application of these procedures results in 3D models for the visualization of urban elements of the city of Barcelona. The second concerns the use of Augmented Reality through mobile platforms allowing to understand the city origins and the relation with the actual city morphology, (en)visioning solutions, processes and simulations, making possible for the agents in several domains, to fundament their decisions (and understand them) achieving a faster and wider consensus.

First Steps to Automated Interior Reconstruction from Semantically Enriched Point Clouds and Imagery

NASA Astrophysics Data System (ADS)

Obrock, L. S.; Gülch, E.

2018-05-01

The automated generation of a BIM-Model from sensor data is a huge challenge for the modeling of existing buildings. Currently the measurements and analyses are time consuming, allow little automation and require expensive equipment. We do lack an automated acquisition of semantical information of objects in a building. We are presenting first results of our approach based on imagery and derived products aiming at a more automated modeling of interior for a BIM building model. We examine the building parts and objects visible in the collected images using Deep Learning Methods based on Convolutional Neural Networks. For localization and classification of building parts we apply the FCN8s-Model for pixel-wise Semantic Segmentation. We, so far, reach a Pixel Accuracy of 77.2 % and a mean Intersection over Union of 44.2 %. We finally use the network for further reasoning on the images of the interior room. We combine the segmented images with the original images and use photogrammetric methods to produce a three-dimensional point cloud. We code the extracted object types as colours of the 3D-points. We thus are able to uniquely classify the points in three-dimensional space. We preliminary investigate a simple extraction method for colour and material of building parts. It is shown, that the combined images are very well suited to further extract more semantic information for the BIM-Model. With the presented methods we see a sound basis for further automation of acquisition and modeling of semantic and geometric information of interior rooms for a BIM-Model.

Effect of paternal blue catfish strain effects on hatchery fry production and performance of channel catfish X blue catfish F1 hybrid fry production and fingerling performance under commercial conditions

USDA-ARS?s Scientific Manuscript database

Four hundred four-year old mature Gold Kist strain channel catfish, Ictalurus punctatus were induced to spawn with 10 mg common carp pituitary extract (CPE) /kg BW in 8 spawning trials. The stripped eggs were fertilized with sperm of either D&B or Rio Grande blue catfish, I.furcatus to produce D&B ...

Current trends in sample preparation for cosmetic analysis.

PubMed

Zhong, Zhixiong; Li, Gongke

2017-01-01

The widespread applications of cosmetics in modern life make their analysis particularly important from a safety point of view. There is a wide variety of restricted ingredients and prohibited substances that primarily influence the safety of cosmetics. Sample preparation for cosmetic analysis is a crucial step as the complex matrices may seriously interfere with the determination of target analytes. In this review, some new developments (2010-2016) in sample preparation techniques for cosmetic analysis, including liquid-phase microextraction, solid-phase microextraction, matrix solid-phase dispersion, pressurized liquid extraction, cloud point extraction, ultrasound-assisted extraction, and microwave digestion, are presented. Furthermore, the research and progress in sample preparation techniques and their applications in the separation and purification of allowed ingredients and prohibited substances are reviewed. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

An Indoor Slam Method Based on Kinect and Multi-Feature Extended Information Filter

NASA Astrophysics Data System (ADS)

Chang, M.; Kang, Z.

2017-09-01

Based on the frame of ORB-SLAM in this paper the transformation parameters between adjacent Kinect image frames are computed using ORB keypoints, from which priori information matrix and information vector are calculated. The motion update of multi-feature extended information filter is then realized. According to the point cloud data formed by depth image, ICP algorithm was used to extract the point features of the point cloud data in the scene and built an observation model while calculating a-posteriori information matrix and information vector, and weakening the influences caused by the error accumulation in the positioning process. Furthermore, this paper applied ORB-SLAM frame to realize autonomous positioning in real time in interior unknown environment. In the end, Lidar was used to get data in the scene in order to estimate positioning accuracy put forward in this paper.

Laser-based structural sensing and surface damage detection

NASA Astrophysics Data System (ADS)

Guldur, Burcu

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

Market segmentation and positioning: matching creativity with fiscal responsibility.

PubMed

Kiener, M E

1989-01-01

This paper describes an approach to continuing professional education (CPE) program development in nursing within a university environment that utilizes the concepts of market segmentation and positioning. Use of these strategies enables the academic CPE enterprise to move beyond traditional needs assessment practices to create more successful and better-managed CPE programs.

Conjugated polyelectrolyte based real-time fluorescence assay for phospholipase C.

PubMed

Liu, Yan; Ogawa, Katsu; Schanze, Kirk S

2008-01-01

A fluorescence turnoff assay for phospholipase C (PLC) from Clostridium perfringens is developed based on the reversible interaction between the natural substrate, phosphatidylcholine, and a fluorescent, water-soluble conjugated polyelectrolyte (CPE). The fluorescence intensity of the CPE in water is increased substantially by the addition of the phospholipid due to the formation of a CPE-lipid complex. Incubation of the CPE-lipid complex with the enzyme PLC causes the fluorescence intensity to decrease (turnoff sensor); the response arises due to PLC-catalyzed hydrolysis of the phosphatidylcholine, which effectively disrupts the CPE-lipid complex. The PLC assay operates with phospholipid substrate concentrations in the micromolar range, and the analytical detection limit for PLC is <1 nM. The optimized assay provides a convenient, rapid, and real-time sensor for PLC activity. The real-time fluorescence intensity from the CPE can be converted to substrate concentration by using an ex situ calibration curve, allowing PLC-catalyzed reaction rates and kinetic parameters to be determined. PLC activation by Ca2+ and inhibition by EDTA and fluoride ion are demonstrated using the optimized sensor.

Impedance Analysis of Ovarian Cancer Cells upon Challenge with C-terminal Clostridium Perfringens Enterotoxin

NASA Astrophysics Data System (ADS)

Gordon, Geoffrey; Lo, Chun-Min

2007-03-01

Both in vitro and animal studies in breast, prostate, and ovarian cancers have shown that clostridium perfringens enterotoxin (CPE), which binds to CLDN4, may have an important therapeutic benefit, as it is rapidly cytotoxic in tissues overexpressing CLDN4. This study sought to evaluate the ability of C-terminal clostridium perfringens enterotoxin (C-CPE), a CLDN4-targetting molecule, to disrupt tight junction barrier function. Electric cell-substrate impedance sensing (ECIS) was used to measure both junctional resistance and average cell-substrate separation of ovarian cancer cell lines after exposure to C-CPE. A total of 14 ovarian cancer cell lines were used, and included cell lines derived from serous, mucinous, and clear cells. Our results showed that junctional resistance increases as CLDN4 expression increases. In addition, C-CPE is non-cytotoxic in ovarian cancer cells expressing CLDN4. However, exposure to C-CPE results in a significant (p<0.05) dose- and CLDN4-dependent decrease in junctional resistance and an increase in cell-substrate separation. Treatment of ovarian cancer cell lines with C-CPE disrupts tight junction barrier function.

Simultaneous spectrophotometric determination of synthetic dyes in food samples after cloud point extraction using multiple response optimizations.

PubMed

Heidarizadi, Elham; Tabaraki, Reza

2016-01-01

A sensitive cloud point extraction method for simultaneous determination of trace amounts of sunset yellow (SY), allura red (AR) and brilliant blue (BB) by spectrophotometry was developed. Experimental parameters such as Triton X-100 concentration, KCl concentration and initial pH on extraction efficiency of dyes were optimized using response surface methodology (RSM) with a Doehlert design. Experimental data were evaluated by applying RSM integrating a desirability function approach. The optimum condition for extraction efficiency of SY, AR and BB simultaneously were: Triton X-100 concentration 0.0635 mol L(-1), KCl concentration 0.11 mol L(-1) and pH 4 with maximum overall desirability D of 0.95. Correspondingly, the maximum extraction efficiency of SY, AR and BB were 100%, 92.23% and 95.69%, respectively. At optimal conditions, extraction efficiencies were 99.8%, 92.48% and 95.96% for SY, AR and BB, respectively. These values were only 0.2%, 0.25% and 0.27% different from the predicted values, suggesting that the desirability function approach with RSM was a useful technique for simultaneously dye extraction. Linear calibration curves were obtained in the range of 0.02-4 for SY, 0.025-2.5 for AR and 0.02-4 μg mL(-1) for BB under optimum condition. Detection limit based on three times the standard deviation of the blank (3Sb) was 0.009, 0.01 and 0.007 μg mL(-1) (n=10) for SY, AR and BB, respectively. The method was successfully used for the simultaneous determination of the dyes in different food samples. Copyright © 2015 Elsevier B.V. All rights reserved.

Application of an aqueous two-phase micellar system to extract bromelain from pineapple (Ananas comosus) peel waste and analysis of bromelain stability in cosmetic formulations.

PubMed

Spir, Lívia Genovez; Ataide, Janaína Artem; De Lencastre Novaes, Letícia Celia; Moriel, Patrícia; Mazzola, Priscila Gava; De Borba Gurpilhares, Daniela; Silveira, Edgar; Pessoa, Adalberto; Tambourgi, Elias Basile

2015-01-01

Bromelain is a set of proteolytic enzymes found in pineapple (Ananas comosus) tissues such as stem, fruit and leaves. Because of its proteolytic activity, bromelain has potential applications in the cosmetic, pharmaceutical, and food industries. The present study focused on the recovery of bromelain from pineapple peel by liquid-liquid extraction in aqueous two-phase micellar systems (ATPMS), using Triton X-114 (TX-114) and McIlvaine buffer, in the absence and presence of electrolytes CaCl2 and KI; the cloud points of the generated extraction systems were studied by plotting binodal curves. Based on the cloud points, three temperatures were selected for extraction: 30, 33, and 36°C for systems in the absence of salts; 40, 43, and 46°C in the presence of KI; 24, 27, and 30°C in the presence of CaCl2 . Total protein and enzymatic activities were analyzed to monitor bromelain. Employing the ATPMS chosen for extraction (0.5 M KI with 3% TX-114, at pH 6.0, at 40°C), the bromelain extract stability was assessed after incorporation into three cosmetic bases: an anhydrous gel, a cream, and a cream-gel formulation. The cream-gel formulation presented as the most appropriate base to convey bromelain, and its optimal storage conditions were found to be 4.0 ± 0.5°C. The selected ATPMS enabled the extraction of a biomolecule with high added value from waste lined-up in a cosmetic formulation, allowing for exploration of further cosmetic potential. © 2015 American Institute of Chemical Engineers.

Glacier discharge and climate variations

NASA Astrophysics Data System (ADS)

Dominguez, M. Carmen; Rodriguez-Puebla, Concepcion; Encinas, Ascension H.; Visus, Isabel; Eraso, Adolfo

2010-05-01

Different studies account for the warming in the polar regions that consequently would affect Glacier Discharge (GD). Since changes in GD may cause large changes in sensible and latent heat fluxes, we ask about the relationships between GD and climate anomalies, which have not been quantified yet. In this study we apply different statistical methods such as correlation, Singular Spectral Analysis and Wavelet to compare the behaviour of GD data in two Experimental Pilot Catchments (CPE), one (CPE-KG-62°S) in the Antarctica and the other (CPE-KVIA-64°N) in the Arctic regions. Both CPE's are measuring sub- and endo-glacier drainage for recording of glacier melt water run-off. The CPE-KG-62°S is providing hourly GD time series since January 2002 in Collins glacier of the Maxwell Bay in King George Island (62°S, 58°W). The second one, CPE-KVIA-64°N, is providing hourly GD time series since September 2003 in the Kviarjökull glacier of the Vatnajökull ice cap in Iceland (64°N, 16°W). The soundings for these measurements are pressure sensors installed in the river of the selected catchments for the ice cap (CPE-KG-62°S) and in the river of the glacier for (CPE-KVIA-64°N). In each CPE, the calibration function between level and discharge has been adjusted, getting a very high correlation coefficient (0.99 for the first one and 0.95 for the second one), which let us devise a precise discharge law for the glacier. We obtained relationships between GD with atmospheric variables such as radiation, temperature, relative humidity, atmospheric pressure and precipitation. We also found a negative response of GD to El Niño teleconnection index. The results are of great interest due to the GD impact on the climate system and in particular for sea level rise.

Synthesis and application of a new thiazolylazo reagent for cloud point extraction and determination of cobalt in pharmaceutical preparations.

PubMed

Yamaki, Regina Terumi; Nunes, Luana Sena; de Oliveira, Hygor Rodrigues; Araújo, André S; Bezerra, Marcos Almeida; Lemos, Valfredo Azevedo

2011-01-01

The synthesis and characterization of the reagent 2-(5-bromothiazolylazo)-4-chlorophenol and its application in the development of a preconcentration procedure for cobalt determination using flame atomic absorption spectrometry after cloud point extraction is presented. This procedure is based on cobalt complexing and entrapment of the metal chelates into micelles of a surfactant-rich phase of Triton X-114. The preconcentration procedure was optimized by using a response surface methodology through the application of the Box-Behnken matrix. Under optimum conditions, the procedure determined the presence of cobalt with an LOD of 2.8 microg/L and LOQ of 9.3 microg/L. The enrichment factor obtained was 25. The precision was evaluated as the RSD, which was 5.5% for 10 microg/L cobalt and 6.9% for 30 microg/L. The accuracy of the procedure was assessed by comparing the results with those found using inductively coupled plasma-optical emission spectrometry. After validation, the procedure was applied to the determination of cobalt in pharmaceutical preparation samples containing cobalamin (vitamin B12).

Pole-Like Road Furniture Detection in Sparse and Unevenly Distributed Mobile Laser Scanning Data

NASA Astrophysics Data System (ADS)

Li, F.; Lehtomäki, M.; Oude Elberink, S.; Vosselman, G.; Puttonen, E.; Kukko, A.; Hyyppä, J.

2018-05-01

Pole-like road furniture detection received much attention due to its traffic functionality in recent years. In this paper, we develop a framework to detect pole-like road furniture from sparse mobile laser scanning data. The framework is carried out in four steps. The unorganised point cloud is first partitioned. Then above ground points are clustered and roughly classified after removing ground points. A slicing check in combination with cylinder masking is proposed to extract pole-like road furniture candidates. Pole-like road furniture are obtained after occlusion analysis in the last stage. The average completeness and correctness of pole-like road furniture in sparse and unevenly distributed mobile laser scanning data was above 0.83. It is comparable to the state of art in the field of pole-like road furniture detection in mobile laser scanning data of good quality and is potentially of practical use in the processing of point clouds collected by autonomous driving platforms.

Patient identification using a near-infrared laser scanner

NASA Astrophysics Data System (ADS)

Manit, Jirapong; Bremer, Christina; Schweikard, Achim; Ernst, Floris

2017-03-01

We propose a new biometric approach where the tissue thickness of a person's forehead is used as a biometric feature. Given that the spatial registration of two 3D laser scans of the same human face usually produces a low error value, the principle of point cloud registration and its error metric can be applied to human classification techniques. However, by only considering the spatial error, it is not possible to reliably verify a person's identity. We propose to use a novel near-infrared laser-based head tracking system to determine an additional feature, the tissue thickness, and include this in the error metric. Using MRI as a ground truth, data from the foreheads of 30 subjects was collected from which a 4D reference point cloud was created for each subject. The measurements from the near-infrared system were registered with all reference point clouds using the ICP algorithm. Afterwards, the spatial and tissue thickness errors were extracted, forming a 2D feature space. For all subjects, the lowest feature distance resulted from the registration of a measurement and the reference point cloud of the same person. The combined registration error features yielded two clusters in the feature space, one from the same subject and another from the other subjects. When only the tissue thickness error was considered, these clusters were less distinct but still present. These findings could help to raise safety standards for head and neck cancer patients and lays the foundation for a future human identification technique.

Determination of rhodium in metallic alloy and water samples using cloud point extraction coupled with spectrophotometric technique

NASA Astrophysics Data System (ADS)

Kassem, Mohammed A.; Amin, Alaa S.

2015-02-01

A new method to estimate rhodium in different samples at trace levels had been developed. Rhodium was complexed with 5-(4‧-nitro-2‧,6‧-dichlorophenylazo)-6-hydroxypyrimidine-2,4-dione (NDPHPD) as a complexing agent in an aqueous medium and concentrated by using Triton X-114 as a surfactant. The investigated rhodium complex was preconcentrated with cloud point extraction process using the nonionic surfactant Triton X-114 to extract rhodium complex from aqueous solutions at pH 4.75. After the phase separation at 50 °C, the surfactant-rich phase was heated again at 100 °C to remove water after decantation and the remaining phase was dissolved using 0.5 mL of acetonitrile. Under optimum conditions, the calibration curve was linear for the concentration range of 0.5-75 ng mL-1 and the detection limit was 0.15 ng mL-1 of the original solution. The enhancement factor of 500 was achieved for 250 mL samples containing the analyte and relative standard deviations were ⩽1.50%. The method was found to be highly selective, fairly sensitive, simple, rapid and economical and safely applied for rhodium determination in different complex materials such as synthetic mixture of alloys and environmental water samples.

MLS data segmentation using Point Cloud Library procedures. (Polish Title: Segmentacja danych MLS z użyciem procedur Point Cloud Library)

NASA Astrophysics Data System (ADS)

Grochocka, M.

2013-12-01

Mobile laser scanning is dynamically developing measurement technology, which is becoming increasingly widespread in acquiring three-dimensional spatial information. Continuous technical progress based on the use of new tools, technology development, and thus the use of existing resources in a better way, reveals new horizons of extensive use of MLS technology. Mobile laser scanning system is usually used for mapping linear objects, and in particular the inventory of roads, railways, bridges, shorelines, shafts, tunnels, and even geometrically complex urban spaces. The measurement is done from the perspective of use of the object, however, does not interfere with the possibilities of movement and work. This paper presents the initial results of the segmentation data acquired by the MLS. The data used in this work was obtained as part of an inventory measurement infrastructure railway line. Measurement of point clouds was carried out using a profile scanners installed on the railway platform. To process the data, the tools of 'open source' Point Cloud Library was used. These tools allow to use templates of programming libraries. PCL is an open, independent project, operating on a large scale for processing 2D/3D image and point clouds. Software PCL is released under the terms of the BSD license (Berkeley Software Distribution License), which means it is a free for commercial and research use. The article presents a number of issues related to the use of this software and its capabilities. Segmentation data is based on applying the templates library pcl_ segmentation, which contains the segmentation algorithms to separate clusters. These algorithms are best suited to the processing point clouds, consisting of a number of spatially isolated regions. Template library performs the extraction of the cluster based on the fit of the model by the consensus method samples for various parametric models (planes, cylinders, spheres, lines, etc.). Most of the mathematical operation is carried out on the basis of Eigen library, a set of templates for linear algebra.

A Phenomenological Investigation of Pharmacists' Experiences, Motivation, and Preferences in the Context of Continuing Pharmacy Education

ERIC Educational Resources Information Center

Ladymon, Laura Beth

2017-01-01

The purpose of this phenomenological study was to describe select Tennessee pharmacists' experiences, motivation, and preferences in the context of continuing pharmacy education (CPE). The pharmacists' experiences, motivation, and preferences related to CPE were generally defined as participating in CPE programming in a manner that meets the needs…

What Do Professional Conference Planners Consider the Most Important Elements for Continuing Professional Education Conference Planning?

ERIC Educational Resources Information Center

Phillips, Virginia B.

2011-01-01

Many adults attend and rely on continuing professional education (CPE) throughout their careers, and CPE is big business for associations. One way associations deliver CPE is through educational conferences. While adult education theories and frameworks offer developmental and operational guidance and advice, there is little practice data to…

3-D Object Recognition from Point Cloud Data

NASA Astrophysics Data System (ADS)

Smith, W.; Walker, A. S.; Zhang, B.

2011-09-01

The market for real-time 3-D mapping includes not only traditional geospatial applications but also navigation of unmanned autonomous vehicles (UAVs). Massively parallel processes such as graphics processing unit (GPU) computing make real-time 3-D object recognition and mapping achievable. Geospatial technologies such as digital photogrammetry and GIS offer advanced capabilities to produce 2-D and 3-D static maps using UAV data. The goal is to develop real-time UAV navigation through increased automation. It is challenging for a computer to identify a 3-D object such as a car, a tree or a house, yet automatic 3-D object recognition is essential to increasing the productivity of geospatial data such as 3-D city site models. In the past three decades, researchers have used radiometric properties to identify objects in digital imagery with limited success, because these properties vary considerably from image to image. Consequently, our team has developed software that recognizes certain types of 3-D objects within 3-D point clouds. Although our software is developed for modeling, simulation and visualization, it has the potential to be valuable in robotics and UAV applications. The locations and shapes of 3-D objects such as buildings and trees are easily recognizable by a human from a brief glance at a representation of a point cloud such as terrain-shaded relief. The algorithms to extract these objects have been developed and require only the point cloud and minimal human inputs such as a set of limits on building size and a request to turn on a squaring option. The algorithms use both digital surface model (DSM) and digital elevation model (DEM), so software has also been developed to derive the latter from the former. The process continues through the following steps: identify and group 3-D object points into regions; separate buildings and houses from trees; trace region boundaries; regularize and simplify boundary polygons; construct complex roofs. Several case studies have been conducted using a variety of point densities, terrain types and building densities. The results have been encouraging. More work is required for better processing of, for example, forested areas, buildings with sides that are not at right angles or are not straight, and single trees that impinge on buildings. Further work may also be required to ensure that the buildings extracted are of fully cartographic quality. A first version will be included in production software later in 2011. In addition to the standard geospatial applications and the UAV navigation, the results have a further advantage: since LiDAR data tends to be accurately georeferenced, the building models extracted can be used to refine image metadata whenever the same buildings appear in imagery for which the GPS/IMU values are poorer than those for the LiDAR.

Abundance indices for determining the status of lake trout restoration in Michigan waters of Lake Superior

USGS Publications Warehouse

Hansen, Michael J.; Schorfhaar, Richard G.; Peck, James W.; Selgeby, James H.; Taylor, William W.

1995-01-01

Self-sustaining populations of lake trout Salvelinus namaycush have returned to most areas in Lake Superior, but progress toward achieving historic commercial yields has been difficult to measure because of unrecorded losses to predation by sea lamprey Petromyzon marinus and to fisheries. Consequently, we developed restoration targets (catch per effort, CPE; geometric mean number per kilometer of 114-mm stretch-meaure gill net during 1929-1943, when historic yields were sustained) from linear relationships between CPE in commercial and assessment fisheries in Michigan. Target CPEs for lake trout restoration were higher and less variable than the modern CPEs in all areas. Modern CPEs generally increased during the 1970s and early 1980s but declined during the late 1980s and early 1990s. Modern CPEs were highest in western Michigan from the Keweenaw Peninsula to Marquette (71 to 81% of target CPEs), but coefficients of variation (CV,SD/mean) of mean CPEs were 1.4 to 2.4 times greater than target CVs. Around Munising, the modern CPE was lower (41% of the target CPE), whereas the CV was 1.9 times greater than the target CV. Around Grand Marais, the modern CPE was lowest among all areas (17% of the target CPE), but the CV was nearly the same (1.1 times the target CV). In Whitefish Bay, the modern CPE was only 28% of the target CPE and the CV was 9.0 times greater, though the modern period was based on only the years 1979-1982 and 1984-1985. Further progress in restoration in most areas can be achieved only if fishery managers adequately protect existing stocks of wild fish from sea lamprey predation and fishery exploitation.

Efficient Detection of Carbapenemase Activity in Enterobacteriaceae by Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry in Less Than 30 Minutes.

PubMed

Lasserre, Camille; De Saint Martin, Luc; Cuzon, Gaelle; Bogaerts, Pierre; Lamar, Estelle; Glupczynski, Youri; Naas, Thierry; Tandé, Didier

2015-07-01

The recognition of carbapenemase-producing Enterobacteriaceae (CPE) isolates is a major laboratory challenge, and their inappropriate or delayed detection may have negative impacts on patient management and on the implementation of infection control measures. We describe here a matrix-assisted laser desorption ionization-time of flight (MALDI-TOF)-based method to detect carbapenemase activity in Enterobacteriaceae. After a 20-min incubation of the isolate with 0.5 mg/ml imipenem at 37°C, supernatants were analyzed by MALDI-TOF in order to identify peaks corresponding to imipenem (300 Da) and an imipenem metabolite (254 Da). A total of 223 strains, 77 CPE (OXA-48 variants, KPC, NDM, VIM, IMI, IMP, and NMC-A) and 146 non-CPE (cephalosporinases, extended-spectrum β-lactamases [ESBLs], and porin defects), were tested and used to calculate a ratio of imipenem hydrolysis: mass spectrometry [MS] ratio = metabolite/(imipenem + metabolite). An MS ratio cutoff was statistically determined to classify strains as carbapenemase producers (MS ratio of ≥0.82). We validated this method first by testing 30 of our 223 isolates (15 CPE and 15 non-CPE) 10 times to calculate an intraclass correlation coefficient (ICC of 0.98), showing the excellent repeatability of the method. Second, 43 strains (25 CPE and 18 non-CPE) different from the 223 strains used to calculate the ratio cutoff were used as external controls and blind tested. They yielded sensitivity and specificity of 100%. The total cost per test is <0.10 U.S. dollars (USD). This easy-to-perform assay is time-saving, cost-efficient, and highly reliable and might be used in any routine laboratory, given the availability of mass spectrometry, to detect CPE. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Detection of enterotoxigenic Clostridium perfringens in meat samples by using molecular methods.

PubMed

Kaneko, Ikuko; Miyamoto, Kazuaki; Mimura, Kanako; Yumine, Natsuko; Utsunomiya, Hirotoshi; Akimoto, Shigeru; McClane, Bruce A

2011-11-01

To prevent food-borne bacterial diseases and to trace bacterial contamination events to foods, microbial source tracking (MST) methods provide important epidemiological information. To apply molecular methods to MST, it is necessary not only to amplify bacterial cells to detection limit levels but also to prepare DNA with reduced inhibitory compounds and contamination. Isolates carrying the Clostridium perfringens enterotoxin gene (cpe) on the chromosome or a plasmid rank among the most important food-borne pathogens. Previous surveys indicated that cpe-positive C. perfringens isolates are present in only ∼5% of nonoutbreak food samples and then only at low numbers, usually less than 3 cells/g. In this study, four molecular assays for the detection of cpe-positive C. perfringens isolates, i.e., ordinary PCR, nested PCR, real-time PCR, and loop-mediated isothermal amplification (LAMP), were developed and evaluated for their reliability using purified DNA. For use in the artificial contamination of meat samples, DNA templates were prepared by three different commercial DNA preparation kits. The four molecular assays always detected cpe when >10³ cells/g of cpe-positive C. perfringens were present, using any kit. Of three tested commercial DNA preparation kits, the InstaGene matrix kit appeared to be most suitable for the testing of a large number of samples. By using the InstaGene matrix kit, the four molecular assays efficiently detected cpe using DNA prepared from enrichment culture specimens of meat samples contaminated with low numbers of cpe-positive C. perfringens vegetative cells or spores. Overall, the current study developed molecular assay protocols for MST to detect the contamination of foods with low numbers of cells, and at a low frequency, of cpe-positive C. perfringens isolates.

ATS-6 - Preliminary results from the 13/18-GHz COMSAT Propagation Experiment

NASA Technical Reports Server (NTRS)

Hyde, G.

1975-01-01

The 13/18-GHz COMSAT Propagation Experiment (CPE) is reviewed, the data acquisition and processing are discussed, and samples of preliminary results are presented. The need for measurements of both hydrometeor-induced attenuation statistics and diversity effectiveness is brought out. The facilitation of the experiment - CPE dual frequency and diversity site location, the CPE ground transmit terminals, the CPE transponder on Applications Technology Satellite-6 (ATS-6), and the CPE receive and data acquisition system - is briefly examined. The on-line preprocessing of the received signal is reviewed, followed by a discussion of the off-line processing of this database to remove signal fluctuations not due to hydrometeors. Finally, samples of the results of first-level analysis of the resultant data for the 18-GHz diversity site near Boston, Mass., and for the dual frequency 13/18-GHz site near Detroit, Mich., are presented and discussed.

Critically Engaging "Mutually Engaged Supervisory Processes": A Proposed Theory for CPE Supervisory Education.

PubMed

Fitchett, George; Altenbaumer, Mary L; Atta, Osofo Kwesi; Stowman, Sheryl Lyndes; Vlach, Kyle

2014-12-01

Revisions to the processes for training and certifying supervisors continue to be debated within the Association for Clinical Pastoral Education (ACPE). In 2012 Ragsdale and colleagues published, "Mutually engaged supervisory processes," a qualitative research study utilizing grounded theory based on interviews with 19 recently certified Associate CPE Supervisors, of nine components that facilitate the development of CPE supervisory education students. In this article we critically engage this theory and the research upon which it is based. We also reflect on three issues highlighted by the theory: personal transformation in CPE supervisory education, how CPE supervisory education students develop theoretical foundations for their work, and engaging multicultural issues in supervisory education. We conclude that this theory offers ACPE the possibility of using research to guide future modifications to its practice of Supervisory education. © 2014 Journal of Pastoral Care Publications Inc.

Reconstruction of 3d Models from Point Clouds with Hybrid Representation

NASA Astrophysics Data System (ADS)

Hu, P.; Dong, Z.; Yuan, P.; Liang, F.; Yang, B.

2018-05-01

The three-dimensional (3D) reconstruction of urban buildings from point clouds has long been an active topic in applications related to human activities. However, due to the structures significantly differ in terms of complexity, the task of 3D reconstruction remains a challenging issue especially for the freeform surfaces. In this paper, we present a new reconstruction algorithm which allows the 3D-models of building as a combination of regular structures and irregular surfaces, where the regular structures are parameterized plane primitives and the irregular surfaces are expressed as meshes. The extraction of irregular surfaces starts with an over-segmented method for the unstructured point data, a region growing approach based the adjacent graph of super-voxels is then applied to collapse these super-voxels, and the freeform surfaces can be clustered from the voxels filtered by a thickness threshold. To achieve these regular planar primitives, the remaining voxels with a larger flatness will be further divided into multiscale super-voxels as basic units, and the final segmented planes are enriched and refined in a mutually reinforcing manner under the framework of a global energy optimization. We have implemented the proposed algorithms and mainly tested on two point clouds that differ in point density and urban characteristic, and experimental results on complex building structures illustrated the efficacy of the proposed framework.

Complementary experimental-simulational study of surfactant micellar phase in the extraction process of metallic ions: Effects of temperature and salt concentration

NASA Astrophysics Data System (ADS)

Soto-Ángeles, Alan Gustavo; Rodríguez-Hidalgo, María del Rosario; Soto-Figueroa, César; Vicente, Luis

2018-02-01

The thermoresponsive micellar phase behaviour that exhibits the Triton-X-100 micelles by temperature effect and addition of salt in the extraction process of metallic ions was explored from mesoscopic and experimental points. In the theoretical study, we analyse the formation of Triton-X-100 micelles, load and stabilization of dithizone molecules and metallic ions extraction inside the micellar core at room temperature; finally, a thermal analysis is presented. In the experimental study, the spectrophotometric outcomes confirm the solubility of the copper-dithizone complex in the micellar core, as well as the extraction of metallic ions of aqueous environment via a cloud-point at 332.2 K. The micellar solutions with salt present a low absorbance value compared with the micellar solutions without salt. The decrease in the absorbance value is attributed to a change in the size of hydrophobic region of colloidal micelles. All transitory stages of extraction process are discussed and analysed in this document.

First Prismatic Building Model Reconstruction from Tomosar Point Clouds

NASA Astrophysics Data System (ADS)

Sun, Y.; Shahzad, M.; Zhu, X.

2016-06-01

This paper demonstrates for the first time the potential of explicitly modelling the individual roof surfaces to reconstruct 3-D prismatic building models using spaceborne tomographic synthetic aperture radar (TomoSAR) point clouds. The proposed approach is modular and works as follows: it first extracts the buildings via DSM generation and cutting-off the ground terrain. The DSM is smoothed using BM3D denoising method proposed in (Dabov et al., 2007) and a gradient map of the smoothed DSM is generated based on height jumps. Watershed segmentation is then adopted to oversegment the DSM into different regions. Subsequently, height and polygon complexity constrained merging is employed to refine (i.e., to reduce) the retrieved number of roof segments. Coarse outline of each roof segment is then reconstructed and later refined using quadtree based regularization plus zig-zag line simplification scheme. Finally, height is associated to each refined roof segment to obtain the 3-D prismatic model of the building. The proposed approach is illustrated and validated over a large building (convention center) in the city of Las Vegas using TomoSAR point clouds generated from a stack of 25 images using Tomo-GENESIS software developed at DLR.

Complete Sequence Analysis and Antiviral Screening of Medicinal Plants for Human Coxsackievirus A16 Isolated in Korea

PubMed Central

Song, Jae-Hyoung; Park, Kwisung; Shim, Aeri; Kwon, Bo-Eun; Ahn, Jae-Hee; Choi, Young Jin; Kim, Jae Kyung; Yeo, Sang-Gu; Yoon, Kyungah; Ko, Hyun-Jeong

2015-01-01

Objectives Coxsackievirus A group 16 strain (CVA16) is one of the predominant causative agents of hand, foot, and mouth disease (HFMD). Methods Using a specimen from a male patient with HFMD, we isolated and performed sequencing of the Korean CVA16 strain and compared it with a G10 reference strain. Also, we were investigated the effects of medicinal plant extract on the cytopathic effects (CPE) by CPE reduction assay against Korean CVA16. Results Phylogenetic analysis showed that the Korean CVA16 isolate belonged to cluster B-1 and was closely related to the strain PM-15765-00 isolated in Malaysia in 2000. The Korean CVA16 isolate showed 73.2% nucleotide identity to the G10 prototype strain and 98.7% nucleotide identity to PM-15765-00. Next, we assessed whether the Korean CVA16 isolate could be used for in vitro screening of antiviral agents to treat HFMD infection. Vero cells infected with the Korean CVA16 isolate showed a cytopathic effect 2 days after the infection, and the treatment of cells with Cornus officinalis, Acer triflorum, Pulsatilla koreana, and Clematis heracleifolia var. davidiana Hemsl extracts exhibited strong antiviral activity against CVA16. Conclusion Collectively, our work provides potential candidates for the development of vaccine and novel drugs to treat the CVA16 strain isolated from a Korean patient. PMID:25737832

Complete sequence analysis and antiviral screening of medicinal plants for human coxsackievirus a16 isolated in Korea.

PubMed

Song, Jae-Hyoung; Park, Kwisung; Shim, Aeri; Kwon, Bo-Eun; Ahn, Jae-Hee; Choi, Young Jin; Kim, Jae Kyung; Yeo, Sang-Gu; Yoon, Kyungah; Ko, Hyun-Jeong

2015-02-01

Coxsackievirus A group 16 strain (CVA16) is one of the predominant causative agents of hand, foot, and mouth disease (HFMD). Using a specimen from a male patient with HFMD, we isolated and performed sequencing of the Korean CVA16 strain and compared it with a G10 reference strain. Also, we were investigated the effects of medicinal plant extract on the cytopathic effects (CPE) by CPE reduction assay against Korean CVA16. Phylogenetic analysis showed that the Korean CVA16 isolate belonged to cluster B-1 and was closely related to the strain PM-15765-00 isolated in Malaysia in 2000. The Korean CVA16 isolate showed 73.2% nucleotide identity to the G10 prototype strain and 98.7% nucleotide identity to PM-15765-00. Next, we assessed whether the Korean CVA16 isolate could be used for in vitro screening of antiviral agents to treat HFMD infection. Vero cells infected with the Korean CVA16 isolate showed a cytopathic effect 2 days after the infection, and the treatment of cells with Cornus officinalis, Acer triflorum, Pulsatilla koreana, and Clematis heracleifolia var. davidiana Hemsl extracts exhibited strong antiviral activity against CVA16. Collectively, our work provides potential candidates for the development of vaccine and novel drugs to treat the CVA16 strain isolated from a Korean patient.

Deterrents to Nurses' Participation in Continuing Professional Education as Perceived by Licensed Nurses in Oklahoma

ERIC Educational Resources Information Center

Fahnestock, Annetta Bethene

2012-01-01

Little is known about the deterrents to licensed nurses' participation in continuing professional education (CPE) in Oklahoma, the licensed nurses' preferred method for obtaining CPE, and the ways in which employers support participation in CPE. A random sample of 78 licensed nurses in Oklahoma completed a 20 item questionnaire and a 40 item…

Efficient Open Source Lidar for Desktop Users

NASA Astrophysics Data System (ADS)

Flanagan, Jacob P.

Lidar --- Light Detection and Ranging --- is a remote sensing technology that utilizes a device similar to a rangefinder to determine a distance to a target. A laser pulse is shot at an object and the time it takes for the pulse to return in measured. The distance to the object is easily calculated using the speed property of light. For lidar, this laser is moved (primarily in a rotational movement usually accompanied by a translational movement) and records the distances to objects several thousands of times per second. From this, a 3 dimensional structure can be procured in the form of a point cloud. A point cloud is a collection of 3 dimensional points with at least an x, a y and a z attribute. These 3 attributes represent the position of a single point in 3 dimensional space. Other attributes can be associated with the points that include properties such as the intensity of the return pulse, the color of the target or even the time the point was recorded. Another very useful, post processed attribute is point classification where a point is associated with the type of object the point represents (i.e. ground.). Lidar has gained popularity and advancements in the technology has made its collection easier and cheaper creating larger and denser datasets. The need to handle this data in a more efficiently manner has become a necessity; The processing, visualizing or even simply loading lidar can be computationally intensive due to its very large size. Standard remote sensing and geographical information systems (GIS) software (ENVI, ArcGIS, etc.) was not originally built for optimized point cloud processing and its implementation is an afterthought and therefore inefficient. Newer, more optimized software for point cloud processing (QTModeler, TopoDOT, etc.) usually lack more advanced processing tools, requires higher end computers and are very costly. Existing open source lidar approaches the loading and processing of lidar in an iterative fashion that requires implementing batch coding and processing time that could take months for a standard lidar dataset. This project attempts to build a software with the best approach for creating, importing and exporting, manipulating and processing lidar, especially in the environmental field. Development of this software is described in 3 sections - (1) explanation of the search methods for efficiently extracting the "area of interest" (AOI) data from disk (file space), (2) using file space (for storage), budgeting memory space (for efficient processing) and moving between the two, and (3) method development for creating lidar products (usually raster based) used in environmental modeling and analysis (i.e.: hydrology feature extraction, geomorphological studies, ecology modeling, etc.).

Extended polarization in 3rd order SCC-DFTB from chemical potential equilization

PubMed Central

Kaminski, Steve; Giese, Timothy J.; Gaus, Michael; York, Darrin M.; Elstner, Marcus

2012-01-01

In this work we augment the approximate density functional method SCC-DFTB (DFTB3) with the chemical potential equilization (CPE) approach in order to improve the performance for molecular electronic polarizabilities. The CPE method, originally implemented for NDDO type methods by Giese and York, has been shown to emend minimal basis methods wrt response properties significantly, and has been applied to SCC-DFTB recently. CPE allows to overcome this inherent limitation of minimal basis methods by supplying an additional response density. The systematic underestimation is thereby corrected quantitatively without the need to extend the atomic orbital basis, i.e. without increasing the overall computational cost significantly. Especially the dependency of polarizability as a function of molecular charge state was significantly improved from the CPE extension of DFTB3. The empirical parameters introduced by the CPE approach were optimized for 172 organic molecules in order to match the results from density functional methods (DFT) methods using large basis sets. However, the first order derivatives of molecular polarizabilities, as e.g. required to compute Raman activities, are not improved by the current CPE implementation, i.e. Raman spectra are not improved. PMID:22894819

Development and application of a multiplex PCR assay for detection of the Clostridium perfringens enterotoxin-encoding genes cpe and becAB.

PubMed

Yonogi, Shinya; Kanki, Masashi; Ohnishi, Takahiro; Shiono, Masami; Iida, Tetsuya; Kumeda, Yuko

2016-08-01

Clostridium perfringens causes food-borne gastroenteritis following the consumption of contaminated food by producing C. perfringens enterotoxin (CPE) in the intestines. Recently, we reported a novel enterotoxin, binary enterotoxin of C. perfringens (BEC) in C. perfringens isolates, which caused two disease outbreaks in Japan. Consequently, in the event of food poisoning outbreaks caused by C. perfringens, it is now necessary to screen for both the cpe and becAB genes by diagnostic PCR. Here, we present a simple multiplex PCR method for simultaneous detection of cpe, becAB and a C. perfringens control locus, phospholipase C (plc). Applying this method, we investigated the prevalence of cpe- or becAB-carrying C. perfringens strains in human stool and bovine rectum swab samples. Using a total of 169 isolates, we found that the percentage of becAB-carrying strains was very small (0.59%), one-tenth that of cpe-carrying strains. The simple method presented in this study with high specificity and sensitivity to C. perfringens will be a useful tool to survey the global prevalence of becAB-carrying C. perfringens strains. Copyright © 2016 Elsevier B.V. All rights reserved.

Current Continuing Professional Education Practice among Malaysian Nurses

PubMed Central

Chong, Mei Chan; Francis, Karen; Cooper, Simon; Abdullah, Khatijah Lim

2014-01-01

Nurses need to participate in CPE to update their knowledge and increase their competencies. This research was carried out to explore their current practice and the future general needs for CPE. This cross-sectional descriptive study involved registered nurses from government hospitals and health clinics from Peninsular Malaysia. Multistage cluster sampling was used to recruit 1000 nurses from four states of Malaysia. Self-explanatory questionnaires were used to collect the data, which were analyzed using SPSS version 16. Seven hundred and ninety-two nurses participated in this survey. Only 80% (562) of the nurses had engaged in CPE activities during the past 12 months. All attendance for the various activities was below 50%. Workshops were the most popular CPE activity (345, 43.6%) and tertiary education was the most unpopular activity (10, 1.3%). The respondents did perceive the importance of future CPE activities for career development. Mandatory continuing professional education (MCPE) is a key measure to ensure that nurses upgrade their knowledge and skills; however, it is recommended that policy makers and nurse leaders in the continuing professional development unit of health service facilities plan CPE activities to meet registered nurses' (RNs) needs and not simply organizational requirements. PMID:24523961

Claudin-4 Overexpression in Epithelial Ovarian Cancer Is Associated with Hypomethylation and Is a Potential Target for Modulation of Tight Junction Barrier Function Using a C-Terminal Fragment of Clostridium perfringens Enterotoxin1

PubMed Central

Litkouhi, Babak; Kwong, Joseph; Lo, Chun-Min; Smedley, James G; McClane, Bruce A; Aponte, Margarita; Gao, Zhijian; Sarno, Jennifer L; Hinners, Jennifer; Welch, William R; Berkowitz, Ross S; Mok, Samuel C; Garner, Elizabeth I O

2007-01-01

Background Claudin-4, a tight junction (TJ) protein and receptor for the C-terminal fragment of Clostridium perfringens enterotoxin (C-CPE), is overexpressed in epithelial ovarian cancer (EOC). Previous research suggests DNA methylation is a mechanism for claudin-4 overexpression in cancer and that C-CPE acts as an absorption-enhancing agent in claudin-4-expressing cells. We sought to correlate claudin-4 overexpression in EOC with clinical outcomes and TJ barrier function, investigate DNA methylation as a mechanism for overexpression, and evaluate the effect of C-CPE on the TJ. Methods Claudin-4 expression in EOC was quantified and correlated with clinical outcomes. Claudin-4 methylation status was determined, and claudin-4-negative cell lines were treated with a demethylating agent. Electric cell-substrate impedance sensing was used to calculate junctional (paracellular) resistance (Rb) in EOC cells after claudin-4 silencing and after C-CPE treatment. Results Claudin-4 overexpression in EOC does not correlate with survival or other clinical endpoints and is associated with hypomethylation. Claudin-4 overexpression correlates with Rb and C-CPE treatment of EOC cells significantly decreased Rb in a dose- and claudin-4-dependent noncytotoxic manner. Conclusions C-CPE treatment of EOC cells leads to altered TJ function. Further research is needed to determine the potential clinical applications of C-CPE in EOC drug delivery strategies. PMID:17460774

Point-Cloud Compression for Vehicle-Based Mobile Mapping Systems Using Portable Network Graphics

NASA Astrophysics Data System (ADS)

Kohira, K.; Masuda, H.

2017-09-01

A mobile mapping system is effective for capturing dense point-clouds of roads and roadside objects Point-clouds of urban areas, residential areas, and arterial roads are useful for maintenance of infrastructure, map creation, and automatic driving. However, the data size of point-clouds measured in large areas is enormously large. A large storage capacity is required to store such point-clouds, and heavy loads will be taken on network if point-clouds are transferred through the network. Therefore, it is desirable to reduce data sizes of point-clouds without deterioration of quality. In this research, we propose a novel point-cloud compression method for vehicle-based mobile mapping systems. In our compression method, point-clouds are mapped onto 2D pixels using GPS time and the parameters of the laser scanner. Then, the images are encoded in the Portable Networking Graphics (PNG) format and compressed using the PNG algorithm. In our experiments, our method could efficiently compress point-clouds without deteriorating the quality.

Determination of triazole fungicides in environmental water samples by high performance liquid chromatography with cloud point extraction using polyethylene glycol 600 monooleate.

PubMed

Tang, Tao; Qian, Kun; Shi, Tianyu; Wang, Fang; Li, Jianqiang; Cao, Yongsong

2010-11-08

A preconcentration technique known as cloud point extraction was developed for the determination of trace levels of triazole fungicides tricyclazole, triadimefon, tebuconazole and diniconazole in environmental waters. The triazole fungicides were extracted and preconcentrated using polyethylene glycol 600 monooleate (PEG600MO) as a low toxic and environmentally benign nonionic surfactant, and determined by high performance liquid chromatography/ultraviolet detection (HPLC-UV). The extraction conditions were optimized for the four triazole fungicides as follows: 2.0 wt% PEG600MO, 2.5 wt% Na(2)SO(4), equilibration at 45°C for 10 min, and centrifugation at 2000 rpm (533 × g) for 5 min. The triazole fungicides were well separated on a reversed-phase kromasil ODS C(18) column (250 mm × 4.6 mm, 5 μm) with gradient elution at ambient temperature and detected at 225 nm. The calibration range was 0.05-20 μg L(-1) for tricyclazole and 0.5-20 μg L(-1) for the other three classes of analytes with the correlation coefficients over 0.9992. Preconcentration factors were higher than 60-fold for the four selected fungicides. The limits of detection were 6.8-34.5 ng L(-1) (S/N=3) and the recoveries were 82.0-96.0% with the relative standard deviations of 2.8-7.8%. Copyright © 2010 Elsevier B.V. All rights reserved.

Educating CPE supervisors: a grounded theory study.

PubMed

Ragsdale, Judith R; Holloway, Elizabeth L; Ivy, Steven S

2009-01-01

This qualitative study was designed to cull the wisdom of CPE supervisors doing especially competent supervisory education and to develop a theory of CPE supervisory education. Grounded theory methodology included interviewing 11 supervisors and coding the data to identify themes. Four primary dimensions emerged along with a reciprocal core dimension, Supervisory Wisdom, which refers to work the supervisors do in terms of their continuing growth and development.

Applications of Panoramic Images: from 720° Panorama to Interior 3d Models of Augmented Reality

NASA Astrophysics Data System (ADS)

Lee, I.-C.; Tsai, F.

2015-05-01

A series of panoramic images are usually used to generate a 720° panorama image. Although panoramic images are typically used for establishing tour guiding systems, in this research, we demonstrate the potential of using panoramic images acquired from multiple sites to create not only 720° panorama, but also three-dimensional (3D) point clouds and 3D indoor models. Since 3D modeling is one of the goals of this research, the location of the panoramic sites needed to be carefully planned in order to maintain a robust result for close-range photogrammetry. After the images are acquired, panoramic images are processed into 720° panoramas, and these panoramas which can be used directly as panorama guiding systems or other applications. In addition to these straightforward applications, interior orientation parameters can also be estimated while generating 720° panorama. These parameters are focal length, principle point, and lens radial distortion. The panoramic images can then be processed with closerange photogrammetry procedures to extract the exterior orientation parameters and generate 3D point clouds. In this research, VisaulSFM, a structure from motion software is used to estimate the exterior orientation, and CMVS toolkit is used to generate 3D point clouds. Next, the 3D point clouds are used as references to create building interior models. In this research, Trimble Sketchup was used to build the model, and the 3D point cloud was added to the determining of locations of building objects using plane finding procedure. In the texturing process, the panorama images are used as the data source for creating model textures. This 3D indoor model was used as an Augmented Reality model replacing a guide map or a floor plan commonly used in an on-line touring guide system. The 3D indoor model generating procedure has been utilized in two research projects: a cultural heritage site at Kinmen, and Taipei Main Station pedestrian zone guidance and navigation system. The results presented in this paper demonstrate the potential of using panoramic images to generate 3D point clouds and 3D models. However, it is currently a manual and labor-intensive process. A research is being carried out to Increase the degree of automation of these procedures.

An Iterative Closest Points Algorithm for Registration of 3D Laser Scanner Point Clouds with Geometric Features.

PubMed

He, Ying; Liang, Bin; Yang, Jun; Li, Shunzhi; He, Jin

2017-08-11

The Iterative Closest Points (ICP) algorithm is the mainstream algorithm used in the process of accurate registration of 3D point cloud data. The algorithm requires a proper initial value and the approximate registration of two point clouds to prevent the algorithm from falling into local extremes, but in the actual point cloud matching process, it is difficult to ensure compliance with this requirement. In this paper, we proposed the ICP algorithm based on point cloud features (GF-ICP). This method uses the geometrical features of the point cloud to be registered, such as curvature, surface normal and point cloud density, to search for the correspondence relationships between two point clouds and introduces the geometric features into the error function to realize the accurate registration of two point clouds. The experimental results showed that the algorithm can improve the convergence speed and the interval of convergence without setting a proper initial value.

An Iterative Closest Points Algorithm for Registration of 3D Laser Scanner Point Clouds with Geometric Features

PubMed Central

Liang, Bin; Yang, Jun; Li, Shunzhi; He, Jin

2017-01-01

The Iterative Closest Points (ICP) algorithm is the mainstream algorithm used in the process of accurate registration of 3D point cloud data. The algorithm requires a proper initial value and the approximate registration of two point clouds to prevent the algorithm from falling into local extremes, but in the actual point cloud matching process, it is difficult to ensure compliance with this requirement. In this paper, we proposed the ICP algorithm based on point cloud features (GF-ICP). This method uses the geometrical features of the point cloud to be registered, such as curvature, surface normal and point cloud density, to search for the correspondence relationships between two point clouds and introduces the geometric features into the error function to realize the accurate registration of two point clouds. The experimental results showed that the algorithm can improve the convergence speed and the interval of convergence without setting a proper initial value. PMID:28800096

PET attenuation correction for flexible MRI surface coils in hybrid PET/MRI using a 3D depth camera

NASA Astrophysics Data System (ADS)

Frohwein, Lynn J.; Heß, Mirco; Schlicher, Dominik; Bolwin, Konstantin; Büther, Florian; Jiang, Xiaoyi; Schäfers, Klaus P.

2018-01-01

PET attenuation correction for flexible MRI radio frequency surface coils in hybrid PET/MRI is still a challenging task, as position and shape of these coils conform to large inter-patient variabilities. The purpose of this feasibility study is to develop a novel method for the incorporation of attenuation information about flexible surface coils in PET reconstruction using the Microsoft Kinect V2 depth camera. The depth information is used to determine a dense point cloud of the coil’s surface representing the shape of the coil. From a CT template—acquired once in advance—surface information of the coil is extracted likewise and converted into a point cloud. The two point clouds are then registered using a combination of an iterative-closest-point (ICP) method and a partially rigid registration step. Using the transformation derived through the point clouds, the CT template is warped and thereby adapted to the PET/MRI scan setup. The transformed CT template is converted into an attenuation map from Hounsfield units into linear attenuation coefficients. The resulting fitted attenuation map is then integrated into the MRI-based patient-specific DIXON-based attenuation map of the actual PET/MRI scan. A reconstruction of phantom PET data acquired with the coil present in the field-of-view (FoV), but without the corresponding coil attenuation map, shows large artifacts in regions close to the coil. The overall count loss is determined to be around 13% compared to a PET scan without the coil present in the FoV. A reconstruction using the new μ-map resulted in strongly reduced artifacts as well as increased overall PET intensities with a remaining relative difference of about 1% to a PET scan without the coil in the FoV.

Multiple-Primitives Hierarchical Classification of Airborne Laser Scanning Data in Urban Areas

NASA Astrophysics Data System (ADS)

Ni, H.; Lin, X. G.; Zhang, J. X.

2017-09-01

A hierarchical classification method for Airborne Laser Scanning (ALS) data of urban areas is proposed in this paper. This method is composed of three stages among which three types of primitives are utilized, i.e., smooth surface, rough surface, and individual point. In the first stage, the input ALS data is divided into smooth surfaces and rough surfaces by employing a step-wise point cloud segmentation method. In the second stage, classification based on smooth surfaces and rough surfaces is performed. Points in the smooth surfaces are first classified into ground and buildings based on semantic rules. Next, features of rough surfaces are extracted. Then, points in rough surfaces are classified into vegetation and vehicles based on the derived features and Random Forests (RF). In the third stage, point-based features are extracted for the ground points, and then, an individual point classification procedure is performed to classify the ground points into bare land, artificial ground and greenbelt. Moreover, the shortages of the existing studies are analyzed, and experiments show that the proposed method overcomes these shortages and handles more types of objects.

Extraction and representation of common feature from uncertain facial expressions with cloud model.

PubMed

Wang, Shuliang; Chi, Hehua; Yuan, Hanning; Geng, Jing

2017-12-01

Human facial expressions are key ingredient to convert an individual's innate emotion in communication. However, the variation of facial expressions affects the reliable identification of human emotions. In this paper, we present a cloud model to extract facial features for representing human emotion. First, the uncertainties in facial expression are analyzed in the context of cloud model. The feature extraction and representation algorithm is established under cloud generators. With forward cloud generator, facial expression images can be re-generated as many as we like for visually representing the extracted three features, and each feature shows different roles. The effectiveness of the computing model is tested on Japanese Female Facial Expression database. Three common features are extracted from seven facial expression images. Finally, the paper is concluded and remarked.

Evaluation Model for Pavement Surface Distress on 3d Point Clouds from Mobile Mapping System

NASA Astrophysics Data System (ADS)

Aoki, K.; Yamamoto, K.; Shimamura, H.

2012-07-01

This paper proposes a methodology to evaluate the pavement surface distress for maintenance planning of road pavement using 3D point clouds from Mobile Mapping System (MMS). The issue on maintenance planning of road pavement requires scheduled rehabilitation activities for damaged pavement sections to keep high level of services. The importance of this performance-based infrastructure asset management on actual inspection data is globally recognized. Inspection methodology of road pavement surface, a semi-automatic measurement system utilizing inspection vehicles for measuring surface deterioration indexes, such as cracking, rutting and IRI, have already been introduced and capable of continuously archiving the pavement performance data. However, any scheduled inspection using automatic measurement vehicle needs much cost according to the instruments' specification or inspection interval. Therefore, implementation of road maintenance work, especially for the local government, is difficult considering costeffectiveness. Based on this background, in this research, the methodologies for a simplified evaluation for pavement surface and assessment of damaged pavement section are proposed using 3D point clouds data to build urban 3D modelling. The simplified evaluation results of road surface were able to provide useful information for road administrator to find out the pavement section for a detailed examination and for an immediate repair work. In particular, the regularity of enumeration of 3D point clouds was evaluated using Chow-test and F-test model by extracting the section where the structural change of a coordinate value was remarkably achieved. Finally, the validity of the current methodology was investigated by conducting a case study dealing with the actual inspection data of the local roads.

Automated Feature Extraction of Foredune Morphology from Terrestrial Lidar Data

NASA Astrophysics Data System (ADS)

Spore, N.; Brodie, K. L.; Swann, C.

2014-12-01

Foredune morphology is often described in storm impact prediction models using the elevation of the dune crest and dune toe and compared with maximum runup elevations to categorize the storm impact and predicted responses. However, these parameters do not account for other foredune features that may make them more or less erodible, such as alongshore variations in morphology, vegetation coverage, or compaction. The goal of this work is to identify other descriptive features that can be extracted from terrestrial lidar data that may affect the rate of dune erosion under wave attack. Daily, mobile-terrestrial lidar surveys were conducted during a 6-day nor'easter (Hs = 4 m in 6 m water depth) along 20km of coastline near Duck, North Carolina which encompassed a variety of foredune forms in close proximity to each other. This abstract will focus on the tools developed for the automated extraction of the morphological features from terrestrial lidar data, while the response of the dune will be presented by Brodie and Spore as an accompanying abstract. Raw point cloud data can be dense and is often under-utilized due to time and personnel constraints required for analysis, since many algorithms are not fully automated. In our approach, the point cloud is first projected into a local coordinate system aligned with the coastline, and then bare earth points are interpolated onto a rectilinear 0.5 m grid creating a high resolution digital elevation model. The surface is analyzed by identifying features along each cross-shore transect. Surface curvature is used to identify the position of the dune toe, and then beach and berm morphology is extracted shoreward of the dune toe, and foredune morphology is extracted landward of the dune toe. Changes in, and magnitudes of, cross-shore slope, curvature, and surface roughness are used to describe the foredune face and each cross-shore transect is then classified using its pre-storm morphology for storm-response analysis.

Naringin promotes osteogenic differentiation of bone marrow stromal cells by up-regulating Foxc2 expression via the IHH signaling pathway

PubMed Central

Lin, Fei-xiang; Du, Shi-xin; Liu, De-zhong; Hu, Qin-xiao; Yu, Guo-yong; Wu, Chu-cheng; Zheng, Gui-zhou; Xie, Da; Li, Xue-dong; Chang, Bo

2016-01-01

Naringin is an active compound extracted from Rhizoma Drynariae, and studies have revealed that naringin can promote proliferation and osteogenic differentiation of bone marrow stromal cells (BMSCs). In this study, we explored whether naringin could promote osteogenic differentiation of BMSCs by upregulating Foxc2 expression via the Indian hedgehog (IHH) signaling pathway. BMSCs were cultured in basal medium, basal medium with naringin, osteogenic induction medium, osteogenic induction medium with naringin and osteogenic induction medium with naringin in the presence of the IHH inhibitor cyclopamine (CPE). We examined cell proliferation by using a WST-8 assay, and differentiation by Alizarin Red S staining (for mineralization) and alkaline phosphatase (ALP) activity. In addition, we detected core-binding factor α1 (Cbfα1), osteocalcin (OCN), bone sialoprotein (BSP), peroxisome proliferation-activated receptor gamma 2 (PPARγ2) and Foxc2 expression by using RT-PCR. We also determined Foxc2 and IHH protein levels by western blotting. Naringin increased the mineralization of BMSCs, as shown by Alizarin red S assays, and induced ALP activity. In addition, naringin significantly increased the mRNA levels of Foxc2, Cbfα1, OCN, and BSP, while decreasing PPARγ2 mRNA levels. Furthermore, the IHH inhibitor CPE inhibited the osteogenesis-potentiating effects of naringin. Naringin increased Foxc2 and stimulated the activation of IHH, as evidenced by increased expression of proteins that were inhibited by CPE. Our findings indicate that naringin promotes osteogenic differentiation of BMSCs by up-regulating Foxc2 expression via the IHH signaling pathway. PMID:27904711

Naringin promotes osteogenic differentiation of bone marrow stromal cells by up-regulating Foxc2 expression via the IHH signaling pathway.

PubMed

Lin, Fei-Xiang; Du, Shi-Xin; Liu, De-Zhong; Hu, Qin-Xiao; Yu, Guo-Yong; Wu, Chu-Cheng; Zheng, Gui-Zhou; Xie, Da; Li, Xue-Dong; Chang, Bo

2016-01-01

Naringin is an active compound extracted from Rhizoma Drynariae, and studies have revealed that naringin can promote proliferation and osteogenic differentiation of bone marrow stromal cells (BMSCs). In this study, we explored whether naringin could promote osteogenic differentiation of BMSCs by upregulating Foxc2 expression via the Indian hedgehog (IHH) signaling pathway. BMSCs were cultured in basal medium, basal medium with naringin, osteogenic induction medium, osteogenic induction medium with naringin and osteogenic induction medium with naringin in the presence of the IHH inhibitor cyclopamine (CPE). We examined cell proliferation by using a WST-8 assay, and differentiation by Alizarin Red S staining (for mineralization) and alkaline phosphatase (ALP) activity. In addition, we detected core-binding factor α1 (Cbfα1), osteocalcin (OCN), bone sialoprotein (BSP), peroxisome proliferation-activated receptor gamma 2 (PPARγ2) and Foxc2 expression by using RT-PCR. We also determined Foxc2 and IHH protein levels by western blotting. Naringin increased the mineralization of BMSCs, as shown by Alizarin red S assays, and induced ALP activity. In addition, naringin significantly increased the mRNA levels of Foxc2, Cbfα1, OCN, and BSP, while decreasing PPARγ2 mRNA levels. Furthermore, the IHH inhibitor CPE inhibited the osteogenesis-potentiating effects of naringin. Naringin increased Foxc2 and stimulated the activation of IHH, as evidenced by increased expression of proteins that were inhibited by CPE. Our findings indicate that naringin promotes osteogenic differentiation of BMSCs by up-regulating Foxc2 expression via the IHH signaling pathway.

Structural elucidation of anti-metastatic rhamnogalacturonan II from the pectinase digest of citrus peels (Citrus unshiu).

PubMed

Park, Hye-Ryung; Park, Su Beom; Hong, Hee-Do; Suh, Hyung Joo; Shin, Kwang-Soon

2017-01-01

The aim of this study was to characterize a polysaccharide found in citrus peels with an anti-metastatic property. CPE-II was purified by the pectinase digestion of citrus peels. During in vivo lung metastasis of Colon26-M3.1, administration of 10μg of CPE-II per mouse showed 81.3% inhibition of metastasis. CPE-II consists of 15 different monosaccharides and 22 different glycosyl linkages, characteristic of rhamnogalacturonan II (RG-II). The primary structure was elucidated based on sugar composition, methylation analysis, oligosaccharide analysis, and sequencing using GC, GC-MS, LC-MS, and ESI-MS/MS analyses. Sequential degradation using partial acid hydrolysis indicated that CPE-II contained Rhap-(1→5)-Kdo, Araf-(1→5)-Dha, an AceA-containing nonasaccharide, and an uronic acid-rich oligosaccharide in addition to an α-(1→4)-galacturono-oligosaccharide main chain. The molecular weight of CPE-II was observed to decrease from 9 to 5kDa at a pH value of <2.0, as observed by HPSEC. Thus, we propose that the anti-metastatic CPE-II is primarily present as an RG-II dimer. Copyright © 2016 Elsevier B.V. All rights reserved.

Predicting crappie recruitment in Ohio reservoirs with spawning stock size, larval density, and chlorophyll concentrations

USGS Publications Warehouse

Bunnell, David B.; Hale, R. Scott; Vanni, Michael J.; Stein, Roy A.

2006-01-01

Stock-recruit models typically use only spawning stock size as a predictor of recruitment to a fishery. In this paper, however, we used spawning stock size as well as larval density and key environmental variables to predict recruitment of white crappies Pomoxis annularis and black crappies P. nigromaculatus, a genus notorious for variable recruitment. We sampled adults and recruits from 11 Ohio reservoirs and larvae from 9 reservoirs during 1998-2001. We sampled chlorophyll as an index of reservoir productivity and obtained daily estimates of water elevation to determine the impact of hydrology on recruitment. Akaike's information criterion (AIC) revealed that Ricker and Beverton-Holt stock-recruit models that included chlorophyll best explained the variation in larval density and age-2 recruits. Specifically, spawning stock catch per effort (CPE) and chlorophyll explained 63-64% of the variation in larval density. In turn, larval density and chlorophyll explained 43-49% of the variation in age-2 recruit CPE. Finally, spawning stock CPE and chlorophyll were the best predictors of recruit CPE (i.e., 74-86%). Although larval density and recruitment increased with chlorophyll, neither was related to seasonal water elevation. Also, the AIC generally did not distinguish between Ricker and Beverton-Holt models. From these relationships, we concluded that crappie recruitment can be limited by spawning stock CPE and larval production when spawning stock sizes are low (i.e., CPE , 5 crappies/net-night). At higher levels of spawning stock sizes, spawning stock CPE and recruitment were less clearly related. To predict recruitment in Ohio reservoirs, managers should assess spawning stock CPE with trap nets and estimate chlorophyll concentrations. To increase crappie recruitment in reservoirs where recruitment is consistently poor, managers should use regulations to increase spawning stock size, which, in turn, should increase larval production and recruits to the fishery.

a Hadoop-Based Algorithm of Generating dem Grid from Point Cloud Data

NASA Astrophysics Data System (ADS)

Jian, X.; Xiao, X.; Chengfang, H.; Zhizhong, Z.; Zhaohui, W.; Dengzhong, Z.

2015-04-01

Airborne LiDAR technology has proven to be the most powerful tools to obtain high-density, high-accuracy and significantly detailed surface information of terrain and surface objects within a short time, and from which the Digital Elevation Model of high quality can be extracted. Point cloud data generated from the pre-processed data should be classified by segmentation algorithms, so as to differ the terrain points from disorganized points, then followed by a procedure of interpolating the selected points to turn points into DEM data. The whole procedure takes a long time and huge computing resource due to high-density, that is concentrated on by a number of researches. Hadoop is a distributed system infrastructure developed by the Apache Foundation, which contains a highly fault-tolerant distributed file system (HDFS) with high transmission rate and a parallel programming model (Map/Reduce). Such a framework is appropriate for DEM generation algorithms to improve efficiency. Point cloud data of Dongting Lake acquired by Riegl LMS-Q680i laser scanner was utilized as the original data to generate DEM by a Hadoop-based algorithms implemented in Linux, then followed by another traditional procedure programmed by C++ as the comparative experiment. Then the algorithm's efficiency, coding complexity, and performance-cost ratio were discussed for the comparison. The results demonstrate that the algorithm's speed depends on size of point set and density of DEM grid, and the non-Hadoop implementation can achieve a high performance when memory is big enough, but the multiple Hadoop implementation can achieve a higher performance-cost ratio, while point set is of vast quantities on the other hand.

D Building FAÇADE Reconstruction Using Handheld Laser Scanning Data

NASA Astrophysics Data System (ADS)

Sadeghi, F.; Arefi, H.; Fallah, A.; Hahn, M.

2015-12-01

3D The three dimensional building modelling has been an interesting topic of research for decades and it seems that photogrammetry methods provide the only economic means to acquire truly 3D city data. According to the enormous developments of 3D building reconstruction with several applications such as navigation system, location based services and urban planning, the need to consider the semantic features (such as windows and doors) becomes more essential than ever, and therefore, a 3D model of buildings as block is not any more sufficient. To reconstruct the façade elements completely, we employed the high density point cloud data that obtained from the handheld laser scanner. The advantage of the handheld laser scanner with capability of direct acquisition of very dense 3D point clouds is that there is no need to derive three dimensional data from multi images using structure from motion techniques. This paper presents a grammar-based algorithm for façade reconstruction using handheld laser scanner data. The proposed method is a combination of bottom-up (data driven) and top-down (model driven) methods in which, at first the façade basic elements are extracted in a bottom-up way and then they are served as pre-knowledge for further processing to complete models especially in occluded and incomplete areas. The first step of data driven modelling is using the conditional RANSAC (RANdom SAmple Consensus) algorithm to detect façade plane in point cloud data and remove noisy objects like trees, pedestrians, traffic signs and poles. Then, the façade planes are divided into three depth layers to detect protrusion, indentation and wall points using density histogram. Due to an inappropriate reflection of laser beams from glasses, the windows appear like holes in point cloud data and therefore, can be distinguished and extracted easily from point cloud comparing to the other façade elements. Next step, is rasterizing the indentation layer that holds the windows and doors information. After rasterization process, the morphological operators are applied in order to remove small irrelevant objects. Next, the horizontal splitting lines are employed to determine floors and vertical splitting lines are employed to detect walls, windows, and doors. The windows, doors and walls elements which are named as terminals are clustered during classification process. Each terminal contains a special property as width. Among terminals, windows and doors are named the geometry tiles in definition of the vocabularies of grammar rules. Higher order structures that inferred by grouping the tiles resulted in the production rules. The rules with three dimensional modelled façade elements constitute formal grammar that is named façade grammar. This grammar holds all the information that is necessary to reconstruct façades in the style of the given building. Thus, it can be used to improve and complete façade reconstruction in areas with no or limited sensor data. Finally, a 3D reconstructed façade model is generated that the accuracy of its geometry size and geometry position depends on the density of the raw point cloud.

Determination of rhodium in metallic alloy and water samples using cloud point extraction coupled with spectrophotometric technique.

PubMed

Kassem, Mohammed A; Amin, Alaa S

2015-02-05

A new method to estimate rhodium in different samples at trace levels had been developed. Rhodium was complexed with 5-(4'-nitro-2',6'-dichlorophenylazo)-6-hydroxypyrimidine-2,4-dione (NDPHPD) as a complexing agent in an aqueous medium and concentrated by using Triton X-114 as a surfactant. The investigated rhodium complex was preconcentrated with cloud point extraction process using the nonionic surfactant Triton X-114 to extract rhodium complex from aqueous solutions at pH 4.75. After the phase separation at 50°C, the surfactant-rich phase was heated again at 100°C to remove water after decantation and the remaining phase was dissolved using 0.5mL of acetonitrile. Under optimum conditions, the calibration curve was linear for the concentration range of 0.5-75ngmL(-1) and the detection limit was 0.15ngmL(-1) of the original solution. The enhancement factor of 500 was achieved for 250mL samples containing the analyte and relative standard deviations were ⩽1.50%. The method was found to be highly selective, fairly sensitive, simple, rapid and economical and safely applied for rhodium determination in different complex materials such as synthetic mixture of alloys and environmental water samples. Copyright © 2014 Elsevier B.V. All rights reserved.

Registration algorithm of point clouds based on multiscale normal features

NASA Astrophysics Data System (ADS)

Lu, Jun; Peng, Zhongtao; Su, Hang; Xia, GuiHua

2015-01-01

The point cloud registration technology for obtaining a three-dimensional digital model is widely applied in many areas. To improve the accuracy and speed of point cloud registration, a registration method based on multiscale normal vectors is proposed. The proposed registration method mainly includes three parts: the selection of key points, the calculation of feature descriptors, and the determining and optimization of correspondences. First, key points are selected from the point cloud based on the changes of magnitude of multiscale curvatures obtained by using principal components analysis. Then the feature descriptor of each key point is proposed, which consists of 21 elements based on multiscale normal vectors and curvatures. The correspondences in a pair of two point clouds are determined according to the descriptor's similarity of key points in the source point cloud and target point cloud. Correspondences are optimized by using a random sampling consistency algorithm and clustering technology. Finally, singular value decomposition is applied to optimized correspondences so that the rigid transformation matrix between two point clouds is obtained. Experimental results show that the proposed point cloud registration algorithm has a faster calculation speed, higher registration accuracy, and better antinoise performance.

Accuracy assessment of building point clouds automatically generated from iphone images

NASA Astrophysics Data System (ADS)

Sirmacek, B.; Lindenbergh, R.

2014-06-01

Low-cost sensor generated 3D models can be useful for quick 3D urban model updating, yet the quality of the models is questionable. In this article, we evaluate the reliability of an automatic point cloud generation method using multi-view iPhone images or an iPhone video file as an input. We register such automatically generated point cloud on a TLS point cloud of the same object to discuss accuracy, advantages and limitations of the iPhone generated point clouds. For the chosen example showcase, we have classified 1.23% of the iPhone point cloud points as outliers, and calculated the mean of the point to point distances to the TLS point cloud as 0.11 m. Since a TLS point cloud might also include measurement errors and noise, we computed local noise values for the point clouds from both sources. Mean (μ) and standard deviation (σ) of roughness histograms are calculated as (μ1 = 0.44 m., σ1 = 0.071 m.) and (μ2 = 0.025 m., σ2 = 0.037 m.) for the iPhone and TLS point clouds respectively. Our experimental results indicate possible usage of the proposed automatic 3D model generation framework for 3D urban map updating, fusion and detail enhancing, quick and real-time change detection purposes. However, further insights should be obtained first on the circumstances that are needed to guarantee a successful point cloud generation from smartphone images.

A graph signal filtering-based approach for detection of different edge types on airborne lidar data

NASA Astrophysics Data System (ADS)

Bayram, Eda; Vural, Elif; Alatan, Aydin

2017-10-01

Airborne Laser Scanning is a well-known remote sensing technology, which provides a dense and highly accurate, yet unorganized point cloud of earth surface. During the last decade, extracting information from the data generated by airborne LiDAR systems has been addressed by many studies in geo-spatial analysis and urban monitoring applications. However, the processing of LiDAR point clouds is challenging due to their irregular structure and 3D geometry. In this study, we propose a novel framework for the detection of the boundaries of an object or scene captured by LiDAR. Our approach is motivated by edge detection techniques in vision research and it is established on graph signal filtering which is an exciting and promising field of signal processing for irregular data types. Due to the convenient applicability of graph signal processing tools on unstructured point clouds, we achieve the detection of the edge points directly on 3D data by using a graph representation that is constructed exclusively to answer the requirements of the application. Moreover, considering the elevation data as the (graph) signal, we leverage aerial characteristic of the airborne LiDAR data. The proposed method can be employed both for discovering the jump edges on a segmentation problem and for exploring the crease edges on a LiDAR object on a reconstruction/modeling problem, by only adjusting the filter characteristics.

Development and testing of methodology for evaluating the performance of multi-input/multi-output digital control systems

NASA Technical Reports Server (NTRS)

Polotzky, Anthony S.; Wieseman, Carol; Hoadley, Sherwood Tiffany; Mukhopadhyay, Vivek

1990-01-01

The development of a controller performance evaluation (CPE) methodology for multiinput/multioutput digital control systems is described. The equations used to obtain the open-loop plant, controller transfer matrices, and return-difference matrices are given. Results of applying the CPE methodology to evaluate MIMO digital flutter suppression systems being tested on an active flexible wing wind-tunnel model are presented to demonstrate the CPE capability.

Pole-Like Street Furniture Decompostion in Mobile Laser Scanning Data

NASA Astrophysics Data System (ADS)

Li, F.; Oude Elberink, S.; Vosselman, G.

2016-06-01

Automatic semantic interpretation of street furniture has become a popular topic in recent years. Current studies detect street furniture as connected components of points above the street level. Street furniture classification based on properties of such components suffers from large intra class variability of shapes and cannot deal with mixed classes like traffic signs attached to light poles. In this paper, we focus on the decomposition of point clouds of pole-like street furniture. A novel street furniture decomposition method is proposed, which consists of three steps: (i) acquirement of prior-knowledge, (ii) pole extraction, (iii) components separation. For the pole extraction, a novel global pole extraction approach is proposed to handle 3 different cases of street furniture. In the evaluation of results, which involves the decomposition of 27 different instances of street furniture, we demonstrate that our method decomposes mixed classes street furniture into poles and different components with respect to different functionalities.

Use of Assisted Photogrammetry for Indoor and Outdoor Navigation Purposes

NASA Astrophysics Data System (ADS)

Pagliari, D.; Cazzaniga, N. E.; Pinto, L.

2015-05-01

Nowadays, devices and applications that require navigation solutions are continuously growing. For instance, consider the increasing demand of mapping information or the development of applications based on users' location. In some case it could be sufficient an approximate solution (e.g. at room level), but in the large amount of cases a better solution is required. The navigation problem has been solved from a long time using Global Navigation Satellite System (GNSS). However, it can be unless in obstructed areas, such as in urban areas or inside buildings. An interesting low cost solution is photogrammetry, assisted using additional information to scale the photogrammetric problem and recovering a solution also in critical situation for image-based methods (e.g. poor textured surfaces). In this paper, the use of assisted photogrammetry has been tested for both outdoor and indoor scenarios. Outdoor navigation problem has been faced developing a positioning system with Ground Control Points extracted from urban maps as constrain and tie points automatically extracted from the images acquired during the survey. The proposed approach has been tested under different scenarios, recovering the followed trajectory with an accuracy of 0.20 m. For indoor navigation a solution has been thought to integrate the data delivered by Microsoft Kinect, by identifying interesting features on the RGB images and re-projecting them on the point clouds generated from the delivered depth maps. Then, these points have been used to estimate the rotation matrix between subsequent point clouds and, consequently, to recover the trajectory with few centimeters of error.

A Framework for Applying Point Clouds Grabbed by Multi-Beam LIDAR in Perceiving the Driving Environment

PubMed Central

Liu, Jian; Liang, Huawei; Wang, Zhiling; Chen, Xiangcheng

2015-01-01

The quick and accurate understanding of the ambient environment, which is composed of road curbs, vehicles, pedestrians, etc., is critical for developing intelligent vehicles. The road elements included in this work are road curbs and dynamic road obstacles that directly affect the drivable area. A framework for the online modeling of the driving environment using a multi-beam LIDAR, i.e., a Velodyne HDL-64E LIDAR, which describes the 3D environment in the form of a point cloud, is reported in this article. First, ground segmentation is performed via multi-feature extraction of the raw data grabbed by the Velodyne LIDAR to satisfy the requirement of online environment modeling. Curbs and dynamic road obstacles are detected and tracked in different manners. Curves are fitted for curb points, and points are clustered into bundles whose form and kinematics parameters are calculated. The Kalman filter is used to track dynamic obstacles, whereas the snake model is employed for curbs. Results indicate that the proposed framework is robust under various environments and satisfies the requirements for online processing. PMID:26404290

Accuracy assessment of airborne LIDAR data and automated extraction of features

NASA Astrophysics Data System (ADS)

Cetin, Ali Fuat

Airborne LIDAR technology is becoming more widely used since it provides fast and dense irregularly spaced 3D point clouds. The coordinates produced as a result of calibration of the system are used for surface modeling and information extraction. In this research a new idea of LIDAR detectable targets is introduced. In the second part of this research, a new technique to delineate the edge of road pavements automatically using only LIDAR is presented. The accuracy of LIDAR data should be determined before exploitation for any information extraction to support a Geographic Information System (GIS) database. Until recently there was no definitive research to provide a methodology for common and practical assessment of both horizontal and vertical accuracy of LIDAR data for end users. The idea used in this research was to use targets of such a size and design so that the position of each target can be determined using the Least Squares Image Matching Technique. The technique used in this research can provide end users and data providers an easy way to evaluate the quality of the product, especially when there are accessible hard surfaces to install the targets. The results of the technique are determined to be in a reasonable range when the point spacing of the data is sufficient. To delineate the edge of pavements, trees and buildings are removed from the point cloud, and the road surfaces are segmented from the remaining terrain data. This is accomplished using the homogeneous nature of road surfaces in intensity and height. There are not many studies to delineate the edge of road pavement after the road surfaces are extracted. In this research, template matching techniques are used with criteria computed by Gray Level Co-occurrence Matrix (GLCM) properties, in order to locate seed pixels in the image. The seed pixels are then used for placement of the matched templates along the road. The accuracy of the delineated edge of pavement is determined by comparing the coordinates of reference points collected via photogrammetry with the coordinates of the nearest points along the delineated edge.

Topographic lidar survey of the Chandeleur Islands, Louisiana, February 6, 2012

USGS Publications Warehouse

Guy, Kristy K.; Plant, Nathaniel G.; Bonisteel-Cormier, Jamie M.

2014-01-01

This Data Series Report contains lidar elevation data collected February 6, 2012, for Chandeleur Islands, Louisiana. Point cloud data in lidar data exchange format (LAS) and bare earth digital elevation models (DEMs) in ERDAS Imagine raster format (IMG) are available as downloadable files. The point cloud data—data points described in three dimensions—were processed to extract bare earth data; therefore, the point cloud data are organized into the following classes: 1– and 17–unclassified, 2–ground, 9–water, and 10–breakline proximity. Digital Aerial Solutions, LLC, (DAS) was contracted by the U.S. Geological Survey (USGS) to collect and process these data. The lidar data were acquired at a horizontal spacing (or nominal pulse spacing) of 0.5 meters (m) or less. The USGS conducted two ground surveys in small areas on the Chandeleur Islands on February 5, 2012. DAS calculated a root mean square error (RMSEz) of 0.034 m by comparing the USGS ground survey point data to triangulated irregular network (TIN) models built from the lidar elevation data. This lidar survey was conducted to document the topography and topographic change of the Chandeleur Islands. The survey supports detailed studies of Louisiana, Mississippi and Alabama barrier islands that resolve annual and episodic changes in beaches, berms and dunes associated with processes driven by storms, sea-level rise, and even human restoration activities. These lidar data are available to Federal, State and local governments, emergency-response officials, resource managers, and the general public.

The observed influence of local anthropogenic pollution on northern Alaskan cloud properties

NASA Astrophysics Data System (ADS)

Maahn, Maximilian; de Boer, Gijs; Creamean, Jessie M.; Feingold, Graham; McFarquhar, Greg M.; Wu, Wei; Mei, Fan

2017-12-01

Due to their importance for the radiation budget, liquid-containing clouds are a key component of the Arctic climate system. Depending on season, they can cool or warm the near-surface air. The radiative properties of these clouds depend strongly on cloud drop sizes, which are governed in part by the availability of cloud condensation nuclei. Here, we investigate how cloud drop sizes are modified in the presence of local emissions from industrial facilities at the North Slope of Alaska. For this, we use aircraft in situ observations of clouds and aerosols from the 5th Department of Energy Atmospheric Radiation Measurement (DOE ARM) Program's Airborne Carbon Measurements (ACME-V) campaign obtained in summer 2015. Comparison of observations from an area with petroleum extraction facilities (Oliktok Point) with data from a reference area relatively free of anthropogenic sources (Utqiaġvik/Barrow) represents an opportunity to quantify the impact of local industrial emissions on cloud properties. In the presence of local industrial emissions, the mean effective radii of cloud droplets are reduced from 12.2 to 9.4 µm, which leads to suppressed drizzle production and precipitation. At the same time, concentrations of refractory black carbon and condensation nuclei are enhanced below the clouds. These results demonstrate that the effects of anthropogenic pollution on local climate need to be considered when planning Arctic industrial infrastructure in a warming environment.

Helicopter-based Photography for use in SfM over the West Greenland Ablation Zone

NASA Astrophysics Data System (ADS)

Mote, T. L.; Tedesco, M.; Astuti, I.; Cotten, D.; Jordan, T.; Rennermalm, A. K.

2015-12-01

Results of low-elevation high-resolution aerial photography from a helicopter are reported for a supraglacial watershed in West Greenland. Data were collected at the end of July 2015 over a supraglacial watershed terminating in the Kangerlussuaq region of Greenland and following the Utrecht University K-Transect of meteorological stations. The aerial photography reported here were complementary observations used to support hyperspectral measurements of albedo, discussed in the Greenland Ice sheet hydrology session of this AGU Fall meeting. A compact digital camera was installed inside a pod mounted on the side of the helicopter together with gyroscopes and accelerometers that were used to estimate the relative orientation. Continuous video was collected on 19 and 21 July flights, and frames extracted from the videos are used to create a series of aerial photos. Individual geo-located aerial photos were also taken on a 24 July flight. We demonstrate that by maintaining a constant flight elevation and a near constant ground speed, a helicopter with a mounted camera can produce 3-D structure of the ablation zone of the ice sheet at unprecedented spatial resolution of the order of 5 - 10 cm. By setting the intervalometer on the camera to 2 seconds, the images obtained provide sufficient overlap (>60%) for digital image alignment, even at a flight elevation of ~170m. As a result, very accurate point matching between photographs can be achieved and an extremely dense RGB encoded point cloud can be extracted. Overlapping images provide a series of stereopairs that can be used to create point cloud data consisting of 3 position and 3 color variables, X, Y, Z, R, G, and B. This point cloud is then used to create orthophotos or large scale digital elevation models, thus accurately displaying ice structure. The geo-referenced images provide a ground spatial resolution of approximately 6 cm, permitting analysis of detailed features, such as cryoconite holes, evolving small order streams, and cracks from hydrofracturing.

Towards a 3d Based Platform for Cultural Heritage Site Survey and Virtual Exploration

NASA Astrophysics Data System (ADS)

Seinturier, J.; Riedinger, C.; Mahiddine, A.; Peloso, D.; Boï, J.-M.; Merad, D.; Drap, P.

2013-07-01

This paper present a 3D platform that enables to make both cultural heritage site survey and its virtual exploration. It provides a single and easy way to use framework for merging multi scaled 3D measurements based on photogrammetry, documentation produced by experts and the knowledge of involved domains leaving the experts able to extract and choose the relevant information to produce the final survey. Taking into account the interpretation of the real world during the process of archaeological surveys is in fact the main goal of a survey. New advances in photogrammetry and the capability to produce dense 3D point clouds do not solve the problem of surveys. New opportunities for 3D representation are now available and we must to use them and find new ways to link geometry and knowledge. The new platform is able to efficiently manage and process large 3D data (points set, meshes) thanks to the implementation of space partition methods coming from the state of the art such as octrees and kd-trees and thus can interact with dense point clouds (thousands to millions of points) in real time. The semantisation of raw 3D data relies on geometric algorithms such as geodetic path computation, surface extraction from dense points cloud and geometrical primitive optimization. The platform provide an interface that enables expert to describe geometric representations of interesting objects like ashlar blocs, stratigraphic units or generic items (contour, lines, … ) directly onto the 3D representation of the site and without explicit links to underlying algorithms. The platform provide two ways for describing geometric representation. If oriented photographs are available, the expert can draw geometry on a photograph and the system computes its 3D representation by projection on the underlying mesh or the points cloud. If photographs are not available or if the expert wants to only use the 3D representation then he can simply draw objects shape on it. When 3D representations of objects of a surveyed site are extracted from the mesh, the link with domain related documentation is done by means of a set of forms designed by experts. Information from these forms are linked with geometry such that documentation can be attached to the viewed objects. Additional semantisation methods related to specific domains have been added to the platform. Beyond realistic rendering of surveyed site, the platform embeds non photorealistic rendering (NPR) algorithms. These algorithms enable to dynamically illustrate objects of interest that are related to knowledge with specific styles. The whole platform is implemented with a Java framework and relies on an actual and effective 3D engine that make available latest rendering methods. We illustrate this work on various photogrammetric survey, in medieval archaeology with the Shawbak castle in Jordan and in underwater archaeology on different marine sites.

Fusion of multi-temporal Airborne Snow Observatory (ASO) lidar data for mountainous vegetation ecosystems studies.

NASA Astrophysics Data System (ADS)

Ferraz, A.; Painter, T. H.; Saatchi, S.; Bormann, K. J.

2016-12-01

Fusion of multi-temporal Airborne Snow Observatory (ASO) lidar data for mountainous vegetation ecosystems studies The NASA Jet Propulsion Laboratory developed the Airborne Snow Observatory (ASO), a coupled scanning lidar system and imaging spectrometer, to quantify the spatial distribution of snow volume and dynamics over mountains watersheds (Painter et al., 2015). To do this, ASO weekly over-flights mountainous areas during snowfall and snowmelt seasons. In addition, there are additional flights in snow-off conditions to calculate Digital Terrain Models (DTM). In this study, we focus on the reliability of ASO lidar data to characterize the 3D forest vegetation structure. The density of a single point cloud acquisition is of nearly 1 pt/m2, which is not optimal to properly characterize vegetation. However, ASO covers a given study site up to 14 times a year that enables computing a high-resolution point cloud by merging single acquisitions. In this study, we present a method to automatically register ASO multi-temporal lidar 3D point clouds. Although flight specifications do not change between acquisition dates, lidar datasets might have significant planimetric shifts due to inaccuracies in platform trajectory estimation introduced by the GPS system and drifts of the IMU. There are a large number of methodologies that address the problem of 3D data registration (Gressin et al., 2013). Briefly, they look for common primitive features in both datasets such as buildings corners, structures like electric poles, DTM breaklines or deformations. However, they are not suited for our experiment. First, single acquisition point clouds have low density that makes the extraction of primitive features difficult. Second, the landscape significantly changes between flights due to snowfall and snowmelt. Therefore, we developed a method to automatically register point clouds using tree apexes as keypoints because they are features that are supposed to experience little change during winter season. We applied the method to 14 lidar datasets (12 snow-on and 2 snow-off) acquired over the Tuolumne River Basin (California) in the year of 2014. To assess the reliability of the merged point cloud, we analyze the quality of vegetation related products such as canopy height models (CHM) and vertical vegetation profiles.

Risk factors for fecal carriage of carbapenemase producing Enterobacteriaceae among intensive care unit patients from a tertiary care center in India.

PubMed

Mittal, Gajanand; Gaind, Rajni; Kumar, Deepak; Kaushik, Gaurav; Gupta, Kunj Bihari; Verma, P K; Deb, Monorama

2016-07-08

Resistance amongst the commensal flora is a serious threat because a very highly populated ecosystem like the gut, may at a later stage, be a source of extra intestinal infections, resistant strains may spread to other host or transfer genetic resistance element to other members of micro-biota including pathogens. This study was carried out to assess fecal colonization by carbapenemase producing Enterobacteriaceae (CPE) and associated risk factors among 100 patients admitted to intensive care unit (ICU). The phenotypic and molecular characterizations of CPE were also included. Colonization with CPE was observed in 6.6 % (8/122) controls. Among ICU patients, fecal carriage of CPE was significantly higher on day 4 (D4) (22 %) as compared to day 1 (D1) (11 %) (p value 0.002). The carbapenemase genes detected included OXA- 48, 181, KPC and NDM-1 with NDM-1 being the predominant carbapenemase in both ICU D1 and D4. Among the 50 CPE isolates, 8 (16 %) were susceptible to meropenem and imipenem (Minimum inhibitory concentration; MIC ≤ 1 mg/L) and all were susceptible to colistin (MIC range 0.125 - 1 mg/L) and tigecycline (MIC range 0.06- 1.5 mg/L). The risk factors associated with CPE carriage were duration of ICU stay, use of ventilator and aminoglycosides. Prior colonization with CPE could result in their influx and spread in ICU, challenging infection control measures. Exposure to ICU further increases risk of colonization with diverse carbapenemase-producing Enterobacteriaceae. Gut colonization with these strains may be a source of endogenous infection and horizontal transfer of these genes in future.

Molecular and epidemiological characterization of carbapenemase-producing Enterobacteriaceae in Norway, 2007 to 2014.

PubMed

Samuelsen, Ørjan; Overballe-Petersen, Søren; Bjørnholt, Jørgen Vildershøj; Brisse, Sylvain; Doumith, Michel; Woodford, Neil; Hopkins, Katie L; Aasnæs, Bettina; Haldorsen, Bjørg; Sundsfjord, Arnfinn

2017-01-01

The prevalence of carbapenemase-producing Enterobacteriaceae (CPE) is increasing worldwide. Here we present associated patient data and molecular, epidemiological and phenotypic characteristics of all CPE isolates in Norway from 2007 to 2014 confirmed at the Norwegian National Advisory Unit on Detection of Antimicrobial Resistance. All confirmed CPE isolates were characterized pheno- and genotypically, including by whole genome sequencing (WGS). Patient data were reviewed retrospectively. In total 59 CPE isolates were identified from 53 patients. Urine was the dominant clinical sample source (37%) and only 15% of the isolates were obtained from faecal screening. The majority of cases (62%) were directly associated with travel or hospitalization abroad, but both intra-hospital transmission and one inter-hospital outbreak were observed. The number of CPE cases/year was low (2-14 cases/year), but an increasing trend was observed. Klebsiella spp. (n = 38) and E. coli (n = 14) were the dominant species and blaKPC (n = 20), blaNDM (n = 19), blaOXA-48-like (n = 12) and blaVIM (n = 7) were the dominant carbapenemase gene families. The CPE isolates were genetically diverse except for K. pneumoniae where clonal group 258 associated with blaKPC dominated. All isolates were multidrug-resistant and a significant proportion (21%) were resistant to colistin. Interestingly, all blaOXA-48-like, and a large proportion of blaNDM-positive Klebsiella spp. (89%) and E. coli (83%) isolates were susceptible in vitro to mecillinam. Thus, mecillinam could have a role in the treatment of uncomplicated urinary tract infections caused by OXA-48- or NDM-producing E. coli or K. pneumoniae. In conclusion, the impact of CPE in Norway is still limited and mainly associated with travel abroad, reflected in the diversity of clones and carbapenemase genes.

Terrestrial laser scanning for geometry extraction and change monitoring of rubble mound breakwaters

NASA Astrophysics Data System (ADS)

Puente, I.; Lindenbergh, R.; González-Jorge, H.; Arias, P.

2014-05-01

Rubble mound breakwaters are coastal defense structures that protect harbors and beaches from the impacts of both littoral drift and storm waves. They occasionally break, leading to catastrophic damage to surrounding human populations and resulting in huge economic and environmental losses. Ensuring their stability is considered to be of vital importance and the major reason for setting up breakwater monitoring systems. Terrestrial laser scanning has been recognized as a monitoring technique of existing infrastructures. Its capability for measuring large amounts of accurate points in a short period of time is also well proven. In this paper we first introduce a method for the automatic extraction of face geometry of concrete cubic blocks, as typically used in breakwaters. Point clouds are segmented based on their orientation and location. Then we compare corresponding cuboids of three co-registered point clouds to estimate their transformation parameters over time. The first method is demonstrated on scan data from the Baiona breakwater (Spain) while the change detection is demonstrated on repeated scan data of concrete bricks, where the changing scenario was simulated. The application of the presented methodology has verified its effectiveness for outlining the 3D breakwater units and analyzing their changes at the millimeter level. Breakwater management activities could benefit from this initial version of the method in order to improve their productivity.

A shape-based segmentation method for mobile laser scanning point clouds

NASA Astrophysics Data System (ADS)

Yang, Bisheng; Dong, Zhen

2013-07-01

Segmentation of mobile laser point clouds of urban scenes into objects is an important step for post-processing (e.g., interpretation) of point clouds. Point clouds of urban scenes contain numerous objects with significant size variability, complex and incomplete structures, and holes or variable point densities, raising great challenges for the segmentation of mobile laser point clouds. This paper addresses these challenges by proposing a shape-based segmentation method. The proposed method first calculates the optimal neighborhood size of each point to derive the geometric features associated with it, and then classifies the point clouds according to geometric features using support vector machines (SVMs). Second, a set of rules are defined to segment the classified point clouds, and a similarity criterion for segments is proposed to overcome over-segmentation. Finally, the segmentation output is merged based on topological connectivity into a meaningful geometrical abstraction. The proposed method has been tested on point clouds of two urban scenes obtained by different mobile laser scanners. The results show that the proposed method segments large-scale mobile laser point clouds with good accuracy and computationally effective time cost, and that it segments pole-like objects particularly well.

A cCPE-based xenon biosensor for magnetic resonance imaging of claudin-expressing cells.

PubMed

Piontek, Anna; Witte, Christopher; May Rose, Honor; Eichner, Miriam; Protze, Jonas; Krause, Gerd; Piontek, Jörg; Schröder, Leif

2017-06-01

The majority of malignant tumors originate from epithelial cells, and many of them are characterized by an overexpression of claudins (Cldns) and their mislocalization out of tight junctions. We utilized the C-terminal claudin-binding domain of Clostridium perfringens enterotoxin (cCPE), with its high affinity to specific members of the claudin family, as the targeting unit for a claudin-sensitive cancer biosensor. To overcome the poor sensitivity of conventional relaxivity-based magnetic resonance imaging (MRI) contrast agents, we utilized the superior sensitivity of xenon Hyper-CEST biosensors. We labeled cCPE for both xenon MRI and fluorescence detection. As one readout module, we employed a cryptophane (CrA) monoacid and, as the second, a fluorescein molecule. Both were conjugated separately to a biotin molecule via a polyethyleneglycol chemical spacer and later via avidin linked to GST-cCPE. Nontransfected HEK293 cells and HEK293 cells stably expressing Cldn4-FLAG were incubated with the cCPE-based biosensor. Fluorescence-based flow cytometry and xenon MRI demonstrated binding of the biosensor specifically to Cldn4-expressing cells. This study provides proof of concept for the use of cCPE as a carrier for diagnostic contrast agents, a novel approach for potential detection of Cldn3/-4-overexpressing tumors for noninvasive early cancer detection. © 2017 New York Academy of Sciences.

A continuous surface reconstruction method on point cloud captured from a 3D surface photogrammetry system.

PubMed

Liu, Wenyang; Cheung, Yam; Sabouri, Pouya; Arai, Tatsuya J; Sawant, Amit; Ruan, Dan

2015-11-01

To accurately and efficiently reconstruct a continuous surface from noisy point clouds captured by a surface photogrammetry system (VisionRT). The authors have developed a level-set based surface reconstruction method on point clouds captured by a surface photogrammetry system (VisionRT). The proposed method reconstructs an implicit and continuous representation of the underlying patient surface by optimizing a regularized fitting energy, offering extra robustness to noise and missing measurements. By contrast to explicit/discrete meshing-type schemes, their continuous representation is particularly advantageous for subsequent surface registration and motion tracking by eliminating the need for maintaining explicit point correspondences as in discrete models. The authors solve the proposed method with an efficient narrowband evolving scheme. The authors evaluated the proposed method on both phantom and human subject data with two sets of complementary experiments. In the first set of experiment, the authors generated a series of surfaces each with different black patches placed on one chest phantom. The resulting VisionRT measurements from the patched area had different degree of noise and missing levels, since VisionRT has difficulties in detecting dark surfaces. The authors applied the proposed method to point clouds acquired under these different configurations, and quantitatively evaluated reconstructed surfaces by comparing against a high-quality reference surface with respect to root mean squared error (RMSE). In the second set of experiment, the authors applied their method to 100 clinical point clouds acquired from one human subject. In the absence of ground-truth, the authors qualitatively validated reconstructed surfaces by comparing the local geometry, specifically mean curvature distributions, against that of the surface extracted from a high-quality CT obtained from the same patient. On phantom point clouds, their method achieved submillimeter reconstruction RMSE under different configurations, demonstrating quantitatively the faith of the proposed method in preserving local structural properties of the underlying surface in the presence of noise and missing measurements, and its robustness toward variations of such characteristics. On point clouds from the human subject, the proposed method successfully reconstructed all patient surfaces, filling regions where raw point coordinate readings were missing. Within two comparable regions of interest in the chest area, similar mean curvature distributions were acquired from both their reconstructed surface and CT surface, with mean and standard deviation of (μrecon=-2.7×10(-3) mm(-1), σrecon=7.0×10(-3) mm(-1)) and (μCT=-2.5×10(-3) mm(-1), σCT=5.3×10(-3) mm(-1)), respectively. The agreement of local geometry properties between the reconstructed surfaces and the CT surface demonstrated the ability of the proposed method in faithfully representing the underlying patient surface. The authors have integrated and developed an accurate level-set based continuous surface reconstruction method on point clouds acquired by a 3D surface photogrammetry system. The proposed method has generated a continuous representation of the underlying phantom and patient surfaces with good robustness against noise and missing measurements. It serves as an important first step for further development of motion tracking methods during radiotherapy.

Extraction of Profile Information from Cloud Contaminated Radiances. Appendixes 2

NASA Technical Reports Server (NTRS)

Smith, W. L.; Zhou, D. K.; Huang, H.-L.; Li, Jun; Liu, X.; Larar, A. M.

2003-01-01

Clouds act to reduce the signal level and may produce noise dependence on the complexity of the cloud properties and the manner in which they are treated in the profile retrieval process. There are essentially three ways to extract profile information from cloud contaminated radiances: (1) cloud-clearing using spatially adjacent cloud contaminated radiance measurements, (2) retrieval based upon the assumption of opaque cloud conditions, and (3) retrieval or radiance assimilation using a physically correct cloud radiative transfer model which accounts for the absorption and scattering of the radiance observed. Cloud clearing extracts the radiance arising from the clear air portion of partly clouded fields of view permitting soundings to the surface or the assimilation of radiances as in the clear field of view case. However, the accuracy of the clear air radiance signal depends upon the cloud height and optical property uniformity across the two fields of view used in the cloud clearing process. The assumption of opaque clouds within the field of view permits relatively accurate profiles to be retrieved down to near cloud top levels, the accuracy near the cloud top level being dependent upon the actual microphysical properties of the cloud. The use of a physically correct cloud radiative transfer model enables accurate retrievals down to cloud top levels and below semi-transparent cloud layers (e.g., cirrus). It should also be possible to assimilate cloudy radiances directly into the model given a physically correct cloud radiative transfer model using geometric and microphysical cloud parameters retrieved from the radiance spectra as initial cloud variables in the radiance assimilation process. This presentation reviews the above three ways to extract profile information from cloud contaminated radiances. NPOESS Airborne Sounder Testbed-Interferometer radiance spectra and Aqua satellite AIRS radiance spectra are used to illustrate how cloudy radiances can be used in the profile retrieval process.

Impact of Pharmacists’ Participation in a Pharmacotherapy Follow-Up Program

PubMed Central

Dualde, Elena; Santonja, Francisco J.; Faus, Maria J.

2012-01-01

Objective. To evaluate the impact of a continuing pharmacy education (CPE) course on Spanish community pharmacists’ participation in a pharmacotherapy follow-up program. Design. Participation in a CPE course offered 4 times over a 4-year period via satellite teleconferencing was monitored and the data analyzed to determine the course’s impact on community pharmacists’ participation in a pharmacotherapy follow-up program. Assessment. Community pharmacists’ participation in the pharmaceutical care CPE course had a slightly positive impact on their participation in the pharmacotherapy follow-up program. In the best profiles, there was a probability of 7.3% that participants would participate in the pharmacotherapy follow-up program. Conclusions. Completion of pharmaceutical care CPE courses did not have a significant impact on pharmacists’ participation in a pharmacotherapy follow-up program. PMID:22438606

Graphite furnace atomic absorption spectrometric determination of vanadium after cloud point extraction in the presence of graphene oxide

NASA Astrophysics Data System (ADS)

López-García, Ignacio; Marín-Hernández, Juan José; Hernández-Córdoba, Manuel

2018-05-01

Vanadium (V) and vanadium (IV) in the presence of a small concentration of graphene oxide (0.05 mg mL-1) are quantitatively transferred to the coacervate obtained with Triton X-114 in a cloud point microextraction process. The surfactant-rich phase is directly injected into the graphite atomizer of an atomic absorption spectrometer. Using a 10-mL aliquot sample and 150 μL of a 15% Triton X-114 solution, the enrichment factor for the analyte is 103, which results in a detection limit of 0.02 μg L-1 vanadium. The separation of V(V) and V(IV) using an ion-exchanger allows speciation of the element at low concentrations. Data for seven reference water samples with certified vanadium contents confirm the reliability of the procedure. Several beer samples are also analyzed, those supplied as canned drinks showing low levels of tetravalent vanadium.

LSAH: a fast and efficient local surface feature for point cloud registration

NASA Astrophysics Data System (ADS)

Lu, Rongrong; Zhu, Feng; Wu, Qingxiao; Kong, Yanzi

2018-04-01

Point cloud registration is a fundamental task in high level three dimensional applications. Noise, uneven point density and varying point cloud resolutions are the three main challenges for point cloud registration. In this paper, we design a robust and compact local surface descriptor called Local Surface Angles Histogram (LSAH) and propose an effectively coarse to fine algorithm for point cloud registration. The LSAH descriptor is formed by concatenating five normalized sub-histograms into one histogram. The five sub-histograms are created by accumulating a different type of angle from a local surface patch respectively. The experimental results show that our LSAH is more robust to uneven point density and point cloud resolutions than four state-of-the-art local descriptors in terms of feature matching. Moreover, we tested our LSAH based coarse to fine algorithm for point cloud registration. The experimental results demonstrate that our algorithm is robust and efficient as well.

Above-bottom biomass retrieval of aquatic plants with regression models and SfM data acquired by a UAV platform - A case study in Wild Duck Lake Wetland, Beijing, China

NASA Astrophysics Data System (ADS)

Jing, Ran; Gong, Zhaoning; Zhao, Wenji; Pu, Ruiliang; Deng, Lei

2017-12-01

Above-bottom biomass (ABB) is considered as an important parameter for measuring the growth status of aquatic plants, and is of great significance for assessing health status of wetland ecosystems. In this study, Structure from Motion (SfM) technique was used to rebuild the study area with high overlapped images acquired by an unmanned aerial vehicle (UAV). We generated orthoimages and SfM dense point cloud data, from which vegetation indices (VIs) and SfM point cloud variables including average height (HAVG), standard deviation of height (HSD) and coefficient of variation of height (HCV) were extracted. These VIs and SfM point cloud variables could effectively characterize the growth status of aquatic plants, and thus they could be used to develop a simple linear regression model (SLR) and a stepwise linear regression model (SWL) with field measured ABB samples of aquatic plants. We also utilized a decision tree method to discriminate different types of aquatic plants. The experimental results indicated that (1) the SfM technique could effectively process high overlapped UAV images and thus be suitable for the reconstruction of fine texture feature of aquatic plant canopy structure; and (2) an SWL model based on point cloud variables: HAVG, HSD, HCV and two VIs: NGRDI, ExGR as independent variables has produced the best predictive result of ABB of aquatic plants in the study area, with a coefficient of determination of 0.84 and a relative root mean square error of 7.13%. In this analysis, a novel method for the quantitative inversion of a growth parameter (i.e., ABB) of aquatic plants in wetlands was demonstrated.

Wheat Ear Detection in Plots by Segmenting Mobile Laser Scanner Data

NASA Astrophysics Data System (ADS)

Velumani, K.; Oude Elberink, S.; Yang, M. Y.; Baret, F.

2017-09-01

The use of Light Detection and Ranging (LiDAR) to study agricultural crop traits is becoming popular. Wheat plant traits such as crop height, biomass fractions and plant population are of interest to agronomists and biologists for the assessment of a genotype's performance in the environment. Among these performance indicators, plant population in the field is still widely estimated through manual counting which is a tedious and labour intensive task. The goal of this study is to explore the suitability of LiDAR observations to automate the counting process by the individual detection of wheat ears in the agricultural field. However, this is a challenging task owing to the random cropping pattern and noisy returns present in the point cloud. The goal is achieved by first segmenting the 3D point cloud followed by the classification of segments into ears and non-ears. In this study, two segmentation techniques: a) voxel-based segmentation and b) mean shift segmentation were adapted to suit the segmentation of plant point clouds. An ear classification strategy was developed to distinguish the ear segments from leaves and stems. Finally, the ears extracted by the automatic methods were compared with reference ear segments prepared by manual segmentation. Both the methods had an average detection rate of 85 %, aggregated over different flowering stages. The voxel-based approach performed well for late flowering stages (wheat crops aged 210 days or more) with a mean percentage accuracy of 94 % and takes less than 20 seconds to process 50,000 points with an average point density of 16  points/cm2. Meanwhile, the mean shift approach showed comparatively better counting accuracy of 95% for early flowering stage (crops aged below 225 days) and takes approximately 4 minutes to process 50,000 points.

M cell-targeting strategy facilitates mucosal immune response and enhances protection against CVB3-induced viral myocarditis elicited by chitosan-DNA vaccine.

PubMed

Ye, Ting; Yue, Yan; Fan, Xiangmei; Dong, Chunsheng; Xu, Wei; Xiong, Sidong

2014-07-31

Efficient delivery of antigen to mucosal associated lymphoid tissue is a first and critical step for successful induction of mucosal immunity by vaccines. Considering its potential transcytotic capability, M cell has become a more and more attractive target for mucosal vaccines. In this research, we designed an M cell-targeting strategy by which mucosal delivery system chitosan (CS) was endowed with M cell-targeting ability via conjugating with a CPE30 peptide, C terminal 30 amino acids of clostridium perfringens enterotoxin (CPE), and then evaluated its immune-enhancing ability in the context of coxsackievirus B3 (CVB3)-specific mucosal vaccine consisting of CS and a plasmid encoding CVB3 predominant antigen VP1. It had shown that similar to CS-pVP1, M cell-targeting CPE30-CS-pVP1 vaccine appeared a uniform spherical shape with about 300 nm diameter and +22 mV zeta potential, and could efficiently protect DNA from DNase I digestion. Mice were orally immunized with 4 doses of CPE30-CS-pVP1 containing 50 μg pVP1 at 2-week intervals and challenged with CVB3 4 weeks after the last immunization. Compared with CS-pVP1 vaccine, CPE30-CS-pVP1 vaccine had no obvious impact on CVB3-specific serum IgG level and splenic T cell immune responses, but significantly increased specific fecal SIgA level and augmented mucosal T cell immune responses. Consequently, much milder myocarditis and lower viral load were witnessed in CPE30-CS-pVP1 immunized group. The enhanced immunogenicity and immunoprotection were associated with the M cell-targeting ability of CPE30-CS-pVP1 which improved its mucosal uptake and transcytosis. Our findings indicated that CPE30-CS-pVP1 may represent a novel prophylactic vaccine against CVB3-induced myocarditis, and this M cell-targeting strategy indeed could be applied as a promising and universal platform for mucosal vaccine development. Copyright © 2014 Elsevier Ltd. All rights reserved.

Gold-copper bimetallic nanoparticles supported on nano P zeolite modified carbon paste electrode as an efficient electrocatalyst and sensitive sensor for determination of hydrazine.

PubMed

Amiripour, Fatemeh; Azizi, Seyed Naser; Ghasemi, Shahram

2018-06-01

In this report, a facile, efficient and low cost electrochemical sensor based on bimetallic Au-Cu nanoparticles supported on P nanozeolite modified carbon paste electrode (Au-Cu/NPZ/CPE) was constructed and its efficiency for determination of hydrazine in trace level was studied. For this purpose, agro waste material, stem sweep ash (SSA) was employed as the starting material (silica source) for the synthesis of nano P zeolite (NPZ). After characterization of the synthesized NPZ by analytical instruments (scanning electronic microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD) and Fourier transform infrared (FT-IR) spectroscopy), construction of Au-Cu/NPZ/CPE was performed by three steps procedure involving preparation of nano P zeolite modified carbon paste electrode (NPZ/CPE), introducing Cu +2 ions into nano zeolite structure by ion exchange and electrochemical reduction of Cu +2 ions upon applying constant potential. This procedure is followed by partial replacement of Cu by Au due to galvanic replacement reaction (GRR). The electrochemical properties of hydrazine at the surface of Au-Cu/NPZ/CPE was evaluated using cyclic voltammetry (CV), amperometry, and chronoamperometry methods in 0.1 M phosphate buffer solution (PBS). It was found that the prepared sensor has higher electrocatalytic activity at a relatively lower potential compared to other modified electrodes including Au/NPZ/CPE, Cu/NPZ/CPE, Au-Cu/CPE and etc. Moreover, the proposed electrochemical sensor presented the favorable analytical properties for determination of hydrazine such as low detection limit (0.04 µM), rapid response time (3 s), wide linear range (0.01-150 mM), and high sensitivity (99.53 µA mM -1 ) that are related to the synergic effect of bimetallic of Au-Cu, porous structure and enough surface area of NPZ. In addition, capability of Au-Cu/NPZ/CPE sensor was successfully tested in real samples with good accuracy and precision. Copyright © 2018 Elsevier B.V. All rights reserved.

Reconstruction of Building Outlines in Dense Urban Areas Based on LIDAR Data and Address Points

NASA Astrophysics Data System (ADS)

Jarzabek-Rychard, M.

2012-07-01

The paper presents a comprehensive method for automated extraction and delineation of building outlines in densely built-up areas. A novel approach to outline reconstruction is the use of geocoded building address points. They give information about building location thus highly reduce task complexity. Reconstruction process is executed on 3D point clouds acquired by airborne laser scanner. The method consists of three steps: building detection, delineation and contours refinement. The algorithm is tested against a data set that presents the old market town and its surroundings. The results are discussed and evaluated by comparison to reference cadastral data.

Close Range Photogrammetry Applied to the Documentation of AN Archaeological Site in Gaza Strip, Palestine

NASA Astrophysics Data System (ADS)

Alby, E.; Elter, R.; Ripoche, C.; Quere, N.; de Strasbourg, INSA

2013-07-01

In a geopolitical very complex context as the Gaza Strip it has to be dealt with an enhancement of an archaeological site. This site is the monastery of St. Hilarion. To enable a cultural appropriation of a place with several identified phases of occupation must undertake extensive archaeological excavation. Excavate in this geographical area is to implement emergency excavations, so the aim of such a project can be questioned for each mission. Real estate pressure is also a motivating setting the documentation because the large population density does not allow systematic studies of underground before construction projects. This is also during the construction of a road that the site was discovered. Site dimensions are 150 m by 80 m. It is located on a sand dune, 300 m from the sea. To implement the survey, four different levels of detail have been defined for terrestrial photogrammetry. The first level elements are similar to objects, capitals, fragment of columns, tiles for example. Modeling of small objects requires the acquisition of very dense point clouds (density: 1 point / 1 mm on average). The object must then be a maximum area of the sensor of the camera, while retaining in the field of view a reference pattern for the scaling of the point cloud generated. The pictures are taken at a short distance from the object, using the images at full resolution. The main obstacle to the modeling of objects is the presence of noise partly due to the studied materials (sand, smooth rock), which do not favor the detection of points of interest quality. Pretreatments of the cloud will be achieved meticulously since the ouster of points on a surface of a small object results in the formation of a hole with a lack of information, useful to resulting mesh. Level 2 focuses on the stratigraphic units such as mosaics. The monastery of St. Hilarion identifies thirteen floors of which has been documented years ago by silver photographs, scanned later. Modeling of pavements is to obtain a three-dimensional model of the mosaic in particular to analyze the subsidence, which it may be subjected. The dense point cloud can go beyond by including the geometric shapes of the pavement. The calculation mesh using high-density point cloud colorization allows cloud sufficient to final rendering. Levels 3 and 4 will allow the survey and representation of loci and sectors. Their modeling can be done by colored mesh or textured by a generic pattern but also by geometric primitives. This method requires the segmentation simple geometrical elements and creates a surface geometry by analysis of the sample points. Statistical tools allow the extraction plans meet the requirements of the operator can monitor quantitatively the quality of the final rendering. Each level has constraints on the accuracy of survey and types of representation especially from the point clouds, which are detailed in the complete article.

Cutaneous exposure to clinically-relevant pigeon pea (Cajanus cajan) proteins promote TH2-dependent sensitization and IgE-mediated anaphylaxis in Balb/c mice.

PubMed

Kumar Gupta, Rinkesh; Kumar, Sandeep; Gupta, Kriti; Sharma, Akanksha; Roy, Ruchi; Kumar Verma, Alok; Chaudhari, Bhushan P; Das, Mukul; Ahmad Ansari, Irfan; Dwivedi, Premendra D

2016-11-01

Epicutaneous (EC) sensitization to food allergens may occur when the skin has been lightly damaged. The study here tested whether cutaneous exposure to pigeon pea protein(s) may cause allergic sensitization. BALB/c mice were either orally gavaged or epicutaneously sensitized by repeated application of pigeon pea crude protein extract (CPE) on undamaged areas of skin without any adjuvant; afterwards, both groups were orally challenged with the pigeon pea CPE. Anaphylactic symptoms along with measures of body temperature, MCPT-1, TSLP, pigeon pea-specific IgE and IgG 1 , myeloperoxidase (MPO) activity, T H 2 cytokines, T H 2 transcription factors (TFs) and filaggrin expression were determined. Mast cell staining, eosinophil levels and histopathological analysis of the skin and intestines were also performed. In the epicutaneously-sensitized mice, elevated levels of specific IgE and IgG 1 , as well as of MCPT-1, TSLP, T H 2 cytokines and TFs, higher anaphylactic scores and histological changes in the skin and intestine were indicative of sensitization ability via both routes in the pigeon pea CPE-treated hosts. Elevated levels of mast cells were observed in both the skin and intestine; increased levels of eosinophils and MPO activity were noted only in the skin. Decreased levels of filaggrin in skin may have played a key role in the skin barrier dysfunction, increasing the chances of sensitization. Therefore, the experimental data support the hypothesis that in addition to oral exposure, skin exposure to food allergens can promote T H 2-dependent sensitization, IgE-mediated anaphylaxis and intestinal changes after oral challenge. Based on this, an avoidance of cutaneous exposures to allergens might prevent development of food anaphylaxis.

Comparison of Single and Multi-Scale Method for Leaf and Wood Points Classification from Terrestrial Laser Scanning Data

NASA Astrophysics Data System (ADS)

Wei, Hongqiang; Zhou, Guiyun; Zhou, Junjie

2018-04-01

The classification of leaf and wood points is an essential preprocessing step for extracting inventory measurements and canopy characterization of trees from the terrestrial laser scanning (TLS) data. The geometry-based approach is one of the widely used classification method. In the geometry-based method, it is common practice to extract salient features at one single scale before the features are used for classification. It remains unclear how different scale(s) used affect the classification accuracy and efficiency. To assess the scale effect on the classification accuracy and efficiency, we extracted the single-scale and multi-scale salient features from the point clouds of two oak trees of different sizes and conducted the classification on leaf and wood. Our experimental results show that the balanced accuracy of the multi-scale method is higher than the average balanced accuracy of the single-scale method by about 10 % for both trees. The average speed-up ratio of single scale classifiers over multi-scale classifier for each tree is higher than 30.

Detecting Inspection Objects of Power Line from Cable Inspection Robot LiDAR Data

PubMed Central

Qin, Xinyan; Wu, Gongping; Fan, Fei

2018-01-01

Power lines are extending to complex environments (e.g., lakes and forests), and the distribution of power lines in a tower is becoming complicated (e.g., multi-loop and multi-bundle). Additionally, power line inspection is becoming heavier and more difficult. Advanced LiDAR technology is increasingly being used to solve these difficulties. Based on precise cable inspection robot (CIR) LiDAR data and the distinctive position and orientation system (POS) data, we propose a novel methodology to detect inspection objects surrounding power lines. The proposed method mainly includes four steps: firstly, the original point cloud is divided into single-span data as a processing unit; secondly, the optimal elevation threshold is constructed to remove ground points without the existing filtering algorithm, improving data processing efficiency and extraction accuracy; thirdly, a single power line and its surrounding data can be respectively extracted by a structured partition based on a POS data (SPPD) algorithm from “layer” to “block” according to power line distribution; finally, a partition recognition method is proposed based on the distribution characteristics of inspection objects, highlighting the feature information and improving the recognition effect. The local neighborhood statistics and the 3D region growing method are used to recognize different inspection objects surrounding power lines in a partition. Three datasets were collected by two CIR LIDAR systems in our study. The experimental results demonstrate that an average 90.6% accuracy and average 98.2% precision at the point cloud level can be achieved. The successful extraction indicates that the proposed method is feasible and promising. Our study can be used to obtain precise dimensions of fittings for modeling, as well as automatic detection and location of security risks, so as to improve the intelligence level of power line inspection. PMID:29690560

Detecting Inspection Objects of Power Line from Cable Inspection Robot LiDAR Data.

PubMed

Qin, Xinyan; Wu, Gongping; Lei, Jin; Fan, Fei; Ye, Xuhui

2018-04-22

Power lines are extending to complex environments (e.g., lakes and forests), and the distribution of power lines in a tower is becoming complicated (e.g., multi-loop and multi-bundle). Additionally, power line inspection is becoming heavier and more difficult. Advanced LiDAR technology is increasingly being used to solve these difficulties. Based on precise cable inspection robot (CIR) LiDAR data and the distinctive position and orientation system (POS) data, we propose a novel methodology to detect inspection objects surrounding power lines. The proposed method mainly includes four steps: firstly, the original point cloud is divided into single-span data as a processing unit; secondly, the optimal elevation threshold is constructed to remove ground points without the existing filtering algorithm, improving data processing efficiency and extraction accuracy; thirdly, a single power line and its surrounding data can be respectively extracted by a structured partition based on a POS data (SPPD) algorithm from "layer" to "block" according to power line distribution; finally, a partition recognition method is proposed based on the distribution characteristics of inspection objects, highlighting the feature information and improving the recognition effect. The local neighborhood statistics and the 3D region growing method are used to recognize different inspection objects surrounding power lines in a partition. Three datasets were collected by two CIR LIDAR systems in our study. The experimental results demonstrate that an average 90.6% accuracy and average 98.2% precision at the point cloud level can be achieved. The successful extraction indicates that the proposed method is feasible and promising. Our study can be used to obtain precise dimensions of fittings for modeling, as well as automatic detection and location of security risks, so as to improve the intelligence level of power line inspection.

Reducing overlay sampling for APC-based correction per exposure by replacing measured data with computational prediction

NASA Astrophysics Data System (ADS)

Noyes, Ben F.; Mokaberi, Babak; Oh, Jong Hun; Kim, Hyun Sik; Sung, Jun Ha; Kea, Marc

2016-03-01

One of the keys to successful mass production of sub-20nm nodes in the semiconductor industry is the development of an overlay correction strategy that can meet specifications, reduce the number of layers that require dedicated chuck overlay, and minimize measurement time. Three important aspects of this strategy are: correction per exposure (CPE), integrated metrology (IM), and the prioritization of automated correction over manual subrecipes. The first and third aspects are accomplished through an APC system that uses measurements from production lots to generate CPE corrections that are dynamically applied to future lots. The drawback of this method is that production overlay sampling must be extremely high in order to provide the system with enough data to generate CPE. That drawback makes IM particularly difficult because of the throughput impact that can be created on expensive bottleneck photolithography process tools. The goal is to realize the cycle time and feedback benefits of IM coupled with the enhanced overlay correction capability of automated CPE without impacting process tool throughput. This paper will discuss the development of a system that sends measured data with reduced sampling via an optimized layout to the exposure tool's computational modelling platform to predict and create "upsampled" overlay data in a customizable output layout that is compatible with the fab user CPE APC system. The result is dynamic CPE without the burden of extensive measurement time, which leads to increased utilization of IM.

A Wide Variety of Clostridium perfringens Type A Food-Borne Isolates That Carry a Chromosomal cpe Gene Belong to One Multilocus Sequence Typing Cluster

PubMed Central

Xiao, Yinghua; Wagendorp, Arjen; Moezelaar, Roy; Abee, Tjakko

2012-01-01

Of 98 suspected food-borne Clostridium perfringens isolates obtained from a nationwide survey by the Food and Consumer Product Safety Authority in The Netherlands, 59 strains were identified as C. perfringens type A. Using PCR-based techniques, the cpe gene encoding enterotoxin was detected in eight isolates, showing a chromosomal location for seven isolates and a plasmid location for one isolate. Further characterization of these strains by using (GTG)5 fingerprint repetitive sequence-based PCR analysis distinguished C. perfringens from other sulfite-reducing clostridia but did not allow for differentiation between various types of C. perfringens strains. To characterize the C. perfringens strains further, multilocus sequence typing (MLST) analysis was performed on eight housekeeping genes of both enterotoxic and non-cpe isolates, and the data were combined with a previous global survey covering strains associated with food poisoning, gas gangrene, and isolates from food or healthy individuals. This revealed that the chromosomal cpe strains (food strains and isolates from food poisoning cases) belong to a distinct cluster that is significantly distant from all the other cpe plasmid-carrying and cpe-negative strains. These results suggest that different groups of C. perfringens have undergone niche specialization and that a distinct group of food isolates has specific core genome sequences. Such findings have epidemiological and evolutionary significance. Better understanding of the origin and reservoir of enterotoxic C. perfringens may allow for improved control of this organism in foods. PMID:22865060

Impact of CT perfusion imaging on the assessment of peripheral chronic pulmonary thromboembolism: clinical experience in 62 patients.

PubMed

Le Faivre, Julien; Duhamel, Alain; Khung, Suonita; Faivre, Jean-Baptiste; Lamblin, Nicolas; Remy, Jacques; Remy-Jardin, Martine

2016-11-01

To evaluate the impact of CT perfusion imaging on the detection of peripheral chronic pulmonary embolisms (CPE). 62 patients underwent a dual-energy chest CT angiographic examination with (a) reconstruction of diagnostic and perfusion images; (b) enabling depiction of vascular features of peripheral CPE on diagnostic images and perfusion defects (20 segments/patient; total: 1240 segments examined). The interpretation of diagnostic images was of two types: (a) standard (i.e., based on cross-sectional images alone) or (b) detailed (i.e., based on cross-sectional images and MIPs). The segment-based analysis showed (a) 1179 segments analyzable on both imaging modalities and 61 segments rated as nonanalyzable on perfusion images; (b) the percentage of diseased segments was increased by 7.2 % when perfusion imaging was compared to the detailed reading of diagnostic images, and by 26.6 % when compared to the standard reading of images. At a patient level, the extent of peripheral CPE was higher on perfusion imaging, with a greater impact when compared to the standard reading of diagnostic images (number of patients with a greater number of diseased segments: n = 45; 72.6 % of the study population). Perfusion imaging allows recognition of a greater extent of peripheral CPE compared to diagnostic imaging. • Dual-energy computed tomography generates standard diagnostic imaging and lung perfusion analysis. • Depiction of CPE on central arteries relies on standard diagnostic imaging. • Detection of peripheral CPE is improved by perfusion imaging.

Automatic digital surface model (DSM) generation from aerial imagery data

NASA Astrophysics Data System (ADS)

Zhou, Nan; Cao, Shixiang; He, Hongyan; Xing, Kun; Yue, Chunyu

2018-04-01

Aerial sensors are widely used to acquire imagery for photogrammetric and remote sensing application. In general, the images have large overlapped region, which provide a lot of redundant geometry and radiation information for matching. This paper presents a POS supported dense matching procedure for automatic DSM generation from aerial imagery data. The method uses a coarse-to-fine hierarchical strategy with an effective combination of several image matching algorithms: image radiation pre-processing, image pyramid generation, feature point extraction and grid point generation, multi-image geometrically constraint cross-correlation (MIG3C), global relaxation optimization, multi-image geometrically constrained least squares matching (MIGCLSM), TIN generation and point cloud filtering. The image radiation pre-processing is used in order to reduce the effects of the inherent radiometric problems and optimize the images. The presented approach essentially consists of 3 components: feature point extraction and matching procedure, grid point matching procedure and relational matching procedure. The MIGCLSM method is used to achieve potentially sub-pixel accuracy matches and identify some inaccurate and possibly false matches. The feasibility of the method has been tested on different aerial scale images with different landcover types. The accuracy evaluation is based on the comparison between the automatic extracted DSMs derived from the precise exterior orientation parameters (EOPs) and the POS.

The observed influence of local anthropogenic pollution on northern Alaskan cloud properties

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

Maahn, Maximilian; de Boer, Gijs; Creamean, Jessie M.

Due to their importance for the radiation budget, liquid-containing clouds are a key component of the Arctic climate system. Depending on season, they can cool or warm the near-surface air. The radiative properties of these clouds depend strongly on cloud drop sizes, which are governed in part by the availability of cloud condensation nuclei. Here, we investigate how cloud drop sizes are modified in the presence of local emissions from industrial facilities at the North Slope of Alaska. For this, we use aircraft in situ observations of clouds and aerosols from the 5th Department of Energy Atmospheric Radiation Measurement (DOE ARM)more » Program's Airborne Carbon Measurements (ACME-V) campaign obtained in summer 2015. Comparison of observations from an area with petroleum extraction facilities (Oliktok Point) with data from a reference area relatively free of anthropogenic sources (Utqiaġvik/Barrow) represents an opportunity to quantify the impact of local industrial emissions on cloud properties. In the presence of local industrial emissions, the mean effective radii of cloud droplets are reduced from 12.2 to 9.4 µm, which leads to suppressed drizzle production and precipitation. At the same time, concentrations of refractory black carbon and condensation nuclei are enhanced below the clouds. These results demonstrate that the effects of anthropogenic pollution on local climate need to be considered when planning Arctic industrial infrastructure in a warming environment.« less

The observed influence of local anthropogenic pollution on northern Alaskan cloud properties

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

Maahn, Maximilian; de Boer, Gijs; Creamean, Jessie M.

Due to their importance for the radiation budget, liquid-containing clouds are a key component of the Arctic climate system. Depending on season, they can cool or warm the near-surface air. The radiative properties of these clouds depend strongly on cloud drop sizes, which are governed in part by the availability of cloud condensation nuclei. Here, we investigate how cloud drop sizes are modified in the presence of local emissions from industrial facilities at the North Slope of Alaska. For this, we use aircraft in situ observations of clouds and aerosols from the 5th Department of Energy Atmospheric Radiation Measurement (DOE ARM)more » Program's Airborne Carbon Measurements (ACME-V) campaign obtained in summer 2015. Comparison of observations from an area with petroleum extraction facilities (Oliktok Point) with data from a reference area relatively free of anthropogenic sources (Utqiagvik/Barrow) represents an opportunity to quantify the impact of local industrial emissions on cloud properties. In the presence of local industrial emissions, the mean effective radii of cloud droplets are reduced from 12.2 to 9.4 µm, which leads to suppressed drizzle production and precipitation. At the same time, concentrations of refractory black carbon and condensation nuclei are enhanced below the clouds. These results demonstrate that the effects of anthropogenic pollution on local climate need to be considered when planning Arctic industrial infrastructure in a warming environment.« less

The observed influence of local anthropogenic pollution on northern Alaskan cloud properties

DOE PAGES

Maahn, Maximilian; de Boer, Gijs; Creamean, Jessie M.; ...

2017-12-11

Due to their importance for the radiation budget, liquid-containing clouds are a key component of the Arctic climate system. Depending on season, they can cool or warm the near-surface air. The radiative properties of these clouds depend strongly on cloud drop sizes, which are governed in part by the availability of cloud condensation nuclei. Here, we investigate how cloud drop sizes are modified in the presence of local emissions from industrial facilities at the North Slope of Alaska. For this, we use aircraft in situ observations of clouds and aerosols from the 5th Department of Energy Atmospheric Radiation Measurement (DOE ARM)more » Program's Airborne Carbon Measurements (ACME-V) campaign obtained in summer 2015. Comparison of observations from an area with petroleum extraction facilities (Oliktok Point) with data from a reference area relatively free of anthropogenic sources (Utqiagvik/Barrow) represents an opportunity to quantify the impact of local industrial emissions on cloud properties. In the presence of local industrial emissions, the mean effective radii of cloud droplets are reduced from 12.2 to 9.4 µm, which leads to suppressed drizzle production and precipitation. At the same time, concentrations of refractory black carbon and condensation nuclei are enhanced below the clouds. These results demonstrate that the effects of anthropogenic pollution on local climate need to be considered when planning Arctic industrial infrastructure in a warming environment.« less

D Central Line Extraction of Fossil Oyster Shells

NASA Astrophysics Data System (ADS)

Djuricic, A.; Puttonen, E.; Harzhauser, M.; Mandic, O.; Székely, B.; Pfeifer, N.

2016-06-01

Photogrammetry provides a powerful tool to digitally document protected, inaccessible, and rare fossils. This saves manpower in relation to current documentation practice and makes the fragile specimens more available for paleontological analysis and public education. In this study, high resolution orthophoto (0.5 mm) and digital surface models (1 mm) are used to define fossil boundaries that are then used as an input to automatically extract fossil length information via central lines. In general, central lines are widely used in geosciences as they ease observation, monitoring and evaluation of object dimensions. Here, the 3D central lines are used in a novel paleontological context to study fossilized oyster shells with photogrammetric and LiDAR-obtained 3D point cloud data. 3D central lines of 1121 Crassostrea gryphoides oysters of various shapes and sizes were computed in the study. Central line calculation included: i) Delaunay triangulation between the fossil shell boundary points and formation of the Voronoi diagram; ii) extraction of Voronoi vertices and construction of a connected graph tree from them; iii) reduction of the graph to the longest possible central line via Dijkstra's algorithm; iv) extension of longest central line to the shell boundary and smoothing by an adjustment of cubic spline curve; and v) integration of the central line into the corresponding 3D point cloud. The resulting longest path estimate for the 3D central line is a size parameter that can be applied in oyster shell age determination both in paleontological and biological applications. Our investigation evaluates ability and performance of the central line method to measure shell sizes accurately by comparing automatically extracted central lines with manually collected reference data used in paleontological analysis. Our results show that the automatically obtained central line length overestimated the manually collected reference by 1.5% in the test set, which is deemed sufficient for the selected paleontological application, namely shell age determination.

The coupling analysis between stock market indices based on permutation measures

NASA Astrophysics Data System (ADS)

Shi, Wenbin; Shang, Pengjian; Xia, Jianan; Yeh, Chien-Hung

2016-04-01

Many information-theoretic methods have been proposed for analyzing the coupling dependence between time series. And it is significant to quantify the correlation relationship between financial sequences since the financial market is a complex evolved dynamic system. Recently, we developed a new permutation-based entropy, called cross-permutation entropy (CPE), to detect the coupling structures between two synchronous time series. In this paper, we extend the CPE method to weighted cross-permutation entropy (WCPE), to address some of CPE's limitations, mainly its inability to differentiate between distinct patterns of a certain motif and the sensitivity of patterns close to the noise floor. It shows more stable and reliable results than CPE does when applied it to spiky data and AR(1) processes. Besides, we adapt the CPE method to infer the complexity of short-length time series by freely changing the time delay, and test it with Gaussian random series and random walks. The modified method shows the advantages in reducing deviations of entropy estimation compared with the conventional one. Finally, the weighted cross-permutation entropy of eight important stock indices from the world financial markets is investigated, and some useful and interesting empirical results are obtained.

Ceramide Phosphoethanolamine Biosynthesis in Drosophila Is Mediated by a Unique Ethanolamine Phosphotransferase in the Golgi Lumen♦

PubMed Central

Vacaru, Ana M.; van den Dikkenberg, Joep; Ternes, Philipp; Holthuis, Joost C. M.

2013-01-01

Sphingomyelin (SM) is a vital component of mammalian membranes, providing mechanical stability and a structural framework for plasma membrane organization. Its production involves the transfer of phosphocholine from phosphatidylcholine onto ceramide, a reaction catalyzed by SM synthase in the Golgi lumen. Drosophila lacks SM and instead synthesizes the SM analogue ceramide phosphoethanolamine (CPE) as the principal membrane sphingolipid. The corresponding CPE synthase shares mechanistic features with enzymes mediating phospholipid biosynthesis via the Kennedy pathway. Using a functional cloning strategy, we here identified a CDP-ethanolamine:ceramide ethanolamine phosphotransferase as the enzyme responsible for CPE production in Drosophila. CPE synthase constitutes a new branch within the CDP-alcohol phosphotransferase superfamily with homologues in Arthropoda (insects, spiders, mites, scorpions), Cnidaria (Hydra, sea anemones), and Mollusca (oysters) but not in most other animal phyla. The enzyme resides in the Golgi complex with its active site facing the lumen, contrary to the membrane topology of other CDP-alcohol phosphotransferases. Our findings open up an important new avenue to address the biological role of CPE, an enigmatic membrane constituent of a wide variety of invertebrate and marine organisms. PMID:23449981

Aboveground Biomass Estimation Using Reconstructed Feature of Airborne Discrete-Return LIDAR by Auto-Encoder Neural Network

NASA Astrophysics Data System (ADS)

Li, T.; Wang, Z.; Peng, J.

2018-04-01

Aboveground biomass (AGB) estimation is critical for quantifying carbon stocks and essential for evaluating carbon cycle. In recent years, airborne LiDAR shows its great ability for highly-precision AGB estimation. Most of the researches estimate AGB by the feature metrics extracted from the canopy height distribution of the point cloud which calculated based on precise digital terrain model (DTM). However, if forest canopy density is high, the probability of the LiDAR signal penetrating the canopy is lower, resulting in ground points is not enough to establish DTM. Then the distribution of forest canopy height is imprecise and some critical feature metrics which have a strong correlation with biomass such as percentiles, maximums, means and standard deviations of canopy point cloud can hardly be extracted correctly. In order to address this issue, we propose a strategy of first reconstructing LiDAR feature metrics through Auto-Encoder neural network and then using the reconstructed feature metrics to estimate AGB. To assess the prediction ability of the reconstructed feature metrics, both original and reconstructed feature metrics were regressed against field-observed AGB using the multiple stepwise regression (MS) and the partial least squares regression (PLS) respectively. The results showed that the estimation model using reconstructed feature metrics improved R2 by 5.44 %, 18.09 %, decreased RMSE value by 10.06 %, 22.13 % and reduced RMSEcv by 10.00 %, 21.70 % for AGB, respectively. Therefore, reconstructing LiDAR point feature metrics has potential for addressing AGB estimation challenge in dense canopy area.

Applicability Analysis of Cloth Simulation Filtering Algorithm for Mobile LIDAR Point Cloud

NASA Astrophysics Data System (ADS)

Cai, S.; Zhang, W.; Qi, J.; Wan, P.; Shao, J.; Shen, A.

2018-04-01

Classifying the original point clouds into ground and non-ground points is a key step in LiDAR (light detection and ranging) data post-processing. Cloth simulation filtering (CSF) algorithm, which based on a physical process, has been validated to be an accurate, automatic and easy-to-use algorithm for airborne LiDAR point cloud. As a new technique of three-dimensional data collection, the mobile laser scanning (MLS) has been gradually applied in various fields, such as reconstruction of digital terrain models (DTM), 3D building modeling and forest inventory and management. Compared with airborne LiDAR point cloud, there are some different features (such as point density feature, distribution feature and complexity feature) for mobile LiDAR point cloud. Some filtering algorithms for airborne LiDAR data were directly used in mobile LiDAR point cloud, but it did not give satisfactory results. In this paper, we explore the ability of the CSF algorithm for mobile LiDAR point cloud. Three samples with different shape of the terrain are selected to test the performance of this algorithm, which respectively yields total errors of 0.44 %, 0.77 % and1.20 %. Additionally, large area dataset is also tested to further validate the effectiveness of this algorithm, and results show that it can quickly and accurately separate point clouds into ground and non-ground points. In summary, this algorithm is efficient and reliable for mobile LiDAR point cloud.

Non-hard sphere thermodynamic perturbation theory.

PubMed

Zhou, Shiqi

2011-08-21

A non-hard sphere (HS) perturbation scheme, recently advanced by the present author, is elaborated for several technical matters, which are key mathematical details for implementation of the non-HS perturbation scheme in a coupling parameter expansion (CPE) thermodynamic perturbation framework. NVT-Monte Carlo simulation is carried out for a generalized Lennard-Jones (LJ) 2n-n potential to obtain routine thermodynamic quantities such as excess internal energy, pressure, excess chemical potential, excess Helmholtz free energy, and excess constant volume heat capacity. Then, these new simulation data, and available simulation data in literatures about a hard core attractive Yukawa fluid and a Sutherland fluid, are used to test the non-HS CPE 3rd-order thermodynamic perturbation theory (TPT) and give a comparison between the non-HS CPE 3rd-order TPT and other theoretical approaches. It is indicated that the non-HS CPE 3rd-order TPT is superior to other traditional TPT such as van der Waals/HS (vdW/HS), perturbation theory 2 (PT2)/HS, and vdW/Yukawa (vdW/Y) theory or analytical equation of state such as mean spherical approximation (MSA)-equation of state and is at least comparable to several currently the most accurate Ornstein-Zernike integral equation theories. It is discovered that three technical issues, i.e., opening up new bridge function approximation for the reference potential, choosing proper reference potential, and/or using proper thermodynamic route for calculation of f(ex-ref), chiefly decide the quality of the non-HS CPE TPT. Considering that the non-HS perturbation scheme applies for a wide variety of model fluids, and its implementation in the CPE thermodynamic perturbation framework is amenable to high-order truncation, the non-HS CPE 3rd-order or higher order TPT will be more promising once the above-mentioned three technological advances are established. © 2011 American Institute of Physics

Dominance of IMP-4-Producing Enterobacter cloacae among Carbapenemase-Producing Enterobacteriaceae in Australia

PubMed Central

Townell, Nicola; Nimmo, Graeme R.; George, Narelle M.; Robson, Jennifer; Vohra, Renu; Davis, Louise; Heney, Claire; Paterson, David L.

2015-01-01

The prevalence of carbapenemase-producing Enterobacteriaceae (CPE) has been increasing worldwide. blaIMP has been reported to be the predominant carbapenemase-encoding gene within Enterobacteriaceae in Australia. However, there are limited data currently available on CPE from Queensland, Australia. A total of 58 CPE isolates were isolated between July 2009 and March 2014 from Queensland hospitals. The clonality of isolates was determined by Diversilab repetitive sequence-based PCR. The isolates were investigated for the resistance mechanisms carbapenemase, extended-spectrum β-lactamase, and AmpC β-lactamase and for aminoglycoside resistance and plasmid-mediated quinolone resistance genes by PCR. The plasmid types associated with carbapenemase-encoding genes were characterized. The majority of the CPE were Enterobacter cloacae (n = 29). The majority of Queensland CPE isolates were IMP producers and comprised 11 species (n = 48). Nine NDM-producing Enterobacteriaceae were identified. One NDM-producing Klebsiella pneumoniae isolate coproduced OXA-48. One K. pneumoniae isolate was an OXA-181 producer. The incidence of IMP producers increased significantly in 2013. blaIMP-4 was found in all IMP-producing isolates. blaTEM, qnrB, and aacA4 were common among IMP-4 producers. The HI2 (67%) and L/M (21%) replicons were associated with blaIMP-4. All HI2 plasmids were of sequence type 1 (ST1). All but one of the NDM producers possessed blaCTX-M-15. The 16S rRNA methylase genes found among NDM producers were armA, rmtB, rmtC, and rmtF. The substantial increase in the prevalence of CPE in Queensland has been associated mainly with the emergence E. cloacae strains possessing HI2 plasmids carrying blaIMP-4 over the past 2 years. The importation of NDM producers and/or OXA-48-like producers in patients also contributed to the increased emergence of CPE. PMID:25918153

Investigating the Accuracy of Point Clouds Generated for Rock Surfaces

NASA Astrophysics Data System (ADS)

Seker, D. Z.; Incekara, A. H.

2016-12-01

Point clouds which are produced by means of different techniques are widely used to model the rocks and obtain the properties of rock surfaces like roughness, volume and area. These point clouds can be generated by applying laser scanning and close range photogrammetry techniques. Laser scanning is the most common method to produce point cloud. In this method, laser scanner device produces 3D point cloud at regular intervals. In close range photogrammetry, point cloud can be produced with the help of photographs taken in appropriate conditions depending on developing hardware and software technology. Many photogrammetric software which is open source or not currently provide the generation of point cloud support. Both methods are close to each other in terms of accuracy. Sufficient accuracy in the mm and cm range can be obtained with the help of a qualified digital camera and laser scanner. In both methods, field work is completed in less time than conventional techniques. In close range photogrammetry, any part of rock surfaces can be completely represented owing to overlapping oblique photographs. In contrast to the proximity of the data, these two methods are quite different in terms of cost. In this study, whether or not point cloud produced by photographs can be used instead of point cloud produced by laser scanner device is investigated. In accordance with this purpose, rock surfaces which have complex and irregular shape located in İstanbul Technical University Ayazaga Campus were selected as study object. Selected object is mixture of different rock types and consists of both partly weathered and fresh parts. Study was performed on a part of 30m x 10m rock surface. 2D and 3D analysis were performed for several regions selected from the point clouds of the surface models. 2D analysis is area-based and 3D analysis is volume-based. Analysis conclusions showed that point clouds in both are similar and can be used as alternative to each other. This proved that point cloud produced using photographs which are both economical and enables to produce data in less time can be used in several studies instead of point cloud produced by laser scanner.

Three-dimension reconstruction based on spatial light modulator

NASA Astrophysics Data System (ADS)

Deng, Xuejiao; Zhang, Nanyang; Zeng, Yanan; Yin, Shiliang; Wang, Weiyu

2011-02-01

Three-dimension reconstruction, known as an important research direction of computer graphics, is widely used in the related field such as industrial design and manufacture, construction, aerospace, biology and so on. Via such technology we can obtain three-dimension digital point cloud from a two-dimension image, and then simulate the three-dimensional structure of the physical object for further study. At present, the obtaining of three-dimension digital point cloud data is mainly based on the adaptive optics system with Shack-Hartmann sensor and phase-shifting digital holography. Referring to surface fitting, there are also many available methods such as iterated discrete fourier transform, convolution and image interpolation, linear phase retrieval. The main problems we came across in three-dimension reconstruction are the extraction of feature points and arithmetic of curve fitting. To solve such problems, we can, first of all, calculate the relevant surface normal vector information of each pixel in the light source coordinate system, then these vectors are to be converted to the coordinates of image through the coordinate conversion, so the expectant 3D point cloud get arise. Secondly, after the following procedures of de-noising, repairing, the feature points can later be selected and fitted to get the fitting function of the surface topography by means of Zernike polynomial, so as to reconstruct the determinand's three-dimensional topography. In this paper, a new kind of three-dimension reconstruction algorithm is proposed, with the assistance of which, the topography can be estimated from its grayscale at different sample points. Moreover, the previous stimulation and the experimental results prove that the new algorithm has a strong capability to fit, especially for large-scale objects .

Automated real-time search and analysis algorithms for a non-contact 3D profiling system

NASA Astrophysics Data System (ADS)

Haynes, Mark; Wu, Chih-Hang John; Beck, B. Terry; Peterman, Robert J.

2013-04-01

The purpose of this research is to develop a new means of identifying and extracting geometrical feature statistics from a non-contact precision-measurement 3D profilometer. Autonomous algorithms have been developed to search through large-scale Cartesian point clouds to identify and extract geometrical features. These algorithms are developed with the intent of providing real-time production quality control of cold-rolled steel wires. The steel wires in question are prestressing steel reinforcement wires for concrete members. The geometry of the wire is critical in the performance of the overall concrete structure. For this research a custom 3D non-contact profilometry system has been developed that utilizes laser displacement sensors for submicron resolution surface profiling. Optimizations in the control and sensory system allow for data points to be collected at up to an approximate 400,000 points per second. In order to achieve geometrical feature extraction and tolerancing with this large volume of data, the algorithms employed are optimized for parsing large data quantities. The methods used provide a unique means of maintaining high resolution data of the surface profiles while keeping algorithm running times within practical bounds for industrial application. By a combination of regional sampling, iterative search, spatial filtering, frequency filtering, spatial clustering, and template matching a robust feature identification method has been developed. These algorithms provide an autonomous means of verifying tolerances in geometrical features. The key method of identifying the features is through a combination of downhill simplex and geometrical feature templates. By performing downhill simplex through several procedural programming layers of different search and filtering techniques, very specific geometrical features can be identified within the point cloud and analyzed for proper tolerancing. Being able to perform this quality control in real time provides significant opportunities in cost savings in both equipment protection and waste minimization.

Object Based Image Analysis Combining High Spatial Resolution Imagery and Laser Point Clouds for Urban Land Cover

NASA Astrophysics Data System (ADS)

Zou, Xiaoliang; Zhao, Guihua; Li, Jonathan; Yang, Yuanxi; Fang, Yong

2016-06-01

With the rapid developments of the sensor technology, high spatial resolution imagery and airborne Lidar point clouds can be captured nowadays, which make classification, extraction, evaluation and analysis of a broad range of object features available. High resolution imagery, Lidar dataset and parcel map can be widely used for classification as information carriers. Therefore, refinement of objects classification is made possible for the urban land cover. The paper presents an approach to object based image analysis (OBIA) combing high spatial resolution imagery and airborne Lidar point clouds. The advanced workflow for urban land cover is designed with four components. Firstly, colour-infrared TrueOrtho photo and laser point clouds were pre-processed to derive the parcel map of water bodies and nDSM respectively. Secondly, image objects are created via multi-resolution image segmentation integrating scale parameter, the colour and shape properties with compactness criterion. Image can be subdivided into separate object regions. Thirdly, image objects classification is performed on the basis of segmentation and a rule set of knowledge decision tree. These objects imagery are classified into six classes such as water bodies, low vegetation/grass, tree, low building, high building and road. Finally, in order to assess the validity of the classification results for six classes, accuracy assessment is performed through comparing randomly distributed reference points of TrueOrtho imagery with the classification results, forming the confusion matrix and calculating overall accuracy and Kappa coefficient. The study area focuses on test site Vaihingen/Enz and a patch of test datasets comes from the benchmark of ISPRS WG III/4 test project. The classification results show higher overall accuracy for most types of urban land cover. Overall accuracy is 89.5% and Kappa coefficient equals to 0.865. The OBIA approach provides an effective and convenient way to combine high resolution imagery and Lidar ancillary data for classification of urban land cover.

Reconstruction of forest geometries from terrestrial laser scanning point clouds for canopy radiative transfer modelling

NASA Astrophysics Data System (ADS)

Bremer, Magnus; Schmidtner, Korbinian; Rutzinger, Martin

2015-04-01

The architecture of forest canopies is a key parameter for forest ecological issues helping to model the variability of wood biomass and foliage in space and time. In order to understand the nature of subpixel effects of optical space-borne sensors with coarse spatial resolution, hypothetical 3D canopy models are widely used for the simulation of radiative transfer in forests. Thereby, radiation is traced through the atmosphere and canopy geometries until it reaches the optical sensor. For a realistic simulation scene we decompose terrestrial laser scanning point cloud data of leaf-off larch forest plots in the Austrian Alps and reconstruct detailed model ready input data for radiative transfer simulations. The point clouds are pre-classified into primitive classes using Principle Component Analysis (PCA) using scale adapted radius neighbourhoods. Elongated point structures are extracted as tree trunks. The tree trunks are used as seeds for a Dijkstra-growing procedure, in order to obtain single tree segmentation in the interlinked canopies. For the optimized reconstruction of branching architectures as vector models, point cloud skeletonisation is used in combination with an iterative Dijkstra-growing and by applying distance constraints. This allows conducting a hierarchical reconstruction preferring the tree trunk and higher order branches and avoiding over-skeletonization effects. Based on the reconstructed branching architectures, larch needles are modelled based on the hierarchical level of branches and the geometrical openness of the canopy. For radiative transfer simulations, branch architectures are used as mesh geometries representing branches as cylindrical pipes. Needles are either used as meshes or as voxel-turbids. The presented workflow allows an automatic classification and single tree segmentation in interlinked canopies. The iterative Dijkstra-growing using distance constraints generated realistic reconstruction results. As the mesh representation of branches proved to be sufficient for the simulation approach, the modelling of huge amounts of needles is much more efficient in voxel-turbid representation.

A continuous surface reconstruction method on point cloud captured from a 3D surface photogrammetry system

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

Liu, Wenyang; Cheung, Yam; Sabouri, Pouya

2015-11-15

Purpose: To accurately and efficiently reconstruct a continuous surface from noisy point clouds captured by a surface photogrammetry system (VisionRT). Methods: The authors have developed a level-set based surface reconstruction method on point clouds captured by a surface photogrammetry system (VisionRT). The proposed method reconstructs an implicit and continuous representation of the underlying patient surface by optimizing a regularized fitting energy, offering extra robustness to noise and missing measurements. By contrast to explicit/discrete meshing-type schemes, their continuous representation is particularly advantageous for subsequent surface registration and motion tracking by eliminating the need for maintaining explicit point correspondences as in discretemore » models. The authors solve the proposed method with an efficient narrowband evolving scheme. The authors evaluated the proposed method on both phantom and human subject data with two sets of complementary experiments. In the first set of experiment, the authors generated a series of surfaces each with different black patches placed on one chest phantom. The resulting VisionRT measurements from the patched area had different degree of noise and missing levels, since VisionRT has difficulties in detecting dark surfaces. The authors applied the proposed method to point clouds acquired under these different configurations, and quantitatively evaluated reconstructed surfaces by comparing against a high-quality reference surface with respect to root mean squared error (RMSE). In the second set of experiment, the authors applied their method to 100 clinical point clouds acquired from one human subject. In the absence of ground-truth, the authors qualitatively validated reconstructed surfaces by comparing the local geometry, specifically mean curvature distributions, against that of the surface extracted from a high-quality CT obtained from the same patient. Results: On phantom point clouds, their method achieved submillimeter reconstruction RMSE under different configurations, demonstrating quantitatively the faith of the proposed method in preserving local structural properties of the underlying surface in the presence of noise and missing measurements, and its robustness toward variations of such characteristics. On point clouds from the human subject, the proposed method successfully reconstructed all patient surfaces, filling regions where raw point coordinate readings were missing. Within two comparable regions of interest in the chest area, similar mean curvature distributions were acquired from both their reconstructed surface and CT surface, with mean and standard deviation of (μ{sub recon} = − 2.7 × 10{sup −3} mm{sup −1}, σ{sub recon} = 7.0 × 10{sup −3} mm{sup −1}) and (μ{sub CT} = − 2.5 × 10{sup −3} mm{sup −1}, σ{sub CT} = 5.3 × 10{sup −3} mm{sup −1}), respectively. The agreement of local geometry properties between the reconstructed surfaces and the CT surface demonstrated the ability of the proposed method in faithfully representing the underlying patient surface. Conclusions: The authors have integrated and developed an accurate level-set based continuous surface reconstruction method on point clouds acquired by a 3D surface photogrammetry system. The proposed method has generated a continuous representation of the underlying phantom and patient surfaces with good robustness against noise and missing measurements. It serves as an important first step for further development of motion tracking methods during radiotherapy.« less

A continuous surface reconstruction method on point cloud captured from a 3D surface photogrammetry system

PubMed Central

Liu, Wenyang; Cheung, Yam; Sabouri, Pouya; Arai, Tatsuya J.; Sawant, Amit; Ruan, Dan

2015-01-01

Purpose: To accurately and efficiently reconstruct a continuous surface from noisy point clouds captured by a surface photogrammetry system (VisionRT). Methods: The authors have developed a level-set based surface reconstruction method on point clouds captured by a surface photogrammetry system (VisionRT). The proposed method reconstructs an implicit and continuous representation of the underlying patient surface by optimizing a regularized fitting energy, offering extra robustness to noise and missing measurements. By contrast to explicit/discrete meshing-type schemes, their continuous representation is particularly advantageous for subsequent surface registration and motion tracking by eliminating the need for maintaining explicit point correspondences as in discrete models. The authors solve the proposed method with an efficient narrowband evolving scheme. The authors evaluated the proposed method on both phantom and human subject data with two sets of complementary experiments. In the first set of experiment, the authors generated a series of surfaces each with different black patches placed on one chest phantom. The resulting VisionRT measurements from the patched area had different degree of noise and missing levels, since VisionRT has difficulties in detecting dark surfaces. The authors applied the proposed method to point clouds acquired under these different configurations, and quantitatively evaluated reconstructed surfaces by comparing against a high-quality reference surface with respect to root mean squared error (RMSE). In the second set of experiment, the authors applied their method to 100 clinical point clouds acquired from one human subject. In the absence of ground-truth, the authors qualitatively validated reconstructed surfaces by comparing the local geometry, specifically mean curvature distributions, against that of the surface extracted from a high-quality CT obtained from the same patient. Results: On phantom point clouds, their method achieved submillimeter reconstruction RMSE under different configurations, demonstrating quantitatively the faith of the proposed method in preserving local structural properties of the underlying surface in the presence of noise and missing measurements, and its robustness toward variations of such characteristics. On point clouds from the human subject, the proposed method successfully reconstructed all patient surfaces, filling regions where raw point coordinate readings were missing. Within two comparable regions of interest in the chest area, similar mean curvature distributions were acquired from both their reconstructed surface and CT surface, with mean and standard deviation of (μrecon = − 2.7 × 10−3 mm−1, σrecon = 7.0 × 10−3 mm−1) and (μCT = − 2.5 × 10−3 mm−1, σCT = 5.3 × 10−3 mm−1), respectively. The agreement of local geometry properties between the reconstructed surfaces and the CT surface demonstrated the ability of the proposed method in faithfully representing the underlying patient surface. Conclusions: The authors have integrated and developed an accurate level-set based continuous surface reconstruction method on point clouds acquired by a 3D surface photogrammetry system. The proposed method has generated a continuous representation of the underlying phantom and patient surfaces with good robustness against noise and missing measurements. It serves as an important first step for further development of motion tracking methods during radiotherapy. PMID:26520747

Automatic determination of trunk diameter, crown base and height of scots pine (Pinus Sylvestris L.) Based on analysis of 3D point clouds gathered from multi-station terrestrial laser scanning. (Polish Title: Automatyczne okreslanie srednicy pnia, podstawy korony oraz wysokosci sosny zwyczajnej (Pinus Silvestris L.) Na podstawie analiz chmur punktow 3D pochodzacych z wielostanowiskowego naziemnego skanowania laserowego)

NASA Astrophysics Data System (ADS)

Ratajczak, M.; Wężyk, P.

2015-12-01

Rapid development of terrestrial laser scanning (TLS) in recent years resulted in its recognition and implementation in many industries, including forestry and nature conservation. The use of the 3D TLS point clouds in the process of inventory of trees and stands, as well as in the determination of their biometric features (trunk diameter, tree height, crown base, number of trunk shapes), trees and lumber size (volume of trees) is slowly becoming a practice. In addition to the measurement precision, the primary added value of TLS is the ability to automate the processing of the clouds of points 3D in the direction of the extraction of selected features of trees and stands. The paper presents the original software (GNOM) for the automatic measurement of selected features of trees, based on the cloud of points obtained by the ground laser scanner FARO. With the developed algorithms (GNOM), the location of tree trunks on the circular research surface was specified and the measurement was performed; the measurement covered the DBH (l: 1.3m), further diameters of tree trunks at different heights of the tree trunk, base of the tree crown and volume of the tree trunk (the selection measurement method), as well as the tree crown. Research works were performed in the territory of the Niepolomice Forest in an unmixed pine stand (Pinussylvestris L.) on the circular surface with a radius of 18 m, within which there were 16 pine trees (14 of them were cut down). It was characterized by a two-storey and even-aged construction (147 years old) and was devoid of undergrowth. Ground scanning was performed just before harvesting. The DBH of 16 pine trees was specified in a fully automatic way, using the algorithm GNOM with an accuracy of +2.1%, as compared to the reference measurement by the DBH measurement device. The medium, absolute measurement error in the cloud of points - using semi-automatic methods "PIXEL" (between points) and PIPE (fitting the cylinder) in the FARO Scene 5.x., showed the error, 3.5% and 5.0%,.respectively The reference height was assumed as the measurement performed by the tape on the cut tree. The average error of automatic determination of the tree height by the algorithm GNOM based on the TLS point clouds amounted to 6.3% and was slightly higher than when using the manual method of measurements on profiles in the TerraScan (Terrasolid; the error of 5.6%). The relatively high value of the error may be mainly related to the small number of points TLS in the upper parts of crowns. The crown height measurement showed the error of +9.5%. The reference in this case was the tape measurement performed already on the trunks of cut pine trees. Processing the clouds of points by the algorithms GNOM for 16 analyzed trees took no longer than 10 min. (37 sec. /tree). The paper mainly showed the TLS measurement innovation and its high precision in acquiring biometric data in forestry, and at the same time also the further need to increase the degree of automation of processing the clouds of points 3D from terrestrial laser scanning.

An evaluative case study of online learning for healthcare professionals.

PubMed

Pullen, Darren L

2006-01-01

This evaluation study assessed the pedagogical and instructional design (e-pedagogy) effectiveness of online continuing professional education (CPE) courses offered by a large Australian CPE provider. A naturalistic theory approach and a multilevel evaluation were used to examine the impact of web-based learning on more than 300 healthcare professionals. Participant satisfaction, learning achievement, self-reported practice performance change, and e-pedagogical courseware characteristics were assessed by various qualitative and quantitative data collection methods. Findings revealed that learning online was an effective means for increasing CPE knowledge (p < .05) and improving self-reported practice performance change (p < .05). Courses containing a clinical tool resulted in an increased self-reported practice performance change over courses that did not (Zobs = 3.757). Online CPE offers a convenient format for healthcare professionals from educationally and geographically diverse populations to update their knowledge and view best practice.

Clostridium perfringens: Comparative effects of heat and osmotic stress on non-enterotoxigenic and enterotoxigenic strains.

PubMed

Abbona, Cinthia Carolina; Stagnitta, Patricia Virginia

2016-06-01

Clostridium perfringens isolates associated with food poisoning carries a chromosomal cpe gene, while non-foodborne human gastrointestinal disease isolates carry a plasmid cpe gene. The enterotoxigenic strains tested produced vegetative cells and spores with significantly higher resistance than non-enterotoxigenic strains. These results suggest that the vegetative cells and spores have a competitive advantage over non-enterotoxigenic strains. However, no explanation has been provided for the significant associations between chromosomal cpe genotypes with the high resistance, which could explain the strong relationship between chromosomal cpe isolates and C. perfringens type A food poisoning. Here, we analyse the action of physical and chemical agent on non-enterotoxigenic and enterotoxigenic regional strains. And this study tested the relationship between the sensitivities of spores and their levels SASPs (small acid soluble proteins) production in the same strains examined. Copyright © 2016 Elsevier Ltd. All rights reserved.

Use of Vertical Aerial Images for Semi-Oblique Mapping

NASA Astrophysics Data System (ADS)

Poli, D.; Moe, K.; Legat, K.; Toschi, I.; Lago, F.; Remondino, F.

2017-05-01

The paper proposes a methodology for the use of the oblique sections of images from large-format photogrammetric cameras, by exploiting the effect of the central perspective geometry in the lateral parts of the nadir images ("semi-oblique" images). The point of origin of the investigation was the execution of a photogrammetric flight over Norcia (Italy), which was seriously damaged after the earthquake of 30/10/2016. Contrary to the original plan of oblique acquisitions, the flight was executed on 15/11/2017 using an UltraCam Eagle camera with focal length 80 mm, and combining two flight plans, rotated by 90º ("crisscross" flight). The images (GSD 5 cm) were used to extract a 2.5D DSM cloud, sampled to a XY-grid size of 2 GSD, a 3D point clouds with a mean spatial resolution of 1 GSD and a 3D mesh model at a resolution of 10 cm of the historic centre of Norcia for a quantitative assessment of the damages. From the acquired nadir images the "semi-oblique" images (forward, backward, left and right views) could be extracted and processed in a modified version of GEOBLY software for measurements and restitution purposes. The potential of such semi-oblique image acquisitions from nadir-view cameras is hereafter shown and commented.

Antiviral activity of polymethoxylated flavones from "Guangchenpi", the edible and medicinal pericarps of citrus reticulata 'Chachi'.

PubMed

Xu, Jiao-Jiao; Wu, Xia; Li, Man-Mei; Li, Guo-Qiang; Yang, Yi-Ting; Luo, Hu-Jie; Huang, Wei-Huang; Chung, Hau Yin; Ye, Wen-Cai; Wang, Guo-Cai; Li, Yao-Lan

2014-03-12

The present study found that the supercritical fluid extract of "Guangchenpi" possessed in vitro antiviral activity against respiratory syncytial virus (RSV). Bioassay-guided isolation and identification of this extract led to obtain five active polymethoxylated flavones (1-5). Cytopathic effect (CPE) reduction assay exhibited that tangeretin (2) and nobiletin (3), two major polymethoxylated flavones in the extract, possessed better anti-RSV effect comparable to the positive control ribavirin. Plaque reduction assay revealed that tangeretin dose-dependently inhibited RSV-induced plaque formation on the HEp-2 cells. This polymethoxylated flavone mainly affected the intracellular replication of RSV, and it also could inhibit RSV entry into the HEp-2 cells. Further investigations with quantitative real-time PCR and confocal and Western blot assays indicated that tangeretin downregulated the expression of RSV phosphoprotein (P protein). Results suggest the potential application of the supercritical fluid extract of "Guangchenpi" and tangeretin in the treatment and the prevention of RSV infection.

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

PubMed

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

2018-03-24

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

Carboxypeptidase E Modulates Intestinal Immune Homeostasis and Protects against Experimental Colitis in Mice

PubMed Central

Pagel, René; Schröder, Torsten; Schlichting, Heidi; Hirose, Misa; Lemcke, Susanne; Klinger, Antje; König, Peter; Karsten, Christian M.; Büning, Jürgen; Lehnert, Hendrik; Fellermann, Klaus; Ibrahim, Saleh M.; Sina, Christian

2014-01-01

Enteroendocrine cells (EEC) produce neuropeptides, which are crucially involved in the maintenance of the intestinal barrier. Hence, EEC dysfunction is suggested to be involved in the complex pathophysiology of inflammatory bowel disease (IBD), which is characterized by decreased intestinal barrier function. However, the underlying mechanisms for EEC dysfunction are not clear and suitable models for a better understanding are lacking. Here, we demonstrate that Carboxypeptidase E (CPE) is specifically expressed in EEC of the murine colon and ileum and that its deficiency is associated with reduced intestinal levels of Neuropeptide Y (NPY) and Peptide YY (PYY), which are both produced by EEC. Moreover, cpe−/− mice exhibit an aggravated course of DSS-induced chronic colitis compared to wildtype littermates. In addition, we observed elevated mucosal IL-6 and KC transcript levels already at baseline conditions in cpe−/− mice. Moreover, supernatants obtained from isolated intestinal crypts of cpe−/− mice lead to increased IL-6 and KC expression in MODE-K cells in the presence of LPS. This effect was reversible by co-administration of recombinant NPY, suggesting a CPE mediated immunosuppressive effect in the intestines by influencing the processing of specific neuropeptides. In this context, the chemotaxis of bone marrow derived macrophages towards respective supernatants was enhanced. In conclusion, our data point to an anti-inflammatory role of CPE in the intestine by influencing local cytokine levels and thus regulating the migration of myeloid immune cells into the mucosa. These findings highlight the importance of EEC for intestinal homeostasis and propose EEC as potential therapeutic targets in IBD. PMID:25051500

Experimental evaluation of ALS point cloud ground extraction over different land cover in the Malopolska Province

NASA Astrophysics Data System (ADS)

Korzeniowska, Karolina; Mandlburger, Gottfried; Klimczyk, Agata

2013-04-01

The paper presents an evaluation of different terrain point extraction algorithms for Airborne Laser Scanning (ALS) point clouds. The research area covers eight test sites in the Małopolska Province (Poland) with varying point density between 3-15points/m² and surface as well as land cover characteristics. In this paper the existing implementations of algorithms were considered. Approaches based on mathematical morphology, progressive densification, robust surface interpolation and segmentation were compared. From the group of morphological filters, the Progressive Morphological Filter (PMF) proposed by Zhang K. et al. (2003) in LIS software was evaluated. From the progressive densification filter methods developed by Axelsson P. (2000) the Martin Isenburg's implementation in LAStools software (LAStools, 2012) was chosen. The third group of methods are surface-based filters. In this study, we used the hierarchic robust interpolation approach by Kraus K., Pfeifer N. (1998) as implemented in SCOP++ (Trimble, 2012). The fourth group of methods works on segmentation. From this filtering concept the segmentation algorithm available in LIS was tested (Wichmann V., 2012). The main aim in executing the automatic classification for ground extraction was operating in default mode or with default parameters which were selected by the developers of the algorithms. It was assumed that the default settings were equivalent to the parameters on which the best results can be achieved. In case it was not possible to apply an algorithm in default mode, a combination of the available and most crucial parameters for ground extraction were selected. As a result of these analyses, several output LAS files with different ground classification were achieved. The results were described on the basis of qualitative and quantitative analyses, both being in a formal description. The classification differences were verified on point cloud data. Qualitative verification of ground extraction was made on the basis of a visual inspection of the results (Sithole G., Vosselman G., 2004; Meng X. et al., 2010). The results of these analyses were described as a graph using weighted assumption. The quantitative analyses were evaluated on a basis of Type I, Type II and Total errors (Sithole G., Vosselman G., 2003). The achieved results show that the analysed algorithms yield different classification accuracies depending on the landscape and land cover. The simplest terrain for ground extraction was flat rural area with sparse vegetation. The most difficult were mountainous areas with very dense vegetation where only a few ground points were available. Generally the LAStools algorithm gives good results in every type of terrain, but the ground surface is too smooth. The LIS Progressive Morphological Filter algorithm gives good results in forested flat and low slope areas. The surface-based algorithm from SCOP++ gives good results in mountainous areas - both forested and built-up because it better preserves steep slopes, sharp ridges and breaklines, but sometimes it fails to remove off-terrain objects from the ground class. The segmentation-based algorithm in LIS gives quite good results in built-up flat areas, but in forested areas it does not work well. Bibliography: Axelsson, P., 2000. DEM generation from laser scanner data using adaptive TIN models. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XXXIII (Pt. B4/1), 110- 117 Kraus, K., Pfeifer, N., 1998. Determination of terrain models in wooded areas with airborne laser scanner data. ISPRS Journal of Photogrammetry & Remote Sensing 53 (4), 193-203 LAStools website http://www.cs.unc.edu/~isenburg/lastools/ (verified in September 2012) Meng, X., Currit, N., Zhao, K., 2010. Ground Filtering Algorithms for Airborne LiDAR Data: A Review of Critical Issues. Remote Sensing 2, 833-860 Sithole, G., Vosselman, G., 2003. Report: ISPRS Comparison of Filters. Commission III, Working Group 3. Department of Geodesy, Faculty of Civil Engineering and Geosciences, Delft University of technology, The Netherlands Sithole, G., Vosselman, G., 2004. Experimental comparison of filter algorithms for bare-Earth extraction form airborne laser scanning point clouds. ISPRS Journal of Photogrammetry & Remote Sensing 59, 85-101 Trimble, 2012 http://www.trimble.com/geospatial/aerial-software.aspx (verified in November 2012) Wichmann, V., 2012. LIS Command Reference, LASERDATA GmbH, 1-231 Zhang, K., Chen, S.-C., Whitman, D., Shyu, M.-L., Yan, J., Zhang, C., 2003. A progressive morphological filter for removing non-ground measurements from airborne LIDAR data. IEEE Transactions on Geoscience and Remote Sensing, 41(4), 872-882

LiDAR Point Cloud and Stereo Image Point Cloud Fusion

DTIC Science & Technology

2013-09-01

LiDAR point cloud (right) highlighting linear edge features ideal for automatic registration...point cloud (right) highlighting linear edge features ideal for automatic registration. Areas where topography is being derived, unfortunately, do...with the least amount of automatic correlation errors was used. The following graphic (Figure 12) shows the coverage of the WV1 stereo triplet as

LESTO: an Open Source GIS-based toolbox for LiDAR analysis

NASA Astrophysics Data System (ADS)

Franceschi, Silvia; Antonello, Andrea; Tonon, Giustino

2015-04-01

During the last five years different research institutes and private companies stared to implement new algorithms to analyze and extract features from LiDAR data but only a few of them also created a public available software. In the field of forestry there are different examples of software that can be used to extract the vegetation parameters from LiDAR data, unfortunately most of them are closed source (even if free), which means that the source code is not shared with the public for anyone to look at or make changes to. In 2014 we started the development of the library LESTO (LiDAR Empowered Sciences Toolbox Opensource): a set of modules for the analysis of LiDAR point cloud with an Open Source approach with the aim of improving the performance of the extraction of the volume of biomass and other vegetation parameters on large areas for mixed forest structures. LESTO contains a set of modules for data handling and analysis implemented within the JGrassTools spatial processing library. The main subsections are dedicated to 1) preprocessing of LiDAR raw data mainly in LAS format (utilities and filtering); 2) creation of raster derived products; 3) flight-lines identification and normalization of the intensity values; 4) tools for extraction of vegetation and buildings. The core of the LESTO library is the extraction of the vegetation parameters. We decided to follow the single tree based approach starting with the implementation of some of the most used algorithms in literature. These have been tweaked and applied on LiDAR derived raster datasets (DTM, DSM) as well as point clouds of raw data. The methods range between the simple extraction of tops and crowns from local maxima, the region growing method, the watershed method and individual tree segmentation on point clouds. The validation procedure consists in finding the matching between field and LiDAR-derived measurements at individual tree and plot level. An automatic validation procedure has been developed considering an Optimizer Algorithm based on Particle Swarm (PS) and a matching procedure which takes the position and the height of the extracted trees respect to the measured ones and iteratively tries to improve the candidate solution changing the models' parameters. Example of application of the LESTO tools will be presented on test sites. Test area consists in a series of circular sampling plots randomly selected from a 50x50 m regular grid within a buffer zone of 150 m from the forest road. Other studies on the same sites take as reference measurements of position, diameter, species and height and proposed allometric relationships. These allometric relationship were obtained for each species deriving the stem volume of single trees based on height and diameter at breast height. LESTO is integrated in the JGrassTools project and available for download at www.jgrasstools.org. A simple and easy to use graphical interface to run the models is available at https://github.com/moovida/STAGE/releases.

A robust real-time surface reconstruction method on point clouds captured from a 3D surface photogrammetry system

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

Liu, Wenyang; Cheung, Yam; Sawant, Amit

2016-05-15

Purpose: To develop a robust and real-time surface reconstruction method on point clouds captured from a 3D surface photogrammetry system. Methods: The authors have developed a robust and fast surface reconstruction method on point clouds acquired by the photogrammetry system, without explicitly solving the partial differential equation required by a typical variational approach. Taking advantage of the overcomplete nature of the acquired point clouds, their method solves and propagates a sparse linear relationship from the point cloud manifold to the surface manifold, assuming both manifolds share similar local geometry. With relatively consistent point cloud acquisitions, the authors propose a sparsemore » regression (SR) model to directly approximate the target point cloud as a sparse linear combination from the training set, assuming that the point correspondences built by the iterative closest point (ICP) is reasonably accurate and have residual errors following a Gaussian distribution. To accommodate changing noise levels and/or presence of inconsistent occlusions during the acquisition, the authors further propose a modified sparse regression (MSR) model to model the potentially large and sparse error built by ICP with a Laplacian prior. The authors evaluated the proposed method on both clinical point clouds acquired under consistent acquisition conditions and on point clouds with inconsistent occlusions. The authors quantitatively evaluated the reconstruction performance with respect to root-mean-squared-error, by comparing its reconstruction results against that from the variational method. Results: On clinical point clouds, both the SR and MSR models have achieved sub-millimeter reconstruction accuracy and reduced the reconstruction time by two orders of magnitude to a subsecond reconstruction time. On point clouds with inconsistent occlusions, the MSR model has demonstrated its advantage in achieving consistent and robust performance despite the introduced occlusions. Conclusions: The authors have developed a fast and robust surface reconstruction method on point clouds captured from a 3D surface photogrammetry system, with demonstrated sub-millimeter reconstruction accuracy and subsecond reconstruction time. It is suitable for real-time motion tracking in radiotherapy, with clear surface structures for better quantifications.« less

A robust real-time surface reconstruction method on point clouds captured from a 3D surface photogrammetry system.

PubMed

Liu, Wenyang; Cheung, Yam; Sawant, Amit; Ruan, Dan

2016-05-01

To develop a robust and real-time surface reconstruction method on point clouds captured from a 3D surface photogrammetry system. The authors have developed a robust and fast surface reconstruction method on point clouds acquired by the photogrammetry system, without explicitly solving the partial differential equation required by a typical variational approach. Taking advantage of the overcomplete nature of the acquired point clouds, their method solves and propagates a sparse linear relationship from the point cloud manifold to the surface manifold, assuming both manifolds share similar local geometry. With relatively consistent point cloud acquisitions, the authors propose a sparse regression (SR) model to directly approximate the target point cloud as a sparse linear combination from the training set, assuming that the point correspondences built by the iterative closest point (ICP) is reasonably accurate and have residual errors following a Gaussian distribution. To accommodate changing noise levels and/or presence of inconsistent occlusions during the acquisition, the authors further propose a modified sparse regression (MSR) model to model the potentially large and sparse error built by ICP with a Laplacian prior. The authors evaluated the proposed method on both clinical point clouds acquired under consistent acquisition conditions and on point clouds with inconsistent occlusions. The authors quantitatively evaluated the reconstruction performance with respect to root-mean-squared-error, by comparing its reconstruction results against that from the variational method. On clinical point clouds, both the SR and MSR models have achieved sub-millimeter reconstruction accuracy and reduced the reconstruction time by two orders of magnitude to a subsecond reconstruction time. On point clouds with inconsistent occlusions, the MSR model has demonstrated its advantage in achieving consistent and robust performance despite the introduced occlusions. The authors have developed a fast and robust surface reconstruction method on point clouds captured from a 3D surface photogrammetry system, with demonstrated sub-millimeter reconstruction accuracy and subsecond reconstruction time. It is suitable for real-time motion tracking in radiotherapy, with clear surface structures for better quantifications.

A robust real-time surface reconstruction method on point clouds captured from a 3D surface photogrammetry system

PubMed Central

Liu, Wenyang; Cheung, Yam; Sawant, Amit; Ruan, Dan

2016-01-01

Purpose: To develop a robust and real-time surface reconstruction method on point clouds captured from a 3D surface photogrammetry system. Methods: The authors have developed a robust and fast surface reconstruction method on point clouds acquired by the photogrammetry system, without explicitly solving the partial differential equation required by a typical variational approach. Taking advantage of the overcomplete nature of the acquired point clouds, their method solves and propagates a sparse linear relationship from the point cloud manifold to the surface manifold, assuming both manifolds share similar local geometry. With relatively consistent point cloud acquisitions, the authors propose a sparse regression (SR) model to directly approximate the target point cloud as a sparse linear combination from the training set, assuming that the point correspondences built by the iterative closest point (ICP) is reasonably accurate and have residual errors following a Gaussian distribution. To accommodate changing noise levels and/or presence of inconsistent occlusions during the acquisition, the authors further propose a modified sparse regression (MSR) model to model the potentially large and sparse error built by ICP with a Laplacian prior. The authors evaluated the proposed method on both clinical point clouds acquired under consistent acquisition conditions and on point clouds with inconsistent occlusions. The authors quantitatively evaluated the reconstruction performance with respect to root-mean-squared-error, by comparing its reconstruction results against that from the variational method. Results: On clinical point clouds, both the SR and MSR models have achieved sub-millimeter reconstruction accuracy and reduced the reconstruction time by two orders of magnitude to a subsecond reconstruction time. On point clouds with inconsistent occlusions, the MSR model has demonstrated its advantage in achieving consistent and robust performance despite the introduced occlusions. Conclusions: The authors have developed a fast and robust surface reconstruction method on point clouds captured from a 3D surface photogrammetry system, with demonstrated sub-millimeter reconstruction accuracy and subsecond reconstruction time. It is suitable for real-time motion tracking in radiotherapy, with clear surface structures for better quantifications. PMID:27147347

Gaussian Radial Basis Function for Efficient Computation of Forest Indirect Illumination

NASA Astrophysics Data System (ADS)

Abbas, Fayçal; Babahenini, Mohamed Chaouki

2018-06-01

Global illumination of natural scenes in real time like forests is one of the most complex problems to solve, because the multiple inter-reflections between the light and material of the objects composing the scene. The major problem that arises is the problem of visibility computation. In fact, the computing of visibility is carried out for all the set of leaves visible from the center of a given leaf, given the enormous number of leaves present in a tree, this computation performed for each leaf of the tree which also reduces performance. We describe a new approach that approximates visibility queries, which precede in two steps. The first step is to generate point cloud representing the foliage. We assume that the point cloud is composed of two classes (visible, not-visible) non-linearly separable. The second step is to perform a point cloud classification by applying the Gaussian radial basis function, which measures the similarity in term of distance between each leaf and a landmark leaf. It allows approximating the visibility requests to extract the leaves that will be used to calculate the amount of indirect illumination exchanged between neighbor leaves. Our approach allows efficiently treat the light exchanges in the scene of a forest, it allows a fast computation and produces images of good visual quality, all this takes advantage of the immense power of computation of the GPU.

A Comprehensive Automated 3D Approach for Building Extraction, Reconstruction, and Regularization from Airborne Laser Scanning Point Clouds

PubMed Central

Dorninger, Peter; Pfeifer, Norbert

2008-01-01

Three dimensional city models are necessary for supporting numerous management applications. For the determination of city models for visualization purposes, several standardized workflows do exist. They are either based on photogrammetry or on LiDAR or on a combination of both data acquisition techniques. However, the automated determination of reliable and highly accurate city models is still a challenging task, requiring a workflow comprising several processing steps. The most relevant are building detection, building outline generation, building modeling, and finally, building quality analysis. Commercial software tools for building modeling require, generally, a high degree of human interaction and most automated approaches described in literature stress the steps of such a workflow individually. In this article, we propose a comprehensive approach for automated determination of 3D city models from airborne acquired point cloud data. It is based on the assumption that individual buildings can be modeled properly by a composition of a set of planar faces. Hence, it is based on a reliable 3D segmentation algorithm, detecting planar faces in a point cloud. This segmentation is of crucial importance for the outline detection and for the modeling approach. We describe the theoretical background, the segmentation algorithm, the outline detection, and the modeling approach, and we present and discuss several actual projects. PMID:27873931

On-line lab-in-syringe cloud point extraction for the spectrophotometric determination of antimony.

PubMed

Frizzarin, Rejane M; Portugal, Lindomar A; Estela, José M; Rocha, Fábio R P; Cerdà, Victor

2016-02-01

Most of the procedures for antimony determination require time-consuming sample preparation (e.g. liquid-liquid extraction with organic solvents), which are harmful to the environment. Because of the high antimony toxicity, a rapid, sensitive and greener procedure for its determination becomes necessary. The goal of this work was to develop an analytical procedure exploiting for the first time the cloud point extraction on a lab-in-syringe flow system aiming at the spectrophotometric determination of antimony. The procedure was based on formation of an ion-pair between the antimony-iodide complex and H(+) followed by extraction with Triton X-114. The factorial design showed that the concentrations of ascorbic acid, H2SO4 and Triton X-114, as well as second and third order interactions were significant at the 95% confidence level. A Box-Behnken design was applied to obtain the response surfaces and to identify the critical values. System is robust at the 95% confidence level. A linear response was observed from 5 to 50 µg L(-1), described by the equation A=0.137+0.050C(Sb) (r=0.998). The detection limit (99.7% confidence level), the coefficient of variation (n=5; 15 µg L(-1)) and the sampling rate was estimated at 1.8 µg L(-1), 1.6% and 16 h(-1), respectively. The procedure allows quantification of antimony in the concentrations established by environmental legislation (6 µg L(-1)) and it was successfully applied to the determination of antimony in freshwater samples and antileishmanial drugs, yielding results in agreement with those obtained by HGFAAS at the 95% confidence level. Copyright © 2015 Elsevier B.V. All rights reserved.

Semi-Automated Approach for Mapping Urban Trees from Integrated Aerial LiDAR Point Cloud and Digital Imagery Datasets

NASA Astrophysics Data System (ADS)

Dogon-Yaro, M. A.; Kumar, P.; Rahman, A. Abdul; Buyuksalih, G.

2016-09-01

Mapping of trees plays an important role in modern urban spatial data management, as many benefits and applications inherit from this detailed up-to-date data sources. Timely and accurate acquisition of information on the condition of urban trees serves as a tool for decision makers to better appreciate urban ecosystems and their numerous values which are critical to building up strategies for sustainable development. The conventional techniques used for extracting trees include ground surveying and interpretation of the aerial photography. However, these techniques are associated with some constraints, such as labour intensive field work and a lot of financial requirement which can be overcome by means of integrated LiDAR and digital image datasets. Compared to predominant studies on trees extraction mainly in purely forested areas, this study concentrates on urban areas, which have a high structural complexity with a multitude of different objects. This paper presented a workflow about semi-automated approach for extracting urban trees from integrated processing of airborne based LiDAR point cloud and multispectral digital image datasets over Istanbul city of Turkey. The paper reveals that the integrated datasets is a suitable technology and viable source of information for urban trees management. As a conclusion, therefore, the extracted information provides a snapshot about location, composition and extent of trees in the study area useful to city planners and other decision makers in order to understand how much canopy cover exists, identify new planting, removal, or reforestation opportunities and what locations have the greatest need or potential to maximize benefits of return on investment. It can also help track trends or changes to the urban trees over time and inform future management decisions.

Characterization of ice nucleating particles during continuous springtime measurements in Prudhoe Bay: an Arctic oilfield location

NASA Astrophysics Data System (ADS)

Creamean, J.; Spada, N. J.; Kirpes, R.; Pratt, K.

2017-12-01

Aerosols that serve as ice nucleating particles (INPs) have the potential to modulate cloud microphysical properties. INPs can thus subsequently impact cloud radiative forcing in addition to modification of precipitation formation processes. In regions such as the Arctic, aerosol-cloud interactions are severely understudied yet have significant implications for surface radiation reaching the sea ice and snow surfaces. Further, uncertainties in model representations of heterogeneous ice nucleation are a significant hindrance to simulating Arctic mixed-phase cloud processes. Characterizing a combination of aerosol chemical, physical, and ice nucleating properties is pertinent to evaluating of the role of aerosols in altering Arctic cloud microphysics. We present preliminary results from an aerosol sampling campaign called INPOP (Ice Nucleating Particles at Oliktok Point), which took place at a U.S. Department of Energy's Atmospheric Radiation Measurement (DOE ARM) facility on the North Slope of Alaska. Three time- and size-resolved aerosol samplers were deployed from 1 Mar to 31 May 2017 and were co-located with routine measurements of aerosol number, size, chemical, and radiative property measurements conducted by DOE ARM at their Aerosol Observing System (AOS). Offline analysis of samples collected at a daily time resolution included composition and morphology via single-particle analysis and drop freezing measurements for INP concentrations, while analysis of 12-hourly samples included mass, optical, and elemental composition. We deliberate the possible influences on the aerosol and INP population from the Prudhoe Bay oilfield resource extraction and daily operations in addition to what may be local background or long-range transported aerosol. To our knowledge our results represent some of the first INP characterization measurements in an Arctic oilfield location and can be used as a benchmark for future INP characterization studies in Arctic locations impacted by local resource extraction pollution. Ultimately, these results can be used to evaluate the impacts of oil exploration activities on Arctic cloud aerosol composition and possible linkages to Arctic cloud ice formation.

Immunization with recombinant bivalent chimera r-Cpae confers protection against alpha toxin and enterotoxin of Clostridium perfringens type A in murine model.

PubMed

Shreya, Das; Uppalapati, Siva R; Kingston, Joseph J; Sripathy, Murali H; Batra, Harsh V

2015-05-01

Clostridium perfringens type A, an anaerobic pathogen is the most potent cause of soft tissue infections like gas gangrene and enteric diseases like food poisoning and enteritis. The disease manifestations are mediated via two important exotoxins, viz. myonecrotic alpha toxin (αC) and enterotoxin (CPE). In the present study, we synthesized a bivalent chimeric protein r-Cpae comprising C-terminal binding regions of αC and CPE using structural vaccinology rationale and assessed its protective efficacy against both alpha toxin (αC) and enterotoxin (CPE) respectively, in murine model. Active immunization of mice with r-Cpae generated high circulating serum IgG (systemic), significantly increased intestinal mucosal s-IgA antibody titres and resulted in substantial protection to the immunized animals (100% and 75% survival) with reduced tissue morbidity when administered with 5×LD(100) doses of αC (intramuscular) and CPE (intra-gastric gavage) respectively. Mouse RBCs and Caco-2 cells incubated with a mixture of anti-r-Cpae antibodies and αC and CPE respectively, illustrated significantly higher protection against the respective toxins. Passive immunization of mice with a similar mixture resulted in 91-100% survival at the end of the 15 days observation period while mice immunized with a concoction of sham sera and respective toxins died within 2-3 days. This work demonstrates the efficacy of the rationally designed r-Cpae chimeric protein as a potential sub unit vaccine candidate against αC and CPE of C. perfringens type A toxemia. Copyright © 2015 Elsevier Ltd. All rights reserved.

Surveillance of carbapenemase-producing Enterobacteriaceae in the Indian Ocean Region between January 2010 and December 2015.

PubMed

Holman, A M; Allyn, J; Miltgen, G; Lugagne, N; Traversier, N; Picot, S; Lignereux, A; Oudin, C; Belmonte, O; Allou, N

2017-09-01

The aim of this study was to trace the emergence of carbapenemase-producing Enterobacteriaceae (CPE) on Reunion Island, a French overseas territory well suited for the surveillance of CPE emergence in patients from the entire Indian Ocean Region. This retrospective multicenter study was conducted on Reunion Island between 2010 and 2015. A total of 43 CPEs were isolated during the course of the study, in 36 patients (50% in the last year alone). Among these patients, 21 had a link with a foreign country (58%), mainly Mauritius (47.6%). Over the same period, CPEs were isolated from 13 of 1735 (0.7%) repatriated patients to Reunion Island from another country of the Indian Ocean Region. The incidence of isolation of CPEs in the repatriated patients treated in Mauritius was higher (9.2%) than in patients treated in Madagascar or the Comoros Islands (<1%, P<0.001). The most commonly isolated microorganism was Klebsiella pneumoniae (39.5%). The most frequently identified carbapenemase was NDM-1 (81.4%); 100% and 56% of the NDM-1 strains were susceptible to tigecycline and colistin, respectively. In-hospital mortality rate was higher in patients presenting with CPE infection than in patients without CPE infection (75% vs. 25%, P=0.04). As elsewhere in the world, the number of CPE cases on Reunion Island is on the rise. Most cases involve patients from Mauritius, which justifies screening and isolating CPE in patients from that country. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Individual white matter fractional anisotropy analysis on patients with MRI negative partial epilepsy.

PubMed

Duning, Thomas; Kellinghaus, Christoph; Mohammadi, Siawoosh; Schiffbauer, Hagen; Keller, Simon; Ringelstein, E Bernd; Knecht, Stefan; Deppe, Michael

2010-02-01

Conventional structural MRI fails to identify a cerebral lesion in 25% of patients with cryptogenic partial epilepsy (CPE). Diffusion tensor imaging is an MRI technique sensitive to microstructural abnormalities of cerebral white matter (WM) by quantification of fractional anisotropy (FA). The objectives of the present study were to identify focal FA abnormalities in patients with CPE who were deemed MRI negative during routine presurgical evaluation. Diffusion tensor imaging at 3 T was performed in 12 patients with CPE and normal conventional MRI and in 67 age matched healthy volunteers. WM integrity was compared between groups on the basis of automated voxel-wise statistics of FA maps using an analysis of covariance. Volumetric measurements from high resolution T1-weighted images were also performed. Significant FA reductions in WM regions encompassing diffuse areas of the brain were observed when all patients as a group were compared with controls. On an individual basis, voxel based analyses revealed widespread symmetrical FA reduction in CPE patients. Furthermore, asymmetrical temporal lobe FA reduction was consistently ipsilateral to the electroclinical focus. No significant correlations were found between FA alterations and clinical data. There were no differences in brain volumes of CPE patients compared with controls. Despite normal conventional MRI, WM integrity abnormalities in CPE patients extend far beyond the epileptogenic zone. Given that unilateral temporal lobe FA abnormalities were consistently observed ipsilateral to the seizure focus, analysis of temporal FA may provide an informative in vivo investigation into the localisation of the epileptogenic zone in MRI negative patients.

Enhanced performance of P(VDF-HFP)-based composite polymer electrolytes doped with organic-inorganic hybrid particles PMMA-ZrO2 for lithium ion batteries

NASA Astrophysics Data System (ADS)

Xiao, Wei; Wang, Zhiyan; Zhang, Yan; Fang, Rui; Yuan, Zun; Miao, Chang; Yan, Xuemin; Jiang, Yu

2018-04-01

To improve the ionic conductivity as well as enhance the mechanical strength of the gel polymer electrolyte, poly(vinylidene fluoride-hexafluoroprolene) (P(VDF-HFP))-based composite polymer electrolyte (CPE) membranes doped with the organic-inorganic hybrid particles poly(methyl methacrylate) -ZrO2 (PMMA-ZrO2) are prepared by phase inversion method, in which PMMA is successfully grafted onto the surface of the homemade nano-ZrO2 particles via in situ polymerization confirmed by FT-IR. XRD and DSC patterns show adding PMMA-ZrO2 particles into P(VDF-HFP) can significantly decrease the crystallinity of the CPE membrane. The CPE membrane doped with 5 wt % PMMA-ZrO2 particles can not only present a homogeneous surface with abundant interconnected micro-pores, but maintain its initial shape after thermal exposure at 160 °C for 1 h, in which the ionic conductivity and lithium ion transference number at room temperature can reach to 3.59 × 10-3 S cm-1 and 0.41, respectively. The fitting results of the EIS plots indicate the doped PMMA-ZrO2 particles can significantly lower the interface resistance and promote lithium ions diffusion rate. The Li/CPE-sPZ/LiCoO2 and Li/CPE-sPZ/Graphite coin cells can deliver excellent rate and cycling performance. Those results suggest the P(VDF-HFP)-based CPE doped with 5 wt % PMMA-ZrO2 particles can become an exciting potential candidate as polymer electrolyte for the lithium ion battery.

Automatic Registration of TLS-TLS and TLS-MLS Point Clouds Using a Genetic Algorithm

PubMed Central

Yan, Li; Xie, Hong; Chen, Changjun

2017-01-01

Registration of point clouds is a fundamental issue in Light Detection and Ranging (LiDAR) remote sensing because point clouds scanned from multiple scan stations or by different platforms need to be transformed to a uniform coordinate reference frame. This paper proposes an efficient registration method based on genetic algorithm (GA) for automatic alignment of two terrestrial LiDAR scanning (TLS) point clouds (TLS-TLS point clouds) and alignment between TLS and mobile LiDAR scanning (MLS) point clouds (TLS-MLS point clouds). The scanning station position acquired by the TLS built-in GPS and the quasi-horizontal orientation of the LiDAR sensor in data acquisition are used as constraints to narrow the search space in GA. A new fitness function to evaluate the solutions for GA, named as Normalized Sum of Matching Scores, is proposed for accurate registration. Our method is divided into five steps: selection of matching points, initialization of population, transformation of matching points, calculation of fitness values, and genetic operation. The method is verified using a TLS-TLS data set and a TLS-MLS data set. The experimental results indicate that the RMSE of registration of TLS-TLS point clouds is 3~5 mm, and that of TLS-MLS point clouds is 2~4 cm. The registration integrating the existing well-known ICP with GA is further proposed to accelerate the optimization and its optimizing time decreases by about 50%. PMID:28850100

Automatic Registration of TLS-TLS and TLS-MLS Point Clouds Using a Genetic Algorithm.

PubMed

Yan, Li; Tan, Junxiang; Liu, Hua; Xie, Hong; Chen, Changjun

2017-08-29

Registration of point clouds is a fundamental issue in Light Detection and Ranging (LiDAR) remote sensing because point clouds scanned from multiple scan stations or by different platforms need to be transformed to a uniform coordinate reference frame. This paper proposes an efficient registration method based on genetic algorithm (GA) for automatic alignment of two terrestrial LiDAR scanning (TLS) point clouds (TLS-TLS point clouds) and alignment between TLS and mobile LiDAR scanning (MLS) point clouds (TLS-MLS point clouds). The scanning station position acquired by the TLS built-in GPS and the quasi-horizontal orientation of the LiDAR sensor in data acquisition are used as constraints to narrow the search space in GA. A new fitness function to evaluate the solutions for GA, named as Normalized Sum of Matching Scores, is proposed for accurate registration. Our method is divided into five steps: selection of matching points, initialization of population, transformation of matching points, calculation of fitness values, and genetic operation. The method is verified using a TLS-TLS data set and a TLS-MLS data set. The experimental results indicate that the RMSE of registration of TLS-TLS point clouds is 3~5 mm, and that of TLS-MLS point clouds is 2~4 cm. The registration integrating the existing well-known ICP with GA is further proposed to accelerate the optimization and its optimizing time decreases by about 50%.

Continuous section extraction and over-underbreak detection of tunnel based on 3D laser technology and image analysis

NASA Astrophysics Data System (ADS)

Wang, Weixing; Wang, Zhiwei; Han, Ya; Li, Shuang; Zhang, Xin

2015-03-01

In order to ensure safety, long term stability and quality control in modern tunneling operations, the acquisition of geotechnical information about encountered rock conditions and detailed installed support information is required. The limited space and time in an operational tunnel environment make the acquiring data challenging. The laser scanning in a tunneling environment, however, shows a great potential. The surveying and mapping of tunnels are crucial for the optimal use after construction and in routine inspections. Most of these applications focus on the geometric information of the tunnels extracted from the laser scanning data. There are two kinds of applications widely discussed: deformation measurement and feature extraction. The traditional deformation measurement in an underground environment is performed with a series of permanent control points installed around the profile of an excavation, which is unsuitable for a global consideration of the investigated area. Using laser scanning for deformation analysis provides many benefits as compared to traditional monitoring techniques. The change in profile is able to be fully characterized and the areas of the anomalous movement can easily be separated from overall trends due to the high density of the point cloud data. Furthermore, monitoring with a laser scanner does not require the permanent installation of control points, therefore the monitoring can be completed more quickly after excavation, and the scanning is non-contact, hence, no damage is done during the installation of temporary control points. The main drawback of using the laser scanning for deformation monitoring is that the point accuracy of the original data is generally the same magnitude as the smallest level of deformations that are to be measured. To overcome this, statistical techniques and three dimensional image processing techniques for the point clouds must be developed. For safely, effectively and easily control the problem of Over Underbreak detection of road and solve the problemof the roadway data collection difficulties, this paper presents a new method of continuous section extraction and Over Underbreak detection of road based on 3D laser scanning technology and image processing, the method is divided into the following three steps: based on Canny edge detection, local axis fitting, continuous extraction section and Over Underbreak detection of section. First, after Canny edge detection, take the least-squares curve fitting method to achieve partial fitting in axis. Then adjust the attitude of local roadway that makes the axis of the roadway be consistent with the direction of the extraction reference, and extract section along the reference direction. Finally, we compare the actual cross-sectional view and the cross-sectional design to complete Overbreak detected. Experimental results show that the proposed method have a great advantage in computing costs and ensure cross-section orthogonal intercept terms compared with traditional detection methods.

Automatic Classification of Trees from Laser Scanning Point Clouds

NASA Astrophysics Data System (ADS)

Sirmacek, B.; Lindenbergh, R.

2015-08-01

Development of laser scanning technologies has promoted tree monitoring studies to a new level, as the laser scanning point clouds enable accurate 3D measurements in a fast and environmental friendly manner. In this paper, we introduce a probability matrix computation based algorithm for automatically classifying laser scanning point clouds into 'tree' and 'non-tree' classes. Our method uses the 3D coordinates of the laser scanning points as input and generates a new point cloud which holds a label for each point indicating if it belongs to the 'tree' or 'non-tree' class. To do so, a grid surface is assigned to the lowest height level of the point cloud. The grids are filled with probability values which are calculated by checking the point density above the grid. Since the tree trunk locations appear with very high values in the probability matrix, selecting the local maxima of the grid surface help to detect the tree trunks. Further points are assigned to tree trunks if they appear in the close proximity of trunks. Since heavy mathematical computations (such as point cloud organization, detailed shape 3D detection methods, graph network generation) are not required, the proposed algorithm works very fast compared to the existing methods. The tree classification results are found reliable even on point clouds of cities containing many different objects. As the most significant weakness, false detection of light poles, traffic signs and other objects close to trees cannot be prevented. Nevertheless, the experimental results on mobile and airborne laser scanning point clouds indicate the possible usage of the algorithm as an important step for tree growth observation, tree counting and similar applications. While the laser scanning point cloud is giving opportunity to classify even very small trees, accuracy of the results is reduced in the low point density areas further away than the scanning location. These advantages and disadvantages of two laser scanning point cloud sources are discussed in detail.

Visual Data Analysis for Satellites

NASA Technical Reports Server (NTRS)

Lau, Yee; Bhate, Sachin; Fitzpatrick, Patrick

2008-01-01

The Visual Data Analysis Package is a collection of programs and scripts that facilitate visual analysis of data available from NASA and NOAA satellites, as well as dropsonde, buoy, and conventional in-situ observations. The package features utilities for data extraction, data quality control, statistical analysis, and data visualization. The Hierarchical Data Format (HDF) satellite data extraction routines from NASA's Jet Propulsion Laboratory were customized for specific spatial coverage and file input/output. Statistical analysis includes the calculation of the relative error, the absolute error, and the root mean square error. Other capabilities include curve fitting through the data points to fill in missing data points between satellite passes or where clouds obscure satellite data. For data visualization, the software provides customizable Generic Mapping Tool (GMT) scripts to generate difference maps, scatter plots, line plots, vector plots, histograms, timeseries, and color fill images.

Power and Thermal Technologies for Air and Space. Delivery Order 0003: Development of High-Performance Solid Oxide Fuel Cell (SOFC) Technology for Remote Base Applications

DTIC Science & Technology

2007-08-01

In recent years, however, anode supported electrode conformations with thin film electrolytes have been heavily explored because they are capable ...further clarify relationship between interlayer morphology and cell performance will be a subject of a future study. Figure 2. SEM Images of SOFC...CPE B1B CPE B2B RB4B CPE B3B R1 R2 10 and R3, which also exhibited a constant slope over the test range, averaged 0.1 +/- 0.02 and 0.9 +/- 0.01

A scalable and multi-purpose point cloud server (PCS) for easier and faster point cloud data management and processing

NASA Astrophysics Data System (ADS)

Cura, Rémi; Perret, Julien; Paparoditis, Nicolas

2017-05-01

In addition to more traditional geographical data such as images (rasters) and vectors, point cloud data are becoming increasingly available. Such data are appreciated for their precision and true three-Dimensional (3D) nature. However, managing point clouds can be difficult due to scaling problems and specificities of this data type. Several methods exist but are usually fairly specialised and solve only one aspect of the management problem. In this work, we propose a comprehensive and efficient point cloud management system based on a database server that works on groups of points (patches) rather than individual points. This system is specifically designed to cover the basic needs of point cloud users: fast loading, compressed storage, powerful patch and point filtering, easy data access and exporting, and integrated processing. Moreover, the proposed system fully integrates metadata (like sensor position) and can conjointly use point clouds with other geospatial data, such as images, vectors, topology and other point clouds. Point cloud (parallel) processing can be done in-base with fast prototyping capabilities. Lastly, the system is built on open source technologies; therefore it can be easily extended and customised. We test the proposed system with several billion points obtained from Lidar (aerial and terrestrial) and stereo-vision. We demonstrate loading speeds in the ˜50 million pts/h per process range, transparent-for-user and greater than 2 to 4:1 compression ratio, patch filtering in the 0.1 to 1 s range, and output in the 0.1 million pts/s per process range, along with classical processing methods, such as object detection.

Fast calculation method of computer-generated hologram using a depth camera with point cloud gridding

NASA Astrophysics Data System (ADS)

Zhao, Yu; Shi, Chen-Xiao; Kwon, Ki-Chul; Piao, Yan-Ling; Piao, Mei-Lan; Kim, Nam

2018-03-01

We propose a fast calculation method for a computer-generated hologram (CGH) of real objects that uses a point cloud gridding method. The depth information of the scene is acquired using a depth camera and the point cloud model is reconstructed virtually. Because each point of the point cloud is distributed precisely to the exact coordinates of each layer, each point of the point cloud can be classified into grids according to its depth. A diffraction calculation is performed on the grids using a fast Fourier transform (FFT) to obtain a CGH. The computational complexity is reduced dramatically in comparison with conventional methods. The feasibility of the proposed method was confirmed by numerical and optical experiments.

Automatic building extraction from LiDAR data fusion of point and grid-based features

NASA Astrophysics Data System (ADS)

Du, Shouji; Zhang, Yunsheng; Zou, Zhengrong; Xu, Shenghua; He, Xue; Chen, Siyang

2017-08-01

This paper proposes a method for extracting buildings from LiDAR point cloud data by combining point-based and grid-based features. To accurately discriminate buildings from vegetation, a point feature based on the variance of normal vectors is proposed. For a robust building extraction, a graph cuts algorithm is employed to combine the used features and consider the neighbor contexture information. As grid feature computing and a graph cuts algorithm are performed on a grid structure, a feature-retained DSM interpolation method is proposed in this paper. The proposed method is validated by the benchmark ISPRS Test Project on Urban Classification and 3D Building Reconstruction and compared to the state-art-of-the methods. The evaluation shows that the proposed method can obtain a promising result both at area-level and at object-level. The method is further applied to the entire ISPRS dataset and to a real dataset of the Wuhan City. The results show a completeness of 94.9% and a correctness of 92.2% at the per-area level for the former dataset and a completeness of 94.4% and a correctness of 95.8% for the latter one. The proposed method has a good potential for large-size LiDAR data.

Genotypic and phenotypic characterization of Clostridium perfringens isolates from Darmbrand cases in post-World War II Germany.

PubMed

Ma, Menglin; Li, Jihong; McClane, Bruce A

2012-12-01

Clostridium perfringens type C strains are the only non-type-A isolates that cause human disease. They are responsible for enteritis necroticans, which was termed Darmbrand when occurring in post-World War II Germany. Darmbrand strains were initially classified as type F because of their exceptional heat resistance but later identified as type C strains. Since only limited information exists regarding Darmbrand strains, this study genetically and phenotypically characterized seven 1940s era Darmbrand-associated strains. Results obtained indicated the following. (i) Five of these Darmbrand isolates belong to type C, carry beta-toxin (cpb) and enterotoxin (cpe) genes on large plasmids, and express both beta-toxin and enterotoxin. The other two isolates are cpe-negative type A. (ii) All seven isolates produce highly heat-resistant spores with D(100) values (the time that a culture must be kept at 100°C to reduce its viability by 90%) of 7 to 40 min. (iii) All of the isolates surveyed produce the same variant small acid-soluble protein 4 (Ssp4) made by type A food poisoning isolates with a chromosomal cpe gene that also produce extremely heat-resistant spores. (iv) The Darmbrand isolates share a genetic background with type A chromosomal-cpe-bearing isolates. Finally, it was shown that both the cpe and cpb genes can be mobilized in Darmbrand isolates. These results suggest that C. perfringens type A and C strains that cause human food-borne illness share a spore heat resistance mechanism that likely favors their survival in temperature-abused food. They also suggest possible evolutionary relationships between Darmbrand strains and type A strains carrying a chromosomal cpe gene.

Decision Support Tool for Early Differential Diagnosis of Acute Lung Injury and Cardiogenic Pulmonary Edema in Medical Critically Ill Patients

PubMed Central

Shahjehan, Khurram; Li, Guangxi; Dhokarh, Rajanigandha; Kashyap, Rahul; Janish, Christopher; Alsara, Anas; Jaffe, Allan S.; Hubmayr, Rolf D.; Gajic, Ognjen

2012-01-01

Background: At the onset of acute hypoxic respiratory failure, critically ill patients with acute lung injury (ALI) may be difficult to distinguish from those with cardiogenic pulmonary edema (CPE). No single clinical parameter provides satisfying prediction. We hypothesized that a combination of those will facilitate early differential diagnosis. Methods: In a population-based retrospective development cohort, validated electronic surveillance identified critically ill adult patients with acute pulmonary edema. Recursive partitioning and logistic regression were used to develop a decision support tool based on routine clinical information to differentiate ALI from CPE. Performance of the score was validated in an independent cohort of referral patients. Blinded post hoc expert review served as gold standard. Results: Of 332 patients in a development cohort, expert reviewers (κ, 0.86) classified 156 as having ALI and 176 as having CPE. The validation cohort had 161 patients (ALI = 113, CPE = 48). The score was based on risk factors for ALI and CPE, age, alcohol abuse, chemotherapy, and peripheral oxygen saturation/Fio2 ratio. It demonstrated good discrimination (area under curve [AUC] = 0.81; 95% CI, 0.77-0.86) and calibration (Hosmer-Lemeshow [HL] P = .16). Similar performance was obtained in the validation cohort (AUC = 0.80; 95% CI, 0.72-0.88; HL P = .13). Conclusions: A simple decision support tool accurately classifies acute pulmonary edema, reserving advanced testing for a subset of patients in whom satisfying prediction cannot be made. This novel tool may facilitate early inclusion of patients with ALI and CPE into research studies as well as improve and rationalize clinical management and resource use. PMID:22030803

Development of an algorithm for phenotypic screening of carbapenemase-producing Enterobacteriaceae in the routine laboratory.

PubMed

Robert, Jérôme; Pantel, Alix; Merens, Audrey; Meiller, Elodie; Lavigne, Jean-Philippe; Nicolas-Chanoine, Marie-Hélène

2017-01-17

Carbapenemase-producing Enterobacteriaceae (CPE) are difficult to identify among carbapenem non-susceptible Enterobacteriaceae (NSE). We designed phenotypic strategies giving priority to high sensitivity for screening putative CPE before further testing. Presence of carbapenemase-encoding genes in ertapenem NSE (MIC > 0.5 mg/l) consecutively isolated in 80 French laboratories between November 2011 and April 2012 was determined by the Check-MDR-CT103 array method. Using the Mueller-Hinton (MH) disk diffusion method, clinical diameter breakpoints of carbapenems other than ertapenem, piperazicillin+tazobactam, ticarcillin+clavulanate and cefepime as well as diameter cut-offs for these antibiotics and temocillin were evaluated alone or combined to determine their performances (sensitivity, specificity, positive and negative likelihood ratios) for identifying putative CPE among these ertapenem-NSE isolates. To increase the screening specificity, these antibiotics were also tested on cloxacillin-containing MH when carbapenem NSE isolates belonged to species producing chromosomal cephalosporinase (AmpC) but Escherichia coli. Out of the 349 ertapenem NSE, 52 (14.9%) were CPE, including 39 producing OXA-48 group carbapenemase, eight KPC and five MBL. A screening strategy based on the following diameter cut offs, ticarcillin+clavulanate <15 mm, temocillin <15 mm, meropenem or imipenem <22 mm, and cefepime <26 mm, showed 100% sensitivity and 68.1% specificity with the better likelihood ratios combination. The specificity increased when a diameter cut-off <32 mm for imipenem (76.1%) or meropenem (78.8%) further tested on cloxacillin-containing MH was added to the previous strategy for AmpC-producing isolates. The proposed strategies that allowed for increasing the likelihood of CPE among ertapenem-NSE isolates should be considered as a surrogate for carbapenemase production before further CPE confirmatory testing.

Prevalence and Molecular Characteristics of Carbapenemase-Producing Enterobacteriaceae From Five Hospitals in Korea.

PubMed

Jeong, Seok Hoon; Kim, Han Sung; Kim, Jae Seok; Shin, Dong Hoon; Kim, Hyun Soo; Park, Min Jeong; Shin, Saeam; Hong, Jun Sung; Lee, Seung Soon; Song, Wonkeun

2016-11-01

The emergence of carbapenemase-producing Enterobacteriaceae (CPE) represents a major clinical problem because these bacteria are resistant to most antibiotics. CPE remain relatively uncommon in Korea. We report the prevalence, clinical characteristics, and molecular epidemiology of CPE isolates collected from five university hospitals in Korea. Between January and December 2015, 393 non-duplicated isolates that were nonsusceptible to ertapenem were analyzed. Production of carbapenemase, extended-spectrum β-lactamase, and AmpC β-lactamase was determined by genotypic tests. Antimicrobial susceptibility profiles were determined by using an Etest. Clonality of Klebsiella pneumoniae carbapenemase (KPC)-2-producing and oxacillinase (OXA)-232-producing Klebsiella pneumoniae isolates was determined by pulsed-field gel electrophoresis (PFGE). Of the 393 isolates tested, 79 (20.1%) were CPE. Of these 79 isolates, 47 (59.5%) harbored the bla(OXA-232) gene while the remaining isolates carried genes bla(KPC-2) (n=27), bla(IMP-1) (n=4), and bla(NDM-1) (n=1). Among the 24 KPC-2 K. pneumoniae isolates from hospital B, 100% were resistant to carbapenems, 8% to colistin, and 0% to tigecycline. Among the 45 OXA-232 K. pneumoniae at hospital C, 95% were resistant to ertapenem, 68% to imipenem, 95% to meropenem, 10% to colistin, and 24% to tigecycline. PFGE analysis revealed a unique pattern for KPC-2 K. pneumoniae and identified 30 isolates belonging to the dominant pulsotypes (PT)1 and PT2 among 41 OXA-232 K. pneumoniae isolates. CPE strains are present in Korea, with the majority of K. pneumoniae isolates producing OXA-232 and KPC-2. The prevalence and predominant genotypes of CPE show hospital-specific differences.

A cost-effective laser scanning method for mapping stream channel geometry and roughness

NASA Astrophysics Data System (ADS)

Lam, Norris; Nathanson, Marcus; Lundgren, Niclas; Rehnström, Robin; Lyon, Steve

2015-04-01

In this pilot project, we combine an Arduino Uno and SICK LMS111 outdoor laser ranging camera to acquire high resolution topographic area scans for a stream channel. The microprocessor and imaging system was installed in a custom gondola and suspended from a wire cable system. To demonstrate the systems capabilities for capturing stream channel topography, a small stream (< 2m wide) in the Krycklan Catchment Study was temporarily diverted and scanned. Area scans along the stream channel resulted in a point spacing of 4mm and a point cloud density of 5600 points/m2 for the 5m by 2m area. A grain size distribution of the streambed material was extracted from the point cloud using a moving window, local maxima search algorithm. The median, 84th and 90th percentiles (common metrics to describe channel roughness) of this distribution were found to be within the range of measured values while the largest modelled element was approximately 35% smaller than its measured counterpart. The laser scanning system captured grain sizes between 30mm and 255mm (coarse gravel/pebbles and boulders based on the Wentworth (1922) scale). This demonstrates that our system was capable of resolving both large-scale geometry (e.g. bed slope and stream channel width) and small-scale channel roughness elements (e.g. coarse gravel/pebbles and boulders) for the study area. We further show that the point cloud resolution is suitable for estimating ecohydraulic parameters such as Manning's n and hydraulic radius. Although more work is needed to fine-tune our system's design, these preliminary results are encouraging, specifically for those with a limited operational budget.

Processing Uav and LIDAR Point Clouds in Grass GIS

NASA Astrophysics Data System (ADS)

Petras, V.; Petrasova, A.; Jeziorska, J.; Mitasova, H.

2016-06-01

Today's methods of acquiring Earth surface data, namely lidar and unmanned aerial vehicle (UAV) imagery, non-selectively collect or generate large amounts of points. Point clouds from different sources vary in their properties such as number of returns, density, or quality. We present a set of tools with applications for different types of points clouds obtained by a lidar scanner, structure from motion technique (SfM), and a low-cost 3D scanner. To take advantage of the vertical structure of multiple return lidar point clouds, we demonstrate tools to process them using 3D raster techniques which allow, for example, the development of custom vegetation classification methods. Dense point clouds obtained from UAV imagery, often containing redundant points, can be decimated using various techniques before further processing. We implemented and compared several decimation techniques in regard to their performance and the final digital surface model (DSM). Finally, we will describe the processing of a point cloud from a low-cost 3D scanner, namely Microsoft Kinect, and its application for interaction with physical models. All the presented tools are open source and integrated in GRASS GIS, a multi-purpose open source GIS with remote sensing capabilities. The tools integrate with other open source projects, specifically Point Data Abstraction Library (PDAL), Point Cloud Library (PCL), and OpenKinect libfreenect2 library to benefit from the open source point cloud ecosystem. The implementation in GRASS GIS ensures long term maintenance and reproducibility by the scientific community but also by the original authors themselves.

Filtering Airborne LIDAR Data by AN Improved Morphological Method Based on Multi-Gradient Analysis

NASA Astrophysics Data System (ADS)

Li, Y.

2013-05-01

The technology of airborne Light Detection And Ranging (LIDAR) is capable of acquiring dense and accurate 3D geospatial data. Although many related efforts have been made by a lot of researchers in the last few years, LIDAR data filtering is still a challenging task, especially for area with high relief or hybrid geographic features. In order to address the bare-ground extraction from LIDAR point clouds of complex landscapes, a novel morphological filtering algorithm is proposed based on multi-gradient analysis in terms of the characteristic of LIDAR data distribution in this paper. Firstly, point clouds are organized by an index mesh. Then, the multigradient of each point is calculated using the morphological method. And, objects are removed gradually by choosing some points to carry on an improved opening operation constrained by multi-gradient iteratively. 15 sample data provided by ISPRS Working Group III/3 are employed to test the filtering algorithm proposed. These sample data include those environments that may lead to filtering difficulty. Experimental results show that filtering algorithm proposed by this paper is of high adaptability to various scenes including urban and rural areas. Omission error, commission error and total error can be simultaneously controlled in a relatively small interval. This algorithm can efficiently remove object points while preserves ground points to a great degree.

Section-Based Tree Species Identification Using Airborne LIDAR Point Cloud

NASA Astrophysics Data System (ADS)

Yao, C.; Zhang, X.; Liu, H.

2017-09-01

The application of LiDAR data in forestry initially focused on mapping forest community, particularly and primarily intended for largescale forest management and planning. Then with the smaller footprint and higher sampling density LiDAR data available, detecting individual tree overstory, estimating crowns parameters and identifying tree species are demonstrated practicable. This paper proposes a section-based protocol of tree species identification taking palm tree as an example. Section-based method is to detect objects through certain profile among different direction, basically along X-axis or Y-axis. And this method improve the utilization of spatial information to generate accurate results. Firstly, separate the tree points from manmade-object points by decision-tree-based rules, and create Crown Height Mode (CHM) by subtracting the Digital Terrain Model (DTM) from the digital surface model (DSM). Then calculate and extract key points to locate individual trees, thus estimate specific tree parameters related to species information, such as crown height, crown radius, and cross point etc. Finally, with parameters we are able to identify certain tree species. Comparing to species information measured on ground, the portion correctly identified trees on all plots could reach up to 90.65 %. The identification result in this research demonstrate the ability to distinguish palm tree using LiDAR point cloud. Furthermore, with more prior knowledge, section-based method enable the process to classify trees into different classes.

a Global Registration Algorithm of the Single-Closed Ring Multi-Stations Point Cloud

NASA Astrophysics Data System (ADS)

Yang, R.; Pan, L.; Xiang, Z.; Zeng, H.

2018-04-01

Aimed at the global registration problem of the single-closed ring multi-stations point cloud, a formula in order to calculate the error of rotation matrix was constructed according to the definition of error. The global registration algorithm of multi-station point cloud was derived to minimize the error of rotation matrix. And fast-computing formulas of transformation matrix with whose implementation steps and simulation experiment scheme was given. Compared three different processing schemes of multi-station point cloud, the experimental results showed that the effectiveness of the new global registration method was verified, and it could effectively complete the global registration of point cloud.

Application of graphene oxide/lanthanum-modified carbon paste electrode for the selective determination of dopamine

NASA Astrophysics Data System (ADS)

Ye, Fengying; Feng, Chenqi; Fu, Ning; Wu, Huihui; Jiang, Jibo; Han, Sheng

2015-12-01

A home-made carbon paste electrode (CPE) was reformed by graphene oxide (GO)/lanthanum (La) complexes, and a modified electrode, called GO-La/CPE, was fabricated for the selective determination of dopamine (DA) by cyclic voltammetry (CV) and differential pulse voltammetry (DPV). Several factors affecting the electrocatalytic performance of the modified sensor were investigated. Owning to the combination of GO and La ions, the GO-La/CPE sensor exhibited large surface area, well selectivity, good repeatability and stability in the oxidation reaction of DA. At optimal conditions, the response of the GO-La/CPE electrode for determining DA was linear in the region of 0.01-0.1 μM and 0.1-400.0 μM. The limit of detection was down to 0.32 nM (S/N = 3). In addition, this modified electrode was successfully applied to the detection of DA in real urine and serum samples by using standard adding method, showing its promising application in the electroanalysis of real samples.

Performance improvement of coherent free-space optical communication with quadrature phase-shift keying modulation using digital phase estimation.

PubMed

Li, Xueliang; Geng, Tianwen; Ma, Shuang; Li, Yatian; Gao, Shijie; Wu, Zhiyong

2017-06-01

The performance of coherent free-space optical (CFSO) communication with phase modulation is limited by both phase fluctuations and intensity scintillations induced by atmospheric turbulence. To improve the system performance, one effective way is to use digital phase estimation. In this paper, a CFSO communication system with quadrature phase-shift keying modulation is studied. With consideration of the effects of log-normal amplitude fluctuations and Gauss phase fluctuations, a two-stage Mth power carrier phase estimation (CPE) scheme is proposed. The simulation results show that the phase noise can be suppressed greatly by this scheme, and the system symbol error rate performance with the two-stage Mth power CPE can be three orders lower than that of the single-stage Mth power CPE. Therefore, the two-stage CPE we proposed can contribute to the performance improvements of the CFSO communication system and has determinate guidance sense to its actual application.

A sensitive amplified sensor based on improved carbon paste electrode with 1-methyl-3-octylimidazolium tetrafluoroborate and ZnO/CNTs nanocomposite for differential pulse voltammetric analysis of raloxifene

NASA Astrophysics Data System (ADS)

Cheraghi, Somaye; Taher, Mohammad Ali; Karimi-Maleh, Hassan

2017-10-01

In this work, we suggested a carbon paste electrode improved with 1-methyl-3-octylimidazolium tetrafluoroborate (1-M-3-OITFB) and ZnO/CNTs nanocomposite (1-M-3-OITFB/ZnO/CNTs/CPE) for electrochemical determination of raloxifene (RXF) as a non-steroidal selective estrogen receptor regulator. The cyclic and differential pulse voltammetric methods were apply for investigation of RXF electrochemical response at a surface of 1-M-3-OITFB/ZnO/CNTs/CPE. Under the best experimental conditions, the 1-M-3-OITFB/ZnO/CNTs/CPE showed a wide linear dynamic range of 0.08 - 400.0 μM. We detected a detection limit of 0.04 μM for RXF analysis using differential pulse voltammetric method (DPV). The 1-M-3-OITFB/ZnO/CNTs/CPE showed high performance ability to RXF analysis in trace amounts on pharmaceutical and clinical preparations.

Generation of Ground Truth Datasets for the Analysis of 3d Point Clouds in Urban Scenes Acquired via Different Sensors

NASA Astrophysics Data System (ADS)

Xu, Y.; Sun, Z.; Boerner, R.; Koch, T.; Hoegner, L.; Stilla, U.

2018-04-01

In this work, we report a novel way of generating ground truth dataset for analyzing point cloud from different sensors and the validation of algorithms. Instead of directly labeling large amount of 3D points requiring time consuming manual work, a multi-resolution 3D voxel grid for the testing site is generated. Then, with the help of a set of basic labeled points from the reference dataset, we can generate a 3D labeled space of the entire testing site with different resolutions. Specifically, an octree-based voxel structure is applied to voxelize the annotated reference point cloud, by which all the points are organized by 3D grids of multi-resolutions. When automatically annotating the new testing point clouds, a voting based approach is adopted to the labeled points within multiple resolution voxels, in order to assign a semantic label to the 3D space represented by the voxel. Lastly, robust line- and plane-based fast registration methods are developed for aligning point clouds obtained via various sensors. Benefiting from the labeled 3D spatial information, we can easily create new annotated 3D point clouds of different sensors of the same scene directly by considering the corresponding labels of 3D space the points located, which would be convenient for the validation and evaluation of algorithms related to point cloud interpretation and semantic segmentation.

Preconcentration and Determination of Trace Vanadium(V) in Beverages by Combination of Ultrasound Assisted-cloud Point Extraction with Spectrophotometry.

PubMed

Kartal Temel, Nuket; Gürkan, Ramazan

2018-03-01

A novel ultrasound assisted-cloud point extraction method was developed for preconcentration and determination of V(V) in beverage samples. After complexation by pyrogallol in presence of safranin T at pH 6.0, V(V) ions as ternary complex are extracted into the micellar phase of Triton X-114. The complex was monitored at 533 nm by spectrophotometry. The matrix effect on the recovery of V(V) from the spiked samples at 50 μg L-1 was evaluated. In optimized conditions, the limits of detection and quantification of the method, respectively, was 0.58 and 1.93 μg L-1 in linear range of 2-500 μg L-1 with sensitivity enhancement and preconcentration factors of 47.7 and 40 for preconcentration from 15 mL of sample solution. The recoveries from spiked samples were in range of 93.8-103.2% with a relative standard deviation ranging from 2.6% to 4.1% (25, 100 and 250 μg L-1, n: 5). The accuracy was verified by analysis of two certified samples, and the results were in a good agreement with the certified values. The intra-day and inter-day precision were tested by reproducibility (as 3.3-3.4%) and repeatability (as 3.4-4.1%) analysis for five replicate measurements of V(V) in quality control samples spiked with 5, 10 and 15 μg L-1. Trace V(V) contents of the selected beverage samples by the developed method were successfully determined.

The One to Multiple Automatic High Accuracy Registration of Terrestrial LIDAR and Optical Images

NASA Astrophysics Data System (ADS)

Wang, Y.; Hu, C.; Xia, G.; Xue, H.

2018-04-01

The registration of ground laser point cloud and close-range image is the key content of high-precision 3D reconstruction of cultural relic object. In view of the requirement of high texture resolution in the field of cultural relic at present, The registration of point cloud and image data in object reconstruction will result in the problem of point cloud to multiple images. In the current commercial software, the two pairs of registration of the two kinds of data are realized by manually dividing point cloud data, manual matching point cloud and image data, manually selecting a two - dimensional point of the same name of the image and the point cloud, and the process not only greatly reduces the working efficiency, but also affects the precision of the registration of the two, and causes the problem of the color point cloud texture joint. In order to solve the above problems, this paper takes the whole object image as the intermediate data, and uses the matching technology to realize the automatic one-to-one correspondence between the point cloud and multiple images. The matching of point cloud center projection reflection intensity image and optical image is applied to realize the automatic matching of the same name feature points, and the Rodrigo matrix spatial similarity transformation model and weight selection iteration are used to realize the automatic registration of the two kinds of data with high accuracy. This method is expected to serve for the high precision and high efficiency automatic 3D reconstruction of cultural relic objects, which has certain scientific research value and practical significance.

Carbapenemase-producing Enterobacteriaceae: Risk factors for infection and impact of resistance on outcomes

PubMed Central

Mariappan, Shanthi; Sekar, Uma; Kamalanathan, Arunagiri

2017-01-01

Background: Carbapenemase-producing Enterobacteriaceae (CPE) have increased in recent years leading to limitations of treatment options. The present study was undertaken to detect CPE, risk factors for acquiring them and their impact on clinical outcomes. Methods: This retrospective observational study included 111 clinically significant Enterobacteriaceae resistant to cephalosporins subclass III and exhibiting a positive modified Hodge test. Screening for carbapenemase production was done by phenotypic methods, and polymerase chain reaction was performed to detect genes encoding them. Retrospectively, the medical records of the patients were perused to assess risk factors for infections with CPE and their impact. The data collected were duration of hospital stay, Intensive Care Unit (ICU) stay, use of invasive devices, mechanical ventilation, the presence of comorbidities, and antimicrobial therapy. The outcome was followed up. Univariate and multivariate analysis of the data were performed using SPSS software. Results: Carbapenemase-encoding genes were detected in 67 isolates. The genes detected were New Delhi metallo-β-lactamase, Verona integron-encoded metallo-β-lactamase, and oxacillinase-181.Although univariate analysis identified risk factors associated with acquiring CPE infections as ICU stay (P = 0.021), mechanical ventilation (P = 0.013), indwelling device (P = 0.011), diabetes mellitus (P = 0.036), usage of multiple antimicrobial agents (P = 0.007), administration of carbapenems (P = 0.042), presence of focal infection or sepsis (P = 0.013), and surgical interventions (P = 0.016), multivariate analysis revealed that all these factors were insignificant. Mortality rate was 56.7% in patients with CPE infections. By both univariate and multivariate analysis of impact of the variables on mortality in these patients, the significant factors were mechanical ventilation (odds ratio [OR]: 0.141, 95% confidence interval [CI]: 0.024–0.812) and presence of indwelling invasive device (OR: 8.034; 95% CI: 2.060–31.335). Conclusion: In this study, no specific factor was identified as an independent risk for acquisition of CPE infection. However, as it is evident by multivariate analysis, there is an increased risk of mortality in patients with CPE infections when they are ventilated and are supported by indwelling devices. PMID:28251105

Brute Force Matching Between Camera Shots and Synthetic Images from Point Clouds

NASA Astrophysics Data System (ADS)

Boerner, R.; Kröhnert, M.

2016-06-01

3D point clouds, acquired by state-of-the-art terrestrial laser scanning techniques (TLS), provide spatial information about accuracies up to several millimetres. Unfortunately, common TLS data has no spectral information about the covered scene. However, the matching of TLS data with images is important for monoplotting purposes and point cloud colouration. Well-established methods solve this issue by matching of close range images and point cloud data by fitting optical camera systems on top of laser scanners or rather using ground control points. The approach addressed in this paper aims for the matching of 2D image and 3D point cloud data from a freely moving camera within an environment covered by a large 3D point cloud, e.g. a 3D city model. The key advantage of the free movement affects augmented reality applications or real time measurements. Therefore, a so-called real image, captured by a smartphone camera, has to be matched with a so-called synthetic image which consists of reverse projected 3D point cloud data to a synthetic projection centre whose exterior orientation parameters match the parameters of the image, assuming an ideal distortion free camera.

An Approach of Web-based Point Cloud Visualization without Plug-in

NASA Astrophysics Data System (ADS)

Ye, Mengxuan; Wei, Shuangfeng; Zhang, Dongmei

2016-11-01

With the advances in three-dimensional laser scanning technology, the demand for visualization of massive point cloud is increasingly urgent, but a few years ago point cloud visualization was limited to desktop-based solutions until the introduction of WebGL, several web renderers are available. This paper addressed the current issues in web-based point cloud visualization, and proposed a method of web-based point cloud visualization without plug-in. The method combines ASP.NET and WebGL technologies, using the spatial database PostgreSQL to store data and the open web technologies HTML5 and CSS3 to implement the user interface, a visualization system online for 3D point cloud is developed by Javascript with the web interactions. Finally, the method is applied to the real case. Experiment proves that the new model is of great practical value which avoids the shortcoming of the existing WebGIS solutions.

Online Continuing Professional Education: An Evaluative Case Study

ERIC Educational Resources Information Center

Pullen, Darren L.

2005-01-01

An evaluation study, assessing the pedagogical and instructional design (e-pedagogy) effectiveness of online continuing professional education (CPE) courses offered by a large Australasian CPE provider to health care professionals (HCPs). The study used a naturalistic theory approach in conjunction with a multilevel evaluation to examine the…

Quality Assurance in Continuing Professional Education. An Analysis.

ERIC Educational Resources Information Center

Tovey, Philip

Based on research conducted in and around universities in the United Kingdom, this book analyzes quality assurance in continuing professional education (CPE). An introduction provides a close look at the terms "quality,""quality assurance," and "CPE." Part I deals with context. Chapter 1 looks at theoretical…

Compact CPE: a full unit of clinical pastoral education in 27 days.

PubMed

Beverly, U H

1990-01-01

Details a four-week Basic Clinical Pastoral Education Unit. Gives a rationale for the abbreviated unit. Notes positive factors as well as limitations of such an educational experience and urges other CPE supervisors to try the compact approach. Critical responses follow the article.

Simultaneous colour visualizations of multiple ALS point cloud attributes for land cover and vegetation analysis

NASA Astrophysics Data System (ADS)

Zlinszky, András; Schroiff, Anke; Otepka, Johannes; Mandlburger, Gottfried; Pfeifer, Norbert

2014-05-01

LIDAR point clouds hold valuable information for land cover and vegetation analysis, not only in the spatial distribution of the points but also in their various attributes. However, LIDAR point clouds are rarely used for visual interpretation, since for most users, the point cloud is difficult to interpret compared to passive optical imagery. Meanwhile, point cloud viewing software is available allowing interactive 3D interpretation, but typically only one attribute at a time. This results in a large number of points with the same colour, crowding the scene and often obscuring detail. We developed a scheme for mapping information from multiple LIDAR point attributes to the Red, Green, and Blue channels of a widely used LIDAR data format, which are otherwise mostly used to add information from imagery to create "photorealistic" point clouds. The possible combinations of parameters are therefore represented in a wide range of colours, but relative differences in individual parameter values of points can be well understood. The visualization was implemented in OPALS software, using a simple and robust batch script, and is viewer independent since the information is stored in the point cloud data file itself. In our case, the following colour channel assignment delivered best results: Echo amplitude in the Red, echo width in the Green and normalized height above a Digital Terrain Model in the Blue channel. With correct parameter scaling (but completely without point classification), points belonging to asphalt and bare soil are dark red, low grassland and crop vegetation are bright red to yellow, shrubs and low trees are green and high trees are blue. Depending on roof material and DTM quality, buildings are shown from red through purple to dark blue. Erroneously high or low points, or points with incorrect amplitude or echo width usually have colours contrasting from terrain or vegetation. This allows efficient visual interpretation of the point cloud in planar, profile and 3D views since it reduces crowding of the scene and delivers intuitive contextual information. The resulting visualization has proved useful for vegetation analysis for habitat mapping, and can also be applied as a first step for point cloud level classification. An interactive demonstration of the visualization script is shown during poster attendance, including the opportunity to view your own point cloud sample files.

Point Cloud Generation from Aerial Image Data Acquired by a Quadrocopter Type Micro Unmanned Aerial Vehicle and a Digital Still Camera

PubMed Central

Rosnell, Tomi; Honkavaara, Eija

2012-01-01

The objective of this investigation was to develop and investigate methods for point cloud generation by image matching using aerial image data collected by quadrocopter type micro unmanned aerial vehicle (UAV) imaging systems. Automatic generation of high-quality, dense point clouds from digital images by image matching is a recent, cutting-edge step forward in digital photogrammetric technology. The major components of the system for point cloud generation are a UAV imaging system, an image data collection process using high image overlaps, and post-processing with image orientation and point cloud generation. Two post-processing approaches were developed: one of the methods is based on Bae Systems’ SOCET SET classical commercial photogrammetric software and another is built using Microsoft®’s Photosynth™ service available in the Internet. Empirical testing was carried out in two test areas. Photosynth processing showed that it is possible to orient the images and generate point clouds fully automatically without any a priori orientation information or interactive work. The photogrammetric processing line provided dense and accurate point clouds that followed the theoretical principles of photogrammetry, but also some artifacts were detected. The point clouds from the Photosynth processing were sparser and noisier, which is to a large extent due to the fact that the method is not optimized for dense point cloud generation. Careful photogrammetric processing with self-calibration is required to achieve the highest accuracy. Our results demonstrate the high performance potential of the approach and that with rigorous processing it is possible to reach results that are consistent with theory. We also point out several further research topics. Based on theoretical and empirical results, we give recommendations for properties of imaging sensor, data collection and processing of UAV image data to ensure accurate point cloud generation. PMID:22368479

Point cloud generation from aerial image data acquired by a quadrocopter type micro unmanned aerial vehicle and a digital still camera.

PubMed

Rosnell, Tomi; Honkavaara, Eija

2012-01-01

The objective of this investigation was to develop and investigate methods for point cloud generation by image matching using aerial image data collected by quadrocopter type micro unmanned aerial vehicle (UAV) imaging systems. Automatic generation of high-quality, dense point clouds from digital images by image matching is a recent, cutting-edge step forward in digital photogrammetric technology. The major components of the system for point cloud generation are a UAV imaging system, an image data collection process using high image overlaps, and post-processing with image orientation and point cloud generation. Two post-processing approaches were developed: one of the methods is based on Bae Systems' SOCET SET classical commercial photogrammetric software and another is built using Microsoft(®)'s Photosynth™ service available in the Internet. Empirical testing was carried out in two test areas. Photosynth processing showed that it is possible to orient the images and generate point clouds fully automatically without any a priori orientation information or interactive work. The photogrammetric processing line provided dense and accurate point clouds that followed the theoretical principles of photogrammetry, but also some artifacts were detected. The point clouds from the Photosynth processing were sparser and noisier, which is to a large extent due to the fact that the method is not optimized for dense point cloud generation. Careful photogrammetric processing with self-calibration is required to achieve the highest accuracy. Our results demonstrate the high performance potential of the approach and that with rigorous processing it is possible to reach results that are consistent with theory. We also point out several further research topics. Based on theoretical and empirical results, we give recommendations for properties of imaging sensor, data collection and processing of UAV image data to ensure accurate point cloud generation.

Pd-Cu/poly(o-Anisidine) nanocomposite as an efficient catalyst for formaldehyde oxidation

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

Hosseini, Sayed Reza, E-mail: r.hosseini@umz.ac.ir; Raoof, Jahan-Bakhsh; Ghasemi, Shahram

Highlights: • o-Anisidine monomer was electro-polymerized at the pCPE surface in acid medium. • Palladium/copper NPs were prepared by galvanic replacement method at the POA/pCPE. • Pd-Cu NPs showed excellent electrocatalytic activity towards formaldehyde oxidation. • The bimetallic Pd-Cu NPs/POA nanocomposite showed satisfactory long-term stability. - Abstract: In this work, for the first time, the electrocatalytic oxidation of formaldehyde in 0.5 M sulfuric acid solution at spherical bimetallic palladium-copper nanoparticles (Pd-Cu NPs) deposited on the poly (o-Anisidine) film modified electrochemically pretreated carbon paste electrode (POA/pCPE) has been investigated. Highly porous POA film prepared by electropolymerization onto the pCPE was usedmore » as a potent support for deposition of the Pd-Cu NPs. The Pd-Cu NPs were prepared through spontaneous and irreversible reaction via galvanic replacement between Pd{sup II} ions and the Cu{sup 0} particles. The prepared Pd-Cu NPs were characterized by scanning electron microscopy, energy dispersive spectroscopy and electrochemical methods. The obtained results showed that the utilization of Cu nanoparticles and pretreatment technique enhances the electrocatalytic activity of the modified electrode towards formaldehyde oxidation. The influence of several parameters on formaldehyde oxidation as well as stability of the Pd-Cu/POA/pCPE has been investigated.« less

Sharing of carbapenemase-encoding plasmids between Enterobacteriaceae in UK sewage uncovered by MinION sequencing

PubMed Central

Blane, Beth; Coll, Francesc; Naydenova, Plamena; Hunt, Martin; Tracey, Alan; Hopkins, Katie L.; Brown, Nicholas M.; Woodford, Neil; Parkhill, Julian

2017-01-01

Dissemination of carbapenem resistance among pathogenic Gram-negative bacteria is a looming medical emergency. Efficient spread of resistance within and between bacterial species is facilitated by mobile genetic elements. We hypothesized that wastewater contributes to the dissemination of carbapenemase-producing Enterobacteriaceae (CPE), and studied this through a cross-sectional observational study of wastewater in the East of England. We isolated clinically relevant species of CPE in untreated and treated wastewater, confirming that waste treatment does not prevent release of CPE into the environment. We observed that CPE-positive plants were restricted to those in direct receipt of hospital waste, suggesting that hospital effluent may play a role in disseminating carbapenem resistance. We postulated that plasmids carrying carbapenemase genes were exchanged between bacterial hosts in sewage, and used short-read (Illumina) and long-read (MinION) technologies to characterize plasmids encoding resistance to antimicrobials and heavy metals. We demonstrated that different CPE species (Enterobacter kobei and Raoultella ornithinolytica) isolated from wastewater from the same treatment plant shared two plasmids of 63 and 280 kb. The former plasmid conferred resistance to carbapenems (blaOXA-48), and the latter to numerous drug classes and heavy metals. We also report the complete genome sequence for Enterobacter kobei. Small, portable sequencing instruments such as the MinION have the potential to improve the quality of information gathered on antimicrobial resistance in the environment. PMID:29026655

Relationships among rotational and conventional grazing systems, stream channels, and macroinvertebrates

USGS Publications Warehouse

Raymond, K.L.; Vondracek, B.

2011-01-01

Cattle grazing in riparian areas can reduce water quality, alter stream channel characteristics, and alter fish and macroinvertebrate assemblage structure. The U.S. Department of Agriculture, Natural Resources Conservation Services has recommended Rotational Grazing (RG) as an alternative management method on livestock and dairy operations to protect riparian areas and water quality. We evaluated 13 stream channel characteristics, benthic macroinvertebrate larvae (BML), and chironomid pupal exuviae (CPE) from 18 sites in the Upper Midwest of the United States in relation to RG and conventional grazing (CG). A Biotic Composite Score comprised of several macroinvertebrate metrics was developed for both the BML assemblage and the CPE assemblage. Multi-Response Permutation Procedures (MRPP) indicated a significant difference in stream channel characteristics between RG and CG. Nonmetric Multidimensional Scaling indicated that RG sites were associated with more stable stream banks, higher quality aquatic habitat, lower soil compaction, and larger particles in the streambed. However, neither MRPP nor Mann-Whitney U tests demonstrated a difference in Biotic Composite Scores for BML or CPE along RG and CG sites. The BML and CPE metrics were significantly correlated, indicating that they were likely responding to similar variables among the study sites. Although stream channel characteristics appeared to respond to grazing management, BML and CPE may have responded to land use throughout the watershed, as well as local land use. ?? 2011 Springer Science+Business Media B.V. (outside the USA).

Maintaining Vitality: Pharmacists’ Continuing Professional Education Decision-Making in the Upper Midwest

PubMed Central

Henkel, Paul Jacob

2018-01-01

Continuing professional education (CPE) plays an important role in continuing professional development of pharmacists for providing quality pharmaceutical care but also to maintain professional and organizational vitality and meet changing community/population needs. The study objective was to describe and understand factors of importance in selection of CPE credit hours among Upper Midwest pharmacists. A cross-sectional study of licensed pharmacists (n = 1239) in Iowa, Minnesota, Nebraska, North Dakota, and South Dakota included completion of a questionnaire on demographics and CPE decision-making. Factor analysis, t-test, and multivariate analyses were performed using Stata 10.1. Pharmacists placed greatest importance on maintaining licensure (mean = 2.72/3.00), personal interest (mean = 2.57), and self-improvement (mean = 2.42). Community/population need (mean = 1.83) was rated as slightly more important (p < 0.01) by retail/community pharmacists, females, and those with a Doctor of Pharmacy degree or pharmacy residency while business growth/development (mean = 1.33) was rated slightly more important (p < 0.01) by retail/community pharmacists. Despite findings that neither community/population need nor business development were among the most important factors in pharmacists’ CPE selection, there exists significant potential for pharmacists to utilize CPE to maintain professional and organizational vitality in the labor market, but more importantly to ensure continued provision of quality pharmaceutical care and patient education. PMID:29389850

Maintaining Vitality: Pharmacists' Continuing Professional Education Decision-Making in the Upper Midwest.

PubMed

Henkel, Paul Jacob; Marvanova, Marketa

2018-02-01

Continuing professional education (CPE) plays an important role in continuing professional development of pharmacists for providing quality pharmaceutical care but also to maintain professional and organizational vitality and meet changing community/population needs. The study objective was to describe and understand factors of importance in selection of CPE credit hours among Upper Midwest pharmacists. A cross-sectional study of licensed pharmacists ( n = 1239) in Iowa, Minnesota, Nebraska, North Dakota, and South Dakota included completion of a questionnaire on demographics and CPE decision-making. Factor analysis, t -test, and multivariate analyses were performed using Stata 10.1. Pharmacists placed greatest importance on maintaining licensure (mean = 2.72/3.00), personal interest (mean = 2.57), and self-improvement (mean = 2.42). Community/population need (mean = 1.83) was rated as slightly more important ( p < 0.01) by retail/community pharmacists, females, and those with a Doctor of Pharmacy degree or pharmacy residency while business growth/development (mean = 1.33) was rated slightly more important ( p < 0.01) by retail/community pharmacists. Despite findings that neither community/population need nor business development were among the most important factors in pharmacists' CPE selection, there exists significant potential for pharmacists to utilize CPE to maintain professional and organizational vitality in the labor market, but more importantly to ensure continued provision of quality pharmaceutical care and patient education.

Multi-temporal monitoring of a regional riparian buffer network (>12,000 km) with LiDAR and photogrammetric point clouds.

PubMed

Michez, Adrien; Piégay, Hervé; Lejeune, Philippe; Claessens, Hugues

2017-11-01

Riparian buffers are of major concern for land and water resource managers despite their relatively low spatial coverage. In Europe, this concern has been acknowledged by different environmental directives which recommend multi-scale monitoring (from local to regional scales). Remote sensing methods could be a cost-effective alternative to field-based monitoring, to build replicable "wall-to-wall" monitoring strategies of large river networks and associated riparian buffers. The main goal of our study is to extract and analyze various parameters of the riparian buffers of up to 12,000 km of river in southern Belgium (Wallonia) from three-dimensional (3D) point clouds based on LiDAR and photogrammetric surveys to i) map riparian buffers parameters on different scales, ii) interpret the regional patterns of the riparian buffers and iii) propose new riparian buffer management indicators. We propose different strategies to synthesize and visualize relevant information at different spatial scales ranging from local (<10 km) to regional scale (>12,000 km). Our results showed that the selected parameters had a clear regional pattern. The reaches of Ardenne ecoregion have channels with the highest flow widths and shallowest depths. In contrast, the reaches of the Loam ecoregion have the narrowest and deepest flow channels. Regional variability in channel width and depth is used to locate management units potentially affected by human impact. Riparian forest of the Loam ecoregion is characterized by the lowest longitudinal continuity and mean tree height, underlining significant human disturbance. As the availability of 3D point clouds at the regional scale is constantly growing, our study proposes reproducible methods which can be integrated into regional monitoring by land managers. With LiDAR still being relatively expensive to acquire, the use of photogrammetric point clouds combined with LiDAR data is a cost-effective means to update the characterization of the riparian forest conditions. Copyright © 2017 Elsevier Ltd. All rights reserved.

a Fast Method for Measuring the Similarity Between 3d Model and 3d Point Cloud

NASA Astrophysics Data System (ADS)

Zhang, Zongliang; Li, Jonathan; Li, Xin; Lin, Yangbin; Zhang, Shanxin; Wang, Cheng

2016-06-01

This paper proposes a fast method for measuring the partial Similarity between 3D Model and 3D point Cloud (SimMC). It is crucial to measure SimMC for many point cloud-related applications such as 3D object retrieval and inverse procedural modelling. In our proposed method, the surface area of model and the Distance from Model to point Cloud (DistMC) are exploited as measurements to calculate SimMC. Here, DistMC is defined as the weighted distance of the distances between points sampled from model and point cloud. Similarly, Distance from point Cloud to Model (DistCM) is defined as the average distance of the distances between points in point cloud and model. In order to reduce huge computational burdens brought by calculation of DistCM in some traditional methods, we define SimMC as the ratio of weighted surface area of model to DistMC. Compared to those traditional SimMC measuring methods that are only able to measure global similarity, our method is capable of measuring partial similarity by employing distance-weighted strategy. Moreover, our method is able to be faster than other partial similarity assessment methods. We demonstrate the superiority of our method both on synthetic data and laser scanning data.

Capturing Revolute Motion and Revolute Joint Parameters with Optical Tracking

NASA Astrophysics Data System (ADS)

Antonya, C.

2017-12-01

Optical tracking of users and various technical systems are becoming more and more popular. It consists of analysing sequence of recorded images using video capturing devices and image processing algorithms. The returned data contains mainly point-clouds, coordinates of markers or coordinates of point of interest. These data can be used for retrieving information related to the geometry of the objects, but also to extract parameters for the analytical model of the system useful in a variety of computer aided engineering simulations. The parameter identification of joints deals with extraction of physical parameters (mainly geometric parameters) for the purpose of constructing accurate kinematic and dynamic models. The input data are the time-series of the marker’s position. The least square method was used for fitting the data into different geometrical shapes (ellipse, circle, plane) and for obtaining the position and orientation of revolute joins.

Motion Estimation System Utilizing Point Cloud Registration

NASA Technical Reports Server (NTRS)

Chen, Qi (Inventor)

2016-01-01

A system and method of estimation motion of a machine is disclosed. The method may include determining a first point cloud and a second point cloud corresponding to an environment in a vicinity of the machine. The method may further include generating a first extended gaussian image (EGI) for the first point cloud and a second EGI for the second point cloud. The method may further include determining a first EGI segment based on the first EGI and a second EGI segment based on the second EGI. The method may further include determining a first two dimensional distribution for points in the first EGI segment and a second two dimensional distribution for points in the second EGI segment. The method may further include estimating motion of the machine based on the first and second two dimensional distributions.

A holistic image segmentation framework for cloud detection and extraction

NASA Astrophysics Data System (ADS)

Shen, Dan; Xu, Haotian; Blasch, Erik; Horvath, Gregory; Pham, Khanh; Zheng, Yufeng; Ling, Haibin; Chen, Genshe

2013-05-01

Atmospheric clouds are commonly encountered phenomena affecting visual tracking from air-borne or space-borne sensors. Generally clouds are difficult to detect and extract because they are complex in shape and interact with sunlight in a complex fashion. In this paper, we propose a clustering game theoretic image segmentation based approach to identify, extract, and patch clouds. In our framework, the first step is to decompose a given image containing clouds. The problem of image segmentation is considered as a "clustering game". Within this context, the notion of a cluster is equivalent to a classical equilibrium concept from game theory, as the game equilibrium reflects both the internal and external (e.g., two-player) cluster conditions. To obtain the evolutionary stable strategies, we explore three evolutionary dynamics: fictitious play, replicator dynamics, and infection and immunization dynamics (InImDyn). Secondly, we use the boundary and shape features to refine the cloud segments. This step can lower the false alarm rate. In the third step, we remove the detected clouds and patch the empty spots by performing background recovery. We demonstrate our cloud detection framework on a video clip provides supportive results.

Antiviral screening of forty-two Egyptian medicinal plants.

PubMed

Soltan, Maha Mohamed; Zaki, Adel Kamal

2009-10-29

Egyptian medicinal plants are well known by their diverse uses in traditional folk medicine to cure various ailments including infectious diseases. Forty-two Egyptian medicinal plant species were selected from local market and were subjected to antiviral screening bioassay to investigate and to evaluate their biological activities. Hydro-alcoholic extracts of each species were separately prepared and tested against three viruses: herpes simplex-1 virus (HSV), poliomyelitis-1 virus (POLIO) and vesicular stomatitis virus (VSV). The antiviral activity were determined by means of the end point titration technique (EPTT) that depends on the ability of plant extract dilutions to inhibit the produced cytopathogenic effect (CPE) and expressed as reduction factor (Rf) of the viral titer. Achillea fragrantissima, Jasonia montana and Globularia arabica are found to have antiviral activity against POLIO in a concentration dependent manner at complete non-toxic concentration range 10-100 microg/ml (Rf 10(6)), 10-100 microg/ml (Rf 10(5)) and 50-100 microg/ml (Rf 10(4)), respectively while Tanacetum sinaicum are found to have moderate antiviral activity against POLIO at concentration of 50-100 microg/ml (Rf 10(2)). Ephedra alata and Moringa peregrina are found to have antiviral activity against HSV (Rf 10(4)). Also, the results revealed that Capparis sinaica, Tamarix nilotica and Cyperus rotundus are found to have virucidal effect against HSV. All the forty-two plant species are found to have no reliable antiviral activity against VSV. The specific indications claimed by the traditional healers are confirmed by antiviral test.

Pointo - a Low Cost Solution to Point Cloud Processing

NASA Astrophysics Data System (ADS)

Houshiar, H.; Winkler, S.

2017-11-01

With advance in technology access to data especially 3D point cloud data becomes more and more an everyday task. 3D point clouds are usually captured with very expensive tools such as 3D laser scanners or very time consuming methods such as photogrammetry. Most of the available softwares for 3D point cloud processing are designed for experts and specialists in this field and are usually very large software packages containing variety of methods and tools. This results in softwares that are usually very expensive to acquire and also very difficult to use. Difficulty of use is caused by complicated user interfaces that is required to accommodate a large list of features. The aim of these complex softwares is to provide a powerful tool for a specific group of specialist. However they are not necessary required by the majority of the up coming average users of point clouds. In addition to complexity and high costs of these softwares they generally rely on expensive and modern hardware and only compatible with one specific operating system. Many point cloud customers are not point cloud processing experts or willing to spend the high acquisition costs of these expensive softwares and hardwares. In this paper we introduce a solution for low cost point cloud processing. Our approach is designed to accommodate the needs of the average point cloud user. To reduce the cost and complexity of software our approach focuses on one functionality at a time in contrast with most available softwares and tools that aim to solve as many problems as possible at the same time. Our simple and user oriented design improve the user experience and empower us to optimize our methods for creation of an efficient software. In this paper we introduce Pointo family as a series of connected softwares to provide easy to use tools with simple design for different point cloud processing requirements. PointoVIEWER and PointoCAD are introduced as the first components of the Pointo family to provide a fast and efficient visualization with the ability to add annotation and documentation to the point clouds.

Institutionalizing Continuing Professional Education (CPE): Toward a Definition of the University Situation.

ERIC Educational Resources Information Center

Toombs, William; Lindsay, Carl A.

Issues related to the institutionalization of continuing professional education (CPE) within the university are considered. The components of marginality, the possible obstacles and incentives to institutionalization, and some of the support necessities are addressed, along with insights gained by a Pennsylvania State University effort to link the…

Student Perceptions of a Conceptual Physical Education Activity Course

ERIC Educational Resources Information Center

Jenkins, Jayne M.; Jenkins, Patience; Collums, Ashley; Werhonig, Gary

2006-01-01

Conceptual physical education (CPE) courses are typically included in university course work to provide students knowledge and skills to engage in physical activity for life. The purpose of this study was to identify CPE course characteristics that contributed to positive and negative student perceptions. Participants included 157 undergraduates…

Validity of association rules extracted by healthcare-data-mining.

PubMed

Takeuchi, Hiroshi; Kodama, Naoki

2014-01-01

A personal healthcare system used with cloud computing has been developed. It enables a daily time-series of personal health and lifestyle data to be stored in the cloud through mobile devices. The cloud automatically extracts personally useful information, such as rules and patterns concerning the user's lifestyle and health condition embedded in their personal big data, by using healthcare-data-mining. This study has verified that the extracted rules on the basis of a daily time-series data stored during a half- year by volunteer users of this system are valid.

Railway Tunnel Clearance Inspection Method Based on 3D Point Cloud from Mobile Laser Scanning

PubMed Central

Zhou, Yuhui; Wang, Shaohua; Mei, Xi; Yin, Wangling; Lin, Chunfeng; Mao, Qingzhou

2017-01-01

Railway tunnel clearance is directly related to the safe operation of trains and upgrading of freight capacity. As more and more railway are put into operation and the operation is continuously becoming faster, the railway tunnel clearance inspection should be more precise and efficient. In view of the problems existing in traditional tunnel clearance inspection methods, such as low density, slow speed and a lot of manual operations, this paper proposes a tunnel clearance inspection approach based on 3D point clouds obtained by a mobile laser scanning system (MLS). First, a dynamic coordinate system for railway tunnel clearance inspection has been proposed. A rail line extraction algorithm based on 3D linear fitting is implemented from the segmented point cloud to establish a dynamic clearance coordinate system. Second, a method to seamlessly connect all rail segments based on the railway clearance restrictions, and a seamless rail alignment is formed sequentially from the middle tunnel section to both ends. Finally, based on the rail alignment and the track clearance coordinate system, different types of clearance frames are introduced for intrusion operation with the tunnel section to realize the tunnel clearance inspection. By taking the Shuanghekou Tunnel of the Chengdu–Kunming Railway as an example, when the clearance inspection is carried out by the method mentioned herein, its precision can reach 0.03 m, and difference types of clearances can be effectively calculated. This method has a wide application prospects. PMID:28880232

Creating high-resolution bare-earth digital elevation models (DEMs) from stereo imagery in an area of densely vegetated deciduous forest using combinations of procedures designed for lidar point cloud filtering

USGS Publications Warehouse

DeWitt, Jessica D.; Warner, Timothy A.; Chirico, Peter G.; Bergstresser, Sarah E.

2017-01-01

For areas of the world that do not have access to lidar, fine-scale digital elevation models (DEMs) can be photogrammetrically created using globally available high-spatial resolution stereo satellite imagery. The resultant DEM is best termed a digital surface model (DSM) because it includes heights of surface features. In densely vegetated conditions, this inclusion can limit its usefulness in applications requiring a bare-earth DEM. This study explores the use of techniques designed for filtering lidar point clouds to mitigate the elevation artifacts caused by above ground features, within the context of a case study of Prince William Forest Park, Virginia, USA. The influences of land cover and leaf-on vs. leaf-off conditions are investigated, and the accuracy of the raw photogrammetric DSM extracted from leaf-on imagery was between that of a lidar bare-earth DEM and the Shuttle Radar Topography Mission DEM. Although the filtered leaf-on photogrammetric DEM retains some artifacts of the vegetation canopy and may not be useful for some applications, filtering procedures significantly improved the accuracy of the modeled terrain. The accuracy of the DSM extracted in leaf-off conditions was comparable in most areas to the lidar bare-earth DEM and filtering procedures resulted in accuracy comparable of that to the lidar DEM.

Study of Huizhou architecture component point cloud in surface reconstruction

NASA Astrophysics Data System (ADS)

Zhang, Runmei; Wang, Guangyin; Ma, Jixiang; Wu, Yulu; Zhang, Guangbin

2017-06-01

Surface reconfiguration softwares have many problems such as complicated operation on point cloud data, too many interaction definitions, and too stringent requirements for inputing data. Thus, it has not been widely popularized so far. This paper selects the unique Huizhou Architecture chuandou wooden beam framework as the research object, and presents a complete set of implementation in data acquisition from point, point cloud preprocessing and finally implemented surface reconstruction. Firstly, preprocessing the acquired point cloud data, including segmentation and filtering. Secondly, the surface’s normals are deduced directly from the point cloud dataset. Finally, the surface reconstruction is studied by using Greedy Projection Triangulation Algorithm. Comparing the reconstructed model with the three-dimensional surface reconstruction softwares, the results show that the proposed scheme is more smooth, time efficient and portable.

What's the Point of a Raster ? Advantages of 3D Point Cloud Processing over Raster Based Methods for Accurate Geomorphic Analysis of High Resolution Topography.

NASA Astrophysics Data System (ADS)

Lague, D.

2014-12-01

High Resolution Topographic (HRT) datasets are predominantly stored and analyzed as 2D raster grids of elevations (i.e., Digital Elevation Models). Raster grid processing is common in GIS software and benefits from a large library of fast algorithms dedicated to geometrical analysis, drainage network computation and topographic change measurement. Yet, all instruments or methods currently generating HRT datasets (e.g., ALS, TLS, SFM, stereo satellite imagery) output natively 3D unstructured point clouds that are (i) non-regularly sampled, (ii) incomplete (e.g., submerged parts of river channels are rarely measured), and (iii) include 3D elements (e.g., vegetation, vertical features such as river banks or cliffs) that cannot be accurately described in a DEM. Interpolating the raw point cloud onto a 2D grid generally results in a loss of position accuracy, spatial resolution and in more or less controlled interpolation. Here I demonstrate how studying earth surface topography and processes directly on native 3D point cloud datasets offers several advantages over raster based methods: point cloud methods preserve the accuracy of the original data, can better handle the evaluation of uncertainty associated to topographic change measurements and are more suitable to study vegetation characteristics and steep features of the landscape. In this presentation, I will illustrate and compare Point Cloud based and Raster based workflows with various examples involving ALS, TLS and SFM for the analysis of bank erosion processes in bedrock and alluvial rivers, rockfall statistics (including rockfall volume estimate directly from point clouds) and the interaction of vegetation/hydraulics and sedimentation in salt marshes. These workflows use 2 recently published algorithms for point cloud classification (CANUPO) and point cloud comparison (M3C2) now implemented in the open source software CloudCompare.

An efficient cloud detection method for high resolution remote sensing panchromatic imagery

NASA Astrophysics Data System (ADS)

Li, Chaowei; Lin, Zaiping; Deng, Xinpu

2018-04-01

In order to increase the accuracy of cloud detection for remote sensing satellite imagery, we propose an efficient cloud detection method for remote sensing satellite panchromatic images. This method includes three main steps. First, an adaptive intensity threshold value combined with a median filter is adopted to extract the coarse cloud regions. Second, a guided filtering process is conducted to strengthen the textural features difference and then we conduct the detection process of texture via gray-level co-occurrence matrix based on the acquired texture detail image. Finally, the candidate cloud regions are extracted by the intersection of two coarse cloud regions above and we further adopt an adaptive morphological dilation to refine them for thin clouds in boundaries. The experimental results demonstrate the effectiveness of the proposed method.

Using Mobile Laser Scanning Data for Features Extraction of High Accuracy Driving Maps

NASA Astrophysics Data System (ADS)

Yang, Bisheng; Liu, Yuan; Liang, Fuxun; Dong, Zhen

2016-06-01

High Accuracy Driving Maps (HADMs) are the core component of Intelligent Drive Assistant Systems (IDAS), which can effectively reduce the traffic accidents due to human error and provide more comfortable driving experiences. Vehicle-based mobile laser scanning (MLS) systems provide an efficient solution to rapidly capture three-dimensional (3D) point clouds of road environments with high flexibility and precision. This paper proposes a novel method to extract road features (e.g., road surfaces, road boundaries, road markings, buildings, guardrails, street lamps, traffic signs, roadside-trees, power lines, vehicles and so on) for HADMs in highway environment. Quantitative evaluations show that the proposed algorithm attains an average precision and recall in terms of 90.6% and 91.2% in extracting road features. Results demonstrate the efficiencies and feasibilities of the proposed method for extraction of road features for HADMs.

Compression of 3D Point Clouds Using a Region-Adaptive Hierarchical Transform.

PubMed

De Queiroz, Ricardo; Chou, Philip A

2016-06-01

In free-viewpoint video, there is a recent trend to represent scene objects as solids rather than using multiple depth maps. Point clouds have been used in computer graphics for a long time and with the recent possibility of real time capturing and rendering, point clouds have been favored over meshes in order to save computation. Each point in the cloud is associated with its 3D position and its color. We devise a method to compress the colors in point clouds which is based on a hierarchical transform and arithmetic coding. The transform is a hierarchical sub-band transform that resembles an adaptive variation of a Haar wavelet. The arithmetic encoding of the coefficients assumes Laplace distributions, one per sub-band. The Laplace parameter for each distribution is transmitted to the decoder using a custom method. The geometry of the point cloud is encoded using the well-established octtree scanning. Results show that the proposed solution performs comparably to the current state-of-the-art, in many occasions outperforming it, while being much more computationally efficient. We believe this work represents the state-of-the-art in intra-frame compression of point clouds for real-time 3D video.

Block Adjustment and Image Matching of WORLDVIEW-3 Stereo Pairs and Accuracy Evaluation

NASA Astrophysics Data System (ADS)

Zuo, C.; Xiao, X.; Hou, Q.; Li, B.

2018-05-01

WorldView-3, as a high-resolution commercial earth observation satellite, which is launched by Digital Global, provides panchromatic imagery of 0.31 m resolution. The positioning accuracy is less than 3.5 meter CE90 without ground control, which can use for large scale topographic mapping. This paper presented the block adjustment for WorldView-3 based on RPC model and achieved the accuracy of 1 : 2000 scale topographic mapping with few control points. On the base of stereo orientation result, this paper applied two kinds of image matching algorithm for DSM extraction: LQM and SGM. Finally, this paper compared the accuracy of the point cloud generated by the two image matching methods with the reference data which was acquired by an airborne laser scanner. The results showed that the RPC adjustment model of WorldView-3 image with small number of GCPs could satisfy the requirement of Chinese Surveying and Mapping regulations for 1 : 2000 scale topographic maps. And the point cloud result obtained through WorldView-3 stereo image matching had higher elevation accuracy, the RMS error of elevation for bare ground area is 0.45 m, while for buildings the accuracy can almost reach 1 meter.

Improved ATLAS HammerCloud Monitoring for Local Site Administration

NASA Astrophysics Data System (ADS)

Böhler, M.; Elmsheuser, J.; Hönig, F.; Legger, F.; Mancinelli, V.; Sciacca, G.

2015-12-01

Every day hundreds of tests are run on the Worldwide LHC Computing Grid for the ATLAS, and CMS experiments in order to evaluate the performance and reliability of the different computing sites. All this activity is steered, controlled, and monitored by the HammerCloud testing infrastructure. Sites with failing functionality tests are auto-excluded from the ATLAS computing grid, therefore it is essential to provide a detailed and well organized web interface for the local site administrators such that they can easily spot and promptly solve site issues. Additional functionality has been developed to extract and visualize the most relevant information. The site administrators can now be pointed easily to major site issues which lead to site blacklisting as well as possible minor issues that are usually not conspicuous enough to warrant the blacklisting of a specific site, but can still cause undesired effects such as a non-negligible job failure rate. This paper summarizes the different developments and optimizations of the HammerCloud web interface and gives an overview of typical use cases.

Translational control by cytoplasmic polyadenylation during Xenopus oocyte maturation: characterization of cis and trans elements and regulation by cyclin/MPF.

PubMed

McGrew, L L; Richter, J D

1990-11-01

The expression of certain maternal mRNAs during oocyte maturation is regulated by cytoplasmic polyadenylation. To understand this process, we have focused on a maternal mRNA from Xenopus termed G10. This mRNA is stored in the cytoplasm of stage 6 oocytes until maturation when the process of poly(A) elongation stimulates its translation. Deletion analysis of the 3' untranslated region of G10 RNA has revealed that two sequence elements, UUUUUUAU and AAUAAA were both necessary and sufficient for polyadenylation and polysomal recruitment. In this communication, we have defined the U-rich region that is optimal for polyadenylation as UUUUUUAUAAAG, henceforth referred to as the cytoplasmic polyadenylation element (CPE). We have also identified unique sequence requirements in the 3' terminus of the RNA that can modulate polyadenylation even in the presence of wild-type cis elements. A time course of cytoplasmic polyadenylation in vivo shows that it is an early event of maturation and that it requires protein synthesis within the first 15 min of exposure to progesterone. MPF and cyclin can both induce polyadenylation but, at least with respect to MPF, cannot obviate the requirement for protein synthesis. To identify factors that may be responsible for maturation-specific polyadenylation, we employed extracts from oocytes and unfertilized eggs, the latter of which correctly polyadenylates exogenously added RNA. UV crosslinking demonstrated that an 82 kd protein binds to the U-rich CPE in egg, but not oocyte, extracts. The data suggest that progesterone, either in addition to or through MPF/cyclin, induces the synthesis of a factor during very early maturation that stimulates polyadenylation.(ABSTRACT TRUNCATED AT 250 WORDS)

TH-AB-202-08: A Robust Real-Time Surface Reconstruction Method On Point Clouds Captured From a 3D Surface Photogrammetry System

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

Liu, W; Sawant, A; Ruan, D

2016-06-15

Purpose: Surface photogrammetry (e.g. VisionRT, C-Rad) provides a noninvasive way to obtain high-frequency measurement for patient motion monitoring in radiotherapy. This work aims to develop a real-time surface reconstruction method on the acquired point clouds, whose acquisitions are subject to noise and missing measurements. In contrast to existing surface reconstruction methods that are usually computationally expensive, the proposed method reconstructs continuous surfaces with comparable accuracy in real-time. Methods: The key idea in our method is to solve and propagate a sparse linear relationship from the point cloud (measurement) manifold to the surface (reconstruction) manifold, taking advantage of the similarity inmore » local geometric topology in both manifolds. With consistent point cloud acquisition, we propose a sparse regression (SR) model to directly approximate the target point cloud as a sparse linear combination from the training set, building the point correspondences by the iterative closest point (ICP) method. To accommodate changing noise levels and/or presence of inconsistent occlusions, we further propose a modified sparse regression (MSR) model to account for the large and sparse error built by ICP, with a Laplacian prior. We evaluated our method on both clinical acquired point clouds under consistent conditions and simulated point clouds with inconsistent occlusions. The reconstruction accuracy was evaluated w.r.t. root-mean-squared-error, by comparing the reconstructed surfaces against those from the variational reconstruction method. Results: On clinical point clouds, both the SR and MSR models achieved sub-millimeter accuracy, with mean reconstruction time reduced from 82.23 seconds to 0.52 seconds and 0.94 seconds, respectively. On simulated point cloud with inconsistent occlusions, the MSR model has demonstrated its advantage in achieving consistent performance despite the introduced occlusions. Conclusion: We have developed a real-time and robust surface reconstruction method on point clouds acquired by photogrammetry systems. It serves an important enabling step for real-time motion tracking in radiotherapy. This work is supported in part by NIH grant R01 CA169102-02.« less