Learn from every mistake! Hierarchical information combination in astronomy

NASA Astrophysics Data System (ADS)

Süveges, Maria; Fotopoulou, Sotiria; Coupon, Jean; Paltani, Stéphane; Eyer, Laurent; Rimoldini, Lorenzo

2017-06-01

Throughout the processing and analysis of survey data, a ubiquitous issue nowadays is that we are spoilt for choice when we need to select a methodology for some of its steps. The alternative methods usually fail and excel in different data regions, and have various advantages and drawbacks, so a combination that unites the strengths of all while suppressing the weaknesses is desirable. We propose to use a two-level hierarchy of learners. Its first level consists of training and applying the possible base methods on the first part of a known set. At the second level, we feed the output probability distributions from all base methods to a second learner trained on the remaining known objects. Using classification of variable stars and photometric redshift estimation as examples, we show that the hierarchical combination is capable of achieving general improvement over averaging-type combination methods, correcting systematics present in all base methods, is easy to train and apply, and thus, it is a promising tool in the astronomical ``Big Data'' era.

Improvement of human cell line activation test (h-CLAT) using short-time exposure methods for prevention of false-negative results.

PubMed

Narita, Kazuto; Ishii, Yuuki; Vo, Phuc Thi Hong; Nakagawa, Fumiko; Ogata, Shinichi; Yamashita, Kunihiko; Kojima, Hajime; Itagaki, Hiroshi

2018-01-01

Recently, animal testing has been affected by increasing ethical, social, and political concerns regarding animal welfare. Several in vitro safety tests for evaluating skin sensitization, such as the human cell line activation test (h-CLAT), have been proposed. However, similar to other tests, the h-CLAT has produced false-negative results, including in tests for acid anhydride and water-insoluble chemicals. In a previous study, we demonstrated that the cause of false-negative results from phthalic anhydride was hydrolysis by an aqueous vehicle, with IL-8 release from THP-1 cells, and that short-time exposure to liquid paraffin (LP) dispersion medium could reduce false-negative results from acid anhydrides. In the present study, we modified the h-CLAT by applying this exposure method. We found that the modified h-CLAT is a promising method for reducing false-negative results obtained from acid anhydrides and chemicals with octanol-water partition coefficients (LogK ow ) greater than 3.5. Based on the outcomes from the present study, a combination of the original and the modified h-CLAT is suggested for reducing false-negative results. Notably, the combination method provided a sensitivity of 95% (overall chemicals) or 93% (chemicals with LogK ow > 2.0), and an accuracy of 88% (overall chemicals) or 81% (chemicals with LogK ow > 2.0). We found that the combined method is a promising evaluation scheme for reducing false-negative results seen in existing in vitro skin-sensitization tests. In the future, we expect a combination of original and modified h-CLAT to be applied in a newly developed in vitro test for evaluating skin sensitization.

LASER BIOLOGY AND MEDICINE: Combined application of optical methods to increase the information content of optical coherent tomography in diagnostics of neoplastic processes

NASA Astrophysics Data System (ADS)

Kuranov, R. V.; Sapozhnikova, V. V.; Shakhova, N. M.; Gelikonov, V. M.; Zagainova, E. V.; Petrova, S. A.

2002-11-01

A combined application of optical methods [optical coherent tomography (OCT), cross-polarisation optical coherent tomography, and fluorescence spectroscopy] is proposed for obtaining information on morphological and biochemical changes occurring in tissues in norm and pathology. It is shown that neoplastic and scar changes in esophagus can be distinguished using a combination of polarisation and standard OCT due to the difference between the depolarising properties of the tissues caused by the structural properties of collagenic fibres in stroma. It is shown that OCT combined with fluorescence spectroscopy with the use of 5-aminolevulinic acid is promising for determining the boundaries of carcinoma of the uterine cervix and vulva. It is found that the tumour boundary detected by optical methods coincides with the morphological boundary and extends beyond colposcopically determined boundary by about 2 mm.

Combined application of optical methods to increase the information content of optical coherent tomography in diagnostics of neoplastic processes

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

Kuranov, R V; Sapozhnikova, V V; Shakhova, N M

2002-11-30

A combined application of optical methods [optical coherent tomography (OCT), cross-polarisation optical coherent tomography, and fluorescence spectroscopy] is proposed for obtaining information on morphological and biochemical changes occurring in tissues in norm and pathology. It is shown that neoplastic and scar changes in esophagus can be distinguished using a combination of polarisation and standard OCT due to the difference between the depolarising properties of the tissues caused by the structural properties of collagenic fibres in stroma. It is shown that OCT combined with fluorescence spectroscopy with the use of 5-aminolevulinic acid is promising for determining the boundaries of carcinoma ofmore » the uterine cervix and vulva. It is found that the tumour boundary detected by optical methods coincides with the morphological boundary and extends beyond colposcopically determined boundary by about 2 mm. (laser biology and medicine)« less

ADVANCING THE STUDY OF VIOLENCE AGAINST WOMEN USING MIXED METHODS: INTEGRATING QUALITATIVE METHODS INTO A QUANTITATIVE RESEARCH PROGRAM

PubMed Central

Testa, Maria; Livingston, Jennifer A.; VanZile-Tamsen, Carol

2011-01-01

A mixed methods approach, combining quantitative with qualitative data methods and analysis, offers a promising means of advancing the study of violence. Integrating semi-structured interviews and qualitative analysis into a quantitative program of research on women’s sexual victimization has resulted in valuable scientific insight and generation of novel hypotheses for testing. This mixed methods approach is described and recommendations for integrating qualitative data into quantitative research are provided. PMID:21307032

Vegetative environmental buffers for reducing downwind odor and VOCs from tunnel-ventilated swine barn

USDA-ARS?s Scientific Manuscript database

Scientists have investigated methods for reducing odor emissions from livestock buildings for decades, yet few technologies have proven effective. Vegetative Environmental Buffers (VEBs), which are specially designed combinations of trees, shrubs and grasses, have shown promise in recent years for ...

Radiogenetic therapy: strategies to overcome tumor resistance.

PubMed

Marples, B; Greco, O; Joiner, M C; Scott, S D

2003-01-01

The aim of cancer gene therapy is to selectively kill malignant cells at the tumor site, by exploiting traits specific to cancer cells and/or solid tumors. Strategies that take advantage of biological features common to different tumor types are particularly promising, since they have wide clinical applicability. Much attention has focused on genetic methods that complement radiotherapy, the principal treatment modality, or that exploit hypoxia, the most ubiquitous characteristic of most solid cancers. The goal of this review is to highlight two promising gene therapy methods developed specifically to target the tumor volume that can be readily used in combination with radiotherapy. The first approach uses radiation-responsive gene promoters to control the selective expression of a suicide gene (e.g., herpes simplex virus thymidine kinase) to irradiated tissue only, leading to targeted cell killing in the presence of a prodrug (e.g., ganciclovir). The second method utilizes oxygen-dependent promoters to produce selective therapeutic gene expression and prodrug activation in hypoxic cells, which are refractive to conventional radiotherapy. Further refining of tumor targeting can be achieved by combining radiation and hypoxia responsive elements in chimeric promoters activated by either and dual stimuli. The in vitro and in vivo studies described in this review suggest that the combination of gene therapy and radiotherapy protocols has potential for use in cancer care, particularly in cases currently refractory to treatment as a result of inherent or hypoxia-mediated radioresistance.

An Intelligent Model for Pairs Trading Using Genetic Algorithms.

PubMed

Huang, Chien-Feng; Hsu, Chi-Jen; Chen, Chi-Chung; Chang, Bao Rong; Li, Chen-An

2015-01-01

Pairs trading is an important and challenging research area in computational finance, in which pairs of stocks are bought and sold in pair combinations for arbitrage opportunities. Traditional methods that solve this set of problems mostly rely on statistical methods such as regression. In contrast to the statistical approaches, recent advances in computational intelligence (CI) are leading to promising opportunities for solving problems in the financial applications more effectively. In this paper, we present a novel methodology for pairs trading using genetic algorithms (GA). Our results showed that the GA-based models are able to significantly outperform the benchmark and our proposed method is capable of generating robust models to tackle the dynamic characteristics in the financial application studied. Based upon the promising results obtained, we expect this GA-based method to advance the research in computational intelligence for finance and provide an effective solution to pairs trading for investment in practice.

An Intelligent Model for Pairs Trading Using Genetic Algorithms

PubMed Central

Hsu, Chi-Jen; Chen, Chi-Chung; Li, Chen-An

2015-01-01

Pairs trading is an important and challenging research area in computational finance, in which pairs of stocks are bought and sold in pair combinations for arbitrage opportunities. Traditional methods that solve this set of problems mostly rely on statistical methods such as regression. In contrast to the statistical approaches, recent advances in computational intelligence (CI) are leading to promising opportunities for solving problems in the financial applications more effectively. In this paper, we present a novel methodology for pairs trading using genetic algorithms (GA). Our results showed that the GA-based models are able to significantly outperform the benchmark and our proposed method is capable of generating robust models to tackle the dynamic characteristics in the financial application studied. Based upon the promising results obtained, we expect this GA-based method to advance the research in computational intelligence for finance and provide an effective solution to pairs trading for investment in practice. PMID:26339236

Vegetative environmental buffers and exhaust fan deflectors for reducing downwind odor and VOCs from tunnel-ventilated swine barns

USDA-ARS?s Scientific Manuscript database

Scientists have investigated methods for reducing odor emissions from livestock buildings for decades, yet few technologies have proven effective. Vegetative Environmental Buffers (VEB), which are specially designed combinations of trees, shrubs and grasses, have shown promise in recent years for r...

Combining single-molecule manipulation and single-molecule detection.

PubMed

Cordova, Juan Carlos; Das, Dibyendu Kumar; Manning, Harris W; Lang, Matthew J

2014-10-01

Single molecule force manipulation combined with fluorescence techniques offers much promise in revealing mechanistic details of biomolecular machinery. Here, we review force-fluorescence microscopy, which combines the best features of manipulation and detection techniques. Three of the mainstay manipulation methods (optical traps, magnetic traps and atomic force microscopy) are discussed with respect to milestones in combination developments, in addition to highlight recent contributions to the field. An overview of additional strategies is discussed, including fluorescence based force sensors for force measurement in vivo. Armed with recent exciting demonstrations of this technology, the field of combined single-molecule manipulation and single-molecule detection is poised to provide unprecedented views of molecular machinery. Copyright © 2014 Elsevier Ltd. All rights reserved.

Prediction-Oriented Marker Selection (PROMISE): With Application to High-Dimensional Regression.

PubMed

Kim, Soyeon; Baladandayuthapani, Veerabhadran; Lee, J Jack

2017-06-01

In personalized medicine, biomarkers are used to select therapies with the highest likelihood of success based on an individual patient's biomarker/genomic profile. Two goals are to choose important biomarkers that accurately predict treatment outcomes and to cull unimportant biomarkers to reduce the cost of biological and clinical verifications. These goals are challenging due to the high dimensionality of genomic data. Variable selection methods based on penalized regression (e.g., the lasso and elastic net) have yielded promising results. However, selecting the right amount of penalization is critical to simultaneously achieving these two goals. Standard approaches based on cross-validation (CV) typically provide high prediction accuracy with high true positive rates but at the cost of too many false positives. Alternatively, stability selection (SS) controls the number of false positives, but at the cost of yielding too few true positives. To circumvent these issues, we propose prediction-oriented marker selection (PROMISE), which combines SS with CV to conflate the advantages of both methods. Our application of PROMISE with the lasso and elastic net in data analysis shows that, compared to CV, PROMISE produces sparse solutions, few false positives, and small type I + type II error, and maintains good prediction accuracy, with a marginal decrease in the true positive rates. Compared to SS, PROMISE offers better prediction accuracy and true positive rates. In summary, PROMISE can be applied in many fields to select regularization parameters when the goals are to minimize false positives and maximize prediction accuracy.

Methods for constraining fine structure constant evolution with OH microwave transitions.

PubMed

Darling, Jeremy

2003-07-04

We investigate the constraints that OH microwave transitions in megamasers and molecular absorbers at cosmological distances may place on the evolution of the fine structure constant alpha=e(2)/ variant Planck's over 2pi c. The centimeter OH transitions are a combination of hyperfine splitting and lambda doubling that can constrain the cosmic evolution of alpha from a single species, avoiding systematic errors in alpha measurements from multiple species which may have relative velocity offsets. The most promising method compares the 18 and 6 cm OH lines, includes a calibration of systematic errors, and offers multiple determinations of alpha in a single object. Comparisons of OH lines to the HI 21 cm line and CO rotational transitions also show promise.

"La Palabra Es Salud" (The Word Is Health): Combining Mixed Methods and CBPR to Understand the Comparative Effectiveness of Popular and Conventional Education

ERIC Educational Resources Information Center

Wiggins, Noelle; Hughes, Adele; Rodriguez, Adriana; Potter, Catherine; Rios-Campos, Teresa

2014-01-01

Increasing recognition of the role of social conditions in health has led to calls for methods that can be used to change social conditions. Popular education has demonstrated great promise as a methodology that can be used to address the underlying social and structural determinants of health. To date, most studies of popular education have used…

Sequential neural text compression.

PubMed

Schmidhuber, J; Heil, S

1996-01-01

The purpose of this paper is to show that neural networks may be promising tools for data compression without loss of information. We combine predictive neural nets and statistical coding techniques to compress text files. We apply our methods to certain short newspaper articles and obtain compression ratios exceeding those of the widely used Lempel-Ziv algorithms (which build the basis of the UNIX functions "compress" and "gzip"). The main disadvantage of our methods is that they are about three orders of magnitude slower than standard methods.

Linearized image reconstruction method for ultrasound modulated electrical impedance tomography based on power density distribution

NASA Astrophysics Data System (ADS)

Song, Xizi; Xu, Yanbin; Dong, Feng

2017-04-01

Electrical resistance tomography (ERT) is a promising measurement technique with important industrial and clinical applications. However, with limited effective measurements, it suffers from poor spatial resolution due to the ill-posedness of the inverse problem. Recently, there has been an increasing research interest in hybrid imaging techniques, utilizing couplings of physical modalities, because these techniques obtain much more effective measurement information and promise high resolution. Ultrasound modulated electrical impedance tomography (UMEIT) is one of the newly developed hybrid imaging techniques, which combines electric and acoustic modalities. A linearized image reconstruction method based on power density is proposed for UMEIT. The interior data, power density distribution, is adopted to reconstruct the conductivity distribution with the proposed image reconstruction method. At the same time, relating the power density change to the change in conductivity, the Jacobian matrix is employed to make the nonlinear problem into a linear one. The analytic formulation of this Jacobian matrix is derived and its effectiveness is also verified. In addition, different excitation patterns are tested and analyzed, and opposite excitation provides the best performance with the proposed method. Also, multiple power density distributions are combined to implement image reconstruction. Finally, image reconstruction is implemented with the linear back-projection (LBP) algorithm. Compared with ERT, with the proposed image reconstruction method, UMEIT can produce reconstructed images with higher quality and better quantitative evaluation results.

Binary Classification of a Large Collection of Environmental Chemicals from Estrogen Receptor Assays by Quantitative Structure-Activity Relationship and Machine Learning Methods

EPA Science Inventory

ABSTRACT: There are thousands of environmental chemicals subject to regulatory decisions for endocrine disrupting potential. A promising approach to manage this large universe of untested chemicals is to use a prioritization filter that combines in vitro assays with in silico QSA...

Designing Coherent Science Education: Implications for Curriculum, Instruction, and Policy. Technology, Education--Connections (TEC) Series

ERIC Educational Resources Information Center

Kali, Yael, Ed.; Linn, Marcia, Ed.; Roseman, Jo Ellen, Ed.

2008-01-01

This edited collection synthesizes current research on the most promising methods and models for designing coherent science instruction. Arising from the National Science Foundation-funded Delineating and Evaluating Coherent Instructional Designs for Education (DECIDE) project, this volume combines the insights of researchers from two Centers for…

Single-pulse enhanced coherent diffraction imaging of bacteria with an X-ray free-electron laser

NASA Astrophysics Data System (ADS)

Fan, Jiadong; Sun, Zhibin; Wang, Yaling; Park, Jaehyun; Kim, Sunam; Gallagher-Jones, Marcus; Kim, Yoonhee; Song, Changyong; Yao, Shengkun; Zhang, Jian; Zhang, Jianhua; Duan, Xiulan; Tono, Kensuke; Yabashi, Makina; Ishikawa, Tetsuya; Fan, Chunhai; Zhao, Yuliang; Chai, Zhifang; Gao, Xueyun; Earnest, Thomas; Jiang, Huaidong

2016-09-01

High-resolution imaging offers one of the most promising approaches for exploring and understanding the structure and function of biomaterials and biological systems. X-ray free-electron lasers (XFELs) combined with coherent diffraction imaging can theoretically provide high-resolution spatial information regarding biological materials using a single XFEL pulse. Currently, the application of this method suffers from the low scattering cross-section of biomaterials and X-ray damage to the sample. However, XFELs can provide pulses of such short duration that the data can be collected using the “diffract and destroy” approach before the effects of radiation damage on the data become significant. These experiments combine the use of enhanced coherent diffraction imaging with single-shot XFEL radiation to investigate the cellular architecture of Staphylococcus aureus with and without labeling by gold (Au) nanoclusters. The resolution of the images reconstructed from these diffraction patterns were twice as high or more for gold-labeled samples, demonstrating that this enhancement method provides a promising approach for the high-resolution imaging of biomaterials and biological systems.

Single-pulse enhanced coherent diffraction imaging of bacteria with an X-ray free-electron laser

PubMed Central

Fan, Jiadong; Sun, Zhibin; Wang, Yaling; Park, Jaehyun; Kim, Sunam; Gallagher-Jones, Marcus; Kim, Yoonhee; Song, Changyong; Yao, Shengkun; Zhang, Jian; Zhang, Jianhua; Duan, Xiulan; Tono, Kensuke; Yabashi, Makina; Ishikawa, Tetsuya; Fan, Chunhai; Zhao, Yuliang; Chai, Zhifang; Gao, Xueyun; Earnest, Thomas; Jiang, Huaidong

2016-01-01

High-resolution imaging offers one of the most promising approaches for exploring and understanding the structure and function of biomaterials and biological systems. X-ray free-electron lasers (XFELs) combined with coherent diffraction imaging can theoretically provide high-resolution spatial information regarding biological materials using a single XFEL pulse. Currently, the application of this method suffers from the low scattering cross-section of biomaterials and X-ray damage to the sample. However, XFELs can provide pulses of such short duration that the data can be collected using the “diffract and destroy” approach before the effects of radiation damage on the data become significant. These experiments combine the use of enhanced coherent diffraction imaging with single-shot XFEL radiation to investigate the cellular architecture of Staphylococcus aureus with and without labeling by gold (Au) nanoclusters. The resolution of the images reconstructed from these diffraction patterns were twice as high or more for gold-labeled samples, demonstrating that this enhancement method provides a promising approach for the high-resolution imaging of biomaterials and biological systems. PMID:27659203

Single-pulse enhanced coherent diffraction imaging of bacteria with an X-ray free-electron laser.

PubMed

Fan, Jiadong; Sun, Zhibin; Wang, Yaling; Park, Jaehyun; Kim, Sunam; Gallagher-Jones, Marcus; Kim, Yoonhee; Song, Changyong; Yao, Shengkun; Zhang, Jian; Zhang, Jianhua; Duan, Xiulan; Tono, Kensuke; Yabashi, Makina; Ishikawa, Tetsuya; Fan, Chunhai; Zhao, Yuliang; Chai, Zhifang; Gao, Xueyun; Earnest, Thomas; Jiang, Huaidong

2016-09-23

High-resolution imaging offers one of the most promising approaches for exploring and understanding the structure and function of biomaterials and biological systems. X-ray free-electron lasers (XFELs) combined with coherent diffraction imaging can theoretically provide high-resolution spatial information regarding biological materials using a single XFEL pulse. Currently, the application of this method suffers from the low scattering cross-section of biomaterials and X-ray damage to the sample. However, XFELs can provide pulses of such short duration that the data can be collected using the "diffract and destroy" approach before the effects of radiation damage on the data become significant. These experiments combine the use of enhanced coherent diffraction imaging with single-shot XFEL radiation to investigate the cellular architecture of Staphylococcus aureus with and without labeling by gold (Au) nanoclusters. The resolution of the images reconstructed from these diffraction patterns were twice as high or more for gold-labeled samples, demonstrating that this enhancement method provides a promising approach for the high-resolution imaging of biomaterials and biological systems.

Full skin quantitative optical coherence elastography achieved by combining vibration and surface acoustic wave methods

NASA Astrophysics Data System (ADS)

Li, Chunhui; Guan, Guangying; Huang, Zhihong; Wang, Ruikang K.; Nabi, Ghulam

2015-03-01

By combining with the phase sensitive optical coherence tomography (PhS-OCT), vibration and surface acoustic wave (SAW) methods have been reported to provide elastography of skin tissue respectively. However, neither of these two methods can provide the elastography in full skin depth in current systems. This paper presents a feasibility study on an optical coherence elastography method which combines both vibration and SAW in order to give the quantitative mechanical properties of skin tissue with full depth range, including epidermis, dermis and subcutaneous fat. Experiments are carried out on layered tissue mimicking phantoms and in vivo human forearm and palm skin. A ring actuator generates vibration while a line actuator were used to excited SAWs. A PhS-OCT system is employed to provide the ultrahigh sensitive measurement of the generated waves. The experimental results demonstrate that by the combination of vibration and SAW method the full skin bulk mechanical properties can be quantitatively measured and further the elastography can be obtained with a sensing depth from ~0mm to ~4mm. This method is promising to apply in clinics where the quantitative elasticity of localized skin diseases is needed to aid the diagnosis and treatment.

Arrow-wing supersonic cruise aircraft structural design concepts evaluation. Volume 3: Sections 12 through 14

NASA Technical Reports Server (NTRS)

Sakata, I. F.; Davis, G. W.

1975-01-01

The design of an economically viable supersonic cruise aircraft requires the lowest attainable structural-mass fraction commensurate with the selected near-term structural material technology. To achieve this goal of minimum structural-mass fraction, various combinations of promising wing and fuselage primary structure were analyzed for the load-temperature environment applicable to the arrow wing configuration. This analysis was conducted in accordance with the design criteria specified and included extensive use of computer-aided analytical methods to screen the candidate concepts and select the most promising concepts for the in-depth structural analysis.

Combined process "helical rolling-pressing" and its effect on the microstructure of ferrous and non-ferrous materials

NASA Astrophysics Data System (ADS)

Naizabekov, Abdrakhman; Lezhnev, Sergey; Arbuz, Alexandr; Panin, Evgeniy

2018-02-01

Ultrafine-grained materials are one of the most promising structural and functional materials. However, the known methods of obtaining them are not enough powerful and technologically advanced for profitable industrial applications. Development of the combined process "helical rolling-pressing" is an attempt to bring technology to produce ultrafine-grained materials to the industry. The combination of intense processing of the surface by helical rolling and the entire cross section of workpiece in equal channel angular matrix, with intense deformation by torsion between rolls and matrix will increase the degree of deformation per pass and allows to mutually compensate disadvantages of these methods in the case of their separate use. This paper describes the development of a laboratory stand and study of influence of combined process "helical rolling-pressing"on the microstructure of tool steel, technical copper and high alloy stainless high-temperature steel.

Template-grown NiFe/Cu/NiFe nanowires for spin transfer devices.

PubMed

Piraux, Luc; Renard, Krystel; Guillemet, Raphael; Matéfi-Tempfli, Stefan; Matéfi-Tempfli, Maria; Antohe, Vlad Andrei; Fusil, Stéphane; Bouzehouane, Karim; Cros, Vincent

2007-09-01

We have developed a new reliable method combining template synthesis and nanolithography-based contacting technique to elaborate current perpendicular-to-plane giant magnetoresistance spin valve nanowires, which are very promising for the exploration of electrical spin transfer phenomena. The method allows the electrical connection of one single nanowire in a large assembly of wires embedded in anodic porous alumina supported on Si substrate with diameters and periodicities to be controllable to a large extent. Both magnetic excitations and switching phenomena driven by a spin-polarized current were clearly demonstrated in our electrodeposited NiFe/Cu/ NiFe trilayer nanowires. This novel approach promises to be of strong interest for subsequent fabrication of phase-locked arrays of spin transfer nano-oscillators with increased output power for microwave applications.

Drug combination studies of curcumin and genistein against rhodesain of Trypanosoma brucei rhodesiense.

PubMed

Ettari, Roberta; Previti, Santo; Maiorana, Santina; Allegra, Alessandro; Schirmeister, Tanja; Grasso, Silvana; Zappalà, Maria

2018-06-13

Curcumin and genistein are two natural products obtained from Curcuma longa L. and soybeans, endowed with many biological properties. Within the last years they were shown to possess also a promising antitrypanosomal activity. In the present paper, we investigated the activity of both curcumin and genistein against rhodesain, the main cysteine protease of Trypanosoma brucei rhodesiense; drug combination studies, according to Chou and Talalay method, allowed us to demonstrate a potent synergistic effect for the combination curcumin-genistein. As a matter of fact, with our experiments we observed that the combination index of curcumin-genistein is < 1 for the reduction from 10 to 90% of rhodesain activity.

NLEAP/GIS approach for identifying and mitigating regional nitrate-nitrogen leaching

USGS Publications Warehouse

Shaffer, M.J.; Hall, M.D.; Wylie, B.K.; Wagner, D.G.; Corwin, D.L.; Loague, K.

1996-01-01

Improved simulation-based methodology is needed to help identify broad geographical areas where potential NO3-N leaching may be occurring from agriculture and suggest management alternatives that minimize the problem. The Nitrate Leaching and Economic Analysis Package (NLEAP) model was applied to estimate regional NO3-N leaching in eastern Colorado. Results show that a combined NLEAP/GIS technology can be used to identify potential NO3-N hot spots in shallow alluvial aquifers under irrigated agriculture. The NLEAP NO3-N Leached (NL) index provided the most promising single index followed by NO3-N Available for Leaching (NAL). The same combined technology also shows promise in identifying Best Management Practice (BMP) methods that help minimize NO3-N leaching in vulnerable areas. Future plans call for linkage of the NLEAP/GIS procedures with groundwater modeling to establish a mechanistic analysis of agriculture-aquifer interactions at a regional scale.

[Mixed methods research in public health: issues and illustration].

PubMed

Guével, Marie-Renée; Pommier, Jeanine

2012-01-01

For many years, researchers in a range of fields have combined quantitative and qualitative methods. However, the combined use of quantitative and qualitative methods has only recently been conceptualized and defined as mixed methods research. Some authors have described the emerging field as a third methodological tradition (in addition to the qualitative and quantitative traditions). Mixed methods research combines different perspectives and facilitates the study of complex interventions or programs, particularly in public health, an area where interdisciplinarity is critical. However, the existing literature is primarily in English. By contrast, the literature in French remains limited. The purpose of this paper is to present the emergence of mixed methods research for francophone public health specialists. A literature review was conducted to identify the main characteristics of mixed methods research. The results provide an overall picture of the mixed methods approach through its history, definitions, and applications, and highlight the tools developed to clarify the approach (typologies) and to implement it (integration of results and quality standards). The tools highlighted in the literature review are illustrated by a study conducted in France. Mixed methods research opens new possibilities for examining complex research questions and provides relevant and promising opportunities for addressing current public health issues in France.

Combined Enzymatic and Mechanical Cell Disruption and Lipid Extraction of Green Alga Neochloris oleoabundans

PubMed Central

Wang, Dongqin; Li, Yanqun; Hu, Xueqiong; Su, Weimin; Zhong, Min

2015-01-01

Microalgal biodiesel is one of the most promising renewable fuels. The wet technique for lipids extraction has advantages over the dry method, such as energy-saving and shorter procedure. The cell disruption is a key factor in wet oil extraction to facilitate the intracellular oil release. Ultrasonication, high-pressure homogenization, enzymatic hydrolysis and the combination of enzymatic hydrolysis with high-pressure homogenization and ultrasonication were employed in this study to disrupt the cells of the microalga Neochloris oleoabundans. The cell disruption degree was investigated. The cell morphology before and after disruption was assessed with scanning and transmission electron microscopy. The energy requirements and the operation cost for wet cell disruption were also estimated. The highest disruption degree, up to 95.41%, assessed by accounting method was achieved by the combination of enzymatic hydrolysis and high-pressure homogenization. A lipid recovery of 92.6% was also obtained by the combined process. The combined process was found to be more efficient and economical compared with the individual process. PMID:25853267

How bootstrap can help in forecasting time series with more than one seasonal pattern

NASA Astrophysics Data System (ADS)

Cordeiro, Clara; Neves, M. Manuela

2012-09-01

The search for the future is an appealing challenge in time series analysis. The diversity of forecasting methodologies is inevitable and is still in expansion. Exponential smoothing methods are the launch platform for modelling and forecasting in time series analysis. Recently this methodology has been combined with bootstrapping revealing a good performance. The algorithm (Boot. EXPOS) using exponential smoothing and bootstrap methodologies, has showed promising results for forecasting time series with one seasonal pattern. In case of more than one seasonal pattern, the double seasonal Holt-Winters methods and the exponential smoothing methods were developed. A new challenge was now to combine these seasonal methods with bootstrap and carry over a similar resampling scheme used in Boot. EXPOS procedure. The performance of such partnership will be illustrated for some well-know data sets existing in software.

Printed organo-functionalized graphene for biosensing applications.

PubMed

Wisitsoraat, A; Mensing, J Ph; Karuwan, C; Sriprachuabwong, C; Jaruwongrungsee, K; Phokharatkul, D; Daniels, T M; Liewhiran, C; Tuantranont, A

2017-01-15

Graphene is a highly promising material for biosensors due to its excellent physical and chemical properties which facilitate electron transfer between the active locales of enzymes or other biomaterials and a transducer surface. Printing technology has recently emerged as a low-cost and practical method for fabrication of flexible and disposable electronics devices. The combination of these technologies is promising for the production and commercialization of low cost sensors. In this review, recent developments in organo-functionalized graphene and printed biosensor technologies are comprehensively covered. Firstly, various methods for printing graphene-based fluids on different substrates are discussed. Secondly, different graphene-based ink materials and preparation methods are described. Lastly, biosensing performances of printed or printable graphene-based electrochemical and field effect transistor sensors for some important analytes are elaborated. The reported printed graphene based sensors exhibit promising properties with good reliability suitable for commercial applications. Among most reports, only a few printed graphene-based biosensors including screen-printed oxidase-functionalized graphene biosensor have been demonstrated. The technology is still at early stage but rapidly growing and will earn great attention in the near future due to increasing demand of low-cost and disposable biosensors. Copyright © 2016 Elsevier B.V. All rights reserved.

Near-edge band structures and band gaps of Cu-based semiconductors predicted by the modified Becke-Johnson potential plus an on-site Coulomb U

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

Zhang, Yubo; Zhang, Jiawei; Wang, Youwei

Diamond-like Cu-based multinary semiconductors are a rich family of materials that hold promise in a wide range of applications. Unfortunately, accurate theoretical understanding of the electronic properties of these materials is hindered by the involvement of Cu d electrons. Density functional theory (DFT) based calculations using the local density approximation or generalized gradient approximation often give qualitative wrong electronic properties of these materials, especially for narrow-gap systems. The modified Becke-Johnson (mBJ) method has been shown to be a promising alternative to more elaborate theory such as the GW approximation for fast materials screening and predictions. However, straightforward applications of themore » mBJ method to these materials still encounter significant difficulties because of the insufficient treatment of the localized d electrons. We show that combining the promise of mBJ potential and the spirit of the well-established DFT + U method leads to a much improved description of the electronic structures, including the most challenging narrow-gap systems. A survey of the band gaps of about 20 Cu-based semiconductors calculated using the mBJ + U method shows that the results agree with reliable values to within ±0.2 eV.« less

High-performance single CdS nanowire (nanobelt) Schottky junction solar cells with Au/graphene Schottky electrodes.

PubMed

Ye, Yu; Dai, Yu; Dai, Lun; Shi, Zujin; Liu, Nan; Wang, Fei; Fu, Lei; Peng, Ruomin; Wen, Xiaonan; Chen, Zhijian; Liu, Zhongfan; Qin, Guogang

2010-12-01

High-performance single CdS nanowire (NW) as well as nanobelt (NB) Schottky junction solar cells were fabricated. Au (5 nm)/graphene combined layers were used as the Schottky contact electrodes to the NWs (NBs). Typical as-fabricated NW solar cell shows excellent photovoltaic behavior with an open circuit voltage of ∼0.15 V, a short circuit current of ∼275.0 pA, and an energy conversion efficiency of up to ∼1.65%. The physical mechanism of the combined Schottky electrode was discussed. We attribute the prominent capability of the devices to the high-performance Schottky combined electrode, which has the merits of low series resistance, high transparency, and good Schottky contact to the CdS NW (NB). Besides, a promising site-controllable patterned graphene transfer method, which has the advantages of economizing graphene material and free from additional etching process, was demonstrated in this work. Our results suggest that semiconductor NWs (NBs) are promising materials for novel solar cells, which have potential application in integrated nano-optoelectronic systems.

Enhanced biodegradation of antibiotic combinations via the sequential treatment of the sludge resulting from pharmaceutical wastewater treatment using white-rot fungi Trametes versicolor and Bjerkandera adusta.

PubMed

Aydin, Sevcan

2016-07-01

While anaerobic treatment is capable of treating pharmaceutical wastewater and removing antibiotics in liquid phases, solid phases may still contain significant amounts of antibiotics following this treatment. The main goal of this study was to evaluate the use of white-rot fungi to remove erythromycin, sulfamethoxazole, and tetracycline combinations from biosolids. The degradation potential of Trametes versicolor and Bjerkandera adusta was evaluated via the sequential treatment of anaerobic sludge. Polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE) analyses were used to identify competition between the autochthonous microbial communities and white-rot fungi. Solid-phase treatment using white-rot fungi substantially reduced antibiotic concentrations and toxicity in sludge. According to PCR-DGGE results, there is an association between species of fungus and antibiotic type as a result of the different transformation pathways of fungal strains. Fungal post-treatment of sludge represents a promising method of removing antibiotic combinations, therefore holding a significant promise as an environmentally friendly means of degrading the antibiotics present in sludge.

Automatic Fringe Detection for Oil Film Interferometry Measurement of Skin Friction

NASA Technical Reports Server (NTRS)

Naughton, Jonathan W.; Decker, Robert K.; Jafari, Farhad

2001-01-01

This report summarizes two years of work on investigating algorithms for automatically detecting fringe patterns in images acquired using oil-drop interferometry for the determination of skin friction. Several different analysis methods were tested, and a combination of a windowed Fourier transform followed by a correlation was found to be most effective. The implementation of this method is discussed and details of the process are described. The results indicate that this method shows promise for automating the fringe detection process, but further testing is required.

Machine Learning Applications to Resting-State Functional MR Imaging Analysis.

PubMed

Billings, John M; Eder, Maxwell; Flood, William C; Dhami, Devendra Singh; Natarajan, Sriraam; Whitlow, Christopher T

2017-11-01

Machine learning is one of the most exciting and rapidly expanding fields within computer science. Academic and commercial research entities are investing in machine learning methods, especially in personalized medicine via patient-level classification. There is great promise that machine learning methods combined with resting state functional MR imaging will aid in diagnosis of disease and guide potential treatment for conditions thought to be impossible to identify based on imaging alone, such as psychiatric disorders. We discuss machine learning methods and explore recent advances. Copyright © 2017 Elsevier Inc. All rights reserved.

Emerging treatments for traumatic brain injury

PubMed Central

Xiong, Ye; Mahmood, Asim; Chopp, Michael

2009-01-01

Background This review summarizes promising approaches for the treatment of traumatic brain injury (TBI), which are either in preclinical or clinical trials. Objective The pathophysiology underlying neurological deficits after TBI is described. An overview of select therapies for TBI with neuroprotective and neurorestorative effects is presented. Methods A literature review of pre-clinical TBI studies and clinical TBI trials related to neuroprotective and neurorestorative therapeutic approaches is provided. Results/conclusion Nearly all phase II/III clinical trials in neuroprotection have failed to show any consistent improvement in outcome for TBI patients. The next decade will witness an increasing number of clinical trials which seek to translate preclinical research discoveries to the clinic. Promising drug- or cell-based therapeutic approaches include erythropoietin and its carbamylated form, statins, bone marrow stromal cells, stem cells singularly or in combination or with biomaterials to reduce brain injury via neuroprotection and promote brain remodeling via angiogenesis, neurogenesis, and synaptogenesis with a final goal to improve functional outcome of TBI patients. In addition, enriched environment and voluntary physical exercise show promise in promoting functional outcome after TBI, and should be evaluated alone or in combination with other treatments as therapeutic approaches for TBI. PMID:19249984

Assessment of the Evolution of Cancer Treatment Therapies

PubMed Central

Arruebo, Manuel; Vilaboa, Nuria; Sáez-Gutierrez, Berta; Lambea, Julio; Tres, Alejandro; Valladares, Mónica; González-Fernández, África

2011-01-01

Cancer therapy has been characterized throughout history by ups and downs, not only due to the ineffectiveness of treatments and side effects, but also by hope and the reality of complete remission and cure in many cases. Within the therapeutic arsenal, alongside surgery in the case of solid tumors, are the antitumor drugs and radiation that have been the treatment of choice in some instances. In recent years, immunotherapy has become an important therapeutic alternative, and is now the first choice in many cases. Nanotechnology has recently arrived on the scene, offering nanostructures as new therapeutic alternatives for controlled drug delivery, for combining imaging and treatment, applying hyperthermia, and providing directed target therapy, among others. These therapies can be applied either alone or in combination with other components (antibodies, peptides, folic acid, etc.). In addition, gene therapy is also offering promising new methods for treatment. Here, we present a review of the evolution of cancer treatments, starting with chemotherapy, surgery, radiation and immunotherapy, and moving on to the most promising cutting-edge therapies (gene therapy and nanomedicine). We offer an historical point of view that covers the arrival of these therapies to clinical practice and the market, and the promises and challenges they present. PMID:24212956

Efficient propagation of the hierarchical equations of motion using the matrix product state method

NASA Astrophysics Data System (ADS)

Shi, Qiang; Xu, Yang; Yan, Yaming; Xu, Meng

2018-05-01

We apply the matrix product state (MPS) method to propagate the hierarchical equations of motion (HEOM). It is shown that the MPS approximation works well in different type of problems, including boson and fermion baths. The MPS method based on the time-dependent variational principle is also found to be applicable to HEOM with over one thousand effective modes. Combining the flexibility of the HEOM in defining the effective modes and the efficiency of the MPS method thus may provide a promising tool in simulating quantum dynamics in condensed phases.

Using Active Learning for Speeding up Calibration in Simulation Models

PubMed Central

Cevik, Mucahit; Ali Ergun, Mehmet; Stout, Natasha K.; Trentham-Dietz, Amy; Craven, Mark; Alagoz, Oguzhan

2015-01-01

Background Most cancer simulation models include unobservable parameters that determine the disease onset and tumor growth. These parameters play an important role in matching key outcomes such as cancer incidence and mortality and their values are typically estimated via lengthy calibration procedure, which involves evaluating large number of combinations of parameter values via simulation. The objective of this study is to demonstrate how machine learning approaches can be used to accelerate the calibration process by reducing the number of parameter combinations that are actually evaluated. Methods Active learning is a popular machine learning method that enables a learning algorithm such as artificial neural networks to interactively choose which parameter combinations to evaluate. We develop an active learning algorithm to expedite the calibration process. Our algorithm determines the parameter combinations that are more likely to produce desired outputs, therefore reduces the number of simulation runs performed during calibration. We demonstrate our method using previously developed University of Wisconsin Breast Cancer Simulation Model (UWBCS). Results In a recent study, calibration of the UWBCS required the evaluation of 378,000 input parameter combinations to build a race-specific model and only 69 of these combinations produced results that closely matched observed data. By using the active learning algorithm in conjunction with standard calibration methods, we identify all 69 parameter combinations by evaluating only 5620 of the 378,000 combinations. Conclusion Machine learning methods hold potential in guiding model developers in the selection of more promising parameter combinations and hence speeding up the calibration process. Applying our machine learning algorithm to one model shows that evaluating only 1.49% of all parameter combinations would be sufficient for the calibration. PMID:26471190

Process optimization using combinatorial design principles: parallel synthesis and design of experiment methods.

PubMed

Gooding, Owen W

2004-06-01

The use of parallel synthesis techniques with statistical design of experiment (DoE) methods is a powerful combination for the optimization of chemical processes. Advances in parallel synthesis equipment and easy to use software for statistical DoE have fueled a growing acceptance of these techniques in the pharmaceutical industry. As drug candidate structures become more complex at the same time that development timelines are compressed, these enabling technologies promise to become more important in the future.

Artificial intelligence in drug combination therapy.

PubMed

Tsigelny, Igor F

2018-02-09

Currently, the development of medicines for complex diseases requires the development of combination drug therapies. It is necessary because in many cases, one drug cannot target all necessary points of intervention. For example, in cancer therapy, a physician often meets a patient having a genomic profile including more than five molecular aberrations. Drug combination therapy has been an area of interest for a while, for example the classical work of Loewe devoted to the synergism of drugs was published in 1928-and it is still used in calculations for optimal drug combinations. More recently, over the past several years, there has been an explosion in the available information related to the properties of drugs and the biomedical parameters of patients. For the drugs, hundreds of 2D and 3D molecular descriptors for medicines are now available, while for patients, large data sets related to genetic/proteomic and metabolomics profiles of the patients are now available, as well as the more traditional data relating to the histology, history of treatments, pretreatment state of the organism, etc. Moreover, during disease progression, the genetic profile can change. Thus, the ability to optimize drug combinations for each patient is rapidly moving beyond the comprehension and capabilities of an individual physician. This is the reason, that biomedical informatics methods have been developed and one of the more promising directions in this field is the application of artificial intelligence (AI). In this review, we discuss several AI methods that have been successfully implemented in several instances of combination drug therapy from HIV, hypertension, infectious diseases to cancer. The data clearly show that the combination of rule-based expert systems with machine learning algorithms may be promising direction in this field. © The Author(s) 2018. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Mapping biomass for a northern forest ecosystem using multi-frequency SAR data

NASA Technical Reports Server (NTRS)

Ranson, K. J.; Sun, Guoqing

1992-01-01

Image processing methods for mapping standing biomass for a forest in Maine, using NASA/JPL airborne synthetic aperture radar (AIRSAR) polarimeter data, are presented. By examining the dependence of backscattering on standing biomass, it is determined that the ratio of HV backscattering from a longer wavelength (P- or L-band) to a shorter wavelength (C) is a good combination for mapping total biomass. This ratio enhances the correlation of the image signature to the standing biomass and compensates for a major part of the variations in backscattering attributed to radar incidence angle. The image processing methods used include image calibration, ratioing, filtering, and segmentation. The image segmentation algorithm uses both means and variances of the image, and it is combined with the image filtering process. Preliminary assessment of the resultant biomass maps suggests that this is a promising method.

A combined positron emission tomography (PET)-electron paramagnetic resonance imaging (EPRI) system: initial evaluation of a prototype scanner

NASA Astrophysics Data System (ADS)

Tseytlin, Mark; Stolin, Alexander V.; Guggilapu, Priyaankadevi; Bobko, Andrey A.; Khramtsov, Valery V.; Tseytlin, Oxana; Raylman, Raymond R.

2018-05-01

The advent of hybrid scanners, combining complementary modalities, has revolutionized the application of advanced imaging technology to clinical practice and biomedical research. In this project, we investigated the melding of two complementary, functional imaging methods: positron emission tomography (PET) and electron paramagnetic resonance imaging (EPRI). PET radiotracers can provide important information about cellular parameters, such as glucose metabolism. While EPR probes can provide assessment of tissue microenvironment, measuring oxygenation and pH, for example. Therefore, a combined PET/EPRI scanner promises to provide new insights not attainable with current imagers by simultaneous acquisition of multiple components of tissue microenvironments. To explore the simultaneous acquisition of PET and EPR images, a prototype system was created by combining two existing scanners. Specifically, a silicon photomultiplier (SiPM)-based PET scanner ring designed as a portable scanner was combined with an EPRI scanner designed for the imaging of small animals. The ability of the system to obtain simultaneous images was assessed with a small phantom consisting of four cylinders containing both a PET tracer and EPR spin probe. The resulting images demonstrated the ability to obtain contemporaneous PET and EPR images without cross-modality interference. Given the promising results from this initial investigation, the next step in this project is the construction of the next generation pre-clinical PET/EPRI scanner for multi-parametric assessment of physiologically-important parameters of tissue microenvironments.

Degradation of organic wastewater by hydrodynamic cavitation combined with acoustic cavitation.

PubMed

Yi, Chunhai; Lu, Qianqian; Wang, Yun; Wang, Yixuan; Yang, Bolun

2018-05-01

In this paper, the decomposition of Rhodamine B (RhB) by hydrodynamic cavitation (HC), acoustic cavitation (AC) and the combination of these individual methods (HAC) have been investigated. The degradation of 20 L RhB aqueous solution was carried out in a self-designed HAC reactor, where hydrodynamic cavitation and acoustic cavitation could take place in the same space simultaneously. The effects of initial concentration, inlet pressure, solution temperature and ultrasonic power were studied and discussed. Obvious synergies were found in the HAC process. The combined method achieved the best conversion, and the synergistic effect in HAC was even up to 119% with the ultrasonic power of 220 W in a treatment time of 30 min. The time-independent synergistic factor based on rate constant was introduced and the maximum value reached 40% in the HAC system. Besides, the hybrid HAC method showed great superiority in energy efficiency at lower ultrasonic power (88-176 W). Therefore, HAC technology can be visualized as a promising method for wastewater treatment with good scale-up possibilities. Copyright © 2018 Elsevier B.V. All rights reserved.

Completely non-destructive elemental analysis of bulky samples by PGAA

NASA Astrophysics Data System (ADS)

Oura, Y.; Nakahara, H.; Sueki, K.; Sato, W.; Saito, A.; Tomizawa, T.; Nishikawa, T.

1999-01-01

NBAA (neutron beam activation analysis), which is a combination of PGAA and INAA by a single neutron irradiation, using an internal monostandard method is proposed as a very unique and promising method for the elemental analysis of voluminous and invaluable archaeological samples which do not allow even a scrape of the surface. It was applied to chinawares, Sueki ware, and bronze mirrors, and proved to be a very effective method for nondestructive analysis of not only major elements but also some minor elements such as boron that help solve archaeological problems of ears and sites of their production.

Exploring the Feasibility and Benefits of Arts-Based Mindfulness-Based Practices with Young People in Need: Aiming to Improve Aspects of Self-Awareness and Resilience

ERIC Educational Resources Information Center

Coholic, Diana A.

2011-01-01

Research in mindfulness-based methods with young people is just emerging in the practice/research literature. While much of this literature describes promising approaches that combine mindfulness with cognitive-behavioral therapy, this paper describes an innovative research-based group program that teaches young people in need mindfulness-based…

Diamond photonics platform enabled by femtosecond laser writing

PubMed Central

Sotillo, Belén; Bharadwaj, Vibhav; Hadden, J. P.; Sakakura, Masaaki; Chiappini, Andrea; Fernandez, Toney Teddy; Longhi, Stefano; Jedrkiewicz, Ottavia; Shimotsuma, Yasuhiko; Criante, Luigino; Osellame, Roberto; Galzerano, Gianluca; Ferrari, Maurizio; Miura, Kiyotaka; Ramponi, Roberta; Barclay, Paul E.; Eaton, Shane Michael

2016-01-01

Diamond is a promising platform for sensing and quantum processing owing to the remarkable properties of the nitrogen-vacancy (NV) impurity. The electrons of the NV center, largely localized at the vacancy site, combine to form a spin triplet, which can be polarized with 532 nm laser light, even at room temperature. The NV’s states are isolated from environmental perturbations making their spin coherence comparable to trapped ions. An important breakthrough would be in connecting, using waveguides, multiple diamond NVs together optically. However, still lacking is an efficient photonic fabrication method for diamond akin to the photolithographic methods that have revolutionized silicon photonics. Here, we report the first demonstration of three dimensional buried optical waveguides in diamond, inscribed by focused femtosecond high repetition rate laser pulses. Within the waveguides, high quality NV properties are observed, making them promising for integrated magnetometer or quantum information systems on a diamond chip. PMID:27748428

Efficient micropropagation and chlorocholine chloride induced stevioside production of Stevia rebaudiana Bertoni.

PubMed

Dey, Avishek; Kundu, Sayanti; Bandyopadhyay, Abhijit; Bhattacharjee, Aloke

2013-01-01

A promising method of micropropagation of Stevia rebaudiana Bertoni has been developed with an aim to increase the biomass, survivability of the plantlets and stevioside production, using chlorocholine chloride (CCC). Microshoots transferred to the MS medium containing different combinations CCC and IBA were found to be most effective in terms of growth pattern, hardening ability of the plantlets and stevioside content, compared to MS medium containing either IBA or CCC. Among other combinations tested, MS medium supplemented with 3 mg/l CCC and 3 mg/l IBA was found most effective in inducing significant changes like reduced shoot length, increased number of roots, higher leaf size, increased biomass and chlorophyll retaining capacity, higher survival percentage and most importantly the elevated stevioside content. Collectively, the major observations of this research indicate that application of CCC in micropropagation of S. rebaudiana Bertoni is a promising approach and has commercial prospects. Copyright © 2012 Académie des sciences. Published by Elsevier SAS. All rights reserved.

Nisin, alone and combined with peptidoglycan-modulating antibiotics: activity against methicillin-resistant Staphylococcus aureus and vancomycin-resistant enterococci.

PubMed

Brumfitt, W; Salton, M R J; Hamilton-Miller, J M T

2002-11-01

We have sought ways to circumvent resistance, by combining nisin with other antibiotics known to target bacterial cell wall biosynthesis. Twenty strains each of methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant enterococci (VRE) were tested in vitro by standardized methods against nisin alone and combined with bacitracin, ramoplanin and chloramphenicol. Ramoplanin was the most potent compound, and bacitracin had the least activity. Two-way synergy was observed with nisin and ramoplanin. However, chloramphenicol was clearly antagonistic to the activity of nisin. Observations of synergy between nisin and ramoplanin against MRSA and VRE offer a promising approach to the concept of combining nisin with inhibitors of cell wall peptidoglycan. Further investigations are needed in order to develop this approach as a clinical possibility.

The efficacy of a low dose combination of topiramate and naltrexone on ethanol reinforcement and consumption in rat models

PubMed Central

Moore, Catherine F; Protzuk, Omar A; Johnson, Bankole A; Lynch, Wendy J

2013-01-01

Rationale Combined medication approaches, by targeting multiple neurotransmitter systems involved in alcohol use disorders (AUDs), may be more efficacious than single-medication approaches. Objectives We examined, in animals models of consumption and reinforcement, the combined effects of naltrexone (an opioid antagonist) and topiramate (a GABA/glutamate modulator), two medications that have shown promise for treating AUDs, hypothesizing that their combination would be more efficacious than either alone. Methods The effects of naltrexone and topiramate on ethanol consumption were examined in alcohol preferring (P) rats (N=10) and in rats from their background strain (Wistar, N=9) using conditions that induce high levels of consumption (24-hr, 3-bottle, free-choice procedure). Low doses of each medication (1 mg/kg, naltrexone; 10 mg/kg, topiramate) were selected in an attempt to maximize their combined efficacy while minimizing potential side-effects. Their effects on ethanol reinforcement were assessed under a progressive-ratio schedule in additional groups of (N=22) P rats. A moderate dose of topiramate (20 mg/kg) was also included to verify topiramate’s efficacy on its own. Results In P rats, but not Wistar rats, the combination effectively and persistently reduced consumption; whereas, neither dose alone was effective. The combination and naltrexone alone were equally effective at reducing ethanol reinforcement; however, with the combination, but not naltrexone alone, this effect was selective for ethanol. All treatments produced a similar decrease in home-cage food consumption. The 20 mg/kg dose of topiramate also effectively reduced ethanol consumption and reinforcement. Conclusions With greater efficacy and fewer side-effects, the combination shows promise as a treatment for AUDs. PMID:24252444

Gene doping.

PubMed

Haisma, H J; de Hon, O

2006-04-01

Together with the rapidly increasing knowledge on genetic therapies as a promising new branch of regular medicine, the issue has arisen whether these techniques might be abused in the field of sports. Previous experiences have shown that drugs that are still in the experimental phases of research may find their way into the athletic world. Both the World Anti-Doping Agency (WADA) and the International Olympic Committee (IOC) have expressed concerns about this possibility. As a result, the method of gene doping has been included in the list of prohibited classes of substances and prohibited methods. This review addresses the possible ways in which knowledge gained in the field of genetic therapies may be misused in elite sports. Many genes are readily available which may potentially have an effect on athletic performance. The sporting world will eventually be faced with the phenomena of gene doping to improve athletic performance. A combination of developing detection methods based on gene arrays or proteomics and a clear education program on the associated risks seems to be the most promising preventive method to counteract the possible application of gene doping.

Markerless gating for lung cancer radiotherapy based on machine learning techniques

NASA Astrophysics Data System (ADS)

Lin, Tong; Li, Ruijiang; Tang, Xiaoli; Dy, Jennifer G.; Jiang, Steve B.

2009-03-01

In lung cancer radiotherapy, radiation to a mobile target can be delivered by respiratory gating, for which we need to know whether the target is inside or outside a predefined gating window at any time point during the treatment. This can be achieved by tracking one or more fiducial markers implanted inside or near the target, either fluoroscopically or electromagnetically. However, the clinical implementation of marker tracking is limited for lung cancer radiotherapy mainly due to the risk of pneumothorax. Therefore, gating without implanted fiducial markers is a promising clinical direction. We have developed several template-matching methods for fluoroscopic marker-less gating. Recently, we have modeled the gating problem as a binary pattern classification problem, in which principal component analysis (PCA) and support vector machine (SVM) are combined to perform the classification task. Following the same framework, we investigated different combinations of dimensionality reduction techniques (PCA and four nonlinear manifold learning methods) and two machine learning classification methods (artificial neural networks—ANN and SVM). Performance was evaluated on ten fluoroscopic image sequences of nine lung cancer patients. We found that among all combinations of dimensionality reduction techniques and classification methods, PCA combined with either ANN or SVM achieved a better performance than the other nonlinear manifold learning methods. ANN when combined with PCA achieves a better performance than SVM in terms of classification accuracy and recall rate, although the target coverage is similar for the two classification methods. Furthermore, the running time for both ANN and SVM with PCA is within tolerance for real-time applications. Overall, ANN combined with PCA is a better candidate than other combinations we investigated in this work for real-time gated radiotherapy.

Combining fibre optic Raman spectroscopy and tactile resonance measurement for tissue characterization

NASA Astrophysics Data System (ADS)

Candefjord, Stefan; Nyberg, Morgan; Jalkanen, Ville; Ramser, Kerstin; Lindahl, Olof A.

2010-12-01

Tissue characterization is fundamental for identification of pathological conditions. Raman spectroscopy (RS) and tactile resonance measurement (TRM) are two promising techniques that measure biochemical content and stiffness, respectively. They have potential to complement the golden standard--histological analysis. By combining RS and TRM, complementary information about tissue content can be obtained and specific drawbacks can be avoided. The aim of this study was to develop a multivariate approach to compare RS and TRM information. The approach was evaluated on measurements at the same points on porcine abdominal tissue. The measurement points were divided into five groups by multivariate analysis of the RS data. A regression analysis was performed and receiver operating characteristic (ROC) curves were used to compare the RS and TRM data. TRM identified one group efficiently (area under ROC curve 0.99). The RS data showed that the proportion of saturated fat was high in this group. The regression analysis showed that stiffness was mainly determined by the amount of fat and its composition. We concluded that RS provided additional, important information for tissue identification that was not provided by TRM alone. The results are promising for development of a method combining RS and TRM for intraoperative tissue characterization.

Using Active Learning for Speeding up Calibration in Simulation Models.

PubMed

Cevik, Mucahit; Ergun, Mehmet Ali; Stout, Natasha K; Trentham-Dietz, Amy; Craven, Mark; Alagoz, Oguzhan

2016-07-01

Most cancer simulation models include unobservable parameters that determine disease onset and tumor growth. These parameters play an important role in matching key outcomes such as cancer incidence and mortality, and their values are typically estimated via a lengthy calibration procedure, which involves evaluating a large number of combinations of parameter values via simulation. The objective of this study is to demonstrate how machine learning approaches can be used to accelerate the calibration process by reducing the number of parameter combinations that are actually evaluated. Active learning is a popular machine learning method that enables a learning algorithm such as artificial neural networks to interactively choose which parameter combinations to evaluate. We developed an active learning algorithm to expedite the calibration process. Our algorithm determines the parameter combinations that are more likely to produce desired outputs and therefore reduces the number of simulation runs performed during calibration. We demonstrate our method using the previously developed University of Wisconsin breast cancer simulation model (UWBCS). In a recent study, calibration of the UWBCS required the evaluation of 378 000 input parameter combinations to build a race-specific model, and only 69 of these combinations produced results that closely matched observed data. By using the active learning algorithm in conjunction with standard calibration methods, we identify all 69 parameter combinations by evaluating only 5620 of the 378 000 combinations. Machine learning methods hold potential in guiding model developers in the selection of more promising parameter combinations and hence speeding up the calibration process. Applying our machine learning algorithm to one model shows that evaluating only 1.49% of all parameter combinations would be sufficient for the calibration. © The Author(s) 2015.

Toward shrimp consumption without chemicals: Combined effects of freezing and modified atmosphere packaging (MAP) on some quality characteristics of Giant Red Shrimp (Aristaeomorpha foliacea) during storage.

PubMed

Bono, Gioacchino; Okpala, Charles Odilichukwu R; Alberio, Giuseppina R A; Messina, Concetta M; Santulli, Andrea; Giacalone, Gabriele; Spagna, Giovanni

2016-04-15

The combined effects of freezing and modified atmosphere packaging (MAP) (100% N2 and 50% N2+50% CO2) on some quality characteristics of Giant Red Shrimp (GRS) (Aristaeomorpha foliacea) was studied during 12-month storage. In particular, the quality characteristics determined proximal and gas compositions, melanosis scores, pH, total volatile basic-nitrogen (TVB-N), thiobarbituric acid (TBA) as well as free amino acid (FAA). In addition, the emergent data were compared to those subject to vacuum packaging as well as conventional preservative method of sulphite treatment (SUL). Most determined qualities exhibited quantitative differences with storage. By comparisons, while pH and TVB-N statistically varied between treatments (P<0.05) and TBA that ranged between ∼0.15 and 0.30 mg MDA/kg appeared least at end of storage for 100% N2 treated-group, the latter having decreased melanosis scores showed such treatments with high promise to keep the colour of GRS sample hence, potential replacement for SUL group. By comparisons also, while some individual FAA values showed increases especially at the 100% N2-treated group, the total FAAs statistically differed with storage (P<0.05). The combination of freezing and MAP treatments as preservative treatment method shows high promise to influence some quality characteristics of GRS samples of this study. Copyright © 2015 Elsevier Ltd. All rights reserved.

Multimodal autofluorescence detection of cancer: from single cells to living organism

NASA Astrophysics Data System (ADS)

Horilova, J.; Cunderlikova, B.; Cagalinec, M.; Chorvat, D.; Marcek Chorvatova, A.

2018-02-01

Multimodal optical imaging of suspected tissues is showing to be a promising method for distinguishing suspected cancerous tissues from healthy ones. In particular, the combination of steady-state spectroscopic methods with timeresolved fluorescence provides more precise insight into native metabolism when focused on tissue autofluorescence. Cancer is linked to specific metabolic remodelation detectable spectroscopically. In this work, we evaluate possibilities and limitations of multimodal optical cancer detection in single cells, collagen-based 3D cell cultures and in living organisms (whole mice), as a representation of gradually increasing complexity of model systems.

Combination of acoustical radiosity and the image source method.

PubMed

Koutsouris, Georgios I; Brunskog, Jonas; Jeong, Cheol-Ho; Jacobsen, Finn

2013-06-01

A combined model for room acoustic predictions is developed, aiming to treat both diffuse and specular reflections in a unified way. Two established methods are incorporated: acoustical radiosity, accounting for the diffuse part, and the image source method, accounting for the specular part. The model is based on conservation of acoustical energy. Losses are taken into account by the energy absorption coefficient, and the diffuse reflections are controlled via the scattering coefficient, which defines the portion of energy that has been diffusely reflected. The way the model is formulated allows for a dynamic control of the image source production, so that no fixed maximum reflection order is required. The model is optimized for energy impulse response predictions in arbitrary polyhedral rooms. The predictions are validated by comparison with published measured data for a real music studio hall. The proposed model turns out to be promising for acoustic predictions providing a high level of detail and accuracy.

A new approach in space-time analysis of multivariate hydrological data: Application to Brazil's Nordeste region rainfall

NASA Astrophysics Data System (ADS)

Sicard, Emeline; Sabatier, Robert; Niel, HéLèNe; Cadier, Eric

2002-12-01

The objective of this paper is to implement an original method for spatial and multivariate data, combining a method of three-way array analysis (STATIS) with geostatistical tools. The variables of interest are the monthly amounts of rainfall in the Nordeste region of Brazil, recorded from 1937 to 1975. The principle of the technique is the calculation of a linear combination of the initial variables, containing a large part of the initial variability and taking into account the spatial dependencies. It is a promising method that is able to analyze triple variability: spatial, seasonal, and interannual. In our case, the first component obtained discriminates a group of rain gauges, corresponding approximately to the Agreste, from all the others. The monthly variables of July and August strongly influence this separation. Furthermore, an annual study brings out the stability of the spatial structure of components calculated for each year.

A review of combinations of electrokinetic applications.

PubMed

Moghadam, Mohamad Jamali; Moayedi, Hossein; Sadeghi, Masoud Mirmohamad; Hajiannia, Alborz

2016-12-01

Anthropogenic activities contaminate many lands and underground waters with dangerous materials. Although polluted soils occupy small parts of the land, the risk they pose to plants, animals, humans, and groundwater is too high. Remediation technologies have been used for many years in order to mitigate pollution or remove pollutants from soils. However, there are some deficiencies in the remediation in complex site conditions such as low permeability and complex composition of some clays or heterogeneous subsurface conditions. Electrokinetic is an effective method in which electrodes are embedded in polluted soil, usually vertically but in some cases horizontally, and a low direct current voltage gradient is applied between the electrodes. The electric gradient initiates movement of contaminants by electromigration (charged chemical movement), electro-osmosis (movement of fluid), electrolysis (chemical reactions due to the electric field), and diffusion. However, sites that are contaminated with heavy metals or mixed contaminants (e.g. a combination of organic compounds with heavy metals and/or radionuclides) are difficult to remediate. There is no technology that can achieve the best results, but combining electrokinetic with other remediation methods, such as bioremediation and geosynthetics, promises to be the most effective method so far. This review focuses on the factors that affect electrokinetic remediation and the state-of-the-art methods that can be combined with electrokinetic.

LORAKS Makes Better SENSE: Phase-Constrained Partial Fourier SENSE Reconstruction without Phase Calibration

PubMed Central

Kim, Tae Hyung; Setsompop, Kawin; Haldar, Justin P.

2016-01-01

Purpose Parallel imaging and partial Fourier acquisition are two classical approaches for accelerated MRI. Methods that combine these approaches often rely on prior knowledge of the image phase, but the need to obtain this prior information can place practical restrictions on the data acquisition strategy. In this work, we propose and evaluate SENSE-LORAKS, which enables combined parallel imaging and partial Fourier reconstruction without requiring prior phase information. Theory and Methods The proposed formulation is based on combining the classical SENSE model for parallel imaging data with the more recent LORAKS framework for MR image reconstruction using low-rank matrix modeling. Previous LORAKS-based methods have successfully enabled calibrationless partial Fourier parallel MRI reconstruction, but have been most successful with nonuniform sampling strategies that may be hard to implement for certain applications. By combining LORAKS with SENSE, we enable highly-accelerated partial Fourier MRI reconstruction for a broader range of sampling trajectories, including widely-used calibrationless uniformly-undersampled trajectories. Results Our empirical results with retrospectively undersampled datasets indicate that when SENSE-LORAKS reconstruction is combined with an appropriate k-space sampling trajectory, it can provide substantially better image quality at high-acceleration rates relative to existing state-of-the-art reconstruction approaches. Conclusion The SENSE-LORAKS framework provides promising new opportunities for highly-accelerated MRI. PMID:27037836

Combining flow cytometry and 16S rRNA gene pyrosequencing: a promising approach for drinking water monitoring and characterization.

PubMed

Prest, E I; El-Chakhtoura, J; Hammes, F; Saikaly, P E; van Loosdrecht, M C M; Vrouwenvelder, J S

2014-10-15

The combination of flow cytometry (FCM) and 16S rRNA gene pyrosequencing data was investigated for the purpose of monitoring and characterizing microbial changes in drinking water distribution systems. High frequency sampling (5 min intervals for 1 h) was performed at the outlet of a treatment plant and at one location in the full-scale distribution network. In total, 52 bulk water samples were analysed with FCM, pyrosequencing and conventional methods (adenosine-triphosphate, ATP; heterotrophic plate count, HPC). FCM and pyrosequencing results individually showed that changes in the microbial community occurred in the water distribution system, which was not detected with conventional monitoring. FCM data showed an increase in the total bacterial cell concentrations (from 345 ± 15 × 10(3) to 425 ± 35 × 10(3) cells mL(-1)) and in the percentage of intact bacterial cells (from 39 ± 3.5% to 53 ± 4.4%) during water distribution. This shift was also observed in the FCM fluorescence fingerprints, which are characteristic of each water sample. A similar shift was detected in the microbial community composition as characterized with pyrosequencing, showing that FCM and genetic fingerprints are congruent. FCM and pyrosequencing data were subsequently combined for the calculation of cell concentration changes for each bacterial phylum. The results revealed an increase in cell concentrations of specific bacterial phyla (e.g., Proteobacteria), along with a decrease in other phyla (e.g., Actinobacteria), which could not be concluded from the two methods individually. The combination of FCM and pyrosequencing methods is a promising approach for future drinking water quality monitoring and for advanced studies on drinking water distribution pipeline ecology. Copyright © 2014 Elsevier Ltd. All rights reserved.

Antibodies as means for selective mass spectrometry.

PubMed

Boström, Tove; Takanen, Jenny Ottosson; Hober, Sophia

2016-05-15

For protein analysis of biological samples, two major strategies are used today; mass spectrometry (MS) and antibody-based methods. Each strategy offers advantages and drawbacks. However, combining the two using an immunoenrichment step with MS analysis brings together the benefits of each method resulting in increased sensitivity, faster analysis and possibility of higher degrees of multiplexing. The immunoenrichment can be performed either on protein or peptide level and quantification standards can be added in order to enable determination of the absolute protein concentration in the sample. The combination of immunoenrichment and MS holds great promise for the future in both proteomics and clinical diagnostics. This review describes different setups of immunoenrichment coupled to mass spectrometry and how these can be utilized in various applications. Copyright © 2015 Elsevier B.V. All rights reserved.

Combining polar organic chemical integrative samplers (POCIS) with toxicity testing to evaluate pesticide mixture effects on natural phototrophic biofilms.

PubMed

Pesce, Stéphane; Morin, Soizic; Lissalde, Sophie; Montuelle, Bernard; Mazzella, Nicolas

2011-03-01

Polar organic chemical integrative samplers (POCIS) are valuable tools in passive sampling methods for monitoring polar organic pesticides in freshwaters. Pesticides extracted from the environment using such methods can be used to toxicity tests. This study evaluated the acute effects of POCIS extracts on natural phototrophic biofilm communities. Our results demonstrate an effect of POCIS pesticide mixtures on chlorophyll a fluorescence, photosynthetic efficiency and community structure. Nevertheless, the range of biofilm responses differs according to origin of the biofilms tested, revealing spatial variations in the sensitivity of natural communities in the studied stream. Combining passive sampler extracts with community-level toxicity tests offers promising perspectives for ecological risk assessment. Copyright © 2010 Elsevier Ltd. All rights reserved.

Optical multichannel room temperature magnetic field imaging system for clinical application

PubMed Central

Lembke, G.; Erné, S. N.; Nowak, H.; Menhorn, B.; Pasquarelli, A.

2014-01-01

Optically pumped magnetometers (OPM) are a very promising alternative to the superconducting quantum interference devices (SQUIDs) used nowadays for Magnetic Field Imaging (MFI), a new method of diagnosis based on the measurement of the magnetic field of the human heart. We present a first measurement combining a multichannel OPM-sensor with an existing MFI-system resulting in a fully functional room temperature MFI-system. PMID:24688820

Evaluation of Thermoelectric Performance and Durability of Functionalized Skutterudite Legs

NASA Astrophysics Data System (ADS)

Skomedal, Gunstein; Kristiansen, Nils R.; Sottong, Reinhard; Middleton, Hugh

2017-04-01

Thermoelectric generators are a promising technology for waste heat recovery. As new materials and devices enter a market penetration stage, it is of interest to employ fast and efficient measurement methods to evaluate the long-term stability of thermoelectric materials in combination with metallization and coating (functionalized thermoelectric legs). We have investigated a method for measuring several thermoelectric legs simultaneously. The legs are put under a common temperature gradient, and the electrical characteristics of each leg are measured individually during thermal cycling. Using this method, one can test different types of metallization and coating applied to skutterudite thermoelectric legs and look at the relative changes over time. Postcharacterization of these initial tests with skutterudite legs using a potential Seebeck microprobe and an electron microscope showed that oxidation and interlayer diffusion are the main reasons for the gradual increase in internal resistance and the decrease in open-circuit voltage. Although we only tested skutterudite material in this work, the method is fully capable of testing all kinds of material, metallization, and coating. It is thus a promising method for studying the relationship between failure modes and mechanisms of functionalized thermoelectric legs.

Fabrication of the polarization independent spectral beam combining grating

NASA Astrophysics Data System (ADS)

Liu, Quan; Jin, Yunxia; Wu, Jianhong; Guo, Peiliang

2016-03-01

Owing to damage, thermal issues, and nonlinear optical effects, the output power of fiber laser has been proven to be limited. Beam combining techniques are the attractive solutions to achieve high-power high-brightness fiber laser output. The spectral beam combining (SBC) is a promising method to achieve high average power output without influencing the beam quality. A polarization independent spectral beam combining grating is one of the key elements in the SBC. In this paper the diffraction efficiency of the grating is investigated by rigorous coupled-wave analysis (RCWA). The theoretical -1st order diffraction efficiency of the grating is more than 95% from 1010nm to 1080nm for both TE and TM polarizations. The fabrication tolerance is analyzed. The polarization independent spectral beam combining grating with the period of 1.04μm has been fabricated by holographic lithography - ion beam etching, which are within the fabrication tolerance.

Increasing access to kidney transplantation for sensitized recipient through three-way kidney paired donation with desensitization: The first Indian report

PubMed Central

Kute, Vivek B; Patel, Himanshu V; Shah, Pankaj R; Modi, Pranjal R; Shah, Veena R; Rizvi, Sayyed J; Pal, Bipin C; Modi, Manisha P; Shah, Priya S; Varyani, Umesh T; Wakhare, Pavan S; Shinde, Saiprasad G; Ghodela, Viajay A; Patel, Minaxi H; Trivedi, Varsha B; Trivedi, Hargovind L

2016-01-01

The combination of kidney paired donation (KPD) with desensitization represents a promising method of increasing the rate of living donor kidney transplantation (LDKT) in immunologically challenging patients. Patients who are difficult to match and desensitize due to strong donor specific antibody are may be transplanted by a combination of desensitization and KPD protocol with more immunologically favorable donor. We present our experience of combination of desensitization protocol with three-way KPD which contributed to successful LDKT in highly sensitized end stage renal disease patient. All recipients were discharged with normal and stable allograft function at 24 mo follow up. We believe that this is first report from India where three-way KPD exchange was performed with the combination of KPD and desensitization. The combination of desensitization protocol with KPD improves access and outcomes of LDKT. PMID:27803919

Prophylactic effects of humic acid-glucan combination against experimental liver injury

PubMed Central

Vetvicka, Vaclav; Garcia-Mina, Jose Maria; Yvin, Jean-Claude

2015-01-01

Aim: Despite intensive research, liver diseases represent a significant health problem and current medicine does not offer a substance able to significantly inhibit the hepatotoxicity leading to various stages of liver disease. Based on our previously published studies showing the protective effects of a glucan-humic acid (HA) combination, we focused on the hypothesis that the combination of these two natural molecules can offer prophylactic protection against experimentally induced hepatotoxicity. Materials and Methods: Lipopolysaccharide, carbon tetrachloride, and ethanol were used to experimentally damage the liver. Levels of aspartate aminotransferase, alanine transaminase, alkaline phosphatase, glutathione, superoxide dismutase, and malondialdehyde, known to correspond to the liver damage, were assayed. Results: Using three different hepatotoxins, we found that in all cases, some samples of HA and most of all the glucan-HA combination, offer strong protection against liver damage. Conclusion: Glucan-HA combination is a promising agent for use in liver protection. PMID:26401416

Near-optimal strategies for sub-decimeter satellite tracking with GPS

NASA Technical Reports Server (NTRS)

Yunck, Thomas P.; Wu, Sien-Chong; Wu, Jiun-Tsong

1986-01-01

Decimeter tracking of low Earth orbiters using differential Global Positioning System (GPS) techniques is discussed. A precisely known global network of GPS ground receivers and a receiver aboard the user satellite are needed, and all techniques simultaneously estimate the user and GPS satellite orbits. Strategies include a purely geometric, a fully dynamic, and a hybrid strategy. The last combines dynamic GPS solutions with a geometric user solution. Two powerful extensions of the hybrid strategy show the most promise. The first uses an optimized synthesis of dynamics and geometry in the user solution, while the second uses a gravity adjustment method to exploit data from repeat ground tracks. These techniques promise to deliver subdecimeter accuracy down to the lowest satellite altitudes.

Synergistic effects of tacrolimus and azole antifungal compounds in fluconazole-susceptible and fluconazole-resistant Candida glabrata isolates.

PubMed

Denardi, Laura Bedin; Mario, Débora Alves Nunes; Loreto, Érico Silva; Santurio, Janio Morais; Alves, Sydney Hartz

2015-03-01

In vitro interaction between tacrolimus (FK506) and four azoles (fluconazole, ketoconazole, itraconazole and voriconazole) against thirty clinical isolates of both fluconazole susceptible and -resistant Candida glabrata were evaluated by the checkerboard microdilution method. Synergistic, indifferent or antagonism interactions were found for combinations of the antifungal agents and FK506. A larger synergistic effect was observed for the combinations of FK506 with itraconazole and voriconazole (43%), followed by that of the combination with ketoconazole (37%), against fluconazole-susceptible isolates. For fluconazole-resistant C. glabrata , a higher synergistic effect was obtained from FK506 combined with ketoconazole (77%), itraconazole (73%), voriconazole (63%) and fluconazole (60%). The synergisms that we observed in vitro , notably against fluconazole-resistant C. glabrata isolates, are promising and warrant further analysis of their applications in experimental in vivo studies.

Symbiotic relationship between hydrothermal carbonization technology and anaerobic digestion for food waste in China.

PubMed

Zhou, Ying; Engler, Nils; Nelles, Michael

2018-07-01

Food waste (FW) is traditionally disposed through landfills and incineration in China. Nowadays, there are some promising methods, such as anaerobic digestion (AD) or feeding and composting, which are being applied in pilot cities. However, the inherent characteristics of Chinese FW may be regarded as a double-edged sword in the practical applications of these disposal methods. To overcome these challenges, two modes of the hydrothermal carbonization (HTC) process were reviewed as innovative strategies in this article. Meanwhile, the "symbiotic relationship" between Chinese FW and HTC technologies was highlighted. To improve treatment efficiency of FW, we should not only try different methods and develop existing technologies, but also pay more attention to the utilization and "1 + 1 > 2" synergistic effect of their combinations, such as the combination of HTC and AD as a co-treatment method for saving on the construction cost and avoiding redistribution of social resources. Copyright © 2018 Elsevier Ltd. All rights reserved.

An effective method for thallium bromide purification and research on crystal properties

NASA Astrophysics Data System (ADS)

Zheng, Zhiping; Meng, Fang; Gong, Shuping; Quan, Lin; Wang, Jing; Zhou, Dongxiang

2012-06-01

Thallium bromide (TlBr) is a promising candidate for room-temperature X- and gamma-ray detectors in view of its excellent intrinsic features. However, material purity and crystal quality concerns still limit the use of TlBr crystals as detectors. In this work, a combination of hydrothermal recrystallization (HR) and vacuum distillation (VD) methods were applied to purify TlBr salts prior to crystal growth. Trace impurities at the ppb/ppm level were determined by inductively coupled plasma mass spectroscopy (ICP-MS). The results showed that the impurity concentrations of the TlBr salt decreased significantly after HR and VD purification, and high performance of the resultant TlBr crystal in areas such as electrical and optical properties was achieved. The combination of HR and VD methods could fabricate purer material, with an order of magnitude higher resistivity and better optical quality, than HR or VD method used separately. The possible technological considerations affecting the parameters of the crystals are investigated.

Molecularly imprinted membrane extraction combined with high-performance liquid chromatography for selective analysis of cloxacillin from shrimp samples.

PubMed

Du, Wei; Sun, Min; Guo, Pengqi; Chang, Chun; Fu, Qiang

2018-09-01

Nowadays, the abuse of antibiotics in aquaculture has generated considerable problems for food safety. Therefore, it is imperative to develop a simple and selective method for monitoring illegal use of antibiotics in aquatic products. In this study, a method combined molecularly imprinted membranes (MIMs) extraction and liquid chromatography was developed for the selective analysis of cloxacillin from shrimp samples. The MIMs was synthesized by UV photopolymerization, and characterized by scanning electron microscope, Fourier transform infrared spectra, thermo-gravimetric analysis and swelling test. The results showed that the MIMs exhibited excellent permselectivity, high adsorption capacity and fast adsorption rate for cloxacillin. Finally, the method was utilized to determine cloxacillin from shrimp samples, with good accuracies and acceptable relative standard deviation values for precision. The proposed method was a promising alternative for selective analysis of cloxacillin in shrimp samples, due to the easy-operation and excellent selectivity. Copyright © 2018. Published by Elsevier Ltd.

Innovative visualization and segmentation approaches for telemedicine

NASA Astrophysics Data System (ADS)

Nguyen, D.; Roehrig, Hans; Borders, Marisa H.; Fitzpatrick, Kimberly A.; Roveda, Janet

2014-09-01

In health care applications, we obtain, manage, store and communicate using high quality, large volume of image data through integrated devices. In this paper we propose several promising methods that can assist physicians in image data process and communication. We design a new semi-automated segmentation approach for radiological images, such as CT and MRI to clearly identify the areas of interest. This approach combines the advantages from both the region-based method and boundary-based methods. It has three key steps compose: coarse segmentation by using fuzzy affinity and homogeneity operator, image division and reclassification using the Voronoi Diagram, and refining boundary lines using the level set model.

[Traceability of Wine Varieties Using Near Infrared Spectroscopy Combined with Cyclic Voltammetry].

PubMed

Li, Meng-hua; Li, Jing-ming; Li, Jun-hui; Zhang, Lu-da; Zhao, Long-lian

2015-06-01

To achieve the traceability of wine varieties, a method was proposed to fuse Near-infrared (NIR) spectra and cyclic voltammograms (CV) which contain different information using D-S evidence theory. NIR spectra and CV curves of three different varieties of wines (cabernet sauvignon, merlot, cabernet gernischt) which come from seven different geographical origins were collected separately. The discriminant models were built using PLS-DA method. Based on this, D-S evidence theory was then applied to achieve the integration of the two kinds of discrimination results. After integrated by D-S evidence theory, the accuracy rate of cross-validation is 95.69% and validation set is 94.12% for wine variety identification. When only considering the wine that come from Yantai, the accuracy rate of cross-validation is 99.46% and validation set is 100%. All the traceability models after fusion achieved better results on classification than individual method. These results suggest that the proposed method combining electrochemical information with spectral information using the D-S evidence combination formula is benefit to the improvement of model discrimination effect, and is a promising tool for discriminating different kinds of wines.

Formulation and evaluation of controlled release antibiotic biodegradable implants for post operative site delivery.

PubMed

Mathur, Vijay; Mudnaik, Rajesh; Barde, Laxmikant; Roy, Arghya; Shivhare, Umesh; Bhusari, Kishore

2010-03-01

Biodegradable implants of ciprofloxacin hydrochloride for post operative site delivery were prepared using glyceryl monostearate and different concentrations of polyethylene glycol (PEG 6000), glycerol and Tween 80 as erosion enhancers by compression and molding technique. Formulations were subjected to in vitro drug release by the USP dissolution method, while promising formulations were subjected to in vitro drug release by the agar gel method and also to stability studies. It was observed that glyceryl monostearate formed hydrophobic matrix and delayed the drug delivery. Antibiotic release profile was controlled by using different combinations of erosion enhancers. The formulation prepared by the compression method showed more delayed release compared to formulations prepared by the molding method.

Downdating a time-varying square root information filter

NASA Technical Reports Server (NTRS)

Muellerschoen, Ronald J.

1990-01-01

A new method to efficiently downdate an estimate and covariance generated by a discrete time Square Root Information Filter (SRIF) is presented. The method combines the QR factor downdating algorithm of Gill and the decentralized SRIF algorithm of Bierman. Efficient removal of either measurements or a priori information is possible without loss of numerical integrity. Moreover, the method includes features for detecting potential numerical degradation. Performance on a 300 parameter system with 5800 data points shows that the method can be used in real time and hence is a promising tool for interactive data analysis. Additionally, updating a time-varying SRIF filter with either additional measurements or a priori information proceeds analogously.

Design of an indoor self-positioning system for the visually impaired--simulation with RFID and Bluetooth in a visible light communication system.

PubMed

Liu, Xiaohan; Makino, Hideo; Kobayashi, Suguru; Maeda, Yoshinobu

2007-01-01

After a public experiment of the indoor guidance system using FLC (fluorescent light communication), we found that FLC provides a promising medium for the installation of a guidance system for the visually impaired. However, precise self-positioning was not satisfactorily achieved. In this article, we propose a new self-positioning method, one that uses a combination of RFID (Radio-frequency identification), Bluetooth and FLC. We analyzed the situation and developed a model that combined the three communication modes. Then we performed a series of experiments and get some results in the first step.

A Systematic Review of the Combined Use of Electroconvulsive Therapy and Psychotherapy for Depression

PubMed Central

McClintock, Shawn M.; Brandon, Anna R.; Husain, Mustafa M.; Jarrett, Robin B.

2011-01-01

Objective Electroconvulsive therapy (ECT) is one of the most effective treatments for severe Major Depressive Disorder (MDD). However, after acute phase treatment and initial remission, relapse rates are significant. Strategies to prolong remission include continuation phase ECT, pharmacotherapy, psychotherapy, or their combinations. This systematic review synthesizes extant data regarding the combined use of psychotherapy with ECT for the treatment of patients with severe MDD and offers the hypothesis that augmenting ECT with depression-specific psychotherapy represents a promising strategy for future investigation. Methods The authors performed two independent searches in PsychInfo (1806 – 2009) and MEDLINE (1948 – 2009) using combinations of the following search terms: Electroconvulsive Therapy (including ECT, ECT therapy, electroshock therapy, EST, shock therapy) and Psychotherapy (including cognitive behavioral, interpersonal, group, psychodynamic, psychoanalytic, individual, eclectic, and supportive). We included in this review a total of six articles (English language) that mentioned ECT and psychotherapy in the abstract, and provided a case report, series, or clinical trial. We examined the articles for data related to ECT and psychotherapy treatment characteristics, cohort characteristics, and therapeutic outcome. Results Although research over the past seven decades documenting the combined use of ECT and psychotherapy is limited, the available evidence suggests that testing this combination has promise and may confer additional, positive functional outcomes. Conclusions Significant methodological variability in ECT and psychotherapy procedures, heterogeneous patient cohorts, and inconsistent outcome measures prevent strong conclusions; however, existing research supports the need for future investigations of combined ECT and psychotherapy in well-designed, controlled clinical studies. Depression-specific psychotherapy approaches may need special adaptations in view of the cognitive effects following ECT. PMID:21206376

Effect of Catechins, Green tea Extract and Methylxanthines in Combination with Gentamicin Against Staphylococcus aureus and Pseudomonas aeruginosa

PubMed Central

Fazly Bazzaz, Bibi Sedigheh; Sarabandi, Sahar; Khameneh, Bahman; Hosseinzadeh, Hossein

2016-01-01

Objectives: Bacterial resistant infections have become a global health challenge and threaten the society’s health. Thus, an urgent need exists to find ways to combat resistant pathogens. One promising approach to overcoming bacterial resistance is the use of herbal products. Green tea catechins, the major green tea polyphenols, show antimicrobial activity against resistant pathogens. The present study aimed to investigate the effect of catechins, green tea extract, and methylxanthines in combination with gentamicin against standard and clinical isolates of Staphylococcus aureus (S. aureus) and the standard strain of Pseudomonas aeruginosa (P. aeruginosa). Methods: The minimum inhibitory concentration (MIC) and the minimum bactericidal concentration (MBC) values of different agents against bacterial strains were determined. The interactions of green tea extract, epigallate catechin, epigallocatechin gallate, two types of methylxanthine, caffeine, and theophylline with gentamicin were studied in vitro by using a checkerboard method and calculating the fraction inhibitory concentration index (FICI). Results: The MICs of gentamicin against bacterial strains were in the range of 0.312 - 320 μg/mL. The MIC values of both types of catechins were 62.5 - 250 μg/ mL. Green tea extract showed insufficient antibacterial activity when used alone. Methylxanthines had no intrinsic inhibitory activity against any of the bacterial strains tested. When green tea extract and catechins were combined with gentamicin, the MIC values of gentamicin against the standard strains and a clinical isolate were reduced, and synergistic activities were observed (FICI < 1). A combination of caffeine with gentamicin did not alter the MIC values of gentamicin. Conclusion: The results of the present study revealed that green tea extract and catechins potentiated the antimicrobial action of gentamicin against some clinical isolates of S. aureus and standard P. aeruginosa strains. Therefore, combinations of gentamicin with these natural compounds might be a promising approach to combat microbial resistance. PMID:28097041

IspE Inhibitors Identified by a Combination of In Silico and In Vitro High-Throughput Screening

PubMed Central

Tidten-Luksch, Naomi; Grimaldi, Raffaella; Torrie, Leah S.; Frearson, Julie A.; Hunter, William N.; Brenk, Ruth

2012-01-01

CDP-ME kinase (IspE) contributes to the non-mevalonate or deoxy-xylulose phosphate (DOXP) pathway for isoprenoid precursor biosynthesis found in many species of bacteria and apicomplexan parasites. IspE has been shown to be essential by genetic methods and since it is absent from humans it constitutes a promising target for antimicrobial drug development. Using in silico screening directed against the substrate binding site and in vitro high-throughput screening directed against both, the substrate and co-factor binding sites, non-substrate-like IspE inhibitors have been discovered and structure-activity relationships were derived. The best inhibitors in each series have high ligand efficiencies and favourable physico-chemical properties rendering them promising starting points for drug discovery. Putative binding modes of the ligands were suggested which are consistent with established structure-activity relationships. The applied screening methods were complementary in discovering hit compounds, and a comparison of both approaches highlights their strengths and weaknesses. It is noteworthy that compounds identified by virtual screening methods provided the controls for the biochemical screens. PMID:22563402

Combining cationic and anionic mixed-mode sorbents in a single cartridge to extract basic and acidic pharmaceuticals simultaneously from environmental waters.

PubMed

Salas, Daniela; Borrull, Francesc; Fontanals, Núria; Marcé, Rosa Maria

2018-01-01

The aim of the present study is to broaden the applications of mixed-mode ion-exchange solid-phase extraction sorbents to extract both basic and acidic compounds simultaneously by combining the sorbents in a single cartridge and developing a simplified extraction procedure. Four different cartridges containing negative and positive charges in the same configuration were evaluated and compared to extract a group of basic, neutral, and acidic pharmaceuticals selected as model compounds. After a thorough optimization of the extraction conditions, the four different cartridges showed to be capable of retaining basic and acidic pharmaceuticals simultaneously through ionic interactions, allowing the introduction of a washing step with 15 mL methanol to eliminate interferences retained by hydrophobic interactions. Using the best combined cartridge, a method was developed, validated, and further applied to environmental waters to demonstrate that the method is promising for the extraction of basic and acidic compounds from very complex samples.

Volumetric imaging of fast biological dynamics in deep tissue via wavefront engineering

NASA Astrophysics Data System (ADS)

Kong, Lingjie; Tang, Jianyong; Cui, Meng

2016-03-01

To reveal fast biological dynamics in deep tissue, we combine two wavefront engineering methods that were developed in our laboratory, namely optical phase-locked ultrasound lens (OPLUL) based volumetric imaging and iterative multiphoton adaptive compensation technique (IMPACT). OPLUL is used to generate oscillating defocusing wavefront for fast axial scanning, and IMPACT is used to compensate the wavefront distortions for deep tissue imaging. We show its promising applications in neuroscience and immunology.

Low-Resistivity Zinc Selenide for Heterojunctions

NASA Technical Reports Server (NTRS)

Stirn, R. J.

1986-01-01

Magnetron reactive sputtering enables doping of this semiconductor. Proposed method of reactive sputtering combined with doping shows potential for yielding low-resistivity zinc selenide films. Zinc selenide attractive material for forming heterojunctions with other semiconductor compounds as zinc phosphide, cadmium telluride, and gallium arsenide. Semiconductor junctions promising for future optoelectronic devices, including solar cells and electroluminescent displays. Resistivities of zinc selenide layers deposited by evaporation or chemical vapor deposition too high to form practical heterojunctions.

A hadoop-based method to predict potential effective drug combination.

PubMed

Sun, Yifan; Xiong, Yi; Xu, Qian; Wei, Dongqing

2014-01-01

Combination drugs that impact multiple targets simultaneously are promising candidates for combating complex diseases due to their improved efficacy and reduced side effects. However, exhaustive screening of all possible drug combinations is extremely time-consuming and impractical. Here, we present a novel Hadoop-based approach to predict drug combinations by taking advantage of the MapReduce programming model, which leads to an improvement of scalability of the prediction algorithm. By integrating the gene expression data of multiple drugs, we constructed data preprocessing and the support vector machines and naïve Bayesian classifiers on Hadoop for prediction of drug combinations. The experimental results suggest that our Hadoop-based model achieves much higher efficiency in the big data processing steps with satisfactory performance. We believed that our proposed approach can help accelerate the prediction of potential effective drugs with the increasing of the combination number at an exponential rate in future. The source code and datasets are available upon request.

A Hadoop-Based Method to Predict Potential Effective Drug Combination

PubMed Central

Xiong, Yi; Xu, Qian; Wei, Dongqing

2014-01-01

Combination drugs that impact multiple targets simultaneously are promising candidates for combating complex diseases due to their improved efficacy and reduced side effects. However, exhaustive screening of all possible drug combinations is extremely time-consuming and impractical. Here, we present a novel Hadoop-based approach to predict drug combinations by taking advantage of the MapReduce programming model, which leads to an improvement of scalability of the prediction algorithm. By integrating the gene expression data of multiple drugs, we constructed data preprocessing and the support vector machines and naïve Bayesian classifiers on Hadoop for prediction of drug combinations. The experimental results suggest that our Hadoop-based model achieves much higher efficiency in the big data processing steps with satisfactory performance. We believed that our proposed approach can help accelerate the prediction of potential effective drugs with the increasing of the combination number at an exponential rate in future. The source code and datasets are available upon request. PMID:25147789

Using Ensemble Decisions and Active Selection to Improve Low-Cost Labeling for Multi-View Data

NASA Technical Reports Server (NTRS)

Rebbapragada, Umaa; Wagstaff, Kiri L.

2011-01-01

This paper seeks to improve low-cost labeling in terms of training set reliability (the fraction of correctly labeled training items) and test set performance for multi-view learning methods. Co-training is a popular multiview learning method that combines high-confidence example selection with low-cost (self) labeling. However, co-training with certain base learning algorithms significantly reduces training set reliability, causing an associated drop in prediction accuracy. We propose the use of ensemble labeling to improve reliability in such cases. We also discuss and show promising results on combining low-cost ensemble labeling with active (low-confidence) example selection. We unify these example selection and labeling strategies under collaborative learning, a family of techniques for multi-view learning that we are developing for distributed, sensor-network environments.

Factorization-based texture segmentation

DOE PAGES

Yuan, Jiangye; Wang, Deliang; Cheriyadat, Anil M.

2015-06-17

This study introduces a factorization-based approach that efficiently segments textured images. We use local spectral histograms as features, and construct an M × N feature matrix using M-dimensional feature vectors in an N-pixel image. Based on the observation that each feature can be approximated by a linear combination of several representative features, we factor the feature matrix into two matrices-one consisting of the representative features and the other containing the weights of representative features at each pixel used for linear combination. The factorization method is based on singular value decomposition and nonnegative matrix factorization. The method uses local spectral histogramsmore » to discriminate region appearances in a computationally efficient way and at the same time accurately localizes region boundaries. Finally, the experiments conducted on public segmentation data sets show the promise of this simple yet powerful approach.« less

A hybrid approach to determining cornea mechanical properties in vivo using a combination of nano-indentation and inverse finite element analysis.

PubMed

Abyaneh, M H; Wildman, R D; Ashcroft, I A; Ruiz, P D

2013-11-01

An analysis of the material properties of porcine corneas has been performed. A simple stress relaxation test was performed to determine the viscoelastic properties and a rheological model was built based on the Generalized Maxwell (GM) approach. A validation experiment using nano-indentation showed that an isotropic GM model was insufficient for describing the corneal material behaviour when exposed to a complex stress state. A new technique was proposed for determining the properties, using a combination of nano-indentation experiment, an isotropic and orthotropic GM model and inverse finite element method. The good agreement using this method suggests that this is a promising technique for measuring material properties in vivo and further work should focus on the reliability of the approach in practice. © 2013 Elsevier Ltd. All rights reserved.

Validation of a Salmonella loop-mediated isothermal amplification assay in animal food.

PubMed

Domesle, Kelly J; Yang, Qianru; Hammack, Thomas S; Ge, Beilei

2018-01-02

Loop-mediated isothermal amplification (LAMP) has emerged as a promising alternative to PCR for pathogen detection in food testing and clinical diagnostics. This study aimed to validate a Salmonella LAMP method run on both turbidimetry (LAMP I) and fluorescence (LAMP II) platforms in representative animal food commodities. The U.S. Food and Drug Administration (FDA)'s culture-based Bacteriological Analytical Manual (BAM) method was used as the reference method and a real-time quantitative PCR (qPCR) assay was also performed. The method comparison study followed the FDA's microbiological methods validation guidelines, which align well with those from the AOAC International and ISO. Both LAMP assays were 100% specific among 300 strains (247 Salmonella of 185 serovars and 53 non-Salmonella) tested. The detection limits ranged from 1.3 to 28 cells for six Salmonella strains of various serovars. Six commodities consisting of four animal feed items (cattle feed, chicken feed, horse feed, and swine feed) and two pet food items (dry cat food and dry dog food) all yielded satisfactory results. Compared to the BAM method, the relative levels of detection (RLODs) for LAMP I ranged from 0.317 to 1 with a combined value of 0.610, while those for LAMP II ranged from 0.394 to 1.152 with a combined value of 0.783, which all fell within the acceptability limit (2.5) for an unpaired study. This also suggests that LAMP was more sensitive than the BAM method at detecting low-level Salmonella contamination in animal food and results were available 3days sooner. The performance of LAMP on both platforms was comparable to that of qPCR but notably faster, particularly LAMP II. Given the importance of Salmonella in animal food safety, the LAMP assays validated in this study holds great promise as a rapid, reliable, and robust method for routine screening of Salmonella in these commodities. Published by Elsevier B.V.

Synergism between hydrogen peroxide and seventeen acids against five agri-food-borne fungi and one yeast strain.

PubMed

Martin, H; Maris, P

2012-12-01

The objective of this study was to evaluate fungicidal efficacy of hydrogen peroxide administered in combination with 17 mineral and organic acids authorized for use in the food industry. The assays were performed on a 96-well microplate using a microdilution technique based on the checkerboard titration method. The six selected strains (one yeast and five fungi) were reference strains and strains representative of contaminating fungi found in the food industry. Each synergistic hydrogen peroxide/acid combination found after fifteen minutes contact time at 20 °C in distilled water was then tested in conditions simulating four different use conditions. Twelve combinations were synergistic in distilled water, eleven of these remained synergistic with one or more of the four mineral and organic interfering substances selected. Hydrogen peroxide/formic acid combination remained effective against four strains and was never antagonistic against the other two fungi. Combinations with propionic acid and acetic acid stayed synergistic against two strains. Those with oxalic acid and lactic acid kept their synergism only against Candida albicans. No synergism was detected against Penicillium cyclopium. Synergistic combinations of disinfectants were revealed, among them the promising hydrogen peroxide/formic acid combination. A rapid screening method developed in our laboratory for bacteria was adapted to fungi and used to reveal the synergistic potential of disinfectants and/or sanitizers combinations. © 2012 The Society for Applied Microbiology.

Hermetic edge sealing of photovoltaic modules

NASA Astrophysics Data System (ADS)

1983-02-01

The edge sealing technique is accomplished by a combination of a chemical bond between glass and aluminum, formed by electrostatic bonding, and a metallurgical bond between aluminum and aluminum, formed by ultrasonic welding. Such a glass to metal seal promises to provide a low cost, long lifetime, highly effective hermetic seal which can protect module components from severe environments. Development of the sealing techniques and demonstration of their effectiveness by fabricating a small number of dummy modules, up to eight inches square in size, and testing them for hermeticity using helium leak testing methods are reviewed. Non-destructive test methods are investigated.

Feelings and ethics education: the film dear scientists.

PubMed

Semendeferi, Ioanna

2014-12-01

There is an increasing body of evidence that not only cognition but also emotions shape moral judgment. The conventional teaching of responsible conduct of research, however, does not target emotions; its emphasis is on rational analysis. Here I present a new approach, 'the feelings method,' for incorporating emotions into science ethics education. This method is embodied in Dear Scientists, an innovative film that combines humanities with arts and works at the subconscious level, delivering an intense mix of music and images, contrasted by calm narration. Dear Scientists has struck a chord across the science, humanities, and arts communities-a promising sign.

Speaking for ourselves: feminist methods and community psychology.

PubMed

Cosgrove, L; McHugh, M C

2000-12-01

Although feminist and community psychology share a number of epistemological and methodological perspectives that guide their respective theories and research practices, it has been argued that community psychology has not fully integrated a feminist perspective into the discipline. This paper examines how community psychology and feminist research methods might combine to help us better understand women's experiences without essentializing or universalizing those experiences. The authors offer a series of suggested directions for feminist research that may also prove promising for community psychology. Particular attention is paid to feminist social constructionist approaches insofar as they address the complex relationship between epistemology and methodology.

Hermetic edge sealing of photovoltaic modules

NASA Technical Reports Server (NTRS)

1983-01-01

The edge sealing technique is accomplished by a combination of a chemical bond between glass and aluminum, formed by electrostatic bonding, and a metallurgical bond between aluminum and aluminum, formed by ultrasonic welding. Such a glass to metal seal promises to provide a low cost, long lifetime, highly effective hermetic seal which can protect module components from severe environments. Development of the sealing techniques and demonstration of their effectiveness by fabricating a small number of dummy modules, up to eight inches square in size, and testing them for hermeticity using helium leak testing methods are reviewed. Non-destructive test methods are investigated.

Cross spectral, active and passive approach to face recognition for improved performance

NASA Astrophysics Data System (ADS)

Grudzien, A.; Kowalski, M.; Szustakowski, M.

2017-08-01

Biometrics is a technique for automatic recognition of a person based on physiological or behavior characteristics. Since the characteristics used are unique, biometrics can create a direct link between a person and identity, based on variety of characteristics. The human face is one of the most important biometric modalities for automatic authentication. The most popular method of face recognition which relies on processing of visual information seems to be imperfect. Thermal infrared imagery may be a promising alternative or complement to visible range imaging due to its several reasons. This paper presents an approach of combining both methods.

Developing Discontinuous Galerkin Methods for Solving Multiphysics Problems in General Relativity

NASA Astrophysics Data System (ADS)

Kidder, Lawrence; Field, Scott; Teukolsky, Saul; Foucart, Francois; SXS Collaboration

2016-03-01

Multi-messenger observations of the merger of black hole-neutron star and neutron star-neutron star binaries, and of supernova explosions will probe fundamental physics inaccessible to terrestrial experiments. Modeling these systems requires a relativistic treatment of hydrodynamics, including magnetic fields, as well as neutrino transport and nuclear reactions. The accuracy, efficiency, and robustness of current codes that treat all of these problems is not sufficient to keep up with the observational needs. We are building a new numerical code that uses the Discontinuous Galerkin method with a task-based parallelization strategy, a promising combination that will allow multiphysics applications to be treated both accurately and efficiently on petascale and exascale machines. The code will scale to more than 100,000 cores for efficient exploration of the parameter space of potential sources and allowed physics, and the high-fidelity predictions needed to realize the promise of multi-messenger astronomy. I will discuss the current status of the development of this new code.

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

PubMed

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

2016-01-01

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

Joint effect of unlinked genotypes: application to type 2 diabetes in the EPIC-Potsdam case-cohort study.

PubMed

Knüppel, Sven; Meidtner, Karina; Arregui, Maria; Holzhütter, Hermann-Georg; Boeing, Heiner

2015-07-01

Analyzing multiple single nucleotide polymorphisms (SNPs) is a promising approach to finding genetic effects beyond single-locus associations. We proposed the use of multilocus stepwise regression (MSR) to screen for allele combinations as a method to model joint effects, and compared the results with the often used genetic risk score (GRS), conventional stepwise selection, and the shrinkage method LASSO. In contrast to MSR, the GRS, conventional stepwise selection, and LASSO model each genotype by the risk allele doses. We reanalyzed 20 unlinked SNPs related to type 2 diabetes (T2D) in the EPIC-Potsdam case-cohort study (760 cases, 2193 noncases). No SNP-SNP interactions and no nonlinear effects were found. Two SNP combinations selected by MSR (Nagelkerke's R² = 0.050 and 0.048) included eight SNPs with mean allele combination frequency of 2%. GRS and stepwise selection selected nearly the same SNP combinations consisting of 12 and 13 SNPs (Nagelkerke's R² ranged from 0.020 to 0.029). LASSO showed similar results. The MSR method showed the best model fit measured by Nagelkerke's R² suggesting that further improvement may render this method a useful tool in genetic research. However, our comparison suggests that the GRS is a simple way to model genetic effects since it does not consider linkage, SNP-SNP interactions, and no non-linear effects. © 2015 John Wiley & Sons Ltd/University College London.

An AST-ELM Method for Eliminating the Influence of Charging Phenomenon on ECT.

PubMed

Wang, Xiaoxin; Hu, Hongli; Jia, Huiqin; Tang, Kaihao

2017-12-09

Electrical capacitance tomography (ECT) is a promising imaging technology of permittivity distributions in multiphase flow. To reduce the effect of charging phenomenon on ECT measurement, an improved extreme learning machine method combined with adaptive soft-thresholding (AST-ELM) is presented and studied for image reconstruction. This method can provide a nonlinear mapping model between the capacitance values and medium distributions by using machine learning but not an electromagnetic-sensitive mechanism. Both simulation and experimental tests are carried out to validate the performance of the presented method, and reconstructed images are evaluated by relative error and correlation coefficient. The results have illustrated that the image reconstruction accuracy by the proposed AST-ELM method has greatly improved than that by the conventional methods under the condition with charging object.

An AST-ELM Method for Eliminating the Influence of Charging Phenomenon on ECT

PubMed Central

Wang, Xiaoxin; Hu, Hongli; Jia, Huiqin; Tang, Kaihao

2017-01-01

Electrical capacitance tomography (ECT) is a promising imaging technology of permittivity distributions in multiphase flow. To reduce the effect of charging phenomenon on ECT measurement, an improved extreme learning machine method combined with adaptive soft-thresholding (AST-ELM) is presented and studied for image reconstruction. This method can provide a nonlinear mapping model between the capacitance values and medium distributions by using machine learning but not an electromagnetic-sensitive mechanism. Both simulation and experimental tests are carried out to validate the performance of the presented method, and reconstructed images are evaluated by relative error and correlation coefficient. The results have illustrated that the image reconstruction accuracy by the proposed AST-ELM method has greatly improved than that by the conventional methods under the condition with charging object. PMID:29232850

Promises and Dangers of Combination Therapy.

PubMed

Kruis, Wolfgang; Nguyen, Phuong G; Morgenstern, Julia

2017-01-01

The efficiency of the existing methods of treating inflammatory bowel disease (IBD) is limited. There are 2 ways to address this problem - either create new treatment modalities or optimize current therapies. Optimisation may be accomplished by using combinations of established therapeutic strategies. With regard to topically acting compounds such as 5-aminosalicylic acid, combining oral and rectal preparations is a commonly used method. Another commonly used combination is anti-tumor necrosis factor (TNF)-α antibody modalities together with immunosuppressants (thiopurines, methotrexate). Several aspects favour those combinations such as increased effectivity, prevention of immunogenicity and perhaps less adverse events. Currently, discussion on directly additive therapeutic effects is in progress, which have been demonstrated in some clinical trials. As on date, the combination of infliximab with azathioprine is most likely the most effective treatment of Crohn's disease. On the other hand, a combination therapy with both compounds affecting the immune system has, of course, risks. For sure, the frequency with which serious infectious complications are arising is increasing. Furthermore, the number of patients experiencing malignancies such as hepato-splenic lymphoma or melanoma is strongly suspected to be on the rise. In summary, combinations of current treatments for IBD are widely established. Various strategies have been studied and significant improvements of therapeutic effects have been demonstrated. Unfortunately, some of those proven combinations increase therapeutic risks, for example, increase the frequency of serious infections and also of some malignancies. Therefore, great caution has to be exercised when applying combination therapies. © 2017 S. Karger AG, Basel.

Multifunctional Nanomaterials Utilizing Hybridization Chain Reaction for Molecular Diagnostics and Bioanalytical Applications

NASA Astrophysics Data System (ADS)

Rana, Md. Muhit

DNA nanotechnology has shown great promise in molecular diagnostic, bioanalytical and biomedical applications. The great challenge of detecting target analytes, biomarkers and small molecules, in molecular diagnostics is low yield sensitivity. To address this challenge, different nanomaterials have been used for a long time and to date there is no such cost-effective bioanalytical technique which can detect these target biomarkers (DNA, RNA, circulating DNA/miRNA) or environmental heavy metal ions (Hg2+ and Ag+) in a cost-effective and efficient manner. Herein, we initially discuss two possible bioanalytical detection methods- a) colorimetric and b) fluorometric assays which are very popular nowadays due to their distinctive spectroscopic properties. Finally, we report the promising colorimetric assay using a novel DNA based amplification strategy know as hybridization chain reaction (HCR) for potential application in the visual detection of low copies of biomarkers (miRNAs as little as 20 femtomole in an RNA pool and cell extracts in seven different combinations and Ebola virus DNA as low as 400 attomoles in liquid biopsy mimics in sixteen different combinations), environmental and biological heavy metal ions (mercury and silver concentrations as low as 10 pM in water, soil and urine samples) and also successfully applied to a molecular logic gate operation to distinguish OR and AND logic gates. No results showed any false-positive or false-negative information. On the other hand, we also discuss the future possibilities of HCR amplification technology, which is very promising for fluorometric bioanalysis. The HCR based nanoprobe technology has numerous remarkable advantages over other methods. It is re-programmable, simple, inexpensive, easy to assemble and operate and can be performed with visual and spectroscopic read-outs upon recognition of the target analytes. This rapid, specific and sensitive approach for biomarkers and heavy metal ion detection generates an on-site signal while eliminating the use of sophisticated high-maintenance instrumentation. We demonstrate that this state-of-the-art technology and methodology can potentially serve as an alternative approach to detect novel disease biomarkers, small molecules and inorganic compounds. This approach can be combined with the current existing methods for real-time point-of-care molecular diagnostics and is significant for preclinical or clinical studies.

Polymer nanoassemblies with solvato- and halo-fluorochromism for drug release monitoring and metastasis imaging

PubMed Central

Reichel, Derek; Rychahou, Piotr; Bae, Younsoo

2015-01-01

Background: Theranostics, an emerging technique that combines therapeutic and diagnostic modalities for various diseases, holds promise to detect cancer in early stages, eradicate metastatic tumors and ultimately reduce cancer mortality. Methods & results: This study reports unique polymer nanoassemblies that increase fluorescence intensity upon addition of hydrophobic drugs and either increase or decrease fluorescence intensity in acidic environments, depending on nanoparticle core environment properties. Extensive spectroscopic analyses were performed to determine optimal excitation and emission wavelengths, which enabled real time measurement of drugs releasing from the nanoassemblies and ex vivo imaging of acidic liver metastatic tumors from mice. Conclusion: Polymer nanoassemblies with solvato- and halo-fluorochromic properties are promising platforms to develop novel theranostic tools for the detection and treatment of metastatic tumors. PMID:26446432

Combining sprinkling experiments and superconducting gravimetry in the field: a qualitative approach to identify dominant infiltration patterns

NASA Astrophysics Data System (ADS)

Reich, Marvin; Mikolaj, Michal; Blume, Theresa; Güntner, Andreas

2017-04-01

Hydrological process research at the plot to catchment scale commonly involves invasive field methods, leading to a large amount of point data. A promising alternative, which gained increasing interest in the hydrological community over the last years, is gravimetry. The combination of its non-invasive and integrative nature opens up new possibilities to approach hydrological process research. In this study we combine a field-scale sprinkling experiment with continuous superconducting gravity (SG) measurements. The experimental design consists of 8 sprinkler units, arranged symmetrically within a radius of about ten meters around an iGrav (SG) in a field enclosure. The gravity signal of the infiltrating sprinkling water is analyzed using a simple 3D water mass distribution model. We first conducted a number of virtual sprinkling experiments resulting in different idealized infiltration patterns and determined the pattern specific gravity response. In a next step we determined which combination of idealized infiltration patterns was able to reproduce the gravity response of our real-world experiment at the Wettzell Observatory (Germany). This process hypothesis is then evaluated with measured point-scale soil moisture responses and the results of the time-lapse electric resistivity survey which was carried out during the sprinkling experiment. This study demonstrates that a controlled sprinkling experiment around a gravimeter in combination with a simple infiltration model is sufficient to identify subsurface flow patterns and thus the dominant infiltration processes. As gravimeters become more portable and can actually be deployed in the field, their combination with sprinkling experiments as shown here constitutes a promising possibility to investigate hydrological processes in a non-invasive way.

Robust adaptive multichannel SAR processing based on covariance matrix reconstruction

NASA Astrophysics Data System (ADS)

Tan, Zhen-ya; He, Feng

2018-04-01

With the combination of digital beamforming (DBF) processing, multichannel synthetic aperture radar(SAR) systems in azimuth promise well in high-resolution and wide-swath imaging, whereas conventional processing methods don't take the nonuniformity of scattering coefficient into consideration. This paper brings up a robust adaptive Multichannel SAR processing method which utilizes the Capon spatial spectrum estimator to obtain the spatial spectrum distribution over all ambiguous directions first, and then the interference-plus-noise covariance Matrix is reconstructed based on definition to acquire the Multichannel SAR processing filter. The performance of processing under nonuniform scattering coefficient is promoted by this novel method and it is robust again array errors. The experiments with real measured data demonstrate the effectiveness and robustness of the proposed method.

Discontinuous Galerkin Methods and High-Speed Turbulent Flows

NASA Astrophysics Data System (ADS)

Atak, Muhammed; Larsson, Johan; Munz, Claus-Dieter

2014-11-01

Discontinuous Galerkin methods gain increasing importance within the CFD community as they combine arbitrary high order of accuracy in complex geometries with parallel efficiency. Particularly the discontinuous Galerkin spectral element method (DGSEM) is a promising candidate for both the direct numerical simulation (DNS) and large eddy simulation (LES) of turbulent flows due to its excellent scaling attributes. In this talk, we present a DNS of a compressible turbulent boundary layer along a flat plate at a free-stream Mach number of M = 2.67 and assess the computational efficiency of the DGSEM at performing high-fidelity simulations of both transitional and turbulent boundary layers. We compare the accuracy of the results as well as the computational performance to results using a high order finite difference method.

Identifying city PV roof resource based on Gabor filter

NASA Astrophysics Data System (ADS)

Ruhang, Xu; Zhilin, Liu; Yong, Huang; Xiaoyu, Zhang

2017-06-01

To identify a city’s PV roof resources, the area and ownership distribution of residential buildings in an urban district should be assessed. To achieve this assessment, remote sensing data analysing is a promising approach. Urban building roof area estimation is a major topic for remote sensing image information extraction. There are normally three ways to solve this problem. The first way is pixel-based analysis, which is based on mathematical morphology or statistical methods; the second way is object-based analysis, which is able to combine semantic information and expert knowledge; the third way is signal-processing view method. This paper presented a Gabor filter based method. This result shows that the method is fast and with proper accuracy.

Prediction of in vivo developmental toxicity by combination of Hand1-Luc embryonic stem cell test and metabolic stability test with clarification of metabolically inapplicable candidates.

PubMed

Nagahori, Hirohisa; Suzuki, Noriyuki; Le Coz, Florian; Omori, Takashi; Saito, Koichi

2016-09-30

Hand1-Luc Embryonic Stem Cell Test (Hand1-Luc EST) is a promising alternative method for evaluation of developmental toxicity. However, the problems of predictivity have remained due to appropriateness of the solubility, metabolic system, and prediction model. Therefore, we assessed the usefulness of rat liver S9 metabolic stability test using LC-MS/MS to develop new prediction model. A total of 71 chemicals were analyzed by measuring cytotoxicity and differentiation toxicity, and highly reproducible (CV=20%) results were obtained. The first prediction model was developed by discriminant analysis performed on a full dataset using Hand1-Luc EST, and 66.2% of the chemicals were correctly classified by the cross-validated classification. A second model was developed with additional descriptors obtained from the metabolic stability test to calculate hepatic availability, and an accuracy of 83.3% was obtained with applicability domain of 50.7% (=36/71) after exclusion of 22 metabolically inapplicable candidates, which potentially have a metabolic activation property. A step-wise prediction scheme with combination of Hand1-Luc EST and metabolic stability test was therefore proposed. The current results provide a promising in vitro test method for accurately predicting in vivo developmental toxicity. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Fabrication of polymeric nano-batteries array using anodic aluminum oxide templates.

PubMed

Zhao, Qiang; Cui, Xiaoli; Chen, Ling; Liu, Ling; Sun, Zhenkun; Jiang, Zhiyu

2009-02-01

Rechargeable nano-batteries were fabricated in the array pores of anodic aluminum oxide (AAO) template, combining template method and electrochemical method. The battery consisted of electropolymerized PPy electrode, porous TiO2 separator, and chemically polymerized PAn electrode was fabricated in the array pores of two-step anodizing aluminum oxide (AAO) membrane, based on three-step assembling method. It performs typical electrochemical battery behavior with good charge-discharge ability, and presents a capacity of 25 nAs. AFM results show the hexagonal array of nano-batteries' top side. The nano-battery may be a promising device for the development of Micro-Electro-Mechanical Systems (MEMS), and Nano-Electro-Mechanical Systems (NEMS).

Some methods to regulate low-bias negative differential resistance in σ barrier separating nanoscale molecular transport systems

NASA Astrophysics Data System (ADS)

Shen, Ji-Mei; Liu, Jing; Min, Yi; Zhou, Li-Ping

2016-12-01

Using the first-principles method which combines the nonequilibrium Green’s function (NEGF) with density functional theory (DFT), the role of defect, dopant, barrier length and geometric deformation for low-bias negative differential resistance (NDR) in two capped armchair carbon nanotubes (CNTs) sandwiching σ barrier are systematically analyzed. We found that this method can regulate the negative differential resistance (NDR) effects such as current peak and peak position. The adjusting mechanism may originate from orbital interaction and orbital reconstruction. Our calculations try to manipulate the transport characteristics in energy space by simply manipulating the structure in real space, which may promise the potential applications in nanomolecular-electronics in the future.

Retinal identification based on an Improved Circular Gabor Filter and Scale Invariant Feature Transform.

PubMed

Meng, Xianjing; Yin, Yilong; Yang, Gongping; Xi, Xiaoming

2013-07-18

Retinal identification based on retinal vasculatures in the retina provides the most secure and accurate means of authentication among biometrics and has primarily been used in combination with access control systems at high security facilities. Recently, there has been much interest in retina identification. As digital retina images always suffer from deformations, the Scale Invariant Feature Transform (SIFT), which is known for its distinctiveness and invariance for scale and rotation, has been introduced to retinal based identification. However, some shortcomings like the difficulty of feature extraction and mismatching exist in SIFT-based identification. To solve these problems, a novel preprocessing method based on the Improved Circular Gabor Transform (ICGF) is proposed. After further processing by the iterated spatial anisotropic smooth method, the number of uninformative SIFT keypoints is decreased dramatically. Tested on the VARIA and eight simulated retina databases combining rotation and scaling, the developed method presents promising results and shows robustness to rotations and scale changes.

Retinal Identification Based on an Improved Circular Gabor Filter and Scale Invariant Feature Transform

PubMed Central

Meng, Xianjing; Yin, Yilong; Yang, Gongping; Xi, Xiaoming

2013-01-01

Retinal identification based on retinal vasculatures in the retina provides the most secure and accurate means of authentication among biometrics and has primarily been used in combination with access control systems at high security facilities. Recently, there has been much interest in retina identification. As digital retina images always suffer from deformations, the Scale Invariant Feature Transform (SIFT), which is known for its distinctiveness and invariance for scale and rotation, has been introduced to retinal based identification. However, some shortcomings like the difficulty of feature extraction and mismatching exist in SIFT-based identification. To solve these problems, a novel preprocessing method based on the Improved Circular Gabor Transform (ICGF) is proposed. After further processing by the iterated spatial anisotropic smooth method, the number of uninformative SIFT keypoints is decreased dramatically. Tested on the VARIA and eight simulated retina databases combining rotation and scaling, the developed method presents promising results and shows robustness to rotations and scale changes. PMID:23873409

Effect of Incentives and Mailing Features on Online Health Program Enrollment

PubMed Central

Alexander, Gwen L.; Divine, George W.; Couper, Mick P.; McClure, Jennifer B.; Stopponi, Melanie A.; Fortman, Kristine K.; Tolsma, Dennis D.; Strecher, Victor J.; Johnson, Christine Cole

2008-01-01

Background With the growing use of Internet-based interventions, strategies are needed to encourage broader participation. This study examined the effects of combinations of monetary incentives and mailing characteristics on enrollment, retention, and cost effectiveness for an online health program. Methods In 2004, a recruitment letter was mailed to randomly selected Midwestern integrated health system members aged 21–65 and stratified by gender and race/ethnicity; recipients were randomly pre-assigned to one of 24 combinations of incentives and various mailing characteristics. Enrollment and 3-month retention rates were measured by completion of online surveys. Analysis, completed in 2005, compared enrollment and retention factors using t tests and chi-square tests. Multivariate logistic regression modeling assessed the probability of enrollment and retention. Results Of 12,289 subjects, 531 (4.3%) enrolled online, ranging from 1% to 11% by incentive combination. Highest enrollment occurred with unconditional incentives, and responses varied by gender. Retention rates ranged from 0% to 100%, with highest retention linked to higher-value incentives. The combination of a $2 bill prepaid incentive and the promise of $20 for retention (10% enrollment and 71% retention) was optimal, considering per-subject recruitment costs ($32 enrollment, $70 retention) and equivalent enrollment by gender and race/ethnicity. Conclusions Cash incentives improved enrollment in an online health program. Men and women responded differently to mailing characteristics and incentives. Including a small prepaid monetary incentive ($2 or $5) and revealing the higher promised-retention incentive was cost effective and boosted enrollment. PMID:18407004

Multimodal optical phenotyping of cancer cells

NASA Astrophysics Data System (ADS)

Kastl, Lena; Budde, Björn; Isbach, Michael; Rommel, Christina; Kemper, Björn; Schnekenburger, Jürgen

2015-03-01

There is a growing interest in label-free, optical techniques like digital holographic microscopy (DHM) and optical cell stretching, since the interaction with samples is minimized. Because optical manipulation strongly depends on the optical and physiological properties of the investigated material, we combined the usage of these methods for the characterization of pancreatic tumor cells. Our results demonstrate that cells of distinct differentiation levels, or different expression in only one protein, show differences in their deformability. Additionally, the DHM results showed only few variations in the refractive index, indicating that it does not significantly influence the results of the optical cell stretching. Thus, the combined usage of the two technologies represents a promising new approach for tumor cell characterization.

The integration of acetic acid iontophoresis, orthotic therapy and physical rehabilitation for chronic plantar fasciitis: a case study

PubMed Central

Costa, Ivano A; Dyson, Anita

2007-01-01

A 15-year-old female soccer player presented with chronic plantar fasciitis. She was treated with acetic acid iontophoresis and a combination of rehabilitation protocols, ultrasound, athletic taping, custom orthotics and soft tissue therapies with symptom resolution and return to full activities within a period of 6 weeks. She reported no significant return of symptoms post follow-up at 2 months. Acetic acid iontophoresis has shown promising results and further studies should be considered to determine clinical effectiveness. The combination of acetic acid iontophoresis with conservative treatments may promote recovery within a shorter duration compared to the use of one-method treatment approaches. PMID:17885679

Tuning the Curie temperature of FeCo compounds by tetragonal distortion

NASA Astrophysics Data System (ADS)

Jakobsson, A.; Şaşıoǧlu, E.; Mavropoulos, Ph.; Ležaić, M.; Sanyal, B.; Bihlmayer, G.; Blügel, S.

2013-09-01

Combining density-functional theory calculations with a classical Monte Carlo method, we show that for B2-type FeCo compounds, tetragonal distortion gives rise to a strong reduction of the Curie temperature TC. The TC monotonically decreases from 1575 K (for c /a=1) to 940 K (for c /a=√2 ). We find that the nearest neighbor Fe-Co exchange interaction is sufficient to explain the c/a behavior of the TC. Combination of high magnetocrystalline anisotropy energy with a moderate TC value suggests tetragonal FeCo grown on the Rh substrate with c /a=1.24 to be a promising material for heat-assisted magnetic recording applications.

High-throughput design and optimization of fast lithium ion conductors by the combination of bond-valence method and density functional theory

NASA Astrophysics Data System (ADS)

Xiao, Ruijuan; Li, Hong; Chen, Liquan

2015-09-01

Looking for solid state electrolytes with fast lithium ion conduction is an important prerequisite for developing all-solid-state lithium secondary batteries. By combining the simulation techniques in different levels of accuracy, e.g. the bond-valence (BV) method and the density functional theory (DFT), a high-throughput design and optimization scheme is proposed for searching fast lithium ion conductors as candidate solid state electrolytes for lithium rechargeable batteries. The screening from more than 1000 compounds is performed through BV-based method, and the ability to predict reliable tendency of the Li+ migration energy barriers is confirmed by comparing with the results from DFT calculations. β-Li3PS4 is taken as a model system to demonstrate the application of this combination method in optimizing properties of solid electrolytes. By employing the high-throughput DFT simulations to more than 200 structures of the doping derivatives of β-Li3PS4, the effects of doping on the ionic conductivities in this material are predicted by the BV calculations. The O-doping scheme is proposed as a promising way to improve the kinetic properties of this materials, and the validity of the optimization is proved by the first-principles molecular dynamics (FPMD) simulations.

A random forest learning assisted "divide and conquer" approach for peptide conformation search.

PubMed

Chen, Xin; Yang, Bing; Lin, Zijing

2018-06-11

Computational determination of peptide conformations is challenging as it is a problem of finding minima in a high-dimensional space. The "divide and conquer" approach is promising for reliably reducing the search space size. A random forest learning model is proposed here to expand the scope of applicability of the "divide and conquer" approach. A random forest classification algorithm is used to characterize the distributions of the backbone φ-ψ units ("words"). A random forest supervised learning model is developed to analyze the combinations of the φ-ψ units ("grammar"). It is found that amino acid residues may be grouped as equivalent "words", while the φ-ψ combinations in low-energy peptide conformations follow a distinct "grammar". The finding of equivalent words empowers the "divide and conquer" method with the flexibility of fragment substitution. The learnt grammar is used to improve the efficiency of the "divide and conquer" method by removing unfavorable φ-ψ combinations without the need of dedicated human effort. The machine learning assisted search method is illustrated by efficiently searching the conformations of GGG/AAA/GGGG/AAAA/GGGGG through assembling the structures of GFG/GFGG. Moreover, the computational cost of the new method is shown to increase rather slowly with the peptide length.

Liposome-based drug co-delivery systems in cancer cells.

PubMed

Zununi Vahed, Sepideh; Salehi, Roya; Davaran, Soodabeh; Sharifi, Simin

2017-02-01

Combination therapy and nanotechnology offer a promising therapeutic method in cancer treatment. By improving drug's pharmacokinetics, nanoparticulate systems increase the drug's therapeutic effects while decreasing its adverse side effects related to high dosage. Liposomes are extensively used as drug delivery systems and several liposomal nanomedicines have been approved for clinical applications. In this regard, liposome-based combination chemotherapy (LCC) opens a novel avenue in drug delivery research and has increasingly become a significant approach in clinical cancer treatment. This review paper focuses on LCC strategies including co-delivery of: two chemotherapeutic drugs, chemotherapeutic agent with anti-cancer metals, and chemotherapeutic agent with gene agents and ligand-targeted liposome for co-delivery of chemotherapeutic agents. Definitely, the multidisciplinary method may help improve the efficacy of cancer therapy. An extensive literature review was performed mainly using PubMed. Copyright © 2016 Elsevier B.V. All rights reserved.

Computational inhibitor design against malaria plasmepsins.

PubMed

Bjelic, S; Nervall, M; Gutiérrez-de-Terán, H; Ersmark, K; Hallberg, A; Aqvist, J

2007-09-01

Plasmepsins are aspartic proteases involved in the degradation of the host cell hemoglobin that is used as a food source by the malaria parasite. Plasmepsins are highly promising as drug targets, especially when combined with the inhibition of falcipains that are also involved in hemoglobin catabolism. In this review, we discuss the mechanism of plasmepsins I-IV in view of the interest in transition state mimetics as potential compounds for lead development. Inhibitor development against plasmepsin II as well as relevant crystal structures are summarized in order to give an overview of the field. Application of computational techniques, especially binding affinity prediction by the linear interaction energy method, in the development of malarial plasmepsin inhibitors has been highly successful and is discussed in detail. Homology modeling and molecular docking have been useful in the current inhibitor design project, and the combination of such methods with binding free energy calculations is analyzed.

A computational pipeline for the development of multi-marker bio-signature panels and ensemble classifiers

PubMed Central

2012-01-01

Background Biomarker panels derived separately from genomic and proteomic data and with a variety of computational methods have demonstrated promising classification performance in various diseases. An open question is how to create effective proteo-genomic panels. The framework of ensemble classifiers has been applied successfully in various analytical domains to combine classifiers so that the performance of the ensemble exceeds the performance of individual classifiers. Using blood-based diagnosis of acute renal allograft rejection as a case study, we address the following question in this paper: Can acute rejection classification performance be improved by combining individual genomic and proteomic classifiers in an ensemble? Results The first part of the paper presents a computational biomarker development pipeline for genomic and proteomic data. The pipeline begins with data acquisition (e.g., from bio-samples to microarray data), quality control, statistical analysis and mining of the data, and finally various forms of validation. The pipeline ensures that the various classifiers to be combined later in an ensemble are diverse and adequate for clinical use. Five mRNA genomic and five proteomic classifiers were developed independently using single time-point blood samples from 11 acute-rejection and 22 non-rejection renal transplant patients. The second part of the paper examines five ensembles ranging in size from two to 10 individual classifiers. Performance of ensembles is characterized by area under the curve (AUC), sensitivity, and specificity, as derived from the probability of acute rejection for individual classifiers in the ensemble in combination with one of two aggregation methods: (1) Average Probability or (2) Vote Threshold. One ensemble demonstrated superior performance and was able to improve sensitivity and AUC beyond the best values observed for any of the individual classifiers in the ensemble, while staying within the range of observed specificity. The Vote Threshold aggregation method achieved improved sensitivity for all 5 ensembles, but typically at the cost of decreased specificity. Conclusion Proteo-genomic biomarker ensemble classifiers show promise in the diagnosis of acute renal allograft rejection and can improve classification performance beyond that of individual genomic or proteomic classifiers alone. Validation of our results in an international multicenter study is currently underway. PMID:23216969

A computational pipeline for the development of multi-marker bio-signature panels and ensemble classifiers.

PubMed

Günther, Oliver P; Chen, Virginia; Freue, Gabriela Cohen; Balshaw, Robert F; Tebbutt, Scott J; Hollander, Zsuzsanna; Takhar, Mandeep; McMaster, W Robert; McManus, Bruce M; Keown, Paul A; Ng, Raymond T

2012-12-08

Biomarker panels derived separately from genomic and proteomic data and with a variety of computational methods have demonstrated promising classification performance in various diseases. An open question is how to create effective proteo-genomic panels. The framework of ensemble classifiers has been applied successfully in various analytical domains to combine classifiers so that the performance of the ensemble exceeds the performance of individual classifiers. Using blood-based diagnosis of acute renal allograft rejection as a case study, we address the following question in this paper: Can acute rejection classification performance be improved by combining individual genomic and proteomic classifiers in an ensemble? The first part of the paper presents a computational biomarker development pipeline for genomic and proteomic data. The pipeline begins with data acquisition (e.g., from bio-samples to microarray data), quality control, statistical analysis and mining of the data, and finally various forms of validation. The pipeline ensures that the various classifiers to be combined later in an ensemble are diverse and adequate for clinical use. Five mRNA genomic and five proteomic classifiers were developed independently using single time-point blood samples from 11 acute-rejection and 22 non-rejection renal transplant patients. The second part of the paper examines five ensembles ranging in size from two to 10 individual classifiers. Performance of ensembles is characterized by area under the curve (AUC), sensitivity, and specificity, as derived from the probability of acute rejection for individual classifiers in the ensemble in combination with one of two aggregation methods: (1) Average Probability or (2) Vote Threshold. One ensemble demonstrated superior performance and was able to improve sensitivity and AUC beyond the best values observed for any of the individual classifiers in the ensemble, while staying within the range of observed specificity. The Vote Threshold aggregation method achieved improved sensitivity for all 5 ensembles, but typically at the cost of decreased specificity. Proteo-genomic biomarker ensemble classifiers show promise in the diagnosis of acute renal allograft rejection and can improve classification performance beyond that of individual genomic or proteomic classifiers alone. Validation of our results in an international multicenter study is currently underway.

Ensemble stacking mitigates biases in inference of synaptic connectivity.

PubMed

Chambers, Brendan; Levy, Maayan; Dechery, Joseph B; MacLean, Jason N

2018-01-01

A promising alternative to directly measuring the anatomical connections in a neuronal population is inferring the connections from the activity. We employ simulated spiking neuronal networks to compare and contrast commonly used inference methods that identify likely excitatory synaptic connections using statistical regularities in spike timing. We find that simple adjustments to standard algorithms improve inference accuracy: A signing procedure improves the power of unsigned mutual-information-based approaches and a correction that accounts for differences in mean and variance of background timing relationships, such as those expected to be induced by heterogeneous firing rates, increases the sensitivity of frequency-based methods. We also find that different inference methods reveal distinct subsets of the synaptic network and each method exhibits different biases in the accurate detection of reciprocity and local clustering. To correct for errors and biases specific to single inference algorithms, we combine methods into an ensemble. Ensemble predictions, generated as a linear combination of multiple inference algorithms, are more sensitive than the best individual measures alone, and are more faithful to ground-truth statistics of connectivity, mitigating biases specific to single inference methods. These weightings generalize across simulated datasets, emphasizing the potential for the broad utility of ensemble-based approaches.

Biomarker selection for medical diagnosis using the partial area under the ROC curve

PubMed Central

2014-01-01

Background A biomarker is usually used as a diagnostic or assessment tool in medical research. Finding an ideal biomarker is not easy and combining multiple biomarkers provides a promising alternative. Moreover, some biomarkers based on the optimal linear combination do not have enough discriminatory power. As a result, the aim of this study was to find the significant biomarkers based on the optimal linear combination maximizing the pAUC for assessment of the biomarkers. Methods Under the binormality assumption we obtain the optimal linear combination of biomarkers maximizing the partial area under the receiver operating characteristic curve (pAUC). Related statistical tests are developed for assessment of a biomarker set and of an individual biomarker. Stepwise biomarker selections are introduced to identify those biomarkers of statistical significance. Results The results of simulation study and three real examples, Duchenne Muscular Dystrophy disease, heart disease, and breast tissue example are used to show that our methods are most suitable biomarker selection for the data sets of a moderate number of biomarkers. Conclusions Our proposed biomarker selection approaches can be used to find the significant biomarkers based on hypothesis testing. PMID:24410929

Multiple Representations-Based Face Sketch-Photo Synthesis.

PubMed

Peng, Chunlei; Gao, Xinbo; Wang, Nannan; Tao, Dacheng; Li, Xuelong; Li, Jie

2016-11-01

Face sketch-photo synthesis plays an important role in law enforcement and digital entertainment. Most of the existing methods only use pixel intensities as the feature. Since face images can be described using features from multiple aspects, this paper presents a novel multiple representations-based face sketch-photo-synthesis method that adaptively combines multiple representations to represent an image patch. In particular, it combines multiple features from face images processed using multiple filters and deploys Markov networks to exploit the interacting relationships between the neighboring image patches. The proposed framework could be solved using an alternating optimization strategy and it normally converges in only five outer iterations in the experiments. Our experimental results on the Chinese University of Hong Kong (CUHK) face sketch database, celebrity photos, CUHK Face Sketch FERET Database, IIIT-D Viewed Sketch Database, and forensic sketches demonstrate the effectiveness of our method for face sketch-photo synthesis. In addition, cross-database and database-dependent style-synthesis evaluations demonstrate the generalizability of this novel method and suggest promising solutions for face identification in forensic science.

Accelerated detection of viral particles by combining AC electric field effects and micro-Raman spectroscopy.

PubMed

Tomkins, Matthew Robert; Liao, David Shiqi; Docoslis, Aristides

2015-01-08

A detection method that combines electric field-assisted virus capture on antibody-decorated surfaces with the "fingerprinting" capabilities of micro-Raman spectroscopy is demonstrated for the case of M13 virus in water. The proof-of-principle surface mapping of model bioparticles (protein coated polystyrene spheres) captured by an AC electric field between planar microelectrodes is presented with a methodology for analyzing the resulting spectra by comparing relative peak intensities. The same principle is applied to dielectrophoretically captured M13 phage particles whose presence is indirectly confirmed with micro-Raman spectroscopy using NeutrAvidin-Cy3 as a labeling molecule. It is concluded that the combination of electrokinetically driven virus sampling and micro-Raman based signal transduction provides a promising approach for time-efficient and in situ detection of viruses.

Accelerated Detection of Viral Particles by Combining AC Electric Field Effects and Micro-Raman Spectroscopy

PubMed Central

Tomkins, Matthew Robert; Liao, David Shiqi; Docoslis, Aristides

2015-01-01

A detection method that combines electric field-assisted virus capture on antibody-decorated surfaces with the “fingerprinting” capabilities of micro-Raman spectroscopy is demonstrated for the case of M13 virus in water. The proof-of-principle surface mapping of model bioparticles (protein coated polystyrene spheres) captured by an AC electric field between planar microelectrodes is presented with a methodology for analyzing the resulting spectra by comparing relative peak intensities. The same principle is applied to dielectrophoretically captured M13 phage particles whose presence is indirectly confirmed with micro-Raman spectroscopy using NeutrAvidin-Cy3 as a labeling molecule. It is concluded that the combination of electrokinetically driven virus sampling and micro-Raman based signal transduction provides a promising approach for time-efficient and in situ detection of viruses. PMID:25580902

Prediction of Effective Drug Combinations by an Improved Naïve Bayesian Algorithm.

PubMed

Bai, Li-Yue; Dai, Hao; Xu, Qin; Junaid, Muhammad; Peng, Shao-Liang; Zhu, Xiaolei; Xiong, Yi; Wei, Dong-Qing

2018-02-05

Drug combinatorial therapy is a promising strategy for combating complex diseases due to its fewer side effects, lower toxicity and better efficacy. However, it is not feasible to determine all the effective drug combinations in the vast space of possible combinations given the increasing number of approved drugs in the market, since the experimental methods for identification of effective drug combinations are both labor- and time-consuming. In this study, we conducted systematic analysis of various types of features to characterize pairs of drugs. These features included information about the targets of the drugs, the pathway in which the target protein of a drug was involved in, side effects of drugs, metabolic enzymes of the drugs, and drug transporters. The latter two features (metabolic enzymes and drug transporters) were related to the metabolism and transportation properties of drugs, which were not analyzed or used in previous studies. Then, we devised a novel improved naïve Bayesian algorithm to construct classification models to predict effective drug combinations by using the individual types of features mentioned above. Our results indicated that the performance of our proposed method was indeed better than the naïve Bayesian algorithm and other conventional classification algorithms such as support vector machine and K-nearest neighbor.

Double exposure using 193nm negative tone photoresist

NASA Astrophysics Data System (ADS)

Kim, Ryoung-han; Wallow, Tom; Kye, Jongwook; Levinson, Harry J.; White, Dave

2007-03-01

Double exposure is one of the promising methods for extending lithographic patterning into the low k I regime. In this paper, we demonstrate double patterning of k 1-effective=0.25 with improved process window using a negative resist. Negative resist (TOK N- series) in combination with a bright field mask is proven to provide a large process window in generating 1:3 = trench:line resist features. By incorporating two etch transfer steps into the hard mask material, frequency doubled patterns could be obtained.

Evaluation of the Kinetic Property of Single-Molecule Junctions by Tunneling Current Measurements.

PubMed

Harashima, Takanori; Hasegawa, Yusuke; Kiguchi, Manabu; Nishino, Tomoaki

2018-01-01

We investigated the formation and breaking of single-molecule junctions of two kinds of dithiol molecules by time-resolved tunneling current measurements in a metal nanogap. The resulting current trajectory was statistically analyzed to determine the single-molecule conductance and, more importantly, to reveal the kinetic property of the single-molecular junction. These results suggested that combining a measurement of the single-molecule conductance and statistical analysis is a promising method to uncover the kinetic properties of the single-molecule junction.

A Deep Learning Approach to on-Node Sensor Data Analytics for Mobile or Wearable Devices.

PubMed

Ravi, Daniele; Wong, Charence; Lo, Benny; Yang, Guang-Zhong

2017-01-01

The increasing popularity of wearable devices in recent years means that a diverse range of physiological and functional data can now be captured continuously for applications in sports, wellbeing, and healthcare. This wealth of information requires efficient methods of classification and analysis where deep learning is a promising technique for large-scale data analytics. While deep learning has been successful in implementations that utilize high-performance computing platforms, its use on low-power wearable devices is limited by resource constraints. In this paper, we propose a deep learning methodology, which combines features learned from inertial sensor data together with complementary information from a set of shallow features to enable accurate and real-time activity classification. The design of this combined method aims to overcome some of the limitations present in a typical deep learning framework where on-node computation is required. To optimize the proposed method for real-time on-node computation, spectral domain preprocessing is used before the data are passed onto the deep learning framework. The classification accuracy of our proposed deep learning approach is evaluated against state-of-the-art methods using both laboratory and real world activity datasets. Our results show the validity of the approach on different human activity datasets, outperforming other methods, including the two methods used within our combined pipeline. We also demonstrate that the computation times for the proposed method are consistent with the constraints of real-time on-node processing on smartphones and a wearable sensor platform.

Thermochromatography and activation analysis

NASA Astrophysics Data System (ADS)

Stattarov, G. S.; Kist, A. A.

1999-01-01

Gas thermochromatography is a promising method in combination with neutron activation analysis. The procedure includes heating of irradiated samples in a stream of reacting gas carrier (air, chlorine, etc.) or heating in presence of compounds evolving gas at high temperatures. Gaseous products are passed through a tube with certain temperature gradient filled with various sorbents and the gases condense in different parts of the column. Studies of the processes of producing and trapping of volatile compounds allowed to work out various set-ups of apparatus with sorption tubes of various length and various temperature gradients, various filters, sorbents, etc. Sensitivity of these methods is sufficiently better then in INAA.

Feelings and Ethics Education: The Film Dear Scientists

PubMed Central

Semendeferi, Ioanna

2014-01-01

There is an increasing body of evidence that not only cognition but also emotions shape moral judgment. The conventional teaching of responsible conduct of research, however, does not target emotions; its emphasis is on rational analysis. Here I present a new approach, ‘the feelings method,’ for incorporating emotions into science ethics education. This method is embodied in Dear Scientists, an innovative film that combines humanities with arts and works at the subconscious level, delivering an intense mix of music and images, contrasted by calm narration. Dear Scientists has struck a chord across the science, humanities, and arts communities—a promising sign. PMID:25574256

Evaluation of Four Calcium Channel Blockers as Fluconazole Resistance Inhibitors in Candida glabrata.

PubMed

Alnajjar, Lina M; Bulatova, Nailya R; Darwish, Rula M

2018-04-14

In this study we aimed to evaluate the ability of four calcium channel blockers, verapamil, diltiazem, nicardipine and nifedipine to enhance sensitivity of Candida glabrata strains to fluconazole. The synergistic antifungal effect was examined by checkerboard method; fractional inhibitory concentration index (FIC) was determined. Time-kill curve method was used for the most promising combination to further evaluate the synergetic effects. nicardipine showed additive effect with fluconazole against fluconazole-resistant and fluconazole-susceptible-dose-dependent strains (DSY565 and CBS138) known to express efflux pumps but not against fluconazole-sensitive strains. Nifedipine exhibited additive effect with fluconazole in both checkerboard (0.5< FIC <1) and time-kill curve methods (<2 log10 colony-forming units (CFU)/ml decrease in viable count). Additionally, nifedipine had own antifungal effect consistently against most of the strains used in this study with minimum inhibitory concentration of 8μg/ml. nicardipine showed additive effect with fluconazole in fluconazole-resistant strains of Candida glabrata-most probably via efflux pump inhibition as demonstrated selectively in fluconazole-resistant strains with known efflux pumps. Nifedipine displayed promising antifungal effect alone and additive effects with fluconazole. Copyright © 2018. Published by Elsevier Ltd.

Block matching sparsity regularization-based image reconstruction for incomplete projection data in computed tomography

NASA Astrophysics Data System (ADS)

Cai, Ailong; Li, Lei; Zheng, Zhizhong; Zhang, Hanming; Wang, Linyuan; Hu, Guoen; Yan, Bin

2018-02-01

In medical imaging many conventional regularization methods, such as total variation or total generalized variation, impose strong prior assumptions which can only account for very limited classes of images. A more reasonable sparse representation frame for images is still badly needed. Visually understandable images contain meaningful patterns, and combinations or collections of these patterns can be utilized to form some sparse and redundant representations which promise to facilitate image reconstructions. In this work, we propose and study block matching sparsity regularization (BMSR) and devise an optimization program using BMSR for computed tomography (CT) image reconstruction for an incomplete projection set. The program is built as a constrained optimization, minimizing the L1-norm of the coefficients of the image in the transformed domain subject to data observation and positivity of the image itself. To solve the program efficiently, a practical method based on the proximal point algorithm is developed and analyzed. In order to accelerate the convergence rate, a practical strategy for tuning the BMSR parameter is proposed and applied. The experimental results for various settings, including real CT scanning, have verified the proposed reconstruction method showing promising capabilities over conventional regularization.

The Deformations of Carbon Nanotubes under Cutting.

PubMed

Deng, Jue; Wang, Chao; Guan, Guozhen; Wu, Hao; Sun, Hong; Qiu, Longbin; Chen, Peining; Pan, Zhiyong; Sun, Hao; Zhang, Bo; Che, Renchao; Peng, Huisheng

2017-08-22

The determination of structural evolution at the atomic level is essential to understanding the intrinsic physics and chemistries of nanomaterials. Mechanochemistry represents a promising method to trace structural evolution, but conventional mechanical tension generates random breaking points, which makes it unavailable for effective analysis. It remains difficult to find an appropriate model to study shear deformations. Here, we synthesize high-modulus carbon nanotubes that can be cut precisely, and the structural evolution is efficiently investigated through a combination of geometry phase analysis and first-principles calculations. The lattice fluctuation depends on the anisotropy, chirality, curvature, and slicing rate. The strain distribution further reveals a plastic breaking mechanism for the conjugated carbon atoms under cutting. The resulting sliced carbon nanotubes with controllable sizes and open ends are promising for various applications, for example, as an anode material for lithium-ion batteries.

Chromaticity of the lattice and beam stability in energy-recovery linacs

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

Litvinenko, V.N.

2011-12-23

Energy recovery linacs (ERLs) are an emerging generation of accelerators promising to revolutionize the fields of high-energy physics and photon sciences. These accelerators combine the advantages of linear accelerators with that of storage rings, and hold the promise of delivering electron beams of unprecedented power and quality. Use of superconducting radio-frequency (SRF) cavities converts ERLs into nearly perfect 'perpetuum mobile' accelerators, wherein the beam is accelerated to a desirable energy, used, and then gives the energy back to the RF field. One potential weakness of these devices is transverse beam break-up instability that could severely limit the available beam current.more » In this paper, I present a method of suppressing these dangerous effects using a natural phenomenon in the accelerators, viz., the chromaticity of the transverse motion.« less

Research on the treatment of oily wastewater by coalescence technology.

PubMed

Li, Chunbiao; Li, Meng; Zhang, Xiaoyan

2015-01-01

Recently, oily wastewater treatment has become a hot research topic across the world. Among the common methods for oily wastewater treatment, coalescence is one of the most promising technologies because of its high efficiency, easy operation, smaller land coverage, and lower investment and operational costs. In this research, a new type of ceramic filter material was chosen to investigate the effects of some key factors including particle size of coarse-grained materials, temperature, inflow direction and inflow velocity of the reactor. The aim was to explore the optimum operating conditions for coarse-graining. Results of a series of tests showed that the optimum operating conditions were a combination of grain size 1-3 mm, water temperature 35 °C and up-flow velocity 8 m/h, which promised a maximum oil removal efficiency of 93%.

Improvement of light extraction of LYSO scintillator by using a combination of self-assembly of nanospheres and atomic layer deposition.

PubMed

Zhu, Zhichao; Liu, Bo; Zhang, Haifeng; Ren, Weina; Cheng, Chuanwei; Wu, Shuang; Gu, Mu; Chen, Hong

2015-03-23

The self-assembled monolayer periodic array of polystyrene spheres conformally coated with TiO₂ layer using atomic layer deposition is designed to obtain a further enhancement of light extraction for LYSO scintillator. The maximum enhancement is 149% for the sample with polystyrene spheres conformally coated with TiO₂ layer, while the enhancement is only 76% for the sample with only polystyrene spheres. Such further enhancement could be contributed from the additional modes forming by TiO₂ layer due to its high refractive index, which can be approved by the simulation of electric field distribution. The experimental results are agreement with the simulated results. Furthermore, the prepared structured layer exhibits an excellent combination with the surface of scintillator, which is in favor of the practical application. Therefore, it is safely concluded that the combination of self-assembly method and atomic layer deposition is a promising approach to obtain a significant enhancement of light extraction for a large area. This method can be extended to many other luminescent materials and devices.

Lipid nano-bubble combined with ultrasound for anti-keloids therapy.

PubMed

Wang, Xiao Qing; Li, Zhou-Na; Wang, Qi-Ming; Jin, Hong-Yan; Gao, Zhonggao; Jin, Zhe-Hu

2018-03-01

Keloids were characterized by excessive growth of fibrous tissues, and shared several pathological characteristics with cancer. They did put physical and emotional stress on patients in that keloids could badly change appearance of patients. N-(4-hydroxyphenyl) retinamide (4HPR) showed cytotoxic activity on a wide variety of invasive-growth cells. Our work was aim to prepare N-(4-hydroxyphenyl) retinamide-loaded lipid microbubbles (4HPR-LM) combined with ultrasound for anti-keloid therapy. 4HPR-loaded liposomes (4HPR-L) were first prepared by film evaporation method, and then 4HPR-LM were manufactured by mixing 4HPR-L and perfluoropentane (PFP) with ultrasonic cavitation method. The mean particle size and entrapment efficiency 4HPR-LM were 113 nm and 95%, respectively. The anti-keloids activity of 4HPR-LM was assessed with BALB/c nude mice bearing subcutaneous xenograft keloids model. 4HPR-LM, combined with ultrasound, could significantly induce apoptosis of keloid fibroblasts in vitro and inhibited growth of keloids in vivo. Thus, 4HPR-LM could be considered as a promising agent for anti-keloids therapy.

Advances in the Assessment of Wind Turbine Operating Extreme Loads via More Efficient Calculation Approaches

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

Graf, Peter; Damiani, Rick R.; Dykes, Katherine

2017-01-09

A new adaptive stratified importance sampling (ASIS) method is proposed as an alternative approach for the calculation of the 50 year extreme load under operational conditions, as in design load case 1.1 of the the International Electrotechnical Commission design standard. ASIS combines elements of the binning and extrapolation technique, currently described by the standard, and of the importance sampling (IS) method to estimate load probability of exceedances (POEs). Whereas a Monte Carlo (MC) approach would lead to the sought level of POE with a daunting number of simulations, IS-based techniques are promising as they target the sampling of the inputmore » parameters on the parts of the distributions that are most responsible for the extreme loads, thus reducing the number of runs required. We compared the various methods on select load channels as output from FAST, an aero-hydro-servo-elastic tool for the design and analysis of wind turbines developed by the National Renewable Energy Laboratory (NREL). Our newly devised method, although still in its infancy in terms of tuning of the subparameters, is comparable to the others in terms of load estimation and its variance versus computational cost, and offers great promise going forward due to the incorporation of adaptivity into the already powerful importance sampling concept.« less

Image enhancement for on-site X-ray nondestructive inspection of reinforced concrete structures.

PubMed

Pei, Cuixiang; Wu, Wenjing; Ueaska, Mitsuru

2016-11-22

The use of portable and high-energy X-ray system can provide a very promising approach for on-site nondestructive inspection of inner steel reinforcement of concrete structures. However, the noise properties and contrast of the radiographic images for thick concrete structures do often not meet the demands. To enhance the images, we present a simple and effective method for noise reduction based on a combined curvelet-wavelet transform and local contrast enhancement based on neighborhood operation. To investigate the performance of this method for our X-ray system, we have performed several experiments with using simulated and experimental data. With comparing to other traditional methods, it shows that the proposed image enhancement method has a better performance and can significantly improve the inspection performance for reinforced concrete structures.

Haemodynamic imaging of thoracic stent-grafts by computational fluid dynamics (CFD): presentation of a patient-specific method combining magnetic resonance imaging and numerical simulations.

PubMed

Midulla, Marco; Moreno, Ramiro; Baali, Adil; Chau, Ming; Negre-Salvayre, Anne; Nicoud, Franck; Pruvo, Jean-Pierre; Haulon, Stephan; Rousseau, Hervé

2012-10-01

In the last decade, there was been increasing interest in finding imaging techniques able to provide a functional vascular imaging of the thoracic aorta. The purpose of this paper is to present an imaging method combining magnetic resonance imaging (MRI) and computational fluid dynamics (CFD) to obtain a patient-specific haemodynamic analysis of patients treated by thoracic endovascular aortic repair (TEVAR). MRI was used to obtain boundary conditions. MR angiography (MRA) was followed by cardiac-gated cine sequences which covered the whole thoracic aorta. Phase contrast imaging provided the inlet and outlet profiles. A CFD mesh generator was used to model the arterial morphology, and wall movements were imposed according to the cine imaging. CFD runs were processed using the finite volume (FV) method assuming blood as a homogeneous Newtonian fluid. Twenty patients (14 men; mean age 62.2 years) with different aortic lesions were evaluated. Four-dimensional mapping of velocity and wall shear stress were obtained, depicting different patterns of flow (laminar, turbulent, stenosis-like) and local alterations of parietal stress in-stent and along the native aorta. A computational method using a combined approach with MRI appears feasible and seems promising to provide detailed functional analysis of thoracic aorta after stent-graft implantation. • Functional vascular imaging of the thoracic aorta offers new diagnostic opportunities • CFD can model vascular haemodynamics for clinical aortic problems • Combining CFD with MRI offers patient specific method of aortic analysis • Haemodynamic analysis of stent-grafts could improve clinical management and follow-up.

Another procedure for the preliminary ordering of loci based on two point lod scores.

PubMed

Curtis, D

1994-01-01

Because of the difficulty of performing full likelihood analysis over multiple loci and the large numbers of possible orders, a number of methods have been proposed for quickly evaluating orders and, to a lesser extent, for generating good orders. A new method is proposed which uses a function which is moderately laborious to compute, the sum of lod scores between all pairs of loci. This function can be smoothly minimized by initially allowing the loci to be placed anywhere in space, and only subsequently constraining them to lie along a one-dimensional map. Application of this approach to sample data suggests that it has promise and might usefully be combined with other methods when loci need to be ordered.

Low-dose X-ray computed tomography image reconstruction with a combined low-mAs and sparse-view protocol.

PubMed

Gao, Yang; Bian, Zhaoying; Huang, Jing; Zhang, Yunwan; Niu, Shanzhou; Feng, Qianjin; Chen, Wufan; Liang, Zhengrong; Ma, Jianhua

2014-06-16

To realize low-dose imaging in X-ray computed tomography (CT) examination, lowering milliampere-seconds (low-mAs) or reducing the required number of projection views (sparse-view) per rotation around the body has been widely studied as an easy and effective approach. In this study, we are focusing on low-dose CT image reconstruction from the sinograms acquired with a combined low-mAs and sparse-view protocol and propose a two-step image reconstruction strategy. Specifically, to suppress significant statistical noise in the noisy and insufficient sinograms, an adaptive sinogram restoration (ASR) method is first proposed with consideration of the statistical property of sinogram data, and then to further acquire a high-quality image, a total variation based projection onto convex sets (TV-POCS) method is adopted with a slight modification. For simplicity, the present reconstruction strategy was termed as "ASR-TV-POCS." To evaluate the present ASR-TV-POCS method, both qualitative and quantitative studies were performed on a physical phantom. Experimental results have demonstrated that the present ASR-TV-POCS method can achieve promising gains over other existing methods in terms of the noise reduction, contrast-to-noise ratio, and edge detail preservation.

Estimating snow depth of alpine snowpack via airborne multifrequency passive microwave radiance observations: Colorado, USA

NASA Astrophysics Data System (ADS)

Kim, R. S.; Durand, M. T.; Li, D.; Baldo, E.; Margulis, S. A.; Dumont, M.; Morin, S.

2017-12-01

This paper presents a newly-proposed snow depth retrieval approach for mountainous deep snow using airborne multifrequency passive microwave (PM) radiance observation. In contrast to previous snow depth estimations using satellite PM radiance assimilation, the newly-proposed method utilized single flight observation and deployed the snow hydrologic models. This method is promising since the satellite-based retrieval methods have difficulties to estimate snow depth due to their coarse resolution and computational effort. Indeed, this approach consists of particle filter using combinations of multiple PM frequencies and multi-layer snow physical model (i.e., Crocus) to resolve melt-refreeze crusts. The method was performed over NASA Cold Land Processes Experiment (CLPX) area in Colorado during 2002 and 2003. Results showed that there was a significant improvement over the prior snow depth estimates and the capability to reduce the prior snow depth biases. When applying our snow depth retrieval algorithm using a combination of four PM frequencies (10.7,18.7, 37.0 and 89.0 GHz), the RMSE values were reduced by 48 % at the snow depth transects sites where forest density was less than 5% despite deep snow conditions. This method displayed a sensitivity to different combinations of frequencies, model stratigraphy (i.e. different number of layering scheme for snow physical model) and estimation methods (particle filter and Kalman filter). The prior RMSE values at the forest-covered areas were reduced by 37 - 42 % even in the presence of forest cover.

Single Versus Multiple Events Error Potential Detection in a BCI-Controlled Car Game With Continuous and Discrete Feedback.

PubMed

Kreilinger, Alex; Hiebel, Hannah; Müller-Putz, Gernot R

2016-03-01

This work aimed to find and evaluate a new method for detecting errors in continuous brain-computer interface (BCI) applications. Instead of classifying errors on a single-trial basis, the new method was based on multiple events (MEs) analysis to increase the accuracy of error detection. In a BCI-driven car game, based on motor imagery (MI), discrete events were triggered whenever subjects collided with coins and/or barriers. Coins counted as correct events, whereas barriers were errors. This new method, termed ME method, combined and averaged the classification results of single events (SEs) and determined the correctness of MI trials, which consisted of event sequences instead of SEs. The benefit of this method was evaluated in an offline simulation. In an online experiment, the new method was used to detect erroneous MI trials. Such MI trials were discarded and could be repeated by the users. We found that, even with low SE error potential (ErrP) detection rates, feasible accuracies can be achieved when combining MEs to distinguish erroneous from correct MI trials. Online, all subjects reached higher scores with error detection than without, at the cost of longer times needed for completing the game. Findings suggest that ErrP detection may become a reliable tool for monitoring continuous states in BCI applications when combining MEs. This paper demonstrates a novel technique for detecting errors in online continuous BCI applications, which yields promising results even with low single-trial detection rates.

High-throughput matrix screening identifies synergistic and antagonistic antimalarial drug combinations

PubMed Central

Mott, Bryan T.; Eastman, Richard T.; Guha, Rajarshi; Sherlach, Katy S.; Siriwardana, Amila; Shinn, Paul; McKnight, Crystal; Michael, Sam; Lacerda-Queiroz, Norinne; Patel, Paresma R.; Khine, Pwint; Sun, Hongmao; Kasbekar, Monica; Aghdam, Nima; Fontaine, Shaun D.; Liu, Dongbo; Mierzwa, Tim; Mathews-Griner, Lesley A.; Ferrer, Marc; Renslo, Adam R.; Inglese, James; Yuan, Jing; Roepe, Paul D.; Su, Xin-zhuan; Thomas, Craig J.

2015-01-01

Drug resistance in Plasmodium parasites is a constant threat. Novel therapeutics, especially new drug combinations, must be identified at a faster rate. In response to the urgent need for new antimalarial drug combinations we screened a large collection of approved and investigational drugs, tested 13,910 drug pairs, and identified many promising antimalarial drug combinations. The activity of known antimalarial drug regimens was confirmed and a myriad of new classes of positively interacting drug pairings were discovered. Network and clustering analyses reinforced established mechanistic relationships for known drug combinations and identified several novel mechanistic hypotheses. From eleven screens comprising >4,600 combinations per parasite strain (including duplicates) we further investigated interactions between approved antimalarials, calcium homeostasis modulators, and inhibitors of phosphatidylinositide 3-kinases (PI3K) and the mammalian target of rapamycin (mTOR). These studies highlight important targets and pathways and provide promising leads for clinically actionable antimalarial therapy. PMID:26403635

T-Cell-Based Immunotherapy for Osteosarcoma: Challenges and Opportunities

PubMed Central

Wang, Zhan; Li, Binghao; Ren, Yingqing; Ye, Zhaoming

2016-01-01

Even though combining surgery with chemotherapy has significantly improved the prognosis of osteosarcoma patients, advanced, metastatic, or recurrent osteosarcomas are often non-responsive to chemotherapy, making development of novel efficient therapeutic methods an urgent need. Adoptive immunotherapy has the potential to be a useful non-surgical modality for treatment of osteosarcoma. Recently, alternative strategies, including immunotherapies using naturally occurring or genetically modified T cells, have been found to hold promise in the treatment of hematologic malignancies and solid tumors. In this review, we will discuss possible T-cell-based therapies against osteosarcoma with a special emphasis on combination strategies to improve the effectiveness of adoptive T cell transfer and, thus, to provide a rationale for the clinical development of immunotherapies. PMID:27683579

Low-Voltage Organic Single-Crystal Field-Effect Transistor with Steep Subthreshold Slope.

PubMed

Yang, Fangxu; Sun, Lingjie; Han, Jiangli; Li, Baili; Yu, Xi; Zhang, Xiaotao; Ren, Xiaochen; Hu, Wenping

2018-03-06

Anodization is a promising technique to form high- k dielectrics for low-power organic field-effect transistor (OFET) applications. However, the surface quality of the dielectric, which is mainly inherited from the metal electrode, can be improved further than other fabrication techniques, such as sol-gel. In this study, we applied the template stripping method to fabricate a low-power single-crystalline OFET based on the anodized AlO x dielectric. We found that the template stripping method largely improves the surface roughness of the deposited Al and allows for the formation of a high-quality AlO x high- k dielectric by anodization. The ultraflat AlO x /SAM dielectric combined with a single-crystal 2,6-diphenylanthracene (DPA) semiconductor produced a nearly defect-free interface with a steep subthreshold swing (SS) of 66 mV/decade. The current device is a promising candidate for future ultralow-power applications. Other than metal deposition, template stripping could provide a general approach to improve thin-film quality for many other types of materials and processes.

Myocardial perfusion MRI with sliding-window conjugate-gradient HYPR.

PubMed

Ge, Lan; Kino, Aya; Griswold, Mark; Mistretta, Charles; Carr, James C; Li, Debiao

2009-10-01

First-pass perfusion MRI is a promising technique for detecting ischemic heart disease. However, the diagnostic value of the method is limited by the low spatial coverage, resolution, signal-to-noise ratio (SNR), and cardiac motion-related image artifacts. In this study we investigated the feasibility of using a method that combines sliding window and CG-HYPR methods (SW-CG-HYPR) to reduce the acquisition window for each slice while maintaining the temporal resolution of one frame per heartbeat in myocardial perfusion MRI. This method allows an increased number of slices, reduced motion artifacts, and preserves the relatively high SNR and spatial resolution of the "composite images." Results from eight volunteers demonstrate the feasibility of SW-CG-HYPR for accelerated myocardial perfusion imaging with accurate signal intensity changes of left ventricle blood pool and myocardium. Using this method the acquisition time per cardiac cycle was reduced by a factor of 4 and the number of slices was increased from 3 to 8 as compared to the conventional technique. The SNR of the myocardium at peak enhancement with SW-CG-HYPR (13.83 +/- 2.60) was significantly higher (P < 0.05) than the conventional turbo-FLASH protocol (8.40 +/- 1.62). Also, the spatial resolution of the myocardial perfection images was significantly improved. SW-CG-HYPR is a promising technique for myocardial perfusion MRI. (c) 2009 Wiley-Liss, Inc.

A cost-effective method to prepare curcumin nanosuspensions with enhanced oral bioavailability.

PubMed

Wang, Yutong; Wang, Changyuan; Zhao, Jing; Ding, Yanfang; Li, Lei

2017-01-01

Nanosuspension is one of the most promising strategies to improve the oral bioavailability of insoluble drugs. The existing techniques applied to produce nanosuspensions are classified as "bottom-up" or "top-down" methods, or a combination of both. Curcumin (CUR), a Biopharmaceutics Classification System (BCS) class IV substance, is a promising drug candidate in view of its good bioactivity, but its use is limited due to its poor solubility and permeability. In the present study, CUR nanosuspensions were developed to enhance CUR oral bioavailability using a cost-effective method different from conventional techniques. The physicochemical properties of CUR nanosuspensions were characterized by dynamic light scattering (DLS) and transmission electron microscopy (TEM). The crystalline state of CUR in different nanosuspensions analyzed using differential scanning calorimeter (DSC) and X-ray diffraction analysis (PXRD) confirmed its amorphous state. In vitro dissolution degree of the prepared CUR nanosuspensions using TPGS or Brij78 as stabilizer was greatly increased. Pharmacokinetic studies demonstrated that the oral bioavailability of CUR was increased 3.18 and 3.7 times after administration of CUR/TPGS nanosuspensions or CUR/Brij78 nanosuspensions, when compared with the administration of CUR suspension. CUR nanosuspensions produced by our cost-effective method could improve its oral bioavailability. In addition, the low-cost and time-saving method reported here is highly suitable for a fast and inexpensive preparation. Copyright © 2016 Elsevier Inc. All rights reserved.

Feature Grouping and Selection Over an Undirected Graph.

PubMed

Yang, Sen; Yuan, Lei; Lai, Ying-Cheng; Shen, Xiaotong; Wonka, Peter; Ye, Jieping

2012-01-01

High-dimensional regression/classification continues to be an important and challenging problem, especially when features are highly correlated. Feature selection, combined with additional structure information on the features has been considered to be promising in promoting regression/classification performance. Graph-guided fused lasso (GFlasso) has recently been proposed to facilitate feature selection and graph structure exploitation, when features exhibit certain graph structures. However, the formulation in GFlasso relies on pairwise sample correlations to perform feature grouping, which could introduce additional estimation bias. In this paper, we propose three new feature grouping and selection methods to resolve this issue. The first method employs a convex function to penalize the pairwise l ∞ norm of connected regression/classification coefficients, achieving simultaneous feature grouping and selection. The second method improves the first one by utilizing a non-convex function to reduce the estimation bias. The third one is the extension of the second method using a truncated l 1 regularization to further reduce the estimation bias. The proposed methods combine feature grouping and feature selection to enhance estimation accuracy. We employ the alternating direction method of multipliers (ADMM) and difference of convex functions (DC) programming to solve the proposed formulations. Our experimental results on synthetic data and two real datasets demonstrate the effectiveness of the proposed methods.

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.

Determination of molecular weight of membrane proteins by the use of low-angle laser light scattering combined with high-performance gel chromatography in the presence of a non-ionic surfactant.

PubMed

Maezawa, S; Hayashi, Y; Nakae, T; Ishii, J; Kameyama, K; Takagi, T

1983-09-28

An assessment study was carried out to evaluate the performance of the low-angle laser light scattering technique combined with high-performance gel chromatography in the presence of a nonionic surfactant, octaethyleneglycol n-dodecyl ether, precision differential refractometry and ultraviolet photometry. It was found that the combined technique is highly promising as a method for the determination of the molecular weight of a membrane protein solubilized by the surfactant. For trial, molecular weights of the following membrane proteins of Escherichia coli, both solubilized in oligomeric forms, were measured; porin that forms the transmembrane diffusion pore in the outer membrane, and lambda-receptor protein that facilitates the diffusion of maltose-maltodextrins across the outer membrane. The result obtained indicates that both porin and lambda-receptor protein exist as trimers in the surfactant solution.

Effects of combined xenon and hypothermia on cerebral blood flow and oxygen consumption in newborn piglets measured with a time-resolved near-infrared technique

NASA Astrophysics Data System (ADS)

Fazel Bakhsheshi, Mohammad; Hadway, Jennifer; Morrison, Laura B.; Diop, Mamadou; St. Lawrence, Keith; Lee, Ting-Yim

2013-02-01

Mild hypothermia (HT), in which the brain is cooled to 32-33°C, has been shown to be neuroprotective for neurological emergencies such as head trauma and neonatal asphyxia. Xenon (Xe), a scarce and expensive anesthetic gas, has also shown great promise as a neuroprotectant, particularly when combined with HT. The purpose of the present study was to investigate the combined effect of Xe and HT on the cerebral metabolic rate of oxygen (CMRO2) and cerebral blood flow (CBF). A closed circuit re-breathing system was used to deliver the Xe in order to make the treatment efficient and economical. A bolus-tracking method using indocyanine green (ICG) as a flow tracer with time-resolved near-infrared (TR-NIR) technique was used to measure CBF and CMRO2 in newborn piglets.

Visual affective classification by combining visual and text features.

PubMed

Liu, Ningning; Wang, Kai; Jin, Xin; Gao, Boyang; Dellandréa, Emmanuel; Chen, Liming

2017-01-01

Affective analysis of images in social networks has drawn much attention, and the texts surrounding images are proven to provide valuable semantic meanings about image content, which can hardly be represented by low-level visual features. In this paper, we propose a novel approach for visual affective classification (VAC) task. This approach combines visual representations along with novel text features through a fusion scheme based on Dempster-Shafer (D-S) Evidence Theory. Specifically, we not only investigate different types of visual features and fusion methods for VAC, but also propose textual features to effectively capture emotional semantics from the short text associated to images based on word similarity. Experiments are conducted on three public available databases: the International Affective Picture System (IAPS), the Artistic Photos and the MirFlickr Affect set. The results demonstrate that the proposed approach combining visual and textual features provides promising results for VAC task.

Visual affective classification by combining visual and text features

PubMed Central

Liu, Ningning; Wang, Kai; Jin, Xin; Gao, Boyang; Dellandréa, Emmanuel; Chen, Liming

2017-01-01

Affective analysis of images in social networks has drawn much attention, and the texts surrounding images are proven to provide valuable semantic meanings about image content, which can hardly be represented by low-level visual features. In this paper, we propose a novel approach for visual affective classification (VAC) task. This approach combines visual representations along with novel text features through a fusion scheme based on Dempster-Shafer (D-S) Evidence Theory. Specifically, we not only investigate different types of visual features and fusion methods for VAC, but also propose textual features to effectively capture emotional semantics from the short text associated to images based on word similarity. Experiments are conducted on three public available databases: the International Affective Picture System (IAPS), the Artistic Photos and the MirFlickr Affect set. The results demonstrate that the proposed approach combining visual and textual features provides promising results for VAC task. PMID:28850566

Mid-infrared spectroscopy combined with chemometrics to detect Sclerotinia stem rot on oilseed rape (Brassica napus L.) leaves.

PubMed

Zhang, Chu; Feng, Xuping; Wang, Jian; Liu, Fei; He, Yong; Zhou, Weijun

2017-01-01

Detection of plant diseases in a fast and simple way is crucial for timely disease control. Conventionally, plant diseases are accurately identified by DNA, RNA or serology based methods which are time consuming, complex and expensive. Mid-infrared spectroscopy is a promising technique that simplifies the detection procedure for the disease. Mid-infrared spectroscopy was used to identify the spectral differences between healthy and infected oilseed rape leaves. Two different sample sets from two experiments were used to explore and validate the feasibility of using mid-infrared spectroscopy in detecting Sclerotinia stem rot (SSR) on oilseed rape leaves. The average mid-infrared spectra showed differences between healthy and infected leaves, and the differences varied among different sample sets. Optimal wavenumbers for the 2 sample sets selected by the second derivative spectra were similar, indicating the efficacy of selecting optimal wavenumbers. Chemometric methods were further used to quantitatively detect the oilseed rape leaves infected by SSR, including the partial least squares-discriminant analysis, support vector machine and extreme learning machine. The discriminant models using the full spectra and the optimal wavenumbers of the 2 sample sets were effective for classification accuracies over 80%. The discriminant results for the 2 sample sets varied due to variations in the samples. The use of two sample sets proved and validated the feasibility of using mid-infrared spectroscopy and chemometric methods for detecting SSR on oilseed rape leaves. The similarities among the selected optimal wavenumbers in different sample sets made it feasible to simplify the models and build practical models. Mid-infrared spectroscopy is a reliable and promising technique for SSR control. This study helps in developing practical application of using mid-infrared spectroscopy combined with chemometrics to detect plant disease.

Fusion of lens-free microscopy and mobile-phone microscopy images for high-color-accuracy and high-resolution pathology imaging

NASA Astrophysics Data System (ADS)

Zhang, Yibo; Wu, Yichen; Zhang, Yun; Ozcan, Aydogan

2017-03-01

Digital pathology and telepathology require imaging tools with high-throughput, high-resolution and accurate color reproduction. Lens-free on-chip microscopy based on digital in-line holography is a promising technique towards these needs, as it offers a wide field of view (FOV >20 mm2) and high resolution with a compact, low-cost and portable setup. Color imaging has been previously demonstrated by combining reconstructed images at three discrete wavelengths in the red, green and blue parts of the visible spectrum, i.e., the RGB combination method. However, this RGB combination method is subject to color distortions. To improve the color performance of lens-free microscopy for pathology imaging, here we present a wavelet-based color fusion imaging framework, termed "digital color fusion microscopy" (DCFM), which digitally fuses together a grayscale lens-free microscope image taken at a single wavelength and a low-resolution and low-magnification color-calibrated image taken by a lens-based microscope, which can simply be a mobile phone based cost-effective microscope. We show that the imaging results of an H&E stained breast cancer tissue slide with the DCFM technique come very close to a color-calibrated microscope using a 40x objective lens with 0.75 NA. Quantitative comparison showed 2-fold reduction in the mean color distance using the DCFM method compared to the RGB combination method, while also preserving the high-resolution features of the lens-free microscope. Due to the cost-effective and field-portable nature of both lens-free and mobile-phone microscopy techniques, their combination through the DCFM framework could be useful for digital pathology and telepathology applications, in low-resource and point-of-care settings.

A stacking ensemble learning framework for annual river ice breakup dates

NASA Astrophysics Data System (ADS)

Sun, Wei; Trevor, Bernard

2018-06-01

River ice breakup dates (BDs) are not merely a proxy indicator of climate variability and change, but a direct concern in the management of local ice-caused flooding. A framework of stacking ensemble learning for annual river ice BDs was developed, which included two-level components: member and combining models. The member models described the relations between BD and their affecting indicators; the combining models linked the predicted BD by each member models with the observed BD. Especially, Bayesian regularization back-propagation artificial neural network (BRANN), and adaptive neuro fuzzy inference systems (ANFIS) were employed as both member and combining models. The candidate combining models also included the simple average methods (SAM). The input variables for member models were selected by a hybrid filter and wrapper method. The performances of these models were examined using the leave-one-out cross validation. As the largest unregulated river in Alberta, Canada with ice jams frequently occurring in the vicinity of Fort McMurray, the Athabasca River at Fort McMurray was selected as the study area. The breakup dates and candidate affecting indicators in 1980-2015 were collected. The results showed that, the BRANN member models generally outperformed the ANFIS member models in terms of better performances and simpler structures. The difference between the R and MI rankings of inputs in the optimal member models may imply that the linear correlation based filter method would be feasible to generate a range of candidate inputs for further screening through other wrapper or embedded IVS methods. The SAM and BRANN combining models generally outperformed all member models. The optimal SAM combining model combined two BRANN member models and improved upon them in terms of average squared errors by 14.6% and 18.1% respectively. In this study, for the first time, the stacking ensemble learning was applied to forecasting of river ice breakup dates, which appeared promising for other river ice forecasting problems.

Fluorescence development of fingerprints by combining conjugated polymer nanoparticles with cyanoacrylate fuming.

PubMed

Chen, Hong; Ma, Rong-Liang; Fan, Zhinan; Chen, Yun; Wang, Zizheng; Fan, Li-Juan

2018-05-23

Selecting appropriate developing methods/reagents or their combination to enhance the effect for fingerprint development is of great significance for practical forensic investigation. Ethyl-2-cyanoacrylate ester (superglue) fuming is a popular method for "in-situ" developing fingerprints in forensic science, followed by fluorescence staining to enhance the contrast of the fingerprint image in some occasion. In this study, a series of fluorescent poly(p-phenylene vinylene) (PPV) nanoparticles (NPs) in colloidal solution were successfully prepared and the emission color was tuned via a simple way. The fuming process was carried out using a home-made device. The staining was accomplished by immersing a piece of absorbent cotton into the solution of NPs, and then gently applied on the fumed fingerprints for several times. The PPV NPs were found to have a better developing effect than Rhodamine 6G when excited by 365 nm UV lamp. Different emission colors of NPs are advantageous in developing fingerprints on various substrates. Mechanism study suggested that the NPs were embedded in the porous structure of the superglue resin. In all, the combination of fuming method with the staining by conjugated polymer NPs has been demonstrated to be successful for fluorescent fingerprint development and be promising for more practical forensic applications. Copyright © 2018. Published by Elsevier Inc.

In vitro synergistic effect of fluoroquinolone analogues in combination with artemisinin against Plasmodium falciparum; their antiplasmodial action in rodent malaria model.

PubMed

Agarwal, Drishti; Sharma, Manish; Dixit, Sandeep K; Dutta, Roshan K; Singh, Ashok K; Gupta, Rinkoo D; Awasthi, Satish K

2015-02-05

Emergence of drug-resistant parasite strains has surfaced as a major obstacle in attempts to ameliorate malaria. Current treatment regimen of malaria relies on the concept of artemisinin-based combination therapy (ACT). Fluoroquinolone analogues, compounds 10, 12 and 18 were investigated for their anti-malarial interaction in combination with artemisinin in vitro, against Plasmodium falciparum 3D7 strain, employing fixed-ratio combination isobologram method. In addition, the efficacy of these compounds was evaluated intraperitoneally in BALB/c mice infected with chloroquine-resistant Plasmodium berghei ANKA strain in the Peters' four-day suppressive test. Promising results were obtained in the form of synergistic or additive interactions. Compounds 10 and 12 were found to have highly synergistic interactions with artemisinin. Antiplasmodial effect was further verified by the convincing ED50 values of these compounds, which ranged between 2.31 and 3.09 (mg/kg BW). In vivo studies substantiated the potential of the fluoroquinolone derivatives to be developed as synergistic partners for anti-malarial drug combinations.

An approach for upgrading biomass and pyrolysis product quality using a combination of aqueous phase bio-oil washing and torrefaction pretreatment.

PubMed

Chen, Dengyu; Cen, Kehui; Jing, Xichun; Gao, Jinghui; Li, Chen; Ma, Zhongqing

2017-06-01

Bio-oil undergoes phase separation because of poor stability. Practical application of aqueous phase bio-oil is challenging. In this study, a novel approach that combines aqueous phase bio-oil washing and torrefaction pretreatment was used to upgrade the biomass and pyrolysis product quality. The effects of individual and combined pretreatments on cotton stalk pyrolysis were studied using TG-FTIR and a fixed bed reactor. The results showed that the aqueous phase bio-oil washing pretreatment removed metals and resolved the two pyrolysis peaks in the DTG curve. Importantly, it increased the bio-oil yield and improved the pyrolysis product quality. For example, the water and acid content of bio-oil decreased significantly along with an increase in phenol formation, and the heating value of non-condensable gases improved, and these were more pronounced when combined with torrefaction pretreatment. Therefore, the combined pretreatment is a promising method, which would contribute to the development of polygeneration pyrolysis technology. Copyright © 2017 Elsevier Ltd. All rights reserved.

Preparation of Sandwich-like NiCo2O4/rGO/NiO Heterostructure on Nickel Foam for High-Performance Supercapacitor Electrodes

NASA Astrophysics Data System (ADS)

Li, Delong; Gong, Youning; Wang, Miaosheng; Pan, Chunxu

2017-04-01

A kind of sandwich-like NiCo2O4/rGO/NiO heterostructure composite has been successfully anchored on nickel foam substrate via a three-step hydrothermal method with successive annealing treatment. The smart combination of NiCo2O4, reduced graphene oxide (rGO), and NiO nanostructure in the sandwich-like nano architecture shows a promising synergistic effect for supercapacitors with greatly enhanced electrochemical performance. For serving as supercapacitor electrode, the NiCo2O4/rGO/NiO heterostructure materials exhibit remarkable specific capacitance of 2644 mF cm-2 at current density of 1 mA cm-2, and excellent capacitance retentions of 97.5% after 3000 cycles. It is expected that the present heterostructure will be a promising electrode material for high-performance supercapacitors.

Facile Synthesis of Nanoporous Pt-Y alloy with Enhanced Electrocatalytic Activity and Durability

NASA Astrophysics Data System (ADS)

Cui, Rongjing; Mei, Ling; Han, Guangjie; Chen, Jiyun; Zhang, Genhua; Quan, Ying; Gu, Ning; Zhang, Lei; Fang, Yong; Qian, Bin; Jiang, Xuefan; Han, Zhida

2017-02-01

Recently, Pt-Y alloy has displayed an excellent electrocatalytic activity for oxygen reduction reaction (ORR), and is regarded as a promising cathode catalyst for fuel cells. However, the bulk production of nanoscaled Pt-Y alloy with outstanding catalytic performance remains a great challenge. Here, we address the challenge through a simple dealloying method to synthesize nanoporous Pt-Y alloy (NP-PtY) with a typical ligament size of ~5 nm. By combining the intrinsic superior electrocatalytic activity of Pt-Y alloy with the special nanoporous structure, the NP-PtY bimetallic catalyst presents higher activity for ORR and ethanol oxidation reaction, and better electrocatalytic stability than the commercial Pt/C catalyst and nanoporous Pt alloy. The as-made NP-PtY holds great application potential as a promising electrocatalyst in proton exchange membrane fuel cells due to the advantages of facile preparation and excellent catalytic performance.

Protease activated receptor-2 (PAR2): possible target of phytochemicals.

PubMed

Kakarala, Kavita Kumari; Jamil, Kaiser

2015-09-01

The use of phytochemicals either singly or in combination with other anticancer drugs comes with an advantage of less toxicity and minimal side effects. Signaling pathways play central role in cell cycle, cell growth, metabolism, etc. Thus, the identification of phytochemicals with promising antagonistic effect on the receptor/s playing key role in single transduction may have better therapeutic application. With this background, phytochemicals were screened against protease-activated receptor 2 (PAR2). PAR2 belongs to the superfamily of GPCRs and is an important target for breast cancer. Using in silico methods, this study was able to identify the phytochemicals with promising binding affinity suggesting their therapeutic potential in the treatment of breast cancer. The findings from this study acquires importance as the information on the possible agonists and antagonists of PAR2 is limited due its unique mechanism of activation.

A segmentation/clustering model for the analysis of array CGH data.

PubMed

Picard, F; Robin, S; Lebarbier, E; Daudin, J-J

2007-09-01

Microarray-CGH (comparative genomic hybridization) experiments are used to detect and map chromosomal imbalances. A CGH profile can be viewed as a succession of segments that represent homogeneous regions in the genome whose representative sequences share the same relative copy number on average. Segmentation methods constitute a natural framework for the analysis, but they do not provide a biological status for the detected segments. We propose a new model for this segmentation/clustering problem, combining a segmentation model with a mixture model. We present a new hybrid algorithm called dynamic programming-expectation maximization (DP-EM) to estimate the parameters of the model by maximum likelihood. This algorithm combines DP and the EM algorithm. We also propose a model selection heuristic to select the number of clusters and the number of segments. An example of our procedure is presented, based on publicly available data sets. We compare our method to segmentation methods and to hidden Markov models, and we show that the new segmentation/clustering model is a promising alternative that can be applied in the more general context of signal processing.

Theoretical Sum Frequency Generation Spectroscopy of Peptides

PubMed Central

2015-01-01

Vibrational sum frequency generation (SFG) has become a very promising technique for the study of proteins at interfaces, and it has been applied to important systems such as anti-microbial peptides, ion channel proteins, and human islet amyloid polypeptide. Moreover, so-called “chiral” SFG techniques, which rely on polarization combinations that generate strong signals primarily for chiral molecules, have proven to be particularly discriminatory of protein secondary structure. In this work, we present a theoretical strategy for calculating protein amide I SFG spectra by combining line-shape theory with molecular dynamics simulations. We then apply this method to three model peptides, demonstrating the existence of a significant chiral SFG signal for peptides with chiral centers, and providing a framework for interpreting the results on the basis of the dependence of the SFG signal on the peptide orientation. We also examine the importance of dynamical and coupling effects. Finally, we suggest a simple method for determining a chromophore’s orientation relative to the surface using ratios of experimental heterodyne-detected signals with different polarizations, and test this method using theoretical spectra. PMID:25203677

Tumbling cartilage flap and free auricular composite tissue transplantation for correcting mild and moderate forms of constricted ear.

PubMed

Pan, Bo; Zhao, Yanyong; Zhuang, Hongxing; Lin, Lin; Liu, Lei; Jiang, Haiyue

2010-01-01

To report a new surgical approach that results in a natural size and contour of the external malformed constricted ear. A total of 62 consecutive patients with constricted ear underwent surgery between July 1, 2005, and December 31, 2007. Depending on the features and severity of the deformity, the methods of tumbling cartilage flap (CF), free auricular composite graft, or a combination of these 2 techniques were applied. A total of 45 patients were treated with the method of tumbling CF. Twelve were treated with an auricular composite graft from the contralateral ear, and in 5 patients a combination of the 2 methods was used. In all cases, there was an improvement in the size, shape, and symmetry of the ears, and most patients were satisfied with the outcome. Complications were rare, and there was no donor site deformity. The technique of tumbling CF and free auricular composite graft provides a simple and promising treatment for constricted ears. Furthermore, this technique is easy to apply with a predictable good outcome.

Integrated digital error suppression for improved detection of circulating tumor DNA

PubMed Central

Kurtz, David M.; Chabon, Jacob J.; Scherer, Florian; Stehr, Henning; Liu, Chih Long; Bratman, Scott V.; Say, Carmen; Zhou, Li; Carter, Justin N.; West, Robert B.; Sledge, George W.; Shrager, Joseph B.; Loo, Billy W.; Neal, Joel W.; Wakelee, Heather A.; Diehn, Maximilian; Alizadeh, Ash A.

2016-01-01

High-throughput sequencing of circulating tumor DNA (ctDNA) promises to facilitate personalized cancer therapy. However, low quantities of cell-free DNA (cfDNA) in the blood and sequencing artifacts currently limit analytical sensitivity. To overcome these limitations, we introduce an approach for integrated digital error suppression (iDES). Our method combines in silico elimination of highly stereotypical background artifacts with a molecular barcoding strategy for the efficient recovery of cfDNA molecules. Individually, these two methods each improve the sensitivity of cancer personalized profiling by deep sequencing (CAPP-Seq) by ~3 fold, and synergize when combined to yield ~15-fold improvements. As a result, iDES-enhanced CAPP-Seq facilitates noninvasive variant detection across hundreds of kilobases. Applied to clinical non-small cell lung cancer (NSCLC) samples, our method enabled biopsy-free profiling of EGFR kinase domain mutations with 92% sensitivity and 96% specificity and detection of ctDNA down to 4 in 105 cfDNA molecules. We anticipate that iDES will aid the noninvasive genotyping and detection of ctDNA in research and clinical settings. PMID:27018799

Enhancement of the sludge disintegration and nutrients release by a treatment with potassium ferrate combined with an ultrasonic process.

PubMed

Li, Wei; Yu, Najiaowa; Liu, Qian; Li, Yiran; Ren, Nanqi; Xing, Defeng

2018-09-01

Sludge disintegration by ultrasound is a promising sludge treatment method. In order to enhance the efficiency of the sludge reduction and hydrolysis, potassium ferrate (K 2 FeO 4 ) (PF) was used. A novel method was developed to improve the sludge disintegration-sludge pretreatment by using PF in combination with an ultrasonic treatment (PF + ULT). After a short-term PF + ULT treatment, 17.23% of the volatile suspended solids (VSS) were reduced after a 900-min reaction time, which is 61.3% higher than the VSS reduction for the raw sludge. The supernatant soluble chemical oxygen demand (SCOD), total nitrogen (TN), volatile fatty acids (VFAs), soluble protein and polysaccharides increased by 522.5%, 1029.4%, 878.4%, 2996.6% and 801.9%, respectively. The constituent parts of the dissolved organic matter of the sludge products were released efficiently, which demonstrated the positive effect caused by the PF + ULT. The enhanced sludge disintegration process further alleviates environmental risk and offers a more efficient and convenient method for utilizing sludge. Copyright © 2018 Elsevier B.V. All rights reserved.

Unimolecular Reaction Pathways of a γ-Ketohydroperoxide from Combined Application of Automated Reaction Discovery Methods

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

Grambow, Colin A.; Jamal, Adeel; Li, Yi -Pei

Ketohydroperoxides are important in liquid-phase autoxidation and in gas-phase partial oxidation and pre-ignition chemistry, but because of their low concentration, instability, and various analytical chemistry limitations, it has been challenging to experimentally determine their reactivity, and only a few pathways are known. In the present work, 75 elementary-step unimolecular reactions of the simplest γ-ketohydroperoxide, 3-hydroperoxypropanal, were discovered by a combination of density functional theory with several automated transition-state search algorithms: the Berny algorithm coupled with the freezing string method, single- and double-ended growing string methods, the heuristic KinBot algorithm, and the single-component artificial force induced reaction method (SC-AFIR). The presentmore » joint approach significantly outperforms previous manual and automated transition-state searches – 68 of the reactions of γ-ketohydroperoxide discovered here were previously unknown and completely unexpected. All of the methods found the lowest-energy transition state, which corresponds to the first step of the Korcek mechanism, but each algorithm except for SC-AFIR detected several reactions not found by any of the other methods. We show that the low-barrier chemical reactions involve promising new chemistry that may be relevant in atmospheric and combustion systems. Our study highlights the complexity of chemical space exploration and the advantage of combined application of several approaches. Altogether, the present work demonstrates both the power and the weaknesses of existing fully automated approaches for reaction discovery which suggest possible directions for further method development and assessment in order to enable reliable discovery of all important reactions of any specified reactant(s).« less

Unimolecular Reaction Pathways of a γ-Ketohydroperoxide from Combined Application of Automated Reaction Discovery Methods

DOE PAGES

Grambow, Colin A.; Jamal, Adeel; Li, Yi -Pei; ...

2017-12-22

Ketohydroperoxides are important in liquid-phase autoxidation and in gas-phase partial oxidation and pre-ignition chemistry, but because of their low concentration, instability, and various analytical chemistry limitations, it has been challenging to experimentally determine their reactivity, and only a few pathways are known. In the present work, 75 elementary-step unimolecular reactions of the simplest γ-ketohydroperoxide, 3-hydroperoxypropanal, were discovered by a combination of density functional theory with several automated transition-state search algorithms: the Berny algorithm coupled with the freezing string method, single- and double-ended growing string methods, the heuristic KinBot algorithm, and the single-component artificial force induced reaction method (SC-AFIR). The presentmore » joint approach significantly outperforms previous manual and automated transition-state searches – 68 of the reactions of γ-ketohydroperoxide discovered here were previously unknown and completely unexpected. All of the methods found the lowest-energy transition state, which corresponds to the first step of the Korcek mechanism, but each algorithm except for SC-AFIR detected several reactions not found by any of the other methods. We show that the low-barrier chemical reactions involve promising new chemistry that may be relevant in atmospheric and combustion systems. Our study highlights the complexity of chemical space exploration and the advantage of combined application of several approaches. Altogether, the present work demonstrates both the power and the weaknesses of existing fully automated approaches for reaction discovery which suggest possible directions for further method development and assessment in order to enable reliable discovery of all important reactions of any specified reactant(s).« less

Use of mixed cultures of biocontrol agents to control sheep nematodes.

PubMed

Baloyi, M A; Laing, M D; Yobo, K S

2012-03-23

Biological control is a promising non-chemical approach for the control of gastrointestinal nematodes of sheep. Use of combinations of biocontrol agents have been reported to be an effective method to increase the efficacy of biological control effects. In this study, combinations of either two Bacillus thuringiensis (Bt) or Clonostachys rosea (C. rosea) isolates and Bt+C. rosea isolates were evaluated in vitro in microtitre plates for their biocontrol activity on sheep nematodes. The Baermann technique was used to extract the surviving L3 larval stages of intestinal nematodes and counted under a dissecting microscope to determine the larval counts. Results indicate that there was a significant reduction of nematode counts due to combination of biocontrol agents (P<0.001). Combinations of Bt isolates reduced nematodes counts by 72.8%, 64% and 29.8%. The results revealed a control level of 57% when C. rosea isolates P3+P8 were combined. Combination of Bt and C. rosea isolates B10+P8 caused the greatest mortality of 76.7%. Most combinations were antagonistic, with only a few combinations showing an additive effect. None were synergistic. The isolate combinations were more effective than when isolates were used alone. Copyright © 2011 Elsevier B.V. All rights reserved.

Effects of Dopant Metal Variation and Material Synthesis Method on the Material Properties of Mixed Metal Ferrites in Yttria Stabilized Zirconia for Solar Thermochemical Fuel Production

DOE PAGES

Leonard, Jeffrey; Reyes, Nichole; Allen, Kyle M.; ...

2015-01-01

Mixed metal ferrites have shown much promise in two-step solar-thermochemical fuel production. Previous work has typically focused on evaluating a particular metal ferrite produced by a particular synthesis process, which makes comparisons between studies performed by independent researchers difficult. A comparative study was undertaken to explore the effects different synthesis methods have on the performance of a particular material during redox cycling using thermogravimetry. This study revealed that materials made via wet chemistry methods and extended periods of high temperature calcination yield better redox performance. Differences in redox performance between materials made via wet chemistry methods were minimal and thesemore » demonstrated much better performance than those synthesized via the solid state method. Subsequently, various metal ferrite samples (NiFe 2 O 4 , MgFe 2 O 4 , CoFe 2 O 4 , and MnFe 2 O 4 ) in yttria stabilized zirconia (8YSZ) were synthesized via coprecipitation and tested to determine the most promising metal ferrite combination. It was determined that 10 wt.% CoFe 2 O 4 in 8YSZ produced the highest and most consistent yields of O 2 and CO. By testing the effects of synthesis methods and dopants in a consistent fashion, those aspects of ferrite preparation which are most significant can be revealed. More importantly, these insights can guide future efforts in developing the next generation of thermochemical fuel production materials.« less

LORAKS makes better SENSE: Phase-constrained partial fourier SENSE reconstruction without phase calibration.

PubMed

Kim, Tae Hyung; Setsompop, Kawin; Haldar, Justin P

2017-03-01

Parallel imaging and partial Fourier acquisition are two classical approaches for accelerated MRI. Methods that combine these approaches often rely on prior knowledge of the image phase, but the need to obtain this prior information can place practical restrictions on the data acquisition strategy. In this work, we propose and evaluate SENSE-LORAKS, which enables combined parallel imaging and partial Fourier reconstruction without requiring prior phase information. The proposed formulation is based on combining the classical SENSE model for parallel imaging data with the more recent LORAKS framework for MR image reconstruction using low-rank matrix modeling. Previous LORAKS-based methods have successfully enabled calibrationless partial Fourier parallel MRI reconstruction, but have been most successful with nonuniform sampling strategies that may be hard to implement for certain applications. By combining LORAKS with SENSE, we enable highly accelerated partial Fourier MRI reconstruction for a broader range of sampling trajectories, including widely used calibrationless uniformly undersampled trajectories. Our empirical results with retrospectively undersampled datasets indicate that when SENSE-LORAKS reconstruction is combined with an appropriate k-space sampling trajectory, it can provide substantially better image quality at high-acceleration rates relative to existing state-of-the-art reconstruction approaches. The SENSE-LORAKS framework provides promising new opportunities for highly accelerated MRI. Magn Reson Med 77:1021-1035, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

A novel method of forceps biopsy improves the diagnosis of proximal biliary malignancies.

PubMed

Kulaksiz, Hasan; Strnad, Pavel; Römpp, Achim; von Figura, Guido; Barth, Thomas; Esposito, Irene; Schirmacher, Peter; Henne-Bruns, Doris; Adler, Guido; Stiehl, Adolf

2011-02-01

Tissue specimen collection represents a cornerstone in diagnosis of proximal biliary tract malignancies offering great specificity, but only limited sensitivity. To improve the tumor detection rate, we developed a new method of forceps biopsy and compared it prospectively with endoscopic transpapillary brush cytology. 43 patients with proximal biliary stenoses, which were suspect for malignancy, undergoing endoscopic retrograde cholangiography were prospectively recruited and subjected to both biopsy [using a double-balloon enteroscopy (DBE) forceps under a guidance of a pusher and guiding catheter with guidewire] and transpapillary brush cytology. The cytological/histological findings were compared with the final clinical diagnosis. 35 out of 43 patients had a malignant disease (33 cholangiocarcinomas, 1 hepatocellular carcinoma, 1 gallbladder carcinoma). The sensitivity of cytology and biopsy in these patients was 49 and 69%, respectively. The method with DBE forceps allowed a pinpoint biopsy of the biliary stenoses. Both methods had 100% specificity, and, when combined, 80% of malignant processes were detected. All patients with non-malignant conditions were correctly assigned by both methods. No clinically relevant complications were observed. The combination of forceps biopsy and transpapillary brush cytology is safe and offers superior detection rates compared to both methods alone, and therefore represents a promising approach in evaluation of proximal biliary tract processes.

Evaluation of a Method for Rapid Detection of Listeria monocytogenes in Dry-Cured Ham Based on Impedanciometry Combined with Chromogenic Agar.

PubMed

Labrador, Mirian; Rota, María C; Pérez, Consuelo; Herrera, Antonio; Bayarri, Susana

2018-05-01

The food industry is in need of rapid, reliable methodologies for the detection of Listeria monocytogenes in ready-to-eat products, as an alternative to the International Organization of Standardization (ISO) 11290-1 reference method. The aim of this study was to evaluate impedanciometry combined with chromogenic agar culture for the detection of L. monocytogenes in dry-cured ham. The experimental setup consisted in assaying four strains of L. monocytogenes and two strains of Listeria innocua in pure culture. The method was evaluated according to the ISO 16140:2003 standard through a comparative study with the ISO reference method with 119 samples of dry-cured ham. Significant determination coefficients ( R 2 of up to 0.99) for all strains assayed in pure culture were obtained. The comparative study results had 100% accuracy, 100% specificity, and 100% sensitivity. Impedanciometry followed by chromogenic agar culture was capable of detecting 1 CFU/25 g of food. L. monocytogenes was not detected in the 65 commercial samples tested. The method evaluated herein represents a promising alternative for the food industry in its efforts to control L. monocytogenes. Overall analysis time is shorter and the method permits a straightforward analysis of a large number of samples with reliable results.

Automatically Expanding the Synonym Set of SNOMED CT using Wikipedia.

PubMed

Schlegel, Daniel R; Crowner, Chris; Elkin, Peter L

2015-01-01

Clinical terminologies and ontologies are often used in natural language processing/understanding tasks as a method for semantically tagging text. One ontology commonly used for this task is SNOMED CT. Natural language is rich and varied: many different combinations of words may be used to express the same idea. It is therefore essential that ontologies and terminologies have a rich set of synonyms. One source of synonyms is Wikipedia. We examine methods for aligning concepts in SNOMED CT with articles in Wikipedia so that newly-found synonyms may be added to SNOMED CT. Our experiments show promising results and provide guidance to researchers who wish to use Wikipedia for similar tasks.

Biomagnetic separation of Salmonella Typhimurium with high affine and specific ligand peptides isolated by phage display technique

NASA Astrophysics Data System (ADS)

Steingroewer, Juliane; Bley, Thomas; Bergemann, Christian; Boschke, Elke

2007-04-01

Analyses of food-borne pathogens are of great importance in order to minimize the health risk for customers. Thus, very sensitive and rapid detection methods are required. Current conventional culture techniques are very time consuming. Modern immunoassays and biochemical analysis also require pre-enrichment steps resulting in a turnaround time of at least 24 h. Biomagnetic separation (BMS) is a promising more rapid method. In this study we describe the isolation of high affine and specific peptides from a phage-peptide library, which combined with BMS allows the detection of Salmonella spp. with a similar sensitivity as that of immunomagnetic separation using antibodies.

High density nitrogen-vacancy sensing surface created via He{sup +} ion implantation of {sup 12}C diamond

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

Kleinsasser, Ed E., E-mail: edklein@uw.edu; Stanfield, Matthew M.; Banks, Jannel K. Q.

2016-05-16

We present a promising method for creating high-density ensembles of nitrogen-vacancy centers with narrow spin-resonances for high-sensitivity magnetic imaging. Practically, narrow spin-resonance linewidths substantially reduce the optical and RF power requirements for ensemble-based sensing. The method combines isotope purified diamond growth, in situ nitrogen doping, and helium ion implantation to realize a 100 nm-thick sensing surface. The obtained 10{sup 17 }cm{sup −3} nitrogen-vacancy density is only a factor of 10 less than the highest densities reported to date, with an observed 200 kHz spin resonance linewidth over 10 times narrower.

A new approach to the deposition of nanostructured biocatalytic films

NASA Astrophysics Data System (ADS)

Troitsky, V. I.; Berzina, T. S.; Pastorino, L.; Bernasconi, E.; Nicolini, C.

2003-06-01

In the present work, monolayer engineering was used to fabricate biocatalytic nanostructured thin films based on the enzyme penicillin G acylase. The biocatalytic films with enhanced characteristics were produced by the deposition of alternate-layer assemblies with a predetermined structure using a combination of Langmuir-Blodgett and adsorption techniques. The value of enzyme activity and the level of protein detachment were measured in dependence on the variation of film composition and on the sequence of layer alternation. As a result, highly active and stable structures were found, which could be promising candidates for practical applications. The method of modification of the deposition method to provide continuous film formation on large-area supports is discussed.

Synergistic interaction between the fungus Beauveria bassiana and desiccant dusts applied against poultry red mites (Dermanyssus gallinae).

PubMed

Steenberg, Tove; Kilpinen, Ole

2014-04-01

The poultry red mite, Dermanyssus gallinae, is a major pest in egg production, feeding on laying hens. Widely used non-chemical control methods include desiccant dusts, although their persistence under field conditions is often short. Entomopathogenic fungi may also hold potential for mite control, but these fungi often take several days to kill mites. Laboratory experiments were carried out to study the efficacy of 3 types of desiccant dusts, the fungus Beauveria bassiana and combinations of the two control agents against D. gallinae. There was significant synergistic interaction between each of the desiccant dusts and the fungus, with observed levels of mite mortality significantly higher than those expected for an additive effect (up to 38 % higher). Synergistic interaction between desiccant dust and fungus was found also when different application methods were used for the fungus and at different levels of relative humidity. Although increased levels of mortality were reached due to the synergistic interaction, the speed of lethal action was not influenced by combining the two components. The persistence of the control agents applied separately or in combination did not change over a period of 4 weeks. Overall, combinations of desiccant dusts and fungus conidia seem to hold considerable promise for future non-chemical control of poultry red mites.

Classification of MR brain images by combination of multi-CNNs for AD diagnosis

NASA Astrophysics Data System (ADS)

Cheng, Danni; Liu, Manhua; Fu, Jianliang; Wang, Yaping

2017-07-01

Alzheimer's disease (AD) is an irreversible neurodegenerative disorder with progressive impairment of memory and cognitive functions. Its early diagnosis is crucial for development of future treatment. Magnetic resonance images (MRI) play important role to help understand the brain anatomical changes related to AD. Conventional methods extract the hand-crafted features such as gray matter volumes and cortical thickness and train a classifier to distinguish AD from other groups. Different from these methods, this paper proposes to construct multiple deep 3D convolutional neural networks (3D-CNNs) to learn the various features from local brain images which are combined to make the final classification for AD diagnosis. First, a number of local image patches are extracted from the whole brain image and a 3D-CNN is built upon each local patch to transform the local image into more compact high-level features. Then, the upper convolution and fully connected layers are fine-tuned to combine the multiple 3D-CNNs for image classification. The proposed method can automatically learn the generic features from imaging data for classification. Our method is evaluated using T1-weighted structural MR brain images on 428 subjects including 199 AD patients and 229 normal controls (NC) from Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Experimental results show that the proposed method achieves an accuracy of 87.15% and an AUC (area under the ROC curve) of 92.26% for AD classification, demonstrating the promising classification performances.

Advancing Usability Evaluation through Human Reliability Analysis

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

Ronald L. Boring; David I. Gertman

2005-07-01

This paper introduces a novel augmentation to the current heuristic usability evaluation methodology. The SPAR-H human reliability analysis method was developed for categorizing human performance in nuclear power plants. Despite the specialized use of SPAR-H for safety critical scenarios, the method also holds promise for use in commercial off-the-shelf software usability evaluations. The SPAR-H method shares task analysis underpinnings with human-computer interaction, and it can be easily adapted to incorporate usability heuristics as performance shaping factors. By assigning probabilistic modifiers to heuristics, it is possible to arrive at the usability error probability (UEP). This UEP is not a literal probabilitymore » of error but nonetheless provides a quantitative basis to heuristic evaluation. When combined with a consequence matrix for usability errors, this method affords ready prioritization of usability issues.« less

Insecticide Resistance: Challenge to Pest Management and Basic Research

NASA Astrophysics Data System (ADS)

Brattsten, L. B.; Holyoke, C. W.; Leeper, J. R.; Raffa, K. F.

1986-03-01

The agricultural use of synthetic insecticides usually protects crops but imposes strong selection pressures that can result in the development of resistance. The most important resistance mechanisms are enhancement of the capacity to metabolically detoxify insecticides and alterations in target sites that prevent insecticides from binding to them. Insect control methods must incorporate strategies to minimize resistance development and preserve the utility of the insecticides. The most promising approach, integrated pest management, includes the use of chemical insecticides in combination with improved cultural and biologically based techniques.

QM Automata: A New Class of Restricted Quantum Membrane Automata.

PubMed

Giannakis, Konstantinos; Singh, Alexandros; Kastampolidou, Kalliopi; Papalitsas, Christos; Andronikos, Theodore

2017-01-01

The term "Unconventional Computing" describes the use of non-standard methods and models in computing. It is a recently established field, with many interesting and promising results. In this work we combine notions from quantum computing with aspects of membrane computing to define what we call QM automata. Specifically, we introduce a variant of quantum membrane automata that operate in accordance with the principles of quantum computing. We explore the functionality and capabilities of the QM automata through indicative examples. Finally we suggest future directions for research on QM automata.

Touching the theoretical capacity: synthesizing cubic LiTi2(PO4)3/C nanocomposites for high-performance lithium-ion battery.

PubMed

Deng, Wenjun; Wang, Xusheng; Liu, Chunyi; Li, Chang; Xue, Mianqi; Li, Rui; Pan, Feng

2018-04-05

A cubic LiTi2(PO4)3/C composite is successfully prepared via a simple solvothermal method and further glucose-pyrolysis treatment. The as-fabricated LTP/C material delivers an ultra-high reversible capacity of 144 mA h g-1 at 0.2C rate, which is the highest ever reported, and shows considerable performance improvement compared with before. Combining this with the stable cycling performance and high rate capability, such material has a promising future in practical application.

Continued Development of in Situ Geochronology for Planetary Missions

NASA Technical Reports Server (NTRS)

Devismes, D.; Cohen, B. A.

2015-01-01

The instrument 'Potassium (K) Argon Laser Experiment' (KArLE) is developed and designed for in situ absolute dating of rocks on planetary surfaces. It is based on the K-Ar dating method and uses the Laser Induced Breakdown Spectroscopy - Laser Ablation - Quadrupole Mass Spectrometry (LIBSLA- QMS) technique. We use a dedicated interface to combine two instruments similar to SAM of Mars Science Laboratory (for the QMS) and ChemCam (for the LA and LIBS). The prototype has demonstrated that KArLE is a suitable and promising instrument for in situ absolute dating.

[Effectiveness of FTA Elute® indicating cartridge in combination with hybrid capture 2 for cervical cancer screening].

PubMed

Chen, Feng; Zhang, Xi; Wang, Shaoming; Hu, Shangying; Chen, Wen; Zhao, Fanghui; He, Wei; Zhang, Yuqing; Qiao, Youlin

2015-02-01

To evaluate the effectiveness of FTA Elute® Cartridge (GE healthcare, Kent, UK) in combination with hybrid capture 2 (HC2) testing for cervical cancer screening. From May to June 2012, 412 women aged 25 to 65 years in Jiangxi Tonggu were enrolled in the study. We used pathological outcome as the gold standard, and the accuracy of the FTA card in combination with HC2 testing was investigated from both physician- and self-sampling, respectively. Physician sampling using the FTA card in combination with HC2 testing showed a comparable sensitivity (12/13) with the liquid based medium, but a higher specificity 69.5% (266/383) vs (77.8%, 298/383) (P < 0.001).When self sampling method was used, the sensitivity and specificity of using the FTA card in combination with HC2 testing with liquid based medium was 10/13 vs 8/13(P = 0.625) and (62.3%, 238/382) vs (75.7%, 289/382) (P < 0.001). The agreement of detection results for HC2 between FTA and liquid-based sampling medium was 86.1% (340/395) and 79.5% (314/395). For physician-collected samples used for HC2 testing to detect CIN2+, the accuracy of the FTA card was superior to that of the liquid-based medium (area under the receiver operating characteristic curve (AUC) = 0.898, 95%CI:0.838-0.958). FTA Elute® cartridge in combination with HC2 testing is a promising method of specimen transport for cervical cancer screening programs with a good precision.With further optimization, it could become an effective method for cervical cancer screening in various economic levels of areas.

Combination Immunotherapy in Non-small Cell Lung Cancer.

PubMed

Marmarelis, Melina E; Aggarwal, Charu

2018-05-08

Checkpoint blockade has changed the treatment landscape in non-small cell lung cancer (NSCLC), but single-agent approaches are effective for only a select subset of patients. Here, we will review the evidence for combination immunotherapies in NSCLC and the clinical data evaluating the efficacy of this approach. Clinical trials evaluating combination PD-1 and CTLA-4 blockade as well as PD-1 in combination with agents targeting IDO1, B7-H3, VEGF, and EGFR show promising results. Additional studies targeting other immune pathways like TIGIT, LAG-3, and cellular therapies are ongoing. Combination immunotherapy has the potential to improve outcomes in NSCLC. Data from early clinical trials is promising and reveals that these agents can be administered together safely without a significant increase in toxicity. Further studies are needed to evaluate their long-term safety and efficacy and to determine appropriate patient selection.

Breast cancer evaluation by fluorescent dot detection using combined mathematical morphology and multifractal techniques

PubMed Central

2011-01-01

Background Fluorescence in situ hybridization (FISH) is very accurate method for measuring HER2 gene copies, as a sign of potential breast cancer. This method requires small tissue samples, and has a high sensitivity to detect abnormalities from a histological section. By using multiple colors, this method allows the detection of multiple targets simultaneously. The target parts in the cells become visible as colored dots. The HER-2 probes are visible as orange stained spots under a fluorescent microscope while probes for centromere 17 (CEP-17), the chromosome on which the gene HER-2/neu is located, are visible as green spots. Methods The conventional analysis involves the scoring of the ratio of HER-2/neu over CEP 17 dots within each cell nucleus and then averaging the scores for a number of 60 cells. A ratio of 2.0 of HER-2/neu to CEP 17 copy number denotes amplification. Several methods have been proposed for the detection and automated evaluation (dot counting) of FISH signals. In this paper the combined method based on the mathematical morphology (MM) and inverse multifractal (IMF) analysis is suggested. Similar method was applied recently in detection of microcalcifications in digital mammograms, and was very successful. Results The combined MM using top-hat and bottom-hat filters, and the IMF method was applied to FISH images from Molecular Biology Lab, Department of Pathology, Wielkoposka Cancer Center, Poznan. Initial results indicate that this method can be applied to FISH images for the evaluation of HER2/neu status. Conclusions Mathematical morphology and multifractal approach are used for colored dot detection and counting in FISH images. Initial results derived on clinical cases are promising. Note that the overlapping of colored dots, particularly red/orange dots, needs additional improvements in post-processing. PMID:21489192

A study of various methods for calculating locations of lightning events

NASA Technical Reports Server (NTRS)

Cannon, John R.

1995-01-01

This article reports on the results of numerical experiments on finding the location of lightning events using different numerical methods. The methods include linear least squares, nonlinear least squares, statistical estimations, cluster analysis and angular filters and combinations of such techniques. The experiments involved investigations of methods for excluding fake solutions which are solutions that appear to be reasonable but are in fact several kilometers distant from the actual location. Some of the conclusions derived from the study are that bad data produces fakes, that no fool-proof method of excluding fakes was found, that a short base-line interferometer under development at Kennedy Space Center to measure the direction cosines of an event shows promise as a filter for excluding fakes. The experiments generated a number of open questions, some of which are discussed at the end of the report.

Imaging of surface spin textures on bulk crystals by scanning electron microscopy

NASA Astrophysics Data System (ADS)

Akamine, Hiroshi; Okumura, So; Farjami, Sahar; Murakami, Yasukazu; Nishida, Minoru

2016-11-01

Direct observation of magnetic microstructures is vital for advancing spintronics and other technologies. Here we report a method for imaging surface domain structures on bulk samples by scanning electron microscopy (SEM). Complex magnetic domains, referred to as the maze state in CoPt/FePt alloys, were observed at a spatial resolution of less than 100 nm by using an in-lens annular detector. The method allows for imaging almost all the domain walls in the mazy structure, whereas the visualisation of the domain walls with the classical SEM method was limited. Our method provides a simple way to analyse surface domain structures in the bulk state that can be used in combination with SEM functions such as orientation or composition analysis. Thus, the method extends applications of SEM-based magnetic imaging, and is promising for resolving various problems at the forefront of fields including physics, magnetics, materials science, engineering, and chemistry.

Workshop on Algorithms for Time-Series Analysis

NASA Astrophysics Data System (ADS)

Protopapas, Pavlos

2012-04-01

abstract-type="normal">SummaryThis Workshop covered the four major subjects listed below in two 90-minute sessions. Each talk or tutorial allowed questions, and concluded with a discussion. Classification: Automatic classification using machine-learning methods is becoming a standard in surveys that generate large datasets. Ashish Mahabal (Caltech) reviewed various methods, and presented examples of several applications. Time-Series Modelling: Suzanne Aigrain (Oxford University) discussed autoregressive models and multivariate approaches such as Gaussian Processes. Meta-classification/mixture of expert models: Karim Pichara (Pontificia Universidad Católica, Chile) described the substantial promise which machine-learning classification methods are now showing in automatic classification, and discussed how the various methods can be combined together. Event Detection: Pavlos Protopapas (Harvard) addressed methods of fast identification of events with low signal-to-noise ratios, enlarging on the characterization and statistical issues of low signal-to-noise ratios and rare events.

[Intrapartum foetal monitoring: from stethoscope to ST analysis of the ECG].

PubMed

Westerhuis, Michelle E M H; Strasser, Sanne M; Moons, Karel G M; Mol, Ben Willem J; Visser, Gerard H A; Kwee, Anneke

2009-01-01

Since the 1970s, intrapartum monitoring of the distressed foetus has been managed by continuous registration of the foetal heart rate, together with uterine activity (cardiotocogram; CTG). Use of CTG without additional foetal information leads to unnecessary interventions because of the high number of false-positive signals. Foetal blood sampling (FBS) is a solution to this problem, but is not always consistently carried out. Automated ST analysis of the foetal electrocardiogram (STAN method), combined with the CTG, may lead to reduction of metabolic acidosis, fewer interventions and fewer foetal blood samples. A disadvantage of application of the STAN method is that it is based on visual interpretation of the CTG, with large inter- and intraobserver variability. In spite of this shortcoming the method may be promising.

Orlistat and antisense-miRNA-loaded PLGA-PEG nanoparticles for enhanced triple negative breast cancer therapy

PubMed Central

Bhargava-Shah, Aarohi; Foygel, Kira; Devulapally, Rammohan; Paulmurugan, Ramasamy

2016-01-01

Background: This study explores the use of hydrophilic poly(ethylene glycol)-conjugated poly(lactic-co-glycolic acid) nanoparticles (PLGA-PEG-NPs) as delivery system to improve the antitumor effect of antiobesity drug orlistat for triple-negative breast cancer (TNBC) therapy by improving its bioavailability. Materials & methods: PLGA-PEG-NPs were synthesized by emulsion-diffusion-evaporation method, and the experiments were conducted in vitro in MDA-MB-231 and SKBr3 TNBC and normal breast fibroblast cells. Results: Delivery of orlistat via PLGA-PEG-NPs reduced its IC50 compared with free orlistat. Combined treatment of orlistat-loaded NPs and doxorubicin or antisense-miR-21-loaded NPs significantly enhanced apoptotic effect compared with independent doxorubicin, anti-miR-21-loaded NPs, orlistat-loaded NPs or free orlistat treatments. Conclusion: We demonstrate that orlistat in combination with antisense-miR-21 or current chemotherapy holds great promise as a novel and versatile treatment agent for TNBC. PMID:26787319

Highly improved acarbose production of Actinomyces through the combination of ARTP and penicillin susceptible mutant screening.

PubMed

Ren, Fei; Chen, Long; Tong, Qunyi

2017-01-01

Atmospheric and room temperature plasma (ARTP) was first employed to generate mutants of Actinomyces JN537 for improving acarbose production. To obtain higher acarbose producing strains, the method of screening the strains for susceptibility to penicillin was used after treatment with ARTP. The rationale for the strategy was that mutants showing penicillin susceptibility were likely to be high acarbose producers, as their ability to synthesize cell walls was weak which might enhance metabolic flux to the pathway of acarbose biosynthesis. Acarbose yield of the mutant strain M37 increased by 62.5 % than that of the original strain. The contents of monosaccharides and amino acids of the cell wall of M37 were lower than that of the original strain. The acarbose production ability in mutant strain remained relatively stable after 10 generations. This work provides a promising strategy for obtaining high acarbose-yield strains by combination of ARTP mutation method and efficient screening technique.

Fast 3D shape measurements with reduced motion artifacts

NASA Astrophysics Data System (ADS)

Feng, Shijie; Zuo, Chao; Chen, Qian; Gu, Guohua

2017-10-01

Fringe projection is an extensively used technique for high speed three-dimensional (3D) measurements of dynamic objects. However, the motion often leads to artifacts in reconstructions due to the sequential recording of the set of patterns. In order to reduce the adverse impact of the movement, we present a novel high speed 3D scanning technique combining the fringe projection and stereo. Firstly, promising measuring speed is achieved by modifying the traditional aperiodic sinusoidal patterns so that the fringe images can be cast at kilohertz with the widely used defocusing strategy. Next, a temporal intensity tracing algorithm is developed to further alleviate the influence of motion by accurately tracing the ideal intensity for stereo matching. Then, a combined cost measure is suggested to robustly estimate the cost for each pixel. In comparison with the traditional method where the effect of motion is not considered, experimental results show that the reconstruction accuracy for dynamic objects can be improved by an order of magnitude with the proposed method.

Simultaneous CT-MRI Reconstruction for Constrained Imaging Geometries using Structural Coupling and Compressive Sensing

PubMed Central

Xi, Yan; Zhao, Jun; Bennett, James R.; Stacy, Mitchel R.; Sinusas, Albert J.; Wang, Ge

2016-01-01

Objective A unified reconstruction framework is presented for simultaneous CT-MRI reconstruction. Significance Combined CT-MRI imaging has the potential for improved results in existing preclinical and clinical applications, as well as opening novel research directions for future applications. Methods In an ideal CT-MRI scanner, CT and MRI acquisitions would occur simultaneously, and hence would be inherently registered in space and time. Alternatively, separately acquired CT and MRI scans can be fused to simulate an instantaneous acquisition. In this study, structural coupling and compressive sensing techniques are combined to unify CT and MRI reconstructions. A bidirectional image estimation method was proposed to connect images from different modalities. Hence, CT and MRI data serve as prior knowledge to each other for better CT and MRI image reconstruction than what could be achieved with separate reconstruction. Results Our integrated reconstruction methodology is demonstrated with numerical phantom and real-dataset based experiments, and has yielded promising results. PMID:26672028

Piezoresistive effect in p-type 3C-SiC at high temperatures characterized using Joule heating

PubMed Central

Phan, Hoang-Phuong; Dinh, Toan; Kozeki, Takahiro; Qamar, Afzaal; Namazu, Takahiro; Dimitrijev, Sima; Nguyen, Nam-Trung; Dao, Dzung Viet

2016-01-01

Cubic silicon carbide is a promising material for Micro Electro Mechanical Systems (MEMS) applications in harsh environ-ments and bioapplications thanks to its large band gap, chemical inertness, excellent corrosion tolerance and capability of growth on a Si substrate. This paper reports the piezoresistive effect of p-type single crystalline 3C-SiC characterized at high temperatures, using an in situ measurement method. The experimental results show that the highly doped p-type 3C-SiC possesses a relatively stable gauge factor of approximately 25 to 28 at temperatures varying from 300 K to 573 K. The in situ method proposed in this study also demonstrated that, the combination of the piezoresistive and thermoresistive effects can increase the gauge factor of p-type 3C-SiC to approximately 20% at 573 K. The increase in gauge factor based on the combination of these phenomena could enhance the sensitivity of SiC based MEMS mechanical sensors. PMID:27349378

Piezoresistive effect in p-type 3C-SiC at high temperatures characterized using Joule heating

NASA Astrophysics Data System (ADS)

Phan, Hoang-Phuong; Dinh, Toan; Kozeki, Takahiro; Qamar, Afzaal; Namazu, Takahiro; Dimitrijev, Sima; Nguyen, Nam-Trung; Dao, Dzung Viet

2016-06-01

Cubic silicon carbide is a promising material for Micro Electro Mechanical Systems (MEMS) applications in harsh environ-ments and bioapplications thanks to its large band gap, chemical inertness, excellent corrosion tolerance and capability of growth on a Si substrate. This paper reports the piezoresistive effect of p-type single crystalline 3C-SiC characterized at high temperatures, using an in situ measurement method. The experimental results show that the highly doped p-type 3C-SiC possesses a relatively stable gauge factor of approximately 25 to 28 at temperatures varying from 300 K to 573 K. The in situ method proposed in this study also demonstrated that, the combination of the piezoresistive and thermoresistive effects can increase the gauge factor of p-type 3C-SiC to approximately 20% at 573 K. The increase in gauge factor based on the combination of these phenomena could enhance the sensitivity of SiC based MEMS mechanical sensors.

A Combined Theoretical and Experimental Study for Silver Electroplating

PubMed Central

Liu, Anmin; Ren, Xuefeng; An, Maozhong; Zhang, Jinqiu; Yang, Peixia; Wang, Bo; Zhu, Yongming; Wang, Chong

2014-01-01

A novel method combined theoretical and experimental study for environmental friendly silver electroplating was introduced. Quantum chemical calculations and molecular dynamic (MD) simulations were employed for predicting the behaviour and function of the complexing agents. Electronic properties, orbital information, and single point energies of the 5,5-dimethylhydantoin (DMH), nicotinic acid (NA), as well as their silver(I)-complexes were provided by quantum chemical calculations based on density functional theory (DFT). Adsorption behaviors of the agents on copper and silver surfaces were investigated using MD simulations. Basing on the data of quantum chemical calculations and MD simulations, we believed that DMH and NA could be the promising complexing agents for silver electroplating. The experimental results, including of electrochemical measurement and silver electroplating, further confirmed the above prediction. This efficient and versatile method thus opens a new window to study or design complexing agents for generalized metal electroplating and will vigorously promote the level of this research region. PMID:24452389

Change detection and classification of land cover in multispectral satellite imagery using clustering of sparse approximations (CoSA) over learned feature dictionaries

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

Moody, Daniela I.; Brumby, Steven P.; Rowland, Joel C.

Neuromimetic machine vision and pattern recognition algorithms are of great interest for landscape characterization and change detection in satellite imagery in support of global climate change science and modeling. We present results from an ongoing effort to extend machine vision methods to the environmental sciences, using adaptive sparse signal processing combined with machine learning. A Hebbian learning rule is used to build multispectral, multiresolution dictionaries from regional satellite normalized band difference index data. Land cover labels are automatically generated via our CoSA algorithm: Clustering of Sparse Approximations, using a clustering distance metric that combines spectral and spatial textural characteristics tomore » help separate geologic, vegetative, and hydrologie features. We demonstrate our method on example Worldview-2 satellite images of an Arctic region, and use CoSA labels to detect seasonal surface changes. In conclusion, our results suggest that neuroscience-based models are a promising approach to practical pattern recognition and change detection problems in remote sensing.« less

Change detection and classification of land cover in multispectral satellite imagery using clustering of sparse approximations (CoSA) over learned feature dictionaries

DOE PAGES

Moody, Daniela I.; Brumby, Steven P.; Rowland, Joel C.; ...

2014-10-01

Neuromimetic machine vision and pattern recognition algorithms are of great interest for landscape characterization and change detection in satellite imagery in support of global climate change science and modeling. We present results from an ongoing effort to extend machine vision methods to the environmental sciences, using adaptive sparse signal processing combined with machine learning. A Hebbian learning rule is used to build multispectral, multiresolution dictionaries from regional satellite normalized band difference index data. Land cover labels are automatically generated via our CoSA algorithm: Clustering of Sparse Approximations, using a clustering distance metric that combines spectral and spatial textural characteristics tomore » help separate geologic, vegetative, and hydrologie features. We demonstrate our method on example Worldview-2 satellite images of an Arctic region, and use CoSA labels to detect seasonal surface changes. In conclusion, our results suggest that neuroscience-based models are a promising approach to practical pattern recognition and change detection problems in remote sensing.« less

Toward innovative combinational immunotherapy: A systems biology perspective.

PubMed

Li, Xue-Tao; Yang, Jin-Ji; Wu, Yi-Long; Hou, Jun

2018-05-08

The treatment of non-small-cell lung cancer (NSCLC) has advanced significantly in the last decades. Especially immune checkpoint inhibitors have shown inconceivable effect on enhancing host anti-tumor activity in NSCLC. However, the limitation of checkpoint blockade monotherapy seems unavoidable in most of the NSCLC patients and only ∼20% of them achieved response to monotherapy with immune checkpoint inhibitors. Thus combining immune checkpoint inhibitors with other agents with different action mechanisms holds a promise to revitalize NSCLC treatment, such as the combination of checkpoint inhibitors with angiogenesis inhibitors, or with chemotherapy, as well as the combination of two checkpoint inhibitors. Recently, various combinational strategies have been explored to setup promising combination regimens and to understand the action mechanisms. In this review, we summarize the suspected synergistic mechanisms of several combinational approaches by reviewing the available preclinical and clinical data. Then we discuss in light of the current knowledge of cancer biology and systems biology the important facets to be examined when setting up a framework for developing immunotherapy-based combination strategies. Copyright © 2018. Published by Elsevier Ltd.

Bayesian automated cortical segmentation for neonatal MRI

NASA Astrophysics Data System (ADS)

Chou, Zane; Paquette, Natacha; Ganesh, Bhavana; Wang, Yalin; Ceschin, Rafael; Nelson, Marvin D.; Macyszyn, Luke; Gaonkar, Bilwaj; Panigrahy, Ashok; Lepore, Natasha

2017-11-01

Several attempts have been made in the past few years to develop and implement an automated segmentation of neonatal brain structural MRI. However, accurate automated MRI segmentation remains challenging in this population because of the low signal-to-noise ratio, large partial volume effects and inter-individual anatomical variability of the neonatal brain. In this paper, we propose a learning method for segmenting the whole brain cortical grey matter on neonatal T2-weighted images. We trained our algorithm using a neonatal dataset composed of 3 fullterm and 4 preterm infants scanned at term equivalent age. Our segmentation pipeline combines the FAST algorithm from the FSL library software and a Bayesian segmentation approach to create a threshold matrix that minimizes the error of mislabeling brain tissue types. Our method shows promising results with our pilot training set. In both preterm and full-term neonates, automated Bayesian segmentation generates a smoother and more consistent parcellation compared to FAST, while successfully removing the subcortical structure and cleaning the edges of the cortical grey matter. This method show promising refinement of the FAST segmentation by considerably reducing manual input and editing required from the user, and further improving reliability and processing time of neonatal MR images. Further improvement will include a larger dataset of training images acquired from different manufacturers.

Evaluation of prostate segmentation algorithms for MRI: the PROMISE12 challenge

PubMed Central

Litjens, Geert; Toth, Robert; van de Ven, Wendy; Hoeks, Caroline; Kerkstra, Sjoerd; van Ginneken, Bram; Vincent, Graham; Guillard, Gwenael; Birbeck, Neil; Zhang, Jindang; Strand, Robin; Malmberg, Filip; Ou, Yangming; Davatzikos, Christos; Kirschner, Matthias; Jung, Florian; Yuan, Jing; Qiu, Wu; Gao, Qinquan; Edwards, Philip “Eddie”; Maan, Bianca; van der Heijden, Ferdinand; Ghose, Soumya; Mitra, Jhimli; Dowling, Jason; Barratt, Dean; Huisman, Henkjan; Madabhushi, Anant

2014-01-01

Prostate MRI image segmentation has been an area of intense research due to the increased use of MRI as a modality for the clinical workup of prostate cancer. Segmentation is useful for various tasks, e.g. to accurately localize prostate boundaries for radiotherapy or to initialize multi-modal registration algorithms. In the past, it has been difficult for research groups to evaluate prostate segmentation algorithms on multi-center, multi-vendor and multi-protocol data. Especially because we are dealing with MR images, image appearance, resolution and the presence of artifacts are affected by differences in scanners and/or protocols, which in turn can have a large influence on algorithm accuracy. The Prostate MR Image Segmentation (PROMISE12) challenge was setup to allow a fair and meaningful comparison of segmentation methods on the basis of performance and robustness. In this work we will discuss the initial results of the online PROMISE12 challenge, and the results obtained in the live challenge workshop hosted by the MICCAI2012 conference. In the challenge, 100 prostate MR cases from 4 different centers were included, with differences in scanner manufacturer, field strength and protocol. A total of 11 teams from academic research groups and industry participated. Algorithms showed a wide variety in methods and implementation, including active appearance models, atlas registration and level sets. Evaluation was performed using boundary and volume based metrics which were combined into a single score relating the metrics to human expert performance. The winners of the challenge where the algorithms by teams Imorphics and ScrAutoProstate, with scores of 85.72 and 84.29 overall. Both algorithms where significantly better than all other algorithms in the challenge (p < 0.05) and had an efficient implementation with a run time of 8 minutes and 3 second per case respectively. Overall, active appearance model based approaches seemed to outperform other approaches like multi-atlas registration, both on accuracy and computation time. Although average algorithm performance was good to excellent and the Imorphics algorithm outperformed the second observer on average, we showed that algorithm combination might lead to further improvement, indicating that optimal performance for prostate segmentation is not yet obtained. All results are available online at http://promise12.grand-challenge.org/. PMID:24418598

Molecular cancer classification using a meta-sample-based regularized robust coding method.

PubMed

Wang, Shu-Lin; Sun, Liuchao; Fang, Jianwen

2014-01-01

Previous studies have demonstrated that machine learning based molecular cancer classification using gene expression profiling (GEP) data is promising for the clinic diagnosis and treatment of cancer. Novel classification methods with high efficiency and prediction accuracy are still needed to deal with high dimensionality and small sample size of typical GEP data. Recently the sparse representation (SR) method has been successfully applied to the cancer classification. Nevertheless, its efficiency needs to be improved when analyzing large-scale GEP data. In this paper we present the meta-sample-based regularized robust coding classification (MRRCC), a novel effective cancer classification technique that combines the idea of meta-sample-based cluster method with regularized robust coding (RRC) method. It assumes that the coding residual and the coding coefficient are respectively independent and identically distributed. Similar to meta-sample-based SR classification (MSRC), MRRCC extracts a set of meta-samples from the training samples, and then encodes a testing sample as the sparse linear combination of these meta-samples. The representation fidelity is measured by the l2-norm or l1-norm of the coding residual. Extensive experiments on publicly available GEP datasets demonstrate that the proposed method is more efficient while its prediction accuracy is equivalent to existing MSRC-based methods and better than other state-of-the-art dimension reduction based methods.

Application and outcomes of therapy combining transcranial direct current stimulation and virtual reality: a systematic review.

PubMed

Massetti, Thais; Crocetta, Tânia Brusque; Silva, Talita Dias da; Trevizan, Isabela Lopes; Arab, Claudia; Caromano, Fátima Aparecida; Monteiro, Carlos Bandeira de Mello

2017-08-01

To evaluate the methods and major outcomes of transcranial direct current stimulation (tDCS) combined with virtual reality (VR) therapy in randomized controlled trials. A systematic review was performed following PRISMA guidelines using PubMed, PubMed Central, Web of Science and CAPES periodic databases, with no time restriction. The studies were screened for the following inclusion criteria: human subjects, combination of VR and tDCS methods, and randomized controlled study design. All potentially relevant articles were independently reviewed by two researchers, who reached a consensus on which articles met the inclusion criteria. The PEDro scale was used to evaluate the studies. Eleven studies were included, all of which utilized a variety of tDCS and VR application methods. The main outcomes were found to be beneficial in intervention groups of different populations, including improvements in body sway, gait, stroke recovery, pain management and vegetative reactions. The use of tDCS combined with VR showed positive results in both healthy and impaired patients. Future studies with larger sample sizes and homogeneous participants are required to confirm the benefits of tDCS and VR. Implications for Rehabilitation tDCS with VR intervention can be an alternative to traditional rehabilitation programs. tDCS with VR is a promising type of intervention with a variety of positive effects. Application of tDCS with VR is appropriated to both healthy and impaired patients. There is no consensus of tDCS with VR application.

Current challenges and future perspectives of plant and agricultural biotechnology.

PubMed

Moshelion, Menachem; Altman, Arie

2015-06-01

Advances in understanding plant biology, novel genetic resources, genome modification, and omics technologies generate new solutions for food security and novel biomaterials production under changing environmental conditions. New gene and germplasm candidates that are anticipated to lead to improved crop yields and other plant traits under stress have to pass long development phases based on trial and error using large-scale field evaluation. Therefore, quantitative, objective, and automated screening methods combined with decision-making algorithms are likely to have many advantages, enabling rapid screening of the most promising crop lines at an early stage followed by final mandatory field experiments. The combination of novel molecular tools, screening technologies, and economic evaluation should become the main goal of the plant biotechnological revolution in agriculture. Copyright © 2015 Elsevier Ltd. All rights reserved.

Hydrogen storage in a combined M.sub.xAlH.sub.6/M'.sub.y(NH.sub.2).sub.z system and methods of making and using the same

DOEpatents

Lu, Jun [Salt Lake City, UT; Fang, Zhigang Zak [Salt Lake City, UT; Sohn, Hong Yong [Salt Lake City, UT

2012-04-03

As a promising clean fuel for vehicles, hydrogen can be used for propulsion, either directly or in fuel cells. Hydrogen storage compositions having high storage capacity, good dehydrogenation kinetics, and hydrogen release and uptake reactions which are reversible are disclosed and described. Generally a hydrogen storage composition of a metal aluminum hexahydride and a metal amide can be used. A combined system (Li.sub.3AIH.sub.6/3LiNH.sub.2) with a very high inherent hydrogen capacity (7.3 wt %) can be carried out at moderate temperatures, and with approximately 95% of that inherent hydrogen storage capacity (7.0%) is reversible over repeated cycling of release and uptake.

Laser confocal feedback tomography and nano-step height measurement

PubMed Central

Tan, Yidong; Wang, Weiping; Xu, Chunxin; Zhang, Shulian

2013-01-01

A promising method for tomography and step height measurement is proposed, which combines the high sensitivity of the frequency-shifted feedback laser and the axial positioning ability of confocal microscopy. By demodulating the feedback-induced intensity modulation signals, the obtained amplitude and phase information are used to respectively determine the coarse and fine measurement of the samples. Imaging the micro devices and biological samples by the demodulated amplitude, this approach is proved to be able to achieve the cross-sectional image in highly scattered mediums. And then the successful height measurement of nano-step on a glass-substrate grating by combination of both amplitude and phase information indicates its axial high resolution (better than 2 nm) in a non-ambiguous range of about ten microns. PMID:24145717

PDC-SGB: Prediction of effective drug combinations using a stochastic gradient boosting algorithm.

PubMed

Xu, Qian; Xiong, Yi; Dai, Hao; Kumari, Kotni Meena; Xu, Qin; Ou, Hong-Yu; Wei, Dong-Qing

2017-03-21

Combinatorial therapy is a promising strategy for combating complex diseases by improving the efficacy and reducing the side effects. To facilitate the identification of drug combinations in pharmacology, we proposed a new computational model, termed PDC-SGB, to predict effective drug combinations by integrating biological, chemical and pharmacological information based on a stochastic gradient boosting algorithm. To begin with, a set of 352 golden positive samples were collected from the public drug combination database. Then, a set of 732 dimensional feature vector involving biological, chemical and pharmaceutical information was constructed for each drug combination to describe its properties. To avoid overfitting, the maximum relevance & minimum redundancy (mRMR) method was performed to extract useful ones by removing redundant subsets. Based on the selected features, the three different type of classification algorithms were employed to build the drug combination prediction models. Our results demonstrated that the model based on the stochastic gradient boosting algorithm yield out the best performance. Furthermore, it is indicated that the feature patterns of therapy had powerful ability to discriminate effective drug combinations from non-effective ones. By analyzing various features, it is shown that the enriched features occurred frequently in golden positive samples can help predict novel drug combinations. Copyright © 2017 Elsevier Ltd. All rights reserved.

Feedback System Control Optimized Electrospinning for Fabrication of an Excellent Superhydrophobic Surface.

PubMed

Yang, Jian; Liu, Chuangui; Wang, Boqian; Ding, Xianting

2017-10-13

Superhydrophobic surface, as a promising micro/nano material, has tremendous applications in biological and artificial investigations. The electrohydrodynamics (EHD) technique is a versatile and effective method for fabricating micro- to nanoscale fibers and particles from a variety of materials. A combination of critical parameters, such as mass fraction, ratio of N, N-Dimethylformamide (DMF) to Tetrahydrofuran (THF), inner diameter of needle, feed rate, receiving distance, applied voltage as well as temperature, during electrospinning process, to determine the morphology of the electrospun membranes, which in turn determines the superhydrophobic property of the membrane. In this study, we applied a recently developed feedback system control (FSC) scheme for rapid identification of the optimal combination of these controllable parameters to fabricate superhydrophobic surface by one-step electrospinning method without any further modification. Within five rounds of experiments by testing totally forty-six data points, FSC scheme successfully identified an optimal parameter combination that generated electrospun membranes with a static water contact angle of 160 degrees or larger. Scanning electron microscope (SEM) imaging indicates that the FSC optimized surface attains unique morphology. The optimized setup introduced here therefore serves as a one-step, straightforward, and economic approach to fabricate superhydrophobic surface with electrospinning approach.

The influence of ns- and fs-LA plume local conditions on the performance of a combined LIBS/LA-ICP-MS sensor

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

LaHaye, Nicole L.; Phillips, Mark C.; Duffin, Andrew M.

2016-01-01

Both laser-induced breakdown spectroscopy (LIBS) and laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) are well-established analytical techniques with their own unique advantages and disadvantages. The combination of the two analytical methods is a very promising way to overcome the challenges faced by each method individually. We made a comprehensive comparison of local plasma conditions between nanosecond (ns) and femtosecond (fs) laser ablation (LA) sources in a combined LIBS and LA-ICP-MS system. The optical emission spectra and ICP-MS signal were recorded simultaneously for both ns- and fs-LA and figures of merit of the system were analyzed. Characterization of the plasma was conductedmore » by evaluating temperature and density of the plume under various irradiation conditions using optical emission spectroscopy, and correlations to ns- and fs-LIBS and LA-ICP-MS signal were made. The present study is very useful for providing conditions for a multimodal system as well as giving insight into how laser ablation plume parameters are related to LA-ICP-MS and LIBS results for both ns- and fs-LA.« less

Hybrid Microscopy: Enabling Inexpensive High-Performance Imaging through Combined Physical and Optical Magnifications.

PubMed

Zhang, Yu Shrike; Chang, Jae-Byum; Alvarez, Mario Moisés; Trujillo-de Santiago, Grissel; Aleman, Julio; Batzaya, Byambaa; Krishnadoss, Vaishali; Ramanujam, Aishwarya Aravamudhan; Kazemzadeh-Narbat, Mehdi; Chen, Fei; Tillberg, Paul W; Dokmeci, Mehmet Remzi; Boyden, Edward S; Khademhosseini, Ali

2016-03-15

To date, much effort has been expended on making high-performance microscopes through better instrumentation. Recently, it was discovered that physical magnification of specimens was possible, through a technique called expansion microscopy (ExM), raising the question of whether physical magnification, coupled to inexpensive optics, could together match the performance of high-end optical equipment, at a tiny fraction of the price. Here we show that such "hybrid microscopy" methods--combining physical and optical magnifications--can indeed achieve high performance at low cost. By physically magnifying objects, then imaging them on cheap miniature fluorescence microscopes ("mini-microscopes"), it is possible to image at a resolution comparable to that previously attainable only with benchtop microscopes that present costs orders of magnitude higher. We believe that this unprecedented hybrid technology that combines expansion microscopy, based on physical magnification, and mini-microscopy, relying on conventional optics--a process we refer to as Expansion Mini-Microscopy (ExMM)--is a highly promising alternative method for performing cost-effective, high-resolution imaging of biological samples. With further advancement of the technology, we believe that ExMM will find widespread applications for high-resolution imaging particularly in research and healthcare scenarios in undeveloped countries or remote places.

Reactivity of metal oxide sorbents for removal of sulfur compounds from coal gases at high temperature and pressure

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

Kwon, K.C.; Crowe, E.R.; Gangwal, S.K.

1997-01-01

Hot-gas desulfurization for the integrated gasification combined cycle (IGCC) process has been investigated to effectively remove hydrogen sulfide with various metal oxide sorbents at high temperatures and pressures. Metal oxide sorbents such as zinc titanate oxide, zinc ferrite oxide, copper oxide, manganese oxide and calcium oxide were found to be promising sorbents in comparison with other removal methods such as membrane separation and reactive membrane separation. The removal reaction of H{sub 2}S from coal gas mixtures with zinc titanate oxide sorbents was conducted in a batch reactor. The main objectives of this research are to formulate promising metal oxide sorbentsmore » for removal of hydrogen sulfide from coal gas mixtures, to compare reactivity of a formulated sorbent with a sorbent supplied by the Research Triangle Institute at high temperatures and pressures, and to determine effects of concentrations of moisture contained in coal gas mixtures on equilibrium absorption of H{sub 2}S into metal oxide sorbents. Promising durable metal oxide sorbents with high-sulfur-absorbing capacity were formulated by mixing active metal oxide powders with inert metal oxide powders and calcining these powder mixtures.« less

C-Geranylated flavonoids from Paulownia tomentosa fruits with antimicrobial potential and synergistic activity with antibiotics.

PubMed

Navrátilová, Alice; Nešuta, Ondřej; Vančatová, Irena; Čížek, Alois; Varela-M, Ruben E; López-Abán, Julio; Villa-Pulgarin, Janny A; Mollinedo, Faustino; Muro, Antonio; Žemličková, Helena; Kadlecová, Daniela; Šmejkal, Karel

2016-08-01

Context C-6-Geranylated flavonoids possess promising biological activities. These substances could be a source of lead compounds for the development of therapeutics. Objective The study was designed to evaluate their antibacterial and antileishmanial activity. Materials and methods C-6-Geranylated flavanones were tested in micromolar concentrations against promastigote forms of Leishmania brazilensis, L. donovani, L. infantum, and L. panamensis against methicillin-resistant Staphylococcus aureus (MRSA); and synergistic potential with antibiotics was analyzed. IC50 values (after 72 h) were calculated and compared with that of miltefosine. Flow cytometry and DNA fragmentation analysis were used the mechanism of the effect. Geranylated flavanones or epigallocatechin gallate were combined with oxacillin, tetracycline, and ciprofloxacin, and the effects of these two-component combinations were evaluated. Minimal inhibitory concentrations (MICs) and minimal bactericidal concentrations (MBCs) were established (after 24 h), the synergy was measured by the checkerboard titration technique, and the sums of the fractional inhibitory concentrations (∑FICs) were computed. Results 3'-O-Methyl-5'-O-methyldiplacone and 3'-O-methyldiplacone showed good antileishmanial activities (IC50 8-42 μM). 3'-O-Methyl-5'-hydroxydiplacone activates the apoptotic death at leishmanias, the effect of 3'-O-methyl-5'-O-methyldiplacone has another mechanism. The test of the antibacterial activity showed good effects of 3'-O-methyldiplacol and mimulone against MRSA (MIC 2-16 μg/mL), and in six cases, the results showed synergistic effects when combined with oxacillin. Synergistic effects were also found for the combination of epigallocatechin gallate with tetracycline or oxacillin. Conclusion This work demonstrates anti-MRSA and antileishmanial potential of geranylated flavanones and uncovers their promising synergistic activities with antibiotics. In addition, the mechanism of antileishmanial effect is proposed.

Low-dose X-ray computed tomography image reconstruction with a combined low-mAs and sparse-view protocol

PubMed Central

Gao, Yang; Bian, Zhaoying; Huang, Jing; Zhang, Yunwan; Niu, Shanzhou; Feng, Qianjin; Chen, Wufan; Liang, Zhengrong; Ma, Jianhua

2014-01-01

To realize low-dose imaging in X-ray computed tomography (CT) examination, lowering milliampere-seconds (low-mAs) or reducing the required number of projection views (sparse-view) per rotation around the body has been widely studied as an easy and effective approach. In this study, we are focusing on low-dose CT image reconstruction from the sinograms acquired with a combined low-mAs and sparse-view protocol and propose a two-step image reconstruction strategy. Specifically, to suppress significant statistical noise in the noisy and insufficient sinograms, an adaptive sinogram restoration (ASR) method is first proposed with consideration of the statistical property of sinogram data, and then to further acquire a high-quality image, a total variation based projection onto convex sets (TV-POCS) method is adopted with a slight modification. For simplicity, the present reconstruction strategy was termed as “ASR-TV-POCS.” To evaluate the present ASR-TV-POCS method, both qualitative and quantitative studies were performed on a physical phantom. Experimental results have demonstrated that the present ASR-TV-POCS method can achieve promising gains over other existing methods in terms of the noise reduction, contrast-to-noise ratio, and edge detail preservation. PMID:24977611

Evaluation of genetic diversity among soybean (Glycine max) genotypes using univariate and multivariate analysis.

PubMed

Oliveira, M M; Sousa, L B; Reis, M C; Silva Junior, E G; Cardoso, D B O; Hamawaki, O T; Nogueira, A P O

2017-05-31

The genetic diversity study has paramount importance in breeding programs; hence, it allows selection and choice of the parental genetic divergence, which have the agronomic traits desired by the breeder. This study aimed to characterize the genetic divergence between 24 soybean genotypes through their agronomic traits, using multivariate clustering methods to select the potential genitors for the promising hybrid combinations. Six agronomic traits evaluated were number of days to flowering and maturity, plant height at flowering and maturity, insertion height of the first pod, and yield. The genetic divergence evaluated by multivariate analysis that esteemed first the Mahalanobis' generalized distance (D 2 ), then the clustering using Tocher's optimization methods, and then the unweighted pair group method with arithmetic average (UPGMA). Tocher's optimization method and the UPGMA agreed with the groups' constitution between each other, the formation of eight distinct groups according Tocher's method and seven distinct groups using UPGMA. The trait number of days for flowering (45.66%) was the most efficient to explain dissimilarity between genotypes, and must be one of the main traits considered by the breeder in the moment of genitors choice in soybean-breeding programs. The genetic variability allowed the identification of dissimilar genotypes and with superior performances. The hybridizations UFU 18 x UFUS CARAJÁS, UFU 15 x UFU 13, and UFU 13 x UFUS CARAJÁS are promising to obtain superior segregating populations, which enable the development of more productive genotypes.

Investigating different skin and gastrointestinal tract (GIT) pathologies ex vivo by autofluorescence spectroscopy and optical imaging

NASA Astrophysics Data System (ADS)

Zhelyazkova, A.; Kuzmina, I.; Borisova, E.; Penkov, N.; Genova, Ts.; Spigulis, J.; Avramov, L.

2016-01-01

The skin neoplasias are on a second place in the world statistics of cancer incidence, and gastrointestinal tract (GIT) tumours are also in the "top ten" list. For the most of cutaneous and gastrointestinal tumours could be obtained better prognoses for patients, if an earlier and precise diagnostics procedure is applied. One of the most promising approaches for development of improved diagnostic techniques, is based on optical detection, and analysis of the signatures of biological tissues for detecting the presence of pathological alterations in the investigated objects. It is important to develop and combine novel diagnostic techniques for an accurate early stage diagnosis to improve the chances for skin and GIT tumours treatment. Optical techniques are very promising methods for such noninvasive diagnosis of skin and mucosa tumours, possessing the advantages of deep imaging depth, high resolution, fast imaging speed, and noninvasive character of detection. In this study we combine autofluorescence spectroscopy and optical imaging techniques to develop more precise evaluation of the tissue pathologies investigated. We obtain chromophore maps for GIT and cutaneous samples, with better visualization of the tumours borders and margins. In addition, fluorescence spectra give us information about the early changes in chromophores' contents into the tissues during neoplasia growth.

Assessment of implicit sexual associations in non-incarcerated pedophiles.

PubMed

van Leeuwen, Matthijs L; van Baaren, Rick B; Chakhssi, Farid; Loonen, Marijke G M; Lippman, Maarten; Dijksterhuis, Ap

2013-11-01

Offences committed by pedophiles are crimes that evoke serious public concern and outrage. Although recent research using implicit measures has shown promise in detecting deviant sexual associations, the discriminatory and predictive quality of implicit tasks has not yet surpassed traditional assessment methods such as questionnaires and phallometry. The current research extended previous findings by examining whether a combination of two implicit tasks, the Implicit Association Task (IAT) and the Picture Association Task (PAT), was capable of differentiating pedophiles from non-pedophiles, and whether the PAT, which allows separate analysis for male, female, boy and girl stimulus categories, was more sensitive to specific sexual associations in pedophiles than the IAT. A total of 20 male self-reported pedophiles (10 offender and 10 non-offenders) and 20 male self-reported heterosexual controls completed the two implicit measures. Results indicated that the combination of both tasks produced the strongest results to date in detecting implicit pedophilic preferences (AUC = .97). Additionally, the PAT showed promise in decomposing the sexual associations in pedophiles. Interestingly, as there was an equal distribution of offenders and non-offenders in the pedophile group, it was possible to test for implicit association differences between these groups. This comparison showed no clear link between having these implicit sexual associations and actual offending.

Large-scale exploration and analysis of drug combinations.

PubMed

Li, Peng; Huang, Chao; Fu, Yingxue; Wang, Jinan; Wu, Ziyin; Ru, Jinlong; Zheng, Chunli; Guo, Zihu; Chen, Xuetong; Zhou, Wei; Zhang, Wenjuan; Li, Yan; Chen, Jianxin; Lu, Aiping; Wang, Yonghua

2015-06-15

Drug combinations are a promising strategy for combating complex diseases by improving the efficacy and reducing corresponding side effects. Currently, a widely studied problem in pharmacology is to predict effective drug combinations, either through empirically screening in clinic or pure experimental trials. However, the large-scale prediction of drug combination by a systems method is rarely considered. We report a systems pharmacology framework to predict drug combinations (PreDCs) on a computational model, termed probability ensemble approach (PEA), for analysis of both the efficacy and adverse effects of drug combinations. First, a Bayesian network integrating with a similarity algorithm is developed to model the combinations from drug molecular and pharmacological phenotypes, and the predictions are then assessed with both clinical efficacy and adverse effects. It is illustrated that PEA can predict the combination efficacy of drugs spanning different therapeutic classes with high specificity and sensitivity (AUC = 0.90), which was further validated by independent data or new experimental assays. PEA also evaluates the adverse effects (AUC = 0.95) quantitatively and detects the therapeutic indications for drug combinations. Finally, the PreDC database includes 1571 known and 3269 predicted optimal combinations as well as their potential side effects and therapeutic indications. The PreDC database is available at http://sm.nwsuaf.edu.cn/lsp/predc.php. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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

Lehtomäki, Jouko; Makkonen, Ilja; Harju, Ari

We present a computational scheme for orbital-free density functional theory (OFDFT) that simultaneously provides access to all-electron values and preserves the OFDFT linear scaling as a function of the system size. Using the projector augmented-wave method (PAW) in combination with real-space methods, we overcome some obstacles faced by other available implementation schemes. Specifically, the advantages of using the PAW method are twofold. First, PAW reproduces all-electron values offering freedom in adjusting the convergence parameters and the atomic setups allow tuning the numerical accuracy per element. Second, PAW can provide a solution to some of the convergence problems exhibited in othermore » OFDFT implementations based on Kohn-Sham (KS) codes. Using PAW and real-space methods, our orbital-free results agree with the reference all-electron values with a mean absolute error of 10 meV and the number of iterations required by the self-consistent cycle is comparable to the KS method. The comparison of all-electron and pseudopotential bulk modulus and lattice constant reveal an enormous difference, demonstrating that in order to assess the performance of OFDFT functionals it is necessary to use implementations that obtain all-electron values. The proposed combination of methods is the most promising route currently available. We finally show that a parametrized kinetic energy functional can give lattice constants and bulk moduli comparable in accuracy to those obtained by the KS PBE method, exemplified with the case of diamond.« less

Regularized Dual Averaging Image Reconstruction for Full-Wave Ultrasound Computed Tomography.

PubMed

Matthews, Thomas P; Wang, Kun; Li, Cuiping; Duric, Neb; Anastasio, Mark A

2017-05-01

Ultrasound computed tomography (USCT) holds great promise for breast cancer screening. Waveform inversion-based image reconstruction methods account for higher order diffraction effects and can produce high-resolution USCT images, but are computationally demanding. Recently, a source encoding technique has been combined with stochastic gradient descent (SGD) to greatly reduce image reconstruction times. However, this method bundles the stochastic data fidelity term with the deterministic regularization term. This limitation can be overcome by replacing SGD with a structured optimization method, such as the regularized dual averaging method, that exploits knowledge of the composition of the cost function. In this paper, the dual averaging method is combined with source encoding techniques to improve the effectiveness of regularization while maintaining the reduced reconstruction times afforded by source encoding. It is demonstrated that each iteration can be decomposed into a gradient descent step based on the data fidelity term and a proximal update step corresponding to the regularization term. Furthermore, the regularization term is never explicitly differentiated, allowing nonsmooth regularization penalties to be naturally incorporated. The wave equation is solved by the use of a time-domain method. The effectiveness of this approach is demonstrated through computer simulation and experimental studies. The results suggest that the dual averaging method can produce images with less noise and comparable resolution to those obtained by the use of SGD.

Comparative analysis of feature extraction methods in satellite imagery

NASA Astrophysics Data System (ADS)

Karim, Shahid; Zhang, Ye; Asif, Muhammad Rizwan; Ali, Saad

2017-10-01

Feature extraction techniques are extensively being used in satellite imagery and getting impressive attention for remote sensing applications. The state-of-the-art feature extraction methods are appropriate according to the categories and structures of the objects to be detected. Based on distinctive computations of each feature extraction method, different types of images are selected to evaluate the performance of the methods, such as binary robust invariant scalable keypoints (BRISK), scale-invariant feature transform, speeded-up robust features (SURF), features from accelerated segment test (FAST), histogram of oriented gradients, and local binary patterns. Total computational time is calculated to evaluate the speed of each feature extraction method. The extracted features are counted under shadow regions and preprocessed shadow regions to compare the functioning of each method. We have studied the combination of SURF with FAST and BRISK individually and found very promising results with an increased number of features and less computational time. Finally, feature matching is conferred for all methods.

Unsupervised fuzzy segmentation of 3D magnetic resonance brain images

NASA Astrophysics Data System (ADS)

Velthuizen, Robert P.; Hall, Lawrence O.; Clarke, Laurence P.; Bensaid, Amine M.; Arrington, J. A.; Silbiger, Martin L.

1993-07-01

Unsupervised fuzzy methods are proposed for segmentation of 3D Magnetic Resonance images of the brain. Fuzzy c-means (FCM) has shown promising results for segmentation of single slices. FCM has been investigated for volume segmentations, both by combining results of single slices and by segmenting the full volume. Different strategies and initializations have been tried. In particular, two approaches have been used: (1) a method by which, iteratively, the furthest sample is split off to form a new cluster center, and (2) the traditional FCM in which the membership grade matrix is initialized in some way. Results have been compared with volume segmentations by k-means and with two supervised methods, k-nearest neighbors and region growing. Results of individual segmentations are presented as well as comparisons on the application of the different methods to a number of tumor patient data sets.

Development of a novel hexa-plex PCR method for identification and serotyping of Salmonella species.

PubMed

Li, Ruichao; Wang, Yang; Shen, Jianzhong; Wu, Congming

2014-01-01

Salmonella is one of the most important foodborne pathogens, which causes a huge economic burden worldwide. To detect Salmonella rapidly is very meaningful in preventing salmonellosis and decreasing economic losses. Currently, isolation of Salmonella is confirmed by biochemical and serobased serotyping methods, which are time consuming, labor intensive, and complicated. To solve this problem, a hexa-plex polymerase chain reaction (PCR) method was developed using comparative genomics analysis and multiplex PCR technology to detect Salmonella and Salmonella Typhimurium, Salmonella Enteritidis, Salmonella Agona, Salmonella Choleraesuis, and Salmonella Pullorum simultaneously. The accuracy of this method was tested by a collection of 142 Salmonella. Furthermore, the strategy described in this article to mine serovar-specific fragments for Salmonella could be used to find specific fragments for other Salmonella serotypes and bacteria. The combination of this strategy and multiplex PCR is promising in the rapid identification of foodborne pathogens.

A Lattice Kinetic Monte Carlo Solver for First-Principles Microkinetic Trend Studies

DOE PAGES

Hoffmann, Max J.; Bligaard, Thomas

2018-01-22

Here, mean-field microkinetic models in combination with Brønsted–Evans–Polanyi like scaling relations have proven highly successful in identifying catalyst materials with good or promising reactivity and selectivity. Analysis of the microkinetic model by means of lattice kinetic Monte Carlo promises a faithful description of a range of atomistic features involving short-range ordering of species in the vicinity of an active site. In this paper, we use the “fruit fly” example reaction of CO oxidation on fcc(111) transition and coinage metals to motivate and develop a lattice kinetic Monte Carlo solver suitable for the numerically challenging case of vastly disparate rate constants.more » As a result, we show that for the case of infinitely fast diffusion and absence of adsorbate-adsorbate interaction it is, in fact, possible to match the prediction of the mean-field-theory method and the lattice kinetic Monte Carlo method. As a corollary, we conclude that lattice kinetic Monte Carlo simulations of surface chemical reactions are most likely to provide additional insight over mean-field simulations if diffusion limitations or adsorbate–adsorbate interactions have a significant influence on the mixing of the adsorbates.« less

A Lattice Kinetic Monte Carlo Solver for First-Principles Microkinetic Trend Studies

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

Hoffmann, Max J.; Bligaard, Thomas

Here, mean-field microkinetic models in combination with Brønsted–Evans–Polanyi like scaling relations have proven highly successful in identifying catalyst materials with good or promising reactivity and selectivity. Analysis of the microkinetic model by means of lattice kinetic Monte Carlo promises a faithful description of a range of atomistic features involving short-range ordering of species in the vicinity of an active site. In this paper, we use the “fruit fly” example reaction of CO oxidation on fcc(111) transition and coinage metals to motivate and develop a lattice kinetic Monte Carlo solver suitable for the numerically challenging case of vastly disparate rate constants.more » As a result, we show that for the case of infinitely fast diffusion and absence of adsorbate-adsorbate interaction it is, in fact, possible to match the prediction of the mean-field-theory method and the lattice kinetic Monte Carlo method. As a corollary, we conclude that lattice kinetic Monte Carlo simulations of surface chemical reactions are most likely to provide additional insight over mean-field simulations if diffusion limitations or adsorbate–adsorbate interactions have a significant influence on the mixing of the adsorbates.« less

No catalyst addition and highly efficient dissociation of H2O for the reduction of CO2 to formic acid with Mn.

PubMed

Lyu, Lingyun; Zeng, Xu; Yun, Jun; Wei, Feng; Jin, Fangming

2014-05-20

The "greenhouse effect" caused by the increasing atmospheric CO2 level is becoming extremely serious, and thus, the reduction of CO2 emissions has become an extensive, urgent, and long-term task. The dissociation of water for CO2 reduction with solar energy is regarded as one of the most promising methods for the sustainable development of the environment and energy. However, a high solar-to-fuel efficiency keeps a great challenge. In this work, the first observation of a highly effective, highly selective, and robust system of dissociating water for the reduction of carbon dioxide (CO2) into formic acid with metallic manganese (Mn) is reported. A considerably high formic acid yield of more than 75% on a carbon basis from NaHCO3 was achieved with 98% selectivity in the presence of simple commercially available Mn powder without the addition of any catalyst, and the proposed process is exothermic. Thus, this study may provide a promising method for the highly efficient dissociation of water for CO2 reduction by combining solar-driven thermochemistry with the reduction of MnO into Mn.

Characterizing model uncertainties in the life cycle of lignocellulose-based ethanol fuels.

PubMed

Spatari, Sabrina; MacLean, Heather L

2010-11-15

Renewable and low carbon fuel standards being developed at federal and state levels require an estimation of the life cycle carbon intensity (LCCI) of candidate fuels that can substitute for gasoline, such as second generation bioethanol. Estimating the LCCI of such fuels with a high degree of confidence requires the use of probabilistic methods to account for known sources of uncertainty. We construct life cycle models for the bioconversion of agricultural residue (corn stover) and energy crops (switchgrass) and explicitly examine uncertainty using Monte Carlo simulation. Using statistical methods to identify significant model variables from public data sets and Aspen Plus chemical process models,we estimate stochastic life cycle greenhouse gas (GHG) emissions for the two feedstocks combined with two promising fuel conversion technologies. The approach can be generalized to other biofuel systems. Our results show potentially high and uncertain GHG emissions for switchgrass-ethanol due to uncertain CO₂ flux from land use change and N₂O flux from N fertilizer. However, corn stover-ethanol,with its low-in-magnitude, tight-in-spread LCCI distribution, shows considerable promise for reducing life cycle GHG emissions relative to gasoline and corn-ethanol. Coproducts are important for reducing the LCCI of all ethanol fuels we examine.

Path lumping: An efficient algorithm to identify metastable path channels for conformational dynamics of multi-body systems

NASA Astrophysics Data System (ADS)

Meng, Luming; Sheong, Fu Kit; Zeng, Xiangze; Zhu, Lizhe; Huang, Xuhui

2017-07-01

Constructing Markov state models from large-scale molecular dynamics simulation trajectories is a promising approach to dissect the kinetic mechanisms of complex chemical and biological processes. Combined with transition path theory, Markov state models can be applied to identify all pathways connecting any conformational states of interest. However, the identified pathways can be too complex to comprehend, especially for multi-body processes where numerous parallel pathways with comparable flux probability often coexist. Here, we have developed a path lumping method to group these parallel pathways into metastable path channels for analysis. We define the similarity between two pathways as the intercrossing flux between them and then apply the spectral clustering algorithm to lump these pathways into groups. We demonstrate the power of our method by applying it to two systems: a 2D-potential consisting of four metastable energy channels and the hydrophobic collapse process of two hydrophobic molecules. In both cases, our algorithm successfully reveals the metastable path channels. We expect this path lumping algorithm to be a promising tool for revealing unprecedented insights into the kinetic mechanisms of complex multi-body processes.

A nonrecursive order N preconditioned conjugate gradient: Range space formulation of MDOF dynamics

NASA Technical Reports Server (NTRS)

Kurdila, Andrew J.

1990-01-01

While excellent progress has been made in deriving algorithms that are efficient for certain combinations of system topologies and concurrent multiprocessing hardware, several issues must be resolved to incorporate transient simulation in the control design process for large space structures. Specifically, strategies must be developed that are applicable to systems with numerous degrees of freedom. In addition, the algorithms must have a growth potential in that they must also be amenable to implementation on forthcoming parallel system architectures. For mechanical system simulation, this fact implies that algorithms are required that induce parallelism on a fine scale, suitable for the emerging class of highly parallel processors; and transient simulation methods must be automatically load balancing for a wider collection of system topologies and hardware configurations. These problems are addressed by employing a combination range space/preconditioned conjugate gradient formulation of multi-degree-of-freedom dynamics. The method described has several advantages. In a sequential computing environment, the method has the features that: by employing regular ordering of the system connectivity graph, an extremely efficient preconditioner can be derived from the 'range space metric', as opposed to the system coefficient matrix; because of the effectiveness of the preconditioner, preliminary studies indicate that the method can achieve performance rates that depend linearly upon the number of substructures, hence the title 'Order N'; and the method is non-assembling. Furthermore, the approach is promising as a potential parallel processing algorithm in that the method exhibits a fine parallel granularity suitable for a wide collection of combinations of physical system topologies/computer architectures; and the method is easily load balanced among processors, and does not rely upon system topology to induce parallelism.

Quantitative prediction of drug side effects based on drug-related features.

PubMed

Niu, Yanqing; Zhang, Wen

2017-09-01

Unexpected side effects of drugs are great concern in the drug development, and the identification of side effects is an important task. Recently, machine learning methods are proposed to predict the presence or absence of interested side effects for drugs, but it is difficult to make the accurate prediction for all of them. In this paper, we transform side effect profiles of drugs as their quantitative scores, by summing up their side effects with weights. The quantitative scores may measure the dangers of drugs, and thus help to compare the risk of different drugs. Here, we attempt to predict quantitative scores of drugs, namely the quantitative prediction. Specifically, we explore a variety of drug-related features and evaluate their discriminative powers for the quantitative prediction. Then, we consider several feature combination strategies (direct combination, average scoring ensemble combination) to integrate three informative features: chemical substructures, targets, and treatment indications. Finally, the average scoring ensemble model which produces the better performances is used as the final quantitative prediction model. Since weights for side effects are empirical values, we randomly generate different weights in the simulation experiments. The experimental results show that the quantitative method is robust to different weights, and produces satisfying results. Although other state-of-the-art methods cannot make the quantitative prediction directly, the prediction results can be transformed as the quantitative scores. By indirect comparison, the proposed method produces much better results than benchmark methods in the quantitative prediction. In conclusion, the proposed method is promising for the quantitative prediction of side effects, which may work cooperatively with existing state-of-the-art methods to reveal dangers of drugs.

Shape and structure of N=Z 64Ge: electromagnetic transition rates from the application of the recoil distance method to a knockout reaction.

PubMed

Starosta, K; Dewald, A; Dunomes, A; Adrich, P; Amthor, A M; Baumann, T; Bazin, D; Bowen, M; Brown, B A; Chester, A; Gade, A; Galaviz, D; Glasmacher, T; Ginter, T; Hausmann, M; Horoi, M; Jolie, J; Melon, B; Miller, D; Moeller, V; Norris, R P; Pissulla, T; Portillo, M; Rother, W; Shimbara, Y; Stolz, A; Vaman, C; Voss, P; Weisshaar, D; Zelevinsky, V

2007-07-27

Transition rate measurements are reported for the 2(1)+ and 2(2)+ states in N=Z 64Ge. The experimental results are in excellent agreement with large-scale shell-model calculations applying the recently developed GXPF1A interactions. The measurement was done using the recoil distance method (RDM) and a unique combination of state-of-the-art instruments at the National Superconducting Cyclotron Laboratory (NSCL). States of interest were populated via an intermediate-energy single-neutron knockout reaction. RDM studies of knockout and fragmentation reaction products hold the promise of reaching far from stability and providing lifetime information for excited states in a wide range of nuclei.

Shape and Structure of N=Z Ge64: Electromagnetic Transition Rates from the Application of the Recoil Distance Method to a Knockout Reaction

NASA Astrophysics Data System (ADS)

Starosta, K.; Dewald, A.; Dunomes, A.; Adrich, P.; Amthor, A. M.; Baumann, T.; Bazin, D.; Bowen, M.; Brown, B. A.; Chester, A.; Gade, A.; Galaviz, D.; Glasmacher, T.; Ginter, T.; Hausmann, M.; Horoi, M.; Jolie, J.; Melon, B.; Miller, D.; Moeller, V.; Norris, R. P.; Pissulla, T.; Portillo, M.; Rother, W.; Shimbara, Y.; Stolz, A.; Vaman, C.; Voss, P.; Weisshaar, D.; Zelevinsky, V.

2007-07-01

Transition rate measurements are reported for the 21+ and 22+ states in N=Z Ge64. The experimental results are in excellent agreement with large-scale shell-model calculations applying the recently developed GXPF1A interactions. The measurement was done using the recoil distance method (RDM) and a unique combination of state-of-the-art instruments at the National Superconducting Cyclotron Laboratory (NSCL). States of interest were populated via an intermediate-energy single-neutron knockout reaction. RDM studies of knockout and fragmentation reaction products hold the promise of reaching far from stability and providing lifetime information for excited states in a wide range of nuclei.

PIPS-SBB: A Parallel Distributed-Memory Branch-and-Bound Algorithm for Stochastic Mixed-Integer Programs

DOE PAGES

Munguia, Lluis-Miquel; Oxberry, Geoffrey; Rajan, Deepak

2016-05-01

Stochastic mixed-integer programs (SMIPs) deal with optimization under uncertainty at many levels of the decision-making process. When solved as extensive formulation mixed- integer programs, problem instances can exceed available memory on a single workstation. In order to overcome this limitation, we present PIPS-SBB: a distributed-memory parallel stochastic MIP solver that takes advantage of parallelism at multiple levels of the optimization process. We also show promising results on the SIPLIB benchmark by combining methods known for accelerating Branch and Bound (B&B) methods with new ideas that leverage the structure of SMIPs. Finally, we expect the performance of PIPS-SBB to improve furthermore » as more functionality is added in the future.« less

Optical 3D methods for measurement of prosthetic wear of total hip arthroplasty: principles, verification and results.

PubMed

Rossler, Tomas; Mandat, Dusan; Gallo, Jiri; Hrabovsky, Miroslav; Pochmon, Michal; Havranek, Vitezslav

2009-07-20

Total hip arthroplasty (THA) significantly improves the quality of life in majority of patients with severe osteoarthritis. However, long-term outcomes of THAs are compromised by aseptic loosening and periprosthetic osteolysis which needs revision surgery. Both of these are causally linked to a prosthetic wear deliberated from the prosthetic articulating surfaces. As a result, there is a need to measure the mode and magnitude of wear. The paper evaluates three optical methods proposed for construction of a device for the non-contact prosthetic wear measurement. Of them, the scanning profilometry achieved promising combination of accuracy and repeatability. Simultaneously, it is time efficient to enable the development of a sensor for wear measurement.

On the Use of Parmetric-CAD Systems and Cartesian Methods for Aerodynamic Design

NASA Technical Reports Server (NTRS)

Nemec, Marian; Aftosmis, Michael J.; Pulliam, Thomas H.

2004-01-01

Automated, high-fidelity tools for aerodynamic design face critical issues in attempting to optimize real-life geometry arid in permitting radical design changes. Success in these areas promises not only significantly shorter design- cycle times, but also superior and unconventional designs. To address these issues, we investigate the use of a parmetric-CAD system in conjunction with an embedded-boundary Cartesian method. Our goal is to combine the modeling capabilities of feature-based CAD with the robustness and flexibility of component-based Cartesian volume-mesh generation for complex geometry problems. We present the development of an automated optimization frame-work with a focus on the deployment of such a CAD-based design approach in a heterogeneous parallel computing environment.

Optimum Design of Hypersonic Airbreathing Propulsion

NASA Astrophysics Data System (ADS)

Kobayashi, Hiroaki; Sato, Tetsuya; Tanatsugu, Nobuhiro

The flight of Spaceplane is always under accelarating in the assent way and always under decelarating in the desent way and yet cruising in the return way. Besides, its flight envelope is considerably wider than that of airplane. Thus the integrated design method is required to build the best transportation system optimized taking into account the propulsion system and the airframe under the entire flight conditions. In this paper it is shown an optimization method on TSTO spaceplane system. Genetic algorithm (GA) was applied to optimize design parameters of engine, airframe, and trajectory simultaneously. Several types of engine were quantitatively compared using payload ratio as an evaluating function. It was concluded that precooled turbojets is the most promising engine for TSTO among Turbine Based Combined Cycle (TBCC) engines.

Liquid-Crystal-Enabled Active Plasmonics: A Review

PubMed Central

Si, Guangyuan; Zhao, Yanhui; Leong, Eunice Sok Ping; Liu, Yan Jun

2014-01-01

Liquid crystals are a promising candidate for development of active plasmonics due to their large birefringence, low driving threshold, and versatile driving methods. We review recent progress on the interdisciplinary research field of liquid crystal based plasmonics. The research scope of this field is to build the next generation of reconfigurable plasmonic devices by combining liquid crystals with plasmonic nanostructures. Various active plasmonic devices, such as switches, modulators, color filters, absorbers, have been demonstrated. This review is structured to cover active plasmonic devices from two aspects: functionalities and driven methods. We hope this review would provide basic knowledge for a new researcher to get familiar with the field, and serve as a reference for experienced researchers to keep up the current research trends. PMID:28788515

A novel method combining additive manufacturing and alloy infiltration for NdFeB bonded magnet fabrication

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

Li, Ling; Tirado, Angelica; Conner, Benjamin S.

In this paper, binder jetting additive manufacturing technique is employed to fabricate NdFeB isotropic bonded magnets, followed by an infiltration process with low-melting point eutectic alloys [i.e., Nd 3Cu 0.25Co 0.75 (NdCuCo) and Pr 3Cu 0.25Co 0.75 (PrCuCo)]. Densification and mechanical strength improvement are achieved for the as-printed porous part. Meanwhile, the intrinsic coercivity H ci is enhanced from 732 to 1345 kA/m and 1233 kA/m after diffusion of NdCuCo and PrCuCo, respectively. This study presents a novel method for fabricating complex-shaped bonded magnets with promising mechanical and magnetic properties.

A novel method combining additive manufacturing and alloy infiltration for NdFeB bonded magnet fabrication

DOE PAGES

Li, Ling; Tirado, Angelica; Conner, Benjamin S.; ...

2017-04-27

In this paper, binder jetting additive manufacturing technique is employed to fabricate NdFeB isotropic bonded magnets, followed by an infiltration process with low-melting point eutectic alloys [i.e., Nd 3Cu 0.25Co 0.75 (NdCuCo) and Pr 3Cu 0.25Co 0.75 (PrCuCo)]. Densification and mechanical strength improvement are achieved for the as-printed porous part. Meanwhile, the intrinsic coercivity H ci is enhanced from 732 to 1345 kA/m and 1233 kA/m after diffusion of NdCuCo and PrCuCo, respectively. This study presents a novel method for fabricating complex-shaped bonded magnets with promising mechanical and magnetic properties.

Numerical techniques for solving nonlinear instability problems in smokeless tactical solid rocket motors. [finite difference technique

NASA Technical Reports Server (NTRS)

Baum, J. D.; Levine, J. N.

1980-01-01

The selection of a satisfactory numerical method for calculating the propagation of steep fronted shock life waveforms in a solid rocket motor combustion chamber is discussed. A number of different numerical schemes were evaluated by comparing the results obtained for three problems: the shock tube problems; the linear wave equation, and nonlinear wave propagation in a closed tube. The most promising method--a combination of the Lax-Wendroff, Hybrid and Artificial Compression techniques, was incorporated into an existing nonlinear instability program. The capability of the modified program to treat steep fronted wave instabilities in low smoke tactical motors was verified by solving a number of motor test cases with disturbance amplitudes as high as 80% of the mean pressure.

Cavitation in liquid cryogens. 4: Combined correlations for venturi, hydrofoil, ogives, and pumps

NASA Technical Reports Server (NTRS)

Hord, J.

1974-01-01

The results of a series of experimental and analytical cavitation studies are presented. Cross-correlation is performed of the developed cavity data for a venturi, a hydrofoil and three scaled ogives. The new correlating parameter, MTWO, improves data correlation for these stationary bodies and for pumping equipment. Existing techniques for predicting the cavitating performance of pumping machinery were extended to include variations in flow coefficient, cavitation parameter, and equipment geometry. The new predictive formulations hold promise as a design tool and universal method for correlating pumping machinery performance. Application of these predictive formulas requires prescribed cavitation test data or an independent method of estimating the cavitation parameter for each pump. The latter would permit prediction of performance without testing; potential methods for evaluating the cavitation parameter prior to testing are suggested.

Detection of protein-protein interactions by ribosome display and protein in situ immobilisation.

PubMed

He, Mingyue; Liu, Hong; Turner, Martin; Taussig, Michael J

2009-12-31

We describe a method for identification of protein-protein interactions by combining two cell-free protein technologies, namely ribosome display and protein in situ immobilisation. The method requires only PCR fragments as the starting material, the target proteins being made through cell-free protein synthesis, either associated with their encoding mRNA as ribosome complexes or immobilised on a solid surface. The use of ribosome complexes allows identification of interacting protein partners from their attached coding mRNA. To demonstrate the procedures, we have employed the lymphocyte signalling proteins Vav1 and Grb2 and confirmed the interaction between Grb2 and the N-terminal SH3 domain of Vav1. The method has promise for library screening of pairwise protein interactions, down to the analytical level of individual domain or motif mapping.

Comparative effectiveness research on patients with acute ischemic stroke using Markov decision processes

PubMed Central

2012-01-01

Background Several methodological issues with non-randomized comparative clinical studies have been raised, one of which is whether the methods used can adequately identify uncertainties that evolve dynamically with time in real-world systems. The objective of this study is to compare the effectiveness of different combinations of Traditional Chinese Medicine (TCM) treatments and combinations of TCM and Western medicine interventions in patients with acute ischemic stroke (AIS) by using Markov decision process (MDP) theory. MDP theory appears to be a promising new method for use in comparative effectiveness research. Methods The electronic health records (EHR) of patients with AIS hospitalized at the 2nd Affiliated Hospital of Guangzhou University of Chinese Medicine between May 2005 and July 2008 were collected. Each record was portioned into two "state-action-reward" stages divided by three time points: the first, third, and last day of hospital stay. We used the well-developed optimality technique in MDP theory with the finite horizon criterion to make the dynamic comparison of different treatment combinations. Results A total of 1504 records with a primary diagnosis of AIS were identified. Only states with more than 10 (including 10) patients' information were included, which gave 960 records to be enrolled in the MDP model. Optimal combinations were obtained for 30 types of patient condition. Conclusion MDP theory makes it possible to dynamically compare the effectiveness of different combinations of treatments. However, the optimal interventions obtained by the MDP theory here require further validation in clinical practice. Further exploratory studies with MDP theory in other areas in which complex interventions are common would be worthwhile. PMID:22400712

Determination of thiol metabolites in human urine by stable isotope labeling in combination with pseudo-targeted mass spectrometry analysis

NASA Astrophysics Data System (ADS)

Liu, Ping; Qi, Chu-Bo; Zhu, Quan-Fei; Yuan, Bi-Feng; Feng, Yu-Qi

2016-02-01

Precursor ion scan and multiple reaction monitoring scan (MRM) are two typical scan modes in mass spectrometry analysis. Here, we developed a strategy by combining stable isotope labeling (IL) with liquid chromatography-mass spectrometry (LC-MS) under double precursor ion scan (DPI) and MRM for analysis of thiols in 5 types of human cancer urine. Firstly, the IL-LC-DPI-MS method was applied for non-targeted profiling of thiols from cancer samples. Compared to traditional full scan mode, the DPI method significantly improved identification selectivity and accuracy. 103 thiol candidates were discovered in all cancers and 6 thiols were identified by their standards. It is worth noting that pantetheine, for the first time, was identified in human urine. Secondly, the IL-LC-MRM-MS method was developed for relative quantification of thiols in cancers compared to healthy controls. All the MRM transitions of light and heavy labeled thiols were acquired from urines by using DPI method. Compared to DPI method, the sensitivity of MRM improved by 2.1-11.3 folds. In addition, the concentration of homocysteine, γ-glutamylcysteine and pantetheine enhanced more than two folds in cancer patients compared to healthy controls. Taken together, the method demonstrated to be a promising strategy for identification and comprehensive quantification of thiols in human urines.

Determination of thiol metabolites in human urine by stable isotope labeling in combination with pseudo-targeted mass spectrometry analysis

PubMed Central

Liu, Ping; Qi, Chu-Bo; Zhu, Quan-Fei; Yuan, Bi-Feng; Feng, Yu-Qi

2016-01-01

Precursor ion scan and multiple reaction monitoring scan (MRM) are two typical scan modes in mass spectrometry analysis. Here, we developed a strategy by combining stable isotope labeling (IL) with liquid chromatography-mass spectrometry (LC-MS) under double precursor ion scan (DPI) and MRM for analysis of thiols in 5 types of human cancer urine. Firstly, the IL-LC-DPI-MS method was applied for non-targeted profiling of thiols from cancer samples. Compared to traditional full scan mode, the DPI method significantly improved identification selectivity and accuracy. 103 thiol candidates were discovered in all cancers and 6 thiols were identified by their standards. It is worth noting that pantetheine, for the first time, was identified in human urine. Secondly, the IL-LC-MRM-MS method was developed for relative quantification of thiols in cancers compared to healthy controls. All the MRM transitions of light and heavy labeled thiols were acquired from urines by using DPI method. Compared to DPI method, the sensitivity of MRM improved by 2.1–11.3 folds. In addition, the concentration of homocysteine, γ-glutamylcysteine and pantetheine enhanced more than two folds in cancer patients compared to healthy controls. Taken together, the method demonstrated to be a promising strategy for identification and comprehensive quantification of thiols in human urines. PMID:26888486

Activation of microbubbles by low-intensity pulsed ultrasound enhances the cytotoxicity of curcumin involving apoptosis induction and cell motility inhibition in human breast cancer MDA-MB-231 cells.

PubMed

Li, Yixiang; Wang, Pan; Chen, Xiyang; Hu, Jianmin; Liu, Yichen; Wang, Xiaobing; Liu, Quanhong

2016-11-01

Ultrasound and microbubbles-mediated drug delivery has become a promising strategy to promote drug delivery and its therapeutic efficacy. The aim of this research was to assess the effects of microbubbles (MBs)-combined low-intensity pulsed ultrasound (LPUS) on the delivery and cytotoxicity of curcumin (Cur) to human breast cancer MDA-MB-231 cells. Under the experimental condition, MBs raised the level of acoustic cavitation and enhanced plasma membrane permeability; and cellular uptake of Cur was notably improved by LPUS-MBs treatment, aggravating Cur-induced MDA-MB-231 cells death. The combined treatment markedly caused more obvious changes of cell morphology, F-actin cytoskeleton damage and cell migration inhibition. Our results demonstrated that combination of MBs and LPUS may be an efficient strategy for improving anti-tumor effect of Cur, suggesting a potential effective method for antineoplastic therapy. Copyright © 2016 Elsevier B.V. All rights reserved.

Transcranial electric stimulation (tES) and NeuroImaging: the state-of-the-art, new insights and prospects in basic and clinical neuroscience.

PubMed

Soekadar, Surjo R; Herring, Jim Don; McGonigle, David

2016-10-15

Transcranial electric stimulation (tES) of the brain has attracted an increased interest in recent years. Yet, despite remarkable research efforts to date, the underlying neurobiological mechanisms of tES' effects are still incompletely understood. This Special Issue aims to provide a comprehensive and up-to-date overview of the state-of-the-art in studies combining tES and neuroimaging, while introducing most recent insights and outlining future prospects related to this new and rapidly growing field. The findings reported here combine methodological advancements with insights into the underlying mechanisms of tES itself. At the same time, they also point to the many caveats and specific challenges associated with such studies, which can arise from both technical and biological sources. Besides promising to advance basic neuroscience, combined tES and neuroimaging studies may also substantially change previous conceptions about the methods of action of electric or magnetic stimulation on the brain. Copyright © 2016. Published by Elsevier Inc.

Functional hyper-IL-6 from vaccinia virus-colonized tumors triggers platelet formation and helps to alleviate toxicity of mitomycin C enhanced virus therapy

PubMed Central

2012-01-01

Background Combination of oncolytic vaccinia virus therapy with conventional chemotherapy has shown promise for tumor therapy. However, side effects of chemotherapy including thrombocytopenia, still remain problematic. Methods Here, we describe a novel approach to optimize combination therapy of oncolytic virus and chemotherapy utilizing virus-encoding hyper-IL-6, GLV-1h90, to reduce chemotherapy-associated side effects. Results We showed that the hyper-IL-6 cytokine was successfully produced by GLV-1h90 and was functional both in cell culture as well as in tumor-bearing animals, in which the cytokine-producing vaccinia virus strain was well tolerated. When combined with the chemotherapeutic mitomycin C, the anti-tumor effect of the oncolytic virotherapy was significantly enhanced. Moreover, hyper-IL-6 expression greatly reduced the time interval during which the mice suffered from chemotherapy-induced thrombocytopenia. Conclusion Therefore, future clinical application would benefit from careful investigation of additional cytokine treatment to reduce chemotherapy-induced side effects. PMID:22236378

Predicting Gilthead Sea Bream (Sparus aurata) Freshness by a Novel Combined Technique of 3D Imaging and SW-NIR Spectral Analysis.

PubMed

Ivorra, Eugenio; Verdu, Samuel; Sánchez, Antonio J; Grau, Raúl; Barat, José M

2016-10-19

A technique that combines the spatial resolution of a 3D structured-light (SL) imaging system with the spectral analysis of a hyperspectral short-wave near infrared system was developed for freshness predictions of gilthead sea bream on the first storage days (Days 0-6). This novel approach allows the hyperspectral analysis of very specific fish areas, which provides more information for freshness estimations. The SL system obtains a 3D reconstruction of fish, and an automatic method locates gilthead's pupils and irises. Once these regions are positioned, the hyperspectral camera acquires spectral information and a multivariate statistical study is done. The best region is the pupil with an R² of 0.92 and an RMSE of 0.651 for predictions. We conclude that the combination of 3D technology with the hyperspectral analysis offers plenty of potential and is a very promising technique to non destructively predict gilthead freshness.

Predicting Gilthead Sea Bream (Sparus aurata) Freshness by a Novel Combined Technique of 3D Imaging and SW-NIR Spectral Analysis

PubMed Central

Ivorra, Eugenio; Verdu, Samuel; Sánchez, Antonio J.; Grau, Raúl; Barat, José M.

2016-01-01

A technique that combines the spatial resolution of a 3D structured-light (SL) imaging system with the spectral analysis of a hyperspectral short-wave near infrared system was developed for freshness predictions of gilthead sea bream on the first storage days (Days 0–6). This novel approach allows the hyperspectral analysis of very specific fish areas, which provides more information for freshness estimations. The SL system obtains a 3D reconstruction of fish, and an automatic method locates gilthead’s pupils and irises. Once these regions are positioned, the hyperspectral camera acquires spectral information and a multivariate statistical study is done. The best region is the pupil with an R2 of 0.92 and an RMSE of 0.651 for predictions. We conclude that the combination of 3D technology with the hyperspectral analysis offers plenty of potential and is a very promising technique to non destructively predict gilthead freshness. PMID:27775556

A novel technique for phase synchrony measurement from the complex motor imaginary potential of combined body and limb action

NASA Astrophysics Data System (ADS)

Zhou, Zhong-xing; Wan, Bai-kun; Ming, Dong; Qi, Hong-zhi

2010-08-01

In this study, we proposed and evaluated the use of the empirical mode decomposition (EMD) technique combined with phase synchronization analysis to investigate the human brain synchrony of the supplementary motor area (SMA) and primary motor area (M1) during complex motor imagination of combined body and limb action. We separated the EEG data of the SMA and M1 into intrinsic mode functions (IMFs) using the EMD method and determined the characteristic IMFs by power spectral density (PSD) analysis. Thereafter, the instantaneous phases of the characteristic IMFs were obtained by the Hilbert transformation, and the single-trial phase-locking value (PLV) features for brain synchrony measurement between the SMA and M1 were investigated separately. The classification performance suggests that the proposed approach is effective for phase synchronization analysis and is promising for the application of a brain-computer interface in motor nerve reconstruction of the lower limbs.

[Progress in microalgae culture system for biodiesel combined with reducing carbon dioxide emission].

PubMed

Su, Hongyang; Zhou, Xuefei; Xia, Xuefen; Sun, Zhen; Zhang, Yalei

2011-09-01

Wastewater resources, CO2 emission reduction and microalgae biodiesel are considered as current frontier fields of energy and environmental researches. In this paper, we reviewed the progress in system of microalgae culture for biodiesel production by wastewater and stack gas. Multiple factors including microalgal species, nutrition, culture methods and photobioreactor, which were crucial to the cultivation of microalgae for biodiesel production, were discussed in detail. A valuable culture system of microalgae for biodiesel production or other high value products combined with the treatment of wastewater by microalgae was put forward through the optimizations of algal species and culture technology. The culture system coupled with the treatment of wastewater, the reduction of CO2 emission with the cultivation of microalgae for biodiesel production will reduce the production cost of microalgal biofuel production and the treatment cost of wastewater simultaneously. Therefore, it would be a promising technology with important environmental value, social value and economic value to combine the treatment of wastewater with the cultivation of microalgae for biodiesel production.

Newer influenza antivirals, biotherapeutics and combinations

PubMed Central

Hayden, Frederick G.

2012-01-01

Please cite this paper as: Hayden FG. (2012) Newer Influenza Antivirals, Biotherapeutics and Combinations. Influenza and Other Respiratory Viruses 7(Suppl. 1), 63–75. This summary provides an overview of investigational antiviral agents for influenza and of future directions for development of influenza therapeutics. While progress in developing clinically useful antiviral agents for influenza has been generally slow, especially with respect to seriously ill and high‐risk patients, important clinical studies of intravenous neuraminidase inhibitors, antibodies and drug combinations are currently in progress. The current decade offers the promise of developing small molecular weight inhibitors with novel mechanisms of action, including host‐directed therapies, new biotherapeutics and drug combinations, that should provide more effective antiviral therapies and help mitigate the problem of antiviral resistance. Immunomodulatory interventions also offer promise but need to be based on better understanding of influenza pathogenesis, particularly in seriously ill patients. The development of combination interventions, immunomodulators and host‐directed therapies presents unique clinical trial design and regulatory hurdles that remain to be addressed. PMID:23279899

A new sensitizer DVDMS combined with multiple focused ultrasound treatments: an effective antitumor strategy

NASA Astrophysics Data System (ADS)

Xiong, Wenli; Wang, Pan; Hu, Jianmin; Jia, Yali; Wu, Lijie; Chen, Xiyang; Liu, Quanhong; Wang, Xiaobing

2015-12-01

Sonodynamic therapy (SDT) was developed as a promising noninvasive approach. The present study investigated the antitumor effect of a new sensitizer (sinoporphyrin sodium, referred to as DVDMS) combined with multiple ultrasound treatments on sarcoma 180 both in vitro and in vivo. The combined treatment significantly suppressed cell viability, potentiated apoptosis, and markedly inhibited angiogenesis in vivo. In vivo, the tumor weight inhibition ratio reached 89.82% fifteen days after three sonication treatments plus DVDMS. This effect was stronger than one ultrasound alone (32.56%) and than one round of sonication plus DVDMS (59.33%). DVDMS combined with multiple focused ultrasound treatments initiated tumor tissue destruction, induced cancer cell apoptosis, inhibited tumor angiogenesis, suppressed cancer cell proliferation, and decreased VEGF and PCNA expression levels. Moreover, the treatment did not show obvious signs of side effects or induce a drop in body weight. These results indicated that DVDMS combined with multiple focused ultrasounds may be a promising strategy against solid tumor.

Newer influenza antivirals, biotherapeutics and combinations.

PubMed

Hayden, Frederick G

2013-01-01

This summary provides an overview of investigational antiviral agents for influenza and of future directions for development of influenza therapeutics. While progress in developing clinically useful antiviral agents for influenza has been generally slow, especially with respect to seriously ill and high-risk patients, important clinical studies of intravenous neuraminidase inhibitors, antibodies and drug combinations are currently in progress. The current decade offers the promise of developing small molecular weight inhibitors with novel mechanisms of action, including host-directed therapies, new biotherapeutics and drug combinations, that should provide more effective antiviral therapies and help mitigate the problem of antiviral resistance. Immunomodulatory interventions also offer promise but need to be based on better understanding of influenza pathogenesis, particularly in seriously ill patients. The development of combination interventions, immunomodulators and host-directed therapies presents unique clinical trial design and regulatory hurdles that remain to be addressed. © 2012 Blackwell Publishing Ltd.

RNAi-combined nano-chemotherapeutics to tackle resistant tumors.

PubMed

Tekade, Rakesh Kumar; Tekade, Muktika; Kesharwani, Prashant; D'Emanuele, Antony

2016-11-01

The merger of nanotechnology and combination chemotherapy has shown notable promise in the therapy of resistant tumors. The latest scientific attention encompasses the engagement of anticancer drugs in combination with small interfering (si)RNAs, such as VEGF, XLAP, PGP, MRP-1, BCL-2 and cMyc, to name but a few. siRNAs have shown immense promise to knockout drug resistance genes as well as to recover the sensitivity of resistant tumors to anticancer therapy. The nanotechnology approach could also protect siRNA against RNAse degradation as well as prevent off-target effects. In this article, we discuss the approaches that have been used to deliver of siRNA in combination with chemotherapeutic drugs to treat resistant tumors. We also discuss the stipulations that must be considered in formulating a nanotechnology-assisted siRNA-drug cancer therapy. Copyright © 2016. Published by Elsevier Ltd.

A study of environmental characterization of conventional and advanced aluminum alloys for selection and design. Phase 1: Literature review

NASA Technical Reports Server (NTRS)

Sprowls, D. O.

1984-01-01

A review of the literature is presented with the objectives of identifying relationships between various accelerated stress corrosion testing techniques, and for determining the combination of test methods best suited to selection and design of high strength aluminum alloys. The following areas are reviewed: status of stress-corrosion test standards, the influence of mechanical and environmental factors on stress corrosion testing, correlation of accelerated test data with in-service experience, and procedures used to avoid stress corrosion problems in service. Promising areas for further work are identified.

Biomimetic graphene sensors: functionalizing graphene with peptides

NASA Astrophysics Data System (ADS)

Ishigami, Masa; Nyon Kim, Sang; Naik, Rajesh; Tatulian, Suren A.; Katoch, Jyoti

2012-02-01

Non-covalent biomimetic functionalization of graphene using peptides is one of more promising methods for producing novel sensors with high sensitivity and selectivity. Here we combine atomic force microscopy, Raman spectroscopy, and attenuated total reflection Fourier transform infrared spectroscopy to investigate peptide binding to graphene and graphite. We choose to study a dodecamer peptide identified with phage display to possess affinities for graphite and we find that the peptide forms a complex mesh-like structure upon adsorption on graphene. Moreover, optical spectroscopy reveals that the peptide binds non-covalently to graphene and possesses an optical signature of an ?-helical conformation on graphene.

Identifying the receptor subtype selectivity of retinoid X and retinoic acid receptors via quantum mechanics.

PubMed

Tsuji, Motonori; Shudo, Koichi; Kagechika, Hiroyuki

2017-03-01

Understanding and identifying the receptor subtype selectivity of a ligand is an important issue in the field of drug discovery. Using a combination of classical molecular mechanics and quantum mechanical calculations, this report assesses the receptor subtype selectivity for the human retinoid X receptor (hRXR) and retinoic acid receptor (hRAR) ligand-binding domains (LBDs) complexed with retinoid ligands. The calculated energies show good correlation with the experimentally reported binding affinities. The technique proposed here is a promising method as it reveals the origin of the receptor subtype selectivity of selective ligands.

A Secure and Efficient Handover Authentication Protocol for Wireless Networks

PubMed Central

Wang, Weijia; Hu, Lei

2014-01-01

Handover authentication protocol is a promising access control technology in the fields of WLANs and mobile wireless sensor networks. In this paper, we firstly review an efficient handover authentication protocol, named PairHand, and its existing security attacks and improvements. Then, we present an improved key recovery attack by using the linearly combining method and reanalyze its feasibility on the improved PairHand protocol. Finally, we present a new handover authentication protocol, which not only achieves the same desirable efficiency features of PairHand, but enjoys the provable security in the random oracle model. PMID:24971471

Control of reversible magnetization switching by pulsed circular magnetic field in glass-coated amorphous microwires

NASA Astrophysics Data System (ADS)

Chizhik, Alexander; Zhukov, Arkady; Gonzalez, Julian; Stupakiewicz, Andrzej

2018-02-01

Magnetization reversal in magnetic microwires was studied in the presence of external mechanical stress and helical magnetic fields using the magneto-optical Kerr effect. It was found that a combination of tuned magnetic anisotropy and a direct current or pulsed circular magnetic field activated different types of magnetization reversal scenarios. The application of the pulsed magnetic field of 10 ns time duration induced a transient controlling action to switch the magnetic states without activating a domain wall motion. This created a promising method for tuning the giant magneto-impedance effect.

An Improved Indoor Positioning System Using RGB-D Cameras and Wireless Networks for Use in Complex Environments.

PubMed

Duque Domingo, Jaime; Cerrada, Carlos; Valero, Enrique; Cerrada, Jose A

2017-10-20

This work presents an Indoor Positioning System to estimate the location of people navigating in complex indoor environments. The developed technique combines WiFi Positioning Systems and depth maps , delivering promising results in complex inhabited environments, consisting of various connected rooms, where people are freely moving. This is a non-intrusive system in which personal information about subjects is not needed and, although RGB-D cameras are installed in the sensing area, users are only required to carry their smart-phones. In this article, the methods developed to combine the above-mentioned technologies and the experiments performed to test the system are detailed. The obtained results show a significant improvement in terms of accuracy and performance with respect to previous WiFi-based solutions as well as an extension in the range of operation.

Clinical use of cardiac PET/MRI: current state-of-the-art and potential future applications.

PubMed

Krumm, Patrick; Mangold, Stefanie; Gatidis, Sergios; Nikolaou, Konstantin; Nensa, Felix; Bamberg, Fabian; la Fougère, Christian

2018-05-01

Combined PET/MRI is a novel imaging method integrating the advances of functional and morphological MR imaging with PET applications that include assessment of myocardial viability, perfusion, metabolism of inflammatory tissue and tumors, as well as amyloid deposition imaging. As such, PET/MRI is a promising tool to detect and characterize ischemic and non-ischemic cardiomyopathies. To date, the greatest benefit may be expected for diagnostic evaluation of systemic diseases and cardiac masses that remain unclear in cardiac MRI, as well as for clinical and scientific studies in the setting of ischemic cardiomyopathies. Diagnosis and therapeutic monitoring of cardiac sarcoidosis has the potential of a possible 'killer-application' for combined cardiac PET/MRI. In this article, we review the current evidence and discuss current and potential future applications of cardiac PET/MRI.

Joining dissimilar materials using Friction Stir scribe technique

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

Upadhyay, Piyush; Hovanski, Yuri; Jana, Saumyadeep

2016-10-03

The ability to effectively join materials with vastly different melting points like Aluminum-Steel, Polymer composites - metals has been one of the road blocks in realizing multi-material components for light weighting efforts. Friction stir scribe (FSS) technique is a promising method that produces continuous overlap joint between materials with vastly different melting regimes and high temperature flow characteristics. FSS uses an offset cutting tool at the tip of the FSW pin to create an insitu mechanical interlock between material interfaces. With investments from Vehicle Technology office, US DOE and several automotive manufacturers and suppliers PNNL is developing the FSS processmore » and has demonstrated viability of joining several material combinations. Details of welding trails, unique challenges and mitigation strategies in different material combinations will be discussed. Joint characterization including mechanical tests and joint performances will also be presented.« less

A chirped-pulse Fourier-transform microwave/pulsed uniform flow spectrometer. I. The low-temperature flow system.

PubMed

Oldham, James M; Abeysekera, Chamara; Joalland, Baptiste; Zack, Lindsay N; Prozument, Kirill; Sims, Ian R; Park, G Barratt; Field, Robert W; Suits, Arthur G

2014-10-21

We report the development of a new instrument that combines chirped-pulse microwave spectroscopy with a pulsed uniform supersonic flow. This combination promises a nearly universal detection method that can deliver isomer and conformer specific, quantitative detection and spectroscopic characterization of unstable reaction products and intermediates, product vibrational distributions, and molecular excited states. This first paper in a series of two presents a new pulsed-flow design, at the heart of which is a fast, high-throughput pulsed valve driven by a piezoelectric stack actuator. Uniform flows at temperatures as low as 20 K were readily achieved with only modest pumping requirements, as demonstrated by impact pressure measurements and pure rotational spectroscopy. The proposed technique will be suitable for application in diverse fields including fundamental studies in spectroscopy, kinetics, and reaction dynamics.

Gradient stationary phase optimized selectivity liquid chromatography with conventional columns.

PubMed

Chen, Kai; Lynen, Frédéric; Szucs, Roman; Hanna-Brown, Melissa; Sandra, Pat

2013-05-21

Stationary phase optimized selectivity liquid chromatography (SOSLC) is a promising technique to optimize the selectivity of a given separation. By combination of different stationary phases, SOSLC offers excellent possibilities for method development under both isocratic and gradient conditions. The so far available commercial SOSLC protocol utilizes dedicated column cartridges and corresponding cartridge holders to build up the combined column of different stationary phases. The present work is aimed at developing and extending the gradient SOSLC approach towards coupling conventional columns. Generic tubing was used to connect short commercially available LC columns. Fast and base-line separation of a mixture of 12 compounds containing phenones, benzoic acids and hydroxybenzoates under both isocratic and linear gradient conditions was selected to demonstrate the potential of SOSLC. The influence of the connecting tubing on the deviation of predictions is also discussed.

[Implementation of modern trends in the methods of the ventilation support in the new apparatus for artificial lung ventilation Avenir-221 P].

PubMed

Gal'perin, Iu Sh; Alkhimova, L R; Dmitriev, N D; Kozlova, I A; Nemirovskiĭ, S B; Makarov, M V; Safronov, A Iu

2005-01-01

In the new ventilator Avenir-221 P modern lines of development of ventilation support in intensive therapy of adults and children are implemented. The capacities of the ventilator are successfully combined with its technical decisions which include microprocessor parametrical controlling, programming-controlled electric drive, an information saturation, intuitively clear control system, protection against interruption of power supply sources and oxygen feeding falls. A set of functional characteristics (modes VCV, PCV, Ass/Contr, PSV, SIMV, PEEP, Sigh, etc.) in combination with an original design make the device the most accessible and promising for application in intensive care and resuscitation units of a wide network of Russian hospitals and clinics. The ventilator Avenir-221 P has passed all required tests and is presently commercially available.

Single Cell Multi-Omics Technology: Methodology and Application.

PubMed

Hu, Youjin; An, Qin; Sheu, Katherine; Trejo, Brandon; Fan, Shuxin; Guo, Ying

2018-01-01

In the era of precision medicine, multi-omics approaches enable the integration of data from diverse omics platforms, providing multi-faceted insight into the interrelation of these omics layers on disease processes. Single cell sequencing technology can dissect the genotypic and phenotypic heterogeneity of bulk tissue and promises to deepen our understanding of the underlying mechanisms governing both health and disease. Through modification and combination of single cell assays available for transcriptome, genome, epigenome, and proteome profiling, single cell multi-omics approaches have been developed to simultaneously and comprehensively study not only the unique genotypic and phenotypic characteristics of single cells, but also the combined regulatory mechanisms evident only at single cell resolution. In this review, we summarize the state-of-the-art single cell multi-omics methods and discuss their applications, challenges, and future directions.

Efficient and safe gene delivery to human corneal endothelium using magnetic nanoparticles.

PubMed

Czugala, Marta; Mykhaylyk, Olga; Böhler, Philip; Onderka, Jasmine; Stork, Björn; Wesselborg, Sebastian; Kruse, Friedrich E; Plank, Christian; Singer, Bernhard B; Fuchsluger, Thomas A

2016-07-01

To develop a safe and efficient method for targeted, anti-apoptotic gene therapy of corneal endothelial cells (CECs). Magnetofection (MF), a combination of lipofection with magnetic nanoparticles (MNPs; PEI-Mag2, SO-Mag5, PalD1-Mag1), was tested in human CECs and in explanted human corneas. Effects on cell viability and function were investigated. Immunocompatibility was assessed in human peripheral blood mononuclear cells. Silica iron-oxide MNPs (SO-Mag5) combined with X-tremeGENE-HP achieved high transfection efficiency in human CECs and explanted human corneas, without altering cell viability or function. Magnetofection caused no immunomodulatory effects in human peripheral blood mononuclear cells. Magnetofection with anti-apoptotic P35 gene effectively blocked apoptosis in CECs. Magnetofection is a promising tool for gene therapy of corneal endothelial cells with potential for targeted on-site delivery.

Single Cell Multi-Omics Technology: Methodology and Application

PubMed Central

Hu, Youjin; An, Qin; Sheu, Katherine; Trejo, Brandon; Fan, Shuxin; Guo, Ying

2018-01-01

In the era of precision medicine, multi-omics approaches enable the integration of data from diverse omics platforms, providing multi-faceted insight into the interrelation of these omics layers on disease processes. Single cell sequencing technology can dissect the genotypic and phenotypic heterogeneity of bulk tissue and promises to deepen our understanding of the underlying mechanisms governing both health and disease. Through modification and combination of single cell assays available for transcriptome, genome, epigenome, and proteome profiling, single cell multi-omics approaches have been developed to simultaneously and comprehensively study not only the unique genotypic and phenotypic characteristics of single cells, but also the combined regulatory mechanisms evident only at single cell resolution. In this review, we summarize the state-of-the-art single cell multi-omics methods and discuss their applications, challenges, and future directions. PMID:29732369

A survey and analysis of experimental hydrogen sensors

NASA Technical Reports Server (NTRS)

Hunter, Gary W.

1992-01-01

In order to ascertain the applicability of hydrogen sensors to aerospace applications, a survey was conducted of promising experimental point-contact hydrogen sensors and their operation was analyzed. The techniques discussed are metal-oxide-semiconductor or MOS based sensors, catalytic resistor sensors, acoustic wave detectors, and pyroelectric detectors. All of these sensors depend on the interaction of hydrogen with Pd or a Pd-alloy. It is concluded that no single technique will meet the needs of aerospace applications but a combination of approaches is necessary. The most promising combination is an MOS based sensor with a catalytic resistor.

New approaches in assessing food intake in epidemiology.

PubMed

Conrad, Johanna; Koch, Stefanie A J; Nöthlings, Ute

2018-06-22

A promising direction for improving dietary intake measurement in epidemiologic studies is the combination of short-term and long-term dietary assessment methods using statistical methods. Thereby, web-based instruments are particularly interesting as their application offers several potential advantages such as self-administration and a shorter completion time. The objective of this review is to provide an overview of new web-based short-term instruments and to describe their features. A number of web-based short-term dietary assessment tools for application in different countries and age-groups have been developed so far. Particular attention should be paid to the underlying database and the search function of the tool. Moreover, web-based instruments can improve the estimation of portion sizes by offering several options to the user. Web-based dietary assessment methods are associated with lower costs and reduced burden for participants and researchers, and show a comparable validity with traditional instruments. When there is a need for a web-based tool researcher should consider the adaptation of existing tools rather than developing new instruments. The combination of short-term and long-term instruments seems more feasible with the use of new technology.

Depth Profiles of Mg, Si, and Zn Implants in GaN by Trace Element Accelerator Mass Spectrometry

NASA Astrophysics Data System (ADS)

Ravi Prasad, G. V.; Pelicon, P.; Mitchell, L. J.; McDaniel, F. D.

2003-08-01

GaN is one of the most promising electronic materials for applications requiring high-power, high frequencies, or high-temperatures as well as opto-electronics in the blue to ultraviolet spectral region. We have recently measured depth profiles of Mg, Si, and Zn implants in GaN substrates by the TEAMS particle counting method for both matrix and trace elements, using a gas ionization chamber. Trace Element Accelerator Mass Spectrometry (TEAMS) is a combination of Secondary Ion Mass Spectrometry (SIMS) and Accelerator Mass Spectrometry (AMS) to measure trace elements at ppb levels. Negative ions from a SIMS like source are injected into a tandem accelerator. Molecular interferences inherent with the SIMS method are eliminated in the TEAMS method. Negative ion currents are extremely low with GaN as neither gallium nor nitrogen readily forms negative ions making the depth profile measurements more difficult. The energies of the measured ions are in the range of 4-8 MeV. A careful selection of mass/charge ratios of the detected ions combined with energy-loss behavior of the ions in the ionization chamber eliminated molecular interferences.

The Sternheimer-GW method and the spectral signatures of plasmonic polarons

NASA Astrophysics Data System (ADS)

Giustino, Feliciano

During the past three decades the GW method has emerged among the most promising electronic structure techniques for predictive calculations of quasiparticle band structures. In order to simplify the GW work-flow while at the same time improving the calculation accuracy, we developed the Sternheimer-GW method. In Sternheimer-GW both the screened Coulomb interaction and the electron Green's function are evaluated by using exclusively occupied Kohn-Sham states, as in density-functional perturbation theory. In this talk I will review the basics of Sternheimer-GW, and I will discuss two recent applications to semiconductors and superconductors. In the case of semiconductors we calculated complete energy- and momentum-resolved spectral functions by combining Sternheimer-GW with the cumulant expansion approach. This study revealed the existence of band structure replicas which arise from electron-plasmon interactions. In the case of superconductors we calculated the Coulomb pseudo-potential from first principles, and combined this approach with the Eliashberg theory of the superconducting critical temperature. This work was supported by the Leverhulme Trust (RL-2012-001), the European Research Council (EU FP7/ERC 239578), the UK Engineering and Physical Sciences Research Council (EP/J009857/1), and the Graphene Flagship (EU FP7/604391).

Multiple-image encryption based on double random phase encoding and compressive sensing by using a measurement array preprocessed with orthogonal-basis matrices

NASA Astrophysics Data System (ADS)

Zhang, Luozhi; Zhou, Yuanyuan; Huo, Dongming; Li, Jinxi; Zhou, Xin

2018-09-01

A method is presented for multiple-image encryption by using the combination of orthogonal encoding and compressive sensing based on double random phase encoding. As an original thought in optical encryption, it is demonstrated theoretically and carried out by using the orthogonal-basis matrices to build a modified measurement array, being projected onto the images. In this method, all the images can be compressed in parallel into a stochastic signal and be diffused to be a stationary white noise. Meanwhile, each single-image can be separately reestablished by adopting a proper decryption key combination through the block-reconstruction rather than the entire-rebuilt, for its costs of data and decryption time are greatly decreased, which may be promising both in multi-user multiplexing and huge-image encryption/decryption. Besides, the security of this method is characterized by using the bit-length of key, and the parallelism is investigated as well. The simulations and discussions are also made on the effects of decryption as well as the correlation coefficient by using a series of sampling rates, occlusion attacks, keys with various error rates, etc.

Accurate prediction of subcellular location of apoptosis proteins combining Chou's PseAAC and PsePSSM based on wavelet denoising.

PubMed

Yu, Bin; Li, Shan; Qiu, Wen-Ying; Chen, Cheng; Chen, Rui-Xin; Wang, Lei; Wang, Ming-Hui; Zhang, Yan

2017-12-08

Apoptosis proteins subcellular localization information are very important for understanding the mechanism of programmed cell death and the development of drugs. The prediction of subcellular localization of an apoptosis protein is still a challenging task because the prediction of apoptosis proteins subcellular localization can help to understand their function and the role of metabolic processes. In this paper, we propose a novel method for protein subcellular localization prediction. Firstly, the features of the protein sequence are extracted by combining Chou's pseudo amino acid composition (PseAAC) and pseudo-position specific scoring matrix (PsePSSM), then the feature information of the extracted is denoised by two-dimensional (2-D) wavelet denoising. Finally, the optimal feature vectors are input to the SVM classifier to predict subcellular location of apoptosis proteins. Quite promising predictions are obtained using the jackknife test on three widely used datasets and compared with other state-of-the-art methods. The results indicate that the method proposed in this paper can remarkably improve the prediction accuracy of apoptosis protein subcellular localization, which will be a supplementary tool for future proteomics research.

Low resistivity of graphene nanoribbons with zigzag-dominated edge fabricated by hydrogen plasma etching combined with Zn/HCl pretreatment

NASA Astrophysics Data System (ADS)

Liu, Fengkui; Li, Qi; Wang, Rubing; Xu, Jianbao; Hu, Junxiong; Li, Weiwei; Guo, Yufen; Qian, Yuting; Deng, Wei; Ullah, Zaka; Zeng, Zhongming; Sun, Mengtao; Liu, Liwei

2017-11-01

Graphene nanoribbons (GNRs) have attracted intensive research interest owing to their potential applications in high performance graphene-based electronics. However, the deterioration of electrical performance caused by edge disorder is still an important obstacle to the applications. Here, we report the fabrication of low resistivity GNRs with a zigzag-dominated edge through hydrogen plasma etching combined with the Zn/HCl pretreatment method. This method is based on the anisotropic etching properties of hydrogen plasma in the vicinity of defects created by sputtering zinc (Zn) onto planar graphene. The polarized Raman spectra measurement of GNRs exhibits highly polarization dependence, which reveals the appearance of the zigzag-dominated edge. The as-prepared GNRs exhibit high carrier mobility (˜1332.4 cm2 v-1 s-1) and low resistivity (˜0.7 kΩ) at room temperature. Particularly, the GNRs can carry large current density (5.02 × 108 A cm-2) at high voltage (20.0 V) in the air atmosphere. Our study develops a controllable method to fabricate zigzag edge dominated GNRs for promising applications in transistors, sensors, nanoelectronics, and interconnects.

Accurate prediction of subcellular location of apoptosis proteins combining Chou’s PseAAC and PsePSSM based on wavelet denoising

PubMed Central

Chen, Cheng; Chen, Rui-Xin; Wang, Lei; Wang, Ming-Hui; Zhang, Yan

2017-01-01

Apoptosis proteins subcellular localization information are very important for understanding the mechanism of programmed cell death and the development of drugs. The prediction of subcellular localization of an apoptosis protein is still a challenging task because the prediction of apoptosis proteins subcellular localization can help to understand their function and the role of metabolic processes. In this paper, we propose a novel method for protein subcellular localization prediction. Firstly, the features of the protein sequence are extracted by combining Chou's pseudo amino acid composition (PseAAC) and pseudo-position specific scoring matrix (PsePSSM), then the feature information of the extracted is denoised by two-dimensional (2-D) wavelet denoising. Finally, the optimal feature vectors are input to the SVM classifier to predict subcellular location of apoptosis proteins. Quite promising predictions are obtained using the jackknife test on three widely used datasets and compared with other state-of-the-art methods. The results indicate that the method proposed in this paper can remarkably improve the prediction accuracy of apoptosis protein subcellular localization, which will be a supplementary tool for future proteomics research. PMID:29296195

Dual Combined Real-Time Reverse Transcription Polymerase Chain Reaction Assay for the Diagnosis of Lyssavirus Infection.

PubMed

Dacheux, Laurent; Larrous, Florence; Lavenir, Rachel; Lepelletier, Anthony; Faouzi, Abdellah; Troupin, Cécile; Nourlil, Jalal; Buchy, Philippe; Bourhy, Herve

2016-07-01

The definitive diagnosis of lyssavirus infection (including rabies) in animals and humans is based on laboratory confirmation. The reference techniques for post-mortem rabies diagnosis are still based on direct immunofluorescence and virus isolation, but molecular techniques, such as polymerase chain reaction (PCR) based methods, are increasingly being used and now constitute the principal tools for diagnosing rabies in humans and for epidemiological analyses. However, it remains a key challenge to obtain relevant specificity and sensitivity with these techniques while ensuring that the genetic diversity of lyssaviruses does not compromise detection. We developed a dual combined real-time reverse transcription polymerase chain reaction (combo RT-qPCR) method for pan-lyssavirus detection. This method is based on two complementary technologies: a probe-based (TaqMan) RT-qPCR for detecting the RABV species (pan-RABV RT-qPCR) and a second reaction using an intercalating dye (SYBR Green) to detect other lyssavirus species (pan-lyssa RT-qPCR). The performance parameters of this combined assay were evaluated with a large panel of primary animal samples covering almost all the genetic variability encountered at the viral species level, and they extended to almost all lyssavirus species characterized to date. This method was also evaluated for the diagnosis of human rabies on 211 biological samples (positive n = 76 and negative n = 135) including saliva, skin and brain biopsies. It detected all 41 human cases of rabies tested and confirmed the sensitivity and the interest of skin biopsy (91.5%) and saliva (54%) samples for intra-vitam diagnosis of human rabies. Finally, this method was successfully implemented in two rabies reference laboratories in enzootic countries (Cambodia and Morocco). This combined RT-qPCR method constitutes a relevant, useful, validated tool for the diagnosis of rabies in both humans and animals, and represents a promising tool for lyssavirus surveillance.

Dual Combined Real-Time Reverse Transcription Polymerase Chain Reaction Assay for the Diagnosis of Lyssavirus Infection

PubMed Central

Lavenir, Rachel; Lepelletier, Anthony; Faouzi, Abdellah; Troupin, Cécile; Nourlil, Jalal; Buchy, Philippe; Bourhy, Herve

2016-01-01

The definitive diagnosis of lyssavirus infection (including rabies) in animals and humans is based on laboratory confirmation. The reference techniques for post-mortem rabies diagnosis are still based on direct immunofluorescence and virus isolation, but molecular techniques, such as polymerase chain reaction (PCR) based methods, are increasingly being used and now constitute the principal tools for diagnosing rabies in humans and for epidemiological analyses. However, it remains a key challenge to obtain relevant specificity and sensitivity with these techniques while ensuring that the genetic diversity of lyssaviruses does not compromise detection. We developed a dual combined real-time reverse transcription polymerase chain reaction (combo RT-qPCR) method for pan-lyssavirus detection. This method is based on two complementary technologies: a probe-based (TaqMan) RT-qPCR for detecting the RABV species (pan-RABV RT-qPCR) and a second reaction using an intercalating dye (SYBR Green) to detect other lyssavirus species (pan-lyssa RT-qPCR). The performance parameters of this combined assay were evaluated with a large panel of primary animal samples covering almost all the genetic variability encountered at the viral species level, and they extended to almost all lyssavirus species characterized to date. This method was also evaluated for the diagnosis of human rabies on 211 biological samples (positive n = 76 and negative n = 135) including saliva, skin and brain biopsies. It detected all 41 human cases of rabies tested and confirmed the sensitivity and the interest of skin biopsy (91.5%) and saliva (54%) samples for intra-vitam diagnosis of human rabies. Finally, this method was successfully implemented in two rabies reference laboratories in enzootic countries (Cambodia and Morocco). This combined RT-qPCR method constitutes a relevant, useful, validated tool for the diagnosis of rabies in both humans and animals, and represents a promising tool for lyssavirus surveillance. PMID:27380028

A Better Blend: A Vision for Boosting Student Outcomes with Digital Learning

ERIC Educational Resources Information Center

Public Impact, 2013

2013-01-01

Blended learning that combines digital instruction with live, accountable teachers holds unique promise to improve student outcomes dramatically. Schools will not realize this promise at large scale with technology improvements alone, though, or with technology and today's typical teaching roles. This brief explains how schools can use blended…

Pharmacophore Hybridization To Discover Novel Topoisomerase II Poisons with Promising Antiproliferative Activity.

PubMed

Ortega, Jose Antonio; Riccardi, Laura; Minniti, Elirosa; Borgogno, Marco; Arencibia, Jose M; Greco, Maria L; Minarini, Anna; Sissi, Claudia; De Vivo, Marco

2018-02-08

We used a pharmacophore hybridization strategy to combine key structural elements of merbarone and etoposide and generated new type II topoisomerase (topoII) poisons. This first set of hybrid topoII poisons shows promising antiproliferative activity on human cancer cells, endorsing their further exploration for anticancer drug discovery.

Parameterization of aquatic ecosystem functioning and its natural variation: Hierarchical Bayesian modelling of plankton food web dynamics

NASA Astrophysics Data System (ADS)

Norros, Veera; Laine, Marko; Lignell, Risto; Thingstad, Frede

2017-10-01

Methods for extracting empirically and theoretically sound parameter values are urgently needed in aquatic ecosystem modelling to describe key flows and their variation in the system. Here, we compare three Bayesian formulations for mechanistic model parameterization that differ in their assumptions about the variation in parameter values between various datasets: 1) global analysis - no variation, 2) separate analysis - independent variation and 3) hierarchical analysis - variation arising from a shared distribution defined by hyperparameters. We tested these methods, using computer-generated and empirical data, coupled with simplified and reasonably realistic plankton food web models, respectively. While all methods were adequate, the simulated example demonstrated that a well-designed hierarchical analysis can result in the most accurate and precise parameter estimates and predictions, due to its ability to combine information across datasets. However, our results also highlighted sensitivity to hyperparameter prior distributions as an important caveat of hierarchical analysis. In the more complex empirical example, hierarchical analysis was able to combine precise identification of parameter values with reasonably good predictive performance, although the ranking of the methods was less straightforward. We conclude that hierarchical Bayesian analysis is a promising tool for identifying key ecosystem-functioning parameters and their variation from empirical datasets.

Down syndrome detection from facial photographs using machine learning techniques

NASA Astrophysics Data System (ADS)

Zhao, Qian; Rosenbaum, Kenneth; Sze, Raymond; Zand, Dina; Summar, Marshall; Linguraru, Marius George

2013-02-01

Down syndrome is the most commonly occurring chromosomal condition; one in every 691 babies in United States is born with it. Patients with Down syndrome have an increased risk for heart defects, respiratory and hearing problems and the early detection of the syndrome is fundamental for managing the disease. Clinically, facial appearance is an important indicator in diagnosing Down syndrome and it paves the way for computer-aided diagnosis based on facial image analysis. In this study, we propose a novel method to detect Down syndrome using photography for computer-assisted image-based facial dysmorphology. Geometric features based on facial anatomical landmarks, local texture features based on the Contourlet transform and local binary pattern are investigated to represent facial characteristics. Then a support vector machine classifier is used to discriminate normal and abnormal cases; accuracy, precision and recall are used to evaluate the method. The comparison among the geometric, local texture and combined features was performed using the leave-one-out validation. Our method achieved 97.92% accuracy with high precision and recall for the combined features; the detection results were higher than using only geometric or texture features. The promising results indicate that our method has the potential for automated assessment for Down syndrome from simple, noninvasive imaging data.

Development of a Combined Human Transferrin-Hemoglobin Lateral Immunochromatographic Assay for Accurate and Rapid Fecal Occult Blood Test.

PubMed

Ye, Yuanyuan; Deng, Yin; Mao, Jinju; Yan, Qin; Huang, Yidan; Zhang, Jun; Zheng, Jian; Li, Yue; Chen, Weixian

2018-05-01

Fecal occult bloodtest (FOBT) plays an important role in the diagnosis of gastrointestinal diseases. The sensitivities of current FOBT methods are still not satisfactory. The aim of this study is to develop a combined human transferrin (HTf)-hemoglobin (HHb) lateral flow assay (LFA) for accurate and rapid FOBT. Monoclonal antibodies (MAbs) targeting HTf were developed by conventional methods and paired using LFA strips. The best HTf MAb pair was chosen according to the overall performance on testing limit and specificity. Meanwhile, HHb LFA strips were prepared using previously developed HHb MAbs. The testing limit and specificity were characterized. Based on the selected HTf MAb pair and the verified HHb MAb pair, combined HTf-HHb strips were developed. The combined HTf-HHb strips were used for FOBT of 400 human fecal samples, including 200 gastrointestinal bleeding specimens and 200 healthy subjects. For comparison, the homemade individual HTf and HHb strips, as well as three kinds of commercial FOBT strips, were also used for the FOBT. Two MAb pairs targeting HTf were developed for LFA. Two types of HTf strips were prepared accordingly. The type I was chosen due to its lower detection limit. Using the type I HTf MAb pair and the verified HHb- MAb pair, the combined HTf-HHb strips could detect the HTf at concentrations between 1 ng/mL and 1 x 106 ng/mL and the HHb between 10 ng/mL and 2.5 x 106 ng/mL. Compared to individual HTf and HHb strips and three kinds of commercial strips, the combined strips showed the highest diagnostic sensitivity in FOBT (96.0%). The specificity was a satisfactory 99%. Our combined HTf-HHb test strips are a very promising product for accurate and rapid FOBT.

Improving prediction of heterodimeric protein complexes using combination with pairwise kernel.

PubMed

Ruan, Peiying; Hayashida, Morihiro; Akutsu, Tatsuya; Vert, Jean-Philippe

2018-02-19

Since many proteins become functional only after they interact with their partner proteins and form protein complexes, it is essential to identify the sets of proteins that form complexes. Therefore, several computational methods have been proposed to predict complexes from the topology and structure of experimental protein-protein interaction (PPI) network. These methods work well to predict complexes involving at least three proteins, but generally fail at identifying complexes involving only two different proteins, called heterodimeric complexes or heterodimers. There is however an urgent need for efficient methods to predict heterodimers, since the majority of known protein complexes are precisely heterodimers. In this paper, we use three promising kernel functions, Min kernel and two pairwise kernels, which are Metric Learning Pairwise Kernel (MLPK) and Tensor Product Pairwise Kernel (TPPK). We also consider the normalization forms of Min kernel. Then, we combine Min kernel or its normalization form and one of the pairwise kernels by plugging. We applied kernels based on PPI, domain, phylogenetic profile, and subcellular localization properties to predicting heterodimers. Then, we evaluate our method by employing C-Support Vector Classification (C-SVC), carrying out 10-fold cross-validation, and calculating the average F-measures. The results suggest that the combination of normalized-Min-kernel and MLPK leads to the best F-measure and improved the performance of our previous work, which had been the best existing method so far. We propose new methods to predict heterodimers, using a machine learning-based approach. We train a support vector machine (SVM) to discriminate interacting vs non-interacting protein pairs, based on informations extracted from PPI, domain, phylogenetic profiles and subcellular localization. We evaluate in detail new kernel functions to encode these data, and report prediction performance that outperforms the state-of-the-art.

Combination Treatment With Meropenem Plus Levofloxacin Is Synergistic Against Pseudomonas aeruginosa Infection in a Murine Model of Pneumonia

PubMed Central

Louie, Arnold; Liu, Weiguo; VanGuilder, Michael; Neely, Michael N.; Schumitzky, Alan; Jelliffe, Roger; Fikes, Steven; Kurhanewicz, Stephanie; Robbins, Nichole; Brown, David; Baluya, Dodge; Drusano, George L.

2015-01-01

Background. Meropenem plus levofloxacin treatment was shown to be a promising combination in our in vitro hollow fiber infection model. We strove to validate this finding in a murine Pseudomonas pneumonia model. Methods. A dose-ranging study with meropenem and levofloxacin alone and in combination against Pseudomonas aeruginosa was performed in a granulocytopenic murine pneumonia model. Meropenem and levofloxacin were administered to partially humanize their pharmacokinetic profiles in mouse serum. Total and resistant bacterial populations were estimated after 24 hours of therapy. Pharmacokinetic profiling of both drugs was performed in plasma and epithelial lining fluid, using a population model. Results. Meropenem and levofloxacin penetrations into epithelial lining fluid were 39.3% and 64.3%, respectively. Both monotherapies demonstrated good exposure responses. An innovative combination-therapy analytic approach demonstrated that the combination was statistically significantly synergistic (α = 2.475), as was shown in the hollow fiber infection model. Bacterial resistant to levofloxacin and meropenem was seen in the control arm. Levofloxacin monotherapy selected for resistance to itself. No resistant subpopulations were observed in any combination therapy arm. Conclusions. The combination of meropenem plus levofloxacin was synergistic, producing good bacterial kill and resistance suppression. Given the track record of safety of each agent, this combination may be worthy of clinical trial. PMID:25362196

Tunable Band Alignment with Unperturbed Carrier Mobility of On-Surface Synthesized Organic Semiconducting Wires

PubMed Central

2016-01-01

The tunable properties of molecular materials place them among the favorites for a variety of future generation devices. In addition, to maintain the current trend of miniaturization of those devices, a departure from the present top-down production methods may soon be required and self-assembly appears among the most promising alternatives. On-surface synthesis unites the promises of molecular materials and of self-assembly, with the sturdiness of covalently bonded structures: an ideal scenario for future applications. Following this idea, we report the synthesis of functional extended nanowires by self-assembly. In particular, the products correspond to one-dimensional organic semiconductors. The uniaxial alignment provided by our substrate templates allows us to access with exquisite detail their electronic properties, including the full valence band dispersion, by combining local probes with spatial averaging techniques. We show how, by selectively doping the molecular precursors, the product’s energy level alignment can be tuned without compromising the charge carrier’s mobility. PMID:26841052

Oxygen-deficient photostable Cu2O for enhanced visible light photocatalytic activity.

PubMed

Singh, Mandeep; Jampaiah, Deshetti; Kandjani, Ahmad E; Sabri, Ylias M; Della Gaspera, Enrico; Reineck, Philipp; Judd, Martyna; Langley, Julien; Cox, Nicholas; van Embden, Joel; Mayes, Edwin L H; Gibson, Brant C; Bhargava, Suresh K; Ramanathan, Rajesh; Bansal, Vipul

2018-03-29

Oxygen vacancies in inorganic semiconductors play an important role in reducing electron-hole recombination, which may have important implications in photocatalysis. Cuprous oxide (Cu2O), a visible light active p-type semiconductor, is a promising photocatalyst. However, the synthesis of photostable Cu2O enriched with oxygen defects remains a challenge. We report a simple method for the gram-scale synthesis of highly photostable Cu2O nanoparticles by the hydrolysis of a Cu(i)-triethylamine [Cu(i)-TEA] complex at low temperature. The oxygen vacancies in these Cu2O nanoparticles led to a significant increase in the lifetimes of photogenerated charge carriers upon excitation with visible light. This, in combination with a suitable energy band structure, allowed Cu2O nanoparticles to exhibit outstanding photoactivity in visible light through the generation of electron-mediated hydroxyl (OH˙) radicals. This study highlights the significance of oxygen defects in enhancing the photocatalytic performance of promising semiconductor photocatalysts.

C2 Arylated Benzo[b]thiophene Derivatives as Staphylococcus aureus NorA Efflux Pump Inhibitors.

PubMed

Liger, François; Bouhours, Pascale; Ganem-Elbaz, Carine; Jolivalt, Claude; Pellet-Rostaing, Stéphane; Popowycz, Florence; Paris, Jean-Marc; Lemaire, Marc

2016-02-04

An innovative and straightforward synthesis of second-generation 2-arylbenzo[b]thiophenes as structural analogues of INF55 and the first generation of our laboratory-made molecules was developed. The synthesis of C2-arylated benzo[b]thiophene derivatives was achieved through a method involving direct arylation, followed by simple structural modifications. Among the 34 compounds tested, two of them were potent NorA pump inhibitors, which led to a 16-fold decrease in the ciprofloxacin minimum inhibitory concentration (MIC) against the SA-1199B strain at concentrations of 0.25 and 0.5 μg mL(-1) (1 and 1.5 μm, respectively). This is a promising result relative to that obtained for reserpine (MIC=20 μg mL(-1)), a reference compound amongst NorA pump inhibitors. These molecules thus represent promising candidates to be used in combination with ciprofloxacin against fluoroquinolone-resistant strains. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Towards Precision Medicine in the Clinic: From Biomarker Discovery to Novel Therapeutics.

PubMed

Collins, Dearbhaile C; Sundar, Raghav; Lim, Joline S J; Yap, Timothy A

2017-01-01

Precision medicine continues to be the benchmark to which we strive in cancer research. Seeking out actionable aberrations that can be selectively targeted by drug compounds promises to optimize treatment efficacy and minimize toxicity. Utilizing these different targeted agents in combination or in sequence may further delay resistance to treatments and prolong antitumor responses. Remarkable progress in the field of immunotherapy adds another layer of complexity to the management of cancer patients. Corresponding advances in companion biomarker development, novel methods of serial tumor assessments, and innovative trial designs act synergistically to further precision medicine. Ongoing hurdles such as clonal evolution, intra- and intertumor heterogeneity, and varied mechanisms of drug resistance continue to be challenges to overcome. Large-scale data-sharing and collaborative networks using next-generation sequencing (NGS) platforms promise to take us further into the cancer 'ome' than ever before, with the goal of achieving successful precision medicine. Copyright © 2016 Elsevier Ltd. All rights reserved.

White matter biomarkers from diffusion MRI

NASA Astrophysics Data System (ADS)

Nørhøj Jespersen, Sune

2018-06-01

As part of an issue celebrating 2 decades of Joseph Ackerman editing the Journal of Magnetic Resonance, this paper reviews recent progress in one of the many areas in which Ackerman and his lab has made significant contributions: NMR measurement of diffusion in biological media, specifically in brain tissue. NMR diffusion signals display exquisite sensitivity to tissue microstructure, and have the potential to offer quantitative and specific information on the cellular scale orders of magnitude below nominal image resolution when combined with biophysical modeling. Here, I offer a personal perspective on some recent advances in diffusion imaging, from diffusion kurtosis imaging to microstructural modeling, and the connection between the two. A new result on the estimation accuracy of axial and radial kurtosis with axially symmetric DKI is presented. I moreover touch upon recently suggested generalized diffusion sequences, promising to offer independent microstructural information. We discuss the need and some methods for validation, and end with an outlook on some promising future directions.

Methodological issues in current practice may lead to bias in the development of biomarker combinations for predicting acute kidney injury.

PubMed

Meisner, Allison; Kerr, Kathleen F; Thiessen-Philbrook, Heather; Coca, Steven G; Parikh, Chirag R

2016-02-01

Individual biomarkers of renal injury are only modestly predictive of acute kidney injury (AKI). Using multiple biomarkers has the potential to improve predictive capacity. In this systematic review, statistical methods of articles developing biomarker combinations to predict AKI were assessed. We identified and described three potential sources of bias (resubstitution bias, model selection bias, and bias due to center differences) that may compromise the development of biomarker combinations. Fifteen studies reported developing kidney injury biomarker combinations for the prediction of AKI after cardiac surgery (8 articles), in the intensive care unit (4 articles), or other settings (3 articles). All studies were susceptible to at least one source of bias and did not account for or acknowledge the bias. Inadequate reporting often hindered our assessment of the articles. We then evaluated, when possible (7 articles), the performance of published biomarker combinations in the TRIBE-AKI cardiac surgery cohort. Predictive performance was markedly attenuated in six out of seven cases. Thus, deficiencies in analysis and reporting are avoidable, and care should be taken to provide accurate estimates of risk prediction model performance. Hence, rigorous design, analysis, and reporting of biomarker combination studies are essential to realizing the promise of biomarkers in clinical practice.

Efficient differentially private learning improves drug sensitivity prediction.

PubMed

Honkela, Antti; Das, Mrinal; Nieminen, Arttu; Dikmen, Onur; Kaski, Samuel

2018-02-06

Users of a personalised recommendation system face a dilemma: recommendations can be improved by learning from data, but only if other users are willing to share their private information. Good personalised predictions are vitally important in precision medicine, but genomic information on which the predictions are based is also particularly sensitive, as it directly identifies the patients and hence cannot easily be anonymised. Differential privacy has emerged as a potentially promising solution: privacy is considered sufficient if presence of individual patients cannot be distinguished. However, differentially private learning with current methods does not improve predictions with feasible data sizes and dimensionalities. We show that useful predictors can be learned under powerful differential privacy guarantees, and even from moderately-sized data sets, by demonstrating significant improvements in the accuracy of private drug sensitivity prediction with a new robust private regression method. Our method matches the predictive accuracy of the state-of-the-art non-private lasso regression using only 4x more samples under relatively strong differential privacy guarantees. Good performance with limited data is achieved by limiting the sharing of private information by decreasing the dimensionality and by projecting outliers to fit tighter bounds, therefore needing to add less noise for equal privacy. The proposed differentially private regression method combines theoretical appeal and asymptotic efficiency with good prediction accuracy even with moderate-sized data. As already the simple-to-implement method shows promise on the challenging genomic data, we anticipate rapid progress towards practical applications in many fields. This article was reviewed by Zoltan Gaspari and David Kreil.

Particle-Size-Grouping Model of Precipitation Kinetics in Microalloyed Steels

NASA Astrophysics Data System (ADS)

Xu, Kun; Thomas, Brian G.

2012-03-01

The formation, growth, and size distribution of precipitates greatly affects the microstructure and properties of microalloyed steels. Computational particle-size-grouping (PSG) kinetic models based on population balances are developed to simulate precipitate particle growth resulting from collision and diffusion mechanisms. First, the generalized PSG method for collision is explained clearly and verified. Then, a new PSG method is proposed to model diffusion-controlled precipitate nucleation, growth, and coarsening with complete mass conservation and no fitting parameters. Compared with the original population-balance models, this PSG method saves significant computation and preserves enough accuracy to model a realistic range of particle sizes. Finally, the new PSG method is combined with an equilibrium phase fraction model for plain carbon steels and is applied to simulate the precipitated fraction of aluminum nitride and the size distribution of niobium carbide during isothermal aging processes. Good matches are found with experimental measurements, suggesting that the new PSG method offers a promising framework for the future development of realistic models of precipitation.

Engineering the Pseudomonas aeruginosa II lectin: designing mutants with changed affinity and specificity

NASA Astrophysics Data System (ADS)

Kříž, Zdeněk; Adam, Jan; Mrázková, Jana; Zotos, Petros; Chatzipavlou, Thomais; Wimmerová, Michaela; Koča, Jaroslav

2014-09-01

This article focuses on designing mutations of the PA-IIL lectin from Pseudomonas aeruginosa that lead to change in specificity. Following the previous results revealing the importance of the amino acid triad 22-23-24 (so-called specificity-binding loop), saturation in silico mutagenesis was performed, with the intent of finding mutations that increase the lectin's affinity and modify its specificity. For that purpose, a combination of docking, molecular dynamics and binding free energy calculation was used. The combination of methods revealed mutations that changed the performance of the wild-type lectin and its mutants to their preferred partners. The mutation at position 22 resulted in 85 % in inactivation of the binding site, and the mutation at 23 did not have strong effects thanks to the side chain being pointed away from the binding site. Molecular dynamics simulations followed by binding free energy calculation were performed on mutants with promising results from docking, and also at those where the amino acid at position 24 was replaced for bulkier or longer polar chain. The key mutants were also prepared in vitro and their binding properties determined by isothermal titration calorimetry. Combination of the used methods proved to be able to predict changes in the lectin performance and helped in explaining the data observed experimentally.

Detection of explosive cough events in audio recordings by internal sound analysis.

PubMed

Rocha, B M; Mendes, L; Couceiro, R; Henriques, J; Carvalho, P; Paiva, R P

2017-07-01

We present a new method for the discrimination of explosive cough events, which is based on a combination of spectral content descriptors and pitch-related features. After the removal of near-silent segments, a vector of event boundaries is obtained and a proposed set of 9 features is extracted for each event. Two data sets, recorded using electronic stethoscopes and comprising a total of 46 healthy subjects and 13 patients, were employed to evaluate the method. The proposed feature set is compared to three other sets of descriptors: a baseline, a combination of both sets, and an automatic selection of the best 10 features from both sets. The combined feature set yields good results on the cross-validated database, attaining a sensitivity of 92.3±2.3% and a specificity of 84.7±3.3%. Besides, this feature set seems to generalize well when it is trained on a small data set of patients, with a variety of respiratory and cardiovascular diseases, and tested on a bigger data set of mostly healthy subjects: a sensitivity of 93.4% and a specificity of 83.4% are achieved in those conditions. These results demonstrate that complementing the proposed feature set with a baseline set is a promising approach.

Ten new and emerging trends in residential group living environments.

PubMed

Regnier, Victor; Denton, Alexis

2009-01-01

Residential styled environments for physically challenged people with neuro disabilities are rapidly replacing the standard institutional skilled nursing home. Ten trends are described that utilize residential design approaches to the physical environment while relying on home-care style methods for service delivery. Combined these two forces create powerful differentiators which make group residential settings more friendly and humane. Northern European, as well as, US best practices and prototypes are described that combine housing with services in a range of contexts. The success of northern Europeans in promulgating models of aging-in-place that keep those at risk more independent in the community or within family settings are remarkable. Topics like the impact of small group living clusters, interior design treatments, access to landscape gardens, life skill management methods, movement systems for circulation and exercise, shared space priorities, unit design trends and innovative care giving techniques are introduced. The focus of the article is on specific practices gleaned from cultures and exemplars that appear to increase autonomy, independence and privacy for those who are threatened because of their disabilities with the loss of these lifestyle attributes. Promising concepts of service organization and community outreach are combined with detailed recommendations that address the need for lift technology and safety features in bathrooms and kitchens.

A comparative analysis of alternative approaches for quantifying nonlinear dynamics in cardiovascular system.

PubMed

Chen, Yun; Yang, Hui

2013-01-01

Heart rate variability (HRV) analysis has emerged as an important research topic to evaluate autonomic cardiac function. However, traditional time and frequency-domain analysis characterizes and quantify only linear and stationary phenomena. In the present investigation, we made a comparative analysis of three alternative approaches (i.e., wavelet multifractal analysis, Lyapunov exponents and multiscale entropy analysis) for quantifying nonlinear dynamics in heart rate time series. Note that these extracted nonlinear features provide information about nonlinear scaling behaviors and the complexity of cardiac systems. To evaluate the performance, we used 24-hour HRV recordings from 54 healthy subjects and 29 heart failure patients, available in PhysioNet. Three nonlinear methods are evaluated not only individually but also in combination using three classification algorithms, i.e., linear discriminate analysis, quadratic discriminate analysis and k-nearest neighbors. Experimental results show that three nonlinear methods capture nonlinear dynamics from different perspectives and the combined feature set achieves the best performance, i.e., sensitivity 97.7% and specificity 91.5%. Collectively, nonlinear HRV features are shown to have the promise to identify the disorders in autonomic cardiovascular function.

Improving automatic peptide mass fingerprint protein identification by combining many peak sets.

PubMed

Rögnvaldsson, Thorsteinn; Häkkinen, Jari; Lindberg, Claes; Marko-Varga, György; Potthast, Frank; Samuelsson, Jim

2004-08-05

An automated peak picking strategy is presented where several peak sets with different signal-to-noise levels are combined to form a more reliable statement on the protein identity. The strategy is compared against both manual peak picking and industry standard automated peak picking on a set of mass spectra obtained after tryptic in gel digestion of 2D-gel samples from human fetal fibroblasts. The set of spectra contain samples ranging from strong to weak spectra, and the proposed multiple-scale method is shown to be much better on weak spectra than the industry standard method and a human operator, and equal in performance to these on strong and medium strong spectra. It is also demonstrated that peak sets selected by a human operator display a considerable variability and that it is impossible to speak of a single "true" peak set for a given spectrum. The described multiple-scale strategy both avoids time-consuming parameter tuning and exceeds the human operator in protein identification efficiency. The strategy therefore promises reliable automated user-independent protein identification using peptide mass fingerprints.

Temporal Lobe and “Default” Hemodynamic Brain Modes Discriminate Between Schizophrenia and Bipolar Disorder

PubMed Central

Calhoun, Vince D.; Maciejewski, Paul K.; Pearlson, Godfrey D.; Kiehl, Kent A.

2009-01-01

Schizophrenia and bipolar disorder are currently diagnosed on the basis of psychiatric symptoms and longitudinal course. The determination of a reliable, biologically-based diagnostic indicator of these diseases (a biomarker) could provide the groundwork for developing more rigorous tools for differential diagnosis and treatment assignment. Recently, methods have been used to identify distinct sets of brain regions or “spatial modes” exhibiting temporally coherent brain activity. Using functional magnetic resonance imaging (fMRI) data and a multivariate analysis method, independent component analysis, we combined the temporal lobe and the default modes to discriminate subjects with bipolar disorder, chronic schizophrenia, and healthy controls. Temporal lobe and default mode networks were reliably identified in all participants. Classification results on an independent set of individuals revealed an average sensitivity and specificity of 90 and 95%, respectively. The use of coherent brain networks such as the temporal lobe and default mode networks may provide a more reliable measure of disease state than task-correlated fMRI activity. A combination of two such hemodynamic brain networks shows promise as a biomarker for schizophrenia and bipolar disorder. PMID:17894392

Temporal lobe and "default" hemodynamic brain modes discriminate between schizophrenia and bipolar disorder.

PubMed

Calhoun, Vince D; Maciejewski, Paul K; Pearlson, Godfrey D; Kiehl, Kent A

2008-11-01

Schizophrenia and bipolar disorder are currently diagnosed on the basis of psychiatric symptoms and longitudinal course. The determination of a reliable, biologically-based diagnostic indicator of these diseases (a biomarker) could provide the groundwork for developing more rigorous tools for differential diagnosis and treatment assignment. Recently, methods have been used to identify distinct sets of brain regions or "spatial modes" exhibiting temporally coherent brain activity. Using functional magnetic resonance imaging (fMRI) data and a multivariate analysis method, independent component analysis, we combined the temporal lobe and the default modes to discriminate subjects with bipolar disorder, chronic schizophrenia, and healthy controls. Temporal lobe and default mode networks were reliably identified in all participants. Classification results on an independent set of individuals revealed an average sensitivity and specificity of 90 and 95%, respectively. The use of coherent brain networks such as the temporal lobe and default mode networks may provide a more reliable measure of disease state than task-correlated fMRI activity. A combination of two such hemodynamic brain networks shows promise as a biomarker for schizophrenia and bipolar disorder.

Performance comparison of deep learning and segmentation-based radiomic methods in the task of distinguishing benign and malignant breast lesions on DCE-MRI

NASA Astrophysics Data System (ADS)

Antropova, Natasha; Huynh, Benjamin; Giger, Maryellen

2017-03-01

Intuitive segmentation-based CADx/radiomic features, calculated from the lesion segmentations of dynamic contrast-enhanced magnetic resonance images (DCE-MRIs) have been utilized in the task of distinguishing between malignant and benign lesions. Additionally, transfer learning with pre-trained deep convolutional neural networks (CNNs) allows for an alternative method of radiomics extraction, where the features are derived directly from the image data. However, the comparison of computer-extracted segmentation-based and CNN features in MRI breast lesion characterization has not yet been conducted. In our study, we used a DCE-MRI database of 640 breast cases - 191 benign and 449 malignant. Thirty-eight segmentation-based features were extracted automatically using our quantitative radiomics workstation. Also, 2D ROIs were selected around each lesion on the DCE-MRIs and directly input into a pre-trained CNN AlexNet, yielding CNN features. Each method was investigated separately and in combination in terms of performance in the task of distinguishing between benign and malignant lesions. Area under the ROC curve (AUC) served as the figure of merit. Both methods yielded promising classification performance with round-robin cross-validated AUC values of 0.88 (se =0.01) and 0.76 (se=0.02) for segmentationbased and deep learning methods, respectively. Combination of the two methods enhanced the performance in malignancy assessment resulting in an AUC value of 0.91 (se=0.01), a statistically significant improvement over the performance of the CNN method alone.

The comparative performance of PMI estimation in skeletal remains by three methods (C-14, luminol test and OHI): analysis of 20 cases.

PubMed

Cappella, Annalisa; Gibelli, Daniele; Muccino, Enrico; Scarpulla, Valentina; Cerutti, Elisa; Caruso, Valentina; Sguazza, Emanuela; Mazzarelli, Debora; Cattaneo, Cristina

2015-01-27

When estimating post-mortem interval (PMI) in forensic anthropology, the only method able to give an unambiguous result is the analysis of C-14, although the procedure is expensive. Other methods, such as luminol tests and histological analysis, can be performed as preliminary investigations and may allow the operators to gain a preliminary indication concerning PMI, but they lack scientific verification, although luminol testing has been somewhat more accredited in the past few years. Such methods in fact may provide some help as they are inexpensive and can give a fast response, especially in the phase of preliminary investigations. In this study, 20 court cases of human skeletonized remains were dated by the C-14 method. For two cases, results were chronologically set after the 1950s; for one case, the analysis was not possible technically. The remaining 17 cases showed an archaeological or historical collocation. The same bone samples were also screened with histological examination and with the luminol test. Results showed that only four cases gave a positivity to luminol and a high Oxford Histology Index (OHI) score at the same time: among these, two cases were dated as recent by the radiocarbon analysis. Thus, only two false-positive results were given by the combination of these methods and no false negatives. Thus, the combination of two qualitative methods (luminol test and microscopic analysis) may represent a promising solution to cases where many fragments need to be quickly tested.

A Novel Color Fluorescence Navigation System for Intraoperative Transcutaneous Lymphatic Mapping and Resection of Sentinel Lymph Nodes in Breast Cancer: Comparison with the Combination of Gamma Probe Scanning and Visible Dye Methods.

PubMed

Hokimoto, Norihiro; Sugimoto, Takeki; Namikawa, Tsutomu; Funakoshi, Taku; Oki, Toyokazu; Ogawa, Maho; Fukuhara, Hideo; Inoue, Keiji; Sato, Takayuki; Hanazaki, Kazuhiro

2018-01-01

This study evaluated the clinical efficacy of a novel imaging system (HyperEye Medical System [HEMS]; Mizuho Corp., Tokyo, Japan) that uses the near-infrared (NIR) fluorescence of indocyanine green to analyze sentinel lymph node (SLN) biopsies for the staging of breast cancer. This study enrolled 91 patients with histologically confirmed breast cancer that was clinically node negative with a tumor size <3 cm. We compared SLN identification rates between HEMS and conventional methods (gamma probe scanning using a colloidal radioisotope [RI] and a blue dye method) by analyzing the relationships of lymphatic to axillary lesions and SLNs. The identification rate of SLNs was 100% using HEMS, 97.8% using the RI method, and 95.6% using the blue dye method. Two types of lymphatic pathway (LP) were detected in 39 patients (42.9%) and also clearly identified using HEMS-captured color and NIR fluorescence. The incidence of two or more SLNs was significantly higher in patients with a two-route LP to the axilla group than in those with only one route (p < 0.001; 43.6 vs. 9.6%). The HEMS NIR fluorescence color imaging method is a promising potential modality for higher-level identification of SLNs than a standard combination of the RI and blue dye methods. © 2017 S. Karger AG, Basel.

Effect of ultraviolet and far infrared radiation on microbial decontamination and quality of cumin seeds.

PubMed

Erdoğdu, S Belgin; Ekiz, H İbrahim

2011-01-01

Cumin seeds might be exposed to a high level of natural bacterial contamination, and this could potentially create a public health risk besides leading to problems in exportation. Ultraviolet (UVC) and far infrared (FIR) radiation has low penetration power, and due to that, there might be no detrimental defects to the products during a possible decontamination process. Therefore, the objective of this study was to determine the effect of UVC and FIR treatment on microbial decontamination and quality of cumin seeds. For this purpose, FIR treatment at different exposure times and temperatures were applied followed by constant UVC treatment with an intensity of 10.5 mW/cm² for 2 h. Total mesophilic aerobic bacteria of the cumin seeds were decreased to the target level of 10⁴ CFU/g after 1.57, 2.8, and 4.8 min FIR treatment at 300, 250, and 200 °C, respectively, following a 2 h UVC treatment. Under the given conditions, a complete elimination for total yeast and molds were obtained while there were no significant changes in volatile oil content and color of the cumin seeds. Consequently, combined UVC and FIR treatment was determined to be a promising method for decontamination of the cumin seeds. This research attempts to apply UVC and far infrared (FIR) radiation for pasteurization of cumin seeds. The data suggested that combined UVC and FIR radiation treatments can become a promising new method for pasteurization of cumin seeds without causing any detrimental defect to the quality parameters. The results of this industry partnered (Kadioglu Baharat, Mersin, Turkey--http://www.kadioglubaharat.com) study were already applied in industrial scale production lines. © 2011 Institute of Food Technologists®

Diving deeper into Zebrafish development of social behavior: analyzing high resolution data.

PubMed

Buske, Christine; Gerlai, Robert

2014-08-30

Vertebrate model organisms have been utilized in high throughput screening but only with substantial cost and human capital investment. The zebrafish is a vertebrate model species that is a promising and cost effective candidate for efficient high throughput screening. Larval zebrafish have already been successfully employed in this regard (Lessman, 2011), but adult zebrafish also show great promise. High throughput screening requires the use of a large number of subjects and collection of substantial amount of data. Collection of data is only one of the demanding aspects of screening. However, in most screening approaches that involve behavioral data the main bottleneck that slows throughput is the time consuming aspect of analysis of the collected data. Some automated analytical tools do exist, but often they only work for one subject at a time, eliminating the possibility of fully utilizing zebrafish as a screening tool. This is a particularly important limitation for such complex phenotypes as social behavior. Testing multiple fish at a time can reveal complex social interactions but it may also allow the identification of outliers from a group of mutagenized or pharmacologically treated fish. Here, we describe a novel method using a custom software tool developed within our laboratory, which enables tracking multiple fish, in combination with a sophisticated analytical approach for summarizing and analyzing high resolution behavioral data. This paper focuses on the latter, the analytic tool, which we have developed using the R programming language and environment for statistical computing. We argue that combining sophisticated data collection methods with appropriate analytical tools will propel zebrafish into the future of neurobehavioral genetic research. Copyright © 2014. Published by Elsevier B.V.

Penetrating the Blood-Brain Barrier: Promise of Novel Nanoplatforms and Delivery Vehicles.

PubMed

Ali, Iqbal Unnisa; Chen, Xiaoyuan

2015-10-27

Multifunctional nanoplatforms combining versatile therapeutic modalities with a variety of imaging options have the potential to diagnose, monitor, and treat brain diseases. The promise of nanotechnology can only be realized by the simultaneous development of innovative brain-targeting delivery vehicles capable of penetrating the blood-brain barrier without compromising its structural integrity.

Automatic identification of alpine mass movements based on seismic and infrasound signals

NASA Astrophysics Data System (ADS)

Schimmel, Andreas; Hübl, Johannes

2017-04-01

The automatic detection and identification of alpine mass movements like debris flows, debris floods or landslides gets increasing importance for mitigation measures in the densely populated and intensively used alpine regions. Since this mass movement processes emits characteristically seismic and acoustic waves in the low frequency range this events can be detected and identified based on this signals. So already several approaches for detection and warning systems based on seismic or infrasound signals has been developed. But a combination of both methods, which can increase detection probability and reduce false alarms is currently used very rarely and can serve as a promising method for developing an automatic detection and identification system. So this work presents an approach for a detection and identification system based on a combination of seismic and infrasound sensors, which can detect sediment related mass movements from a remote location unaffected by the process. The system is based on one infrasound sensor and one geophone which are placed co-located and a microcontroller where a specially designed detection algorithm is executed which can detect mass movements in real time directly at the sensor site. Further this work tries to get out more information from the seismic and infrasound spectrum produced by different sediment related mass movements to identify the process type and estimate the magnitude of the event. The system is currently installed and tested on five test sites in Austria, two in Italy and one in Switzerland as well as one in Germany. This high number of test sites is used to get a large database of very different events which will be the basis for a new identification method for alpine mass movements. These tests shows promising results and so this system provides an easy to install and inexpensive approach for a detection and warning system.

New Data Pre-processing on Assessing of Obstructive Sleep Apnea Syndrome: Line Based Normalization Method (LBNM)

NASA Astrophysics Data System (ADS)

Akdemir, Bayram; Güneş, Salih; Yosunkaya, Şebnem

Sleep disorders are a very common unawareness illness among public. Obstructive Sleep Apnea Syndrome (OSAS) is characterized with decreased oxygen saturation level and repetitive upper respiratory tract obstruction episodes during full night sleep. In the present study, we have proposed a novel data normalization method called Line Based Normalization Method (LBNM) to evaluate OSAS using real data set obtained from Polysomnography device as a diagnostic tool in patients and clinically suspected of suffering OSAS. Here, we have combined the LBNM and classification methods comprising C4.5 decision tree classifier and Artificial Neural Network (ANN) to diagnose the OSAS. Firstly, each clinical feature in OSAS dataset is scaled by LBNM method in the range of [0,1]. Secondly, normalized OSAS dataset is classified using different classifier algorithms including C4.5 decision tree classifier and ANN, respectively. The proposed normalization method was compared with min-max normalization, z-score normalization, and decimal scaling methods existing in literature on the diagnosis of OSAS. LBNM has produced very promising results on the assessing of OSAS. Also, this method could be applied to other biomedical datasets.

Prospects for Irradiation in Cellulosic Ethanol Production

PubMed Central

Saini, Anita; Aggarwal, Neeraj K.; Sharma, Anuja; Yadav, Anita

2015-01-01

Second generation bioethanol production technology relies on lignocellulosic biomass composed of hemicelluloses, celluloses, and lignin components. Cellulose and hemicellulose are sources of fermentable sugars. But the structural characteristics of lignocelluloses pose hindrance to the conversion of these sugar polysaccharides into ethanol. The process of ethanol production, therefore, involves an expensive and energy intensive step of pretreatment, which reduces the recalcitrance of lignocellulose and makes feedstock more susceptible to saccharification. Various physical, chemical, biological, or combined methods are employed to pretreat lignocelluloses. Irradiation is one of the common and promising physical methods of pretreatment, which involves ultrasonic waves, microwaves, γ-rays, and electron beam. Irradiation is also known to enhance the effect of saccharification. This review explains the role of different radiations in the production of cellulosic ethanol. PMID:26839707

Low-temperature roll-to-roll coating procedure of dye-sensitized solar cell photoelectrodes on flexible polymer-based substrates

NASA Astrophysics Data System (ADS)

Tinguely, Jean-Claude; Solarska, Renata; Braun, Artur; Graule, Thomas

2011-04-01

A new approach for the large-scale production of flexible photoelectrodes for dye-sensitized solar cells (DSSCs) is presented by roll-to-roll coating of a titanium dioxide nanodispersion containing the block copolymer 'Pluronic®' (PEOx-PPOy-PEOx, PEO: poly(ethylene oxide), PPO: poly(propylene oxide)). Functional DSSCs were assembled and the different coating procedures compared with respect to their solar power conversion efficiency. It is shown that the binder 'Pluronic' can be removed at processing temperatures as low as 140 °C, thus aiding achievement of sufficient adhesion to the ITO-PET support, higher porosity of the TiO2 layer and decreased crack appearance. Further optimization of this method is particularly promising when combined with other known low-temperature methods.

Photodynamic Therapy for Gynecological Diseases and Breast Cancer

PubMed Central

Shishkova, Natashis; Kuznetsova, Olga; Berezov, Temirbolat

2012-01-01

Photodynamic therapy (PDT) is a minimally invasive and promising new method in cancer treatment. Cytotoxic reactive oxygen species (ROS) are generated by the tissue-localized non-toxic sensitizer upon illumination and in the presence of oxygen. Thus, selective destruction of a targeted tumor may be achieved. Compared with traditional cancer treatment, PDI has advantages including higher selectivity and lower rate of toxicity. The high degree of selectivity of the proposed method was applied to cancer diagnosis using fluorescence. This article reviews previous studies done on PDT treatment and photodetection of cervical intraepithelial neoplasia, vulvar intraepithelial neoplasia, ovarian and breast cancer, and PDT application in treating non-cancer lesions. The article also highlights the clinical responses to PDT, and discusses the possibility of enhancing treatment efficacy by combination with immunotherapy and targeted therapy. PMID:23691448

Harnessing Diversity in Wheat to Enhance Grain Yield, Climate Resilience, Disease and Insect Pest Resistance and Nutrition Through Conventional and Modern Breeding Approaches

PubMed Central

Mondal, Suchismita; Rutkoski, Jessica E.; Velu, Govindan; Singh, Pawan K.; Crespo-Herrera, Leonardo A.; Guzmán, Carlos; Bhavani, Sridhar; Lan, Caixia; He, Xinyao; Singh, Ravi P.

2016-01-01

Current trends in population growth and consumption patterns continue to increase the demand for wheat, a key cereal for global food security. Further, multiple abiotic challenges due to climate change and evolving pathogen and pests pose a major concern for increasing wheat production globally. Triticeae species comprising of primary, secondary, and tertiary gene pools represent a rich source of genetic diversity in wheat. The conventional breeding strategies of direct hybridization, backcrossing and selection have successfully introgressed a number of desirable traits associated with grain yield, adaptation to abiotic stresses, disease resistance, and bio-fortification of wheat varieties. However, it is time consuming to incorporate genes conferring tolerance/resistance to multiple stresses in a single wheat variety by conventional approaches due to limitations in screening methods and the lower probabilities of combining desirable alleles. Efforts on developing innovative breeding strategies, novel tools and utilizing genetic diversity for new genes/alleles are essential to improve productivity, reduce vulnerability to diseases and pests and enhance nutritional quality. New technologies of high-throughput phenotyping, genome sequencing and genomic selection are promising approaches to maximize progeny screening and selection to accelerate the genetic gains in breeding more productive varieties. Use of cisgenic techniques to transfer beneficial alleles and their combinations within related species also offer great promise especially to achieve durable rust resistance. PMID:27458472

Swept-frequency feedback interferometry using terahertz frequency QCLs: a method for imaging and materials analysis.

PubMed

Rakić, Aleksandar D; Taimre, Thomas; Bertling, Karl; Lim, Yah Leng; Dean, Paul; Indjin, Dragan; Ikonić, Zoran; Harrison, Paul; Valavanis, Alexander; Khanna, Suraj P; Lachab, Mohammad; Wilson, Stephen J; Linfield, Edmund H; Davies, A Giles

2013-09-23

The terahertz (THz) frequency quantum cascade laser (QCL) is a compact source of high-power radiation with a narrow intrinsic linewidth. As such, THz QCLs are extremely promising sources for applications including high-resolution spectroscopy, heterodyne detection, and coherent imaging. We exploit the remarkable phase-stability of THz QCLs to create a coherent swept-frequency delayed self-homodyning method for both imaging and materials analysis, using laser feedback interferometry. Using our scheme we obtain amplitude-like and phase-like images with minimal signal processing. We determine the physical relationship between the operating parameters of the laser under feedback and the complex refractive index of the target and demonstrate that this coherent detection method enables extraction of complex refractive indices with high accuracy. This establishes an ultimately compact and easy-to-implement THz imaging and materials analysis system, in which the local oscillator, mixer, and detector are all combined into a single laser.

Short-range density functional correlation within the restricted active space CI method

NASA Astrophysics Data System (ADS)

Casanova, David

2018-03-01

In the present work, I introduce a hybrid wave function-density functional theory electronic structure method based on the range separation of the electron-electron Coulomb operator in order to recover dynamic electron correlations missed in the restricted active space configuration interaction (RASCI) methodology. The working equations and the computational algorithm for the implementation of the new approach, i.e., RAS-srDFT, are presented, and the method is tested in the calculation of excitation energies of organic molecules. The good performance of the RASCI wave function in combination with different short-range exchange-correlation functionals in the computation of relative energies represents a quantitative improvement with respect to the RASCI results and paves the path for the development of RAS-srDFT as a promising scheme in the computation of the ground and excited states where nondynamic and dynamic electron correlations are important.

Robust bidirectional links for photonic quantum networks

PubMed Central

Xu, Jin-Shi; Yung, Man-Hong; Xu, Xiao-Ye; Tang, Jian-Shun; Li, Chuan-Feng; Guo, Guang-Can

2016-01-01

Optical fibers are widely used as one of the main tools for transmitting not only classical but also quantum information. We propose and report an experimental realization of a promising method for creating robust bidirectional quantum communication links through paired optical polarization-maintaining fibers. Many limitations of existing protocols can be avoided with the proposed method. In particular, the path and polarization degrees of freedom are combined to deterministically create a photonic decoherence-free subspace without the need for any ancillary photon. This method is input state–independent, robust against dephasing noise, postselection-free, and applicable bidirectionally. To rigorously quantify the amount of quantum information transferred, the optical fibers are analyzed with the tools developed in quantum communication theory. These results not only suggest a practical means for protecting quantum information sent through optical quantum networks but also potentially provide a new physical platform for enriching the structure of the quantum communication theory. PMID:26824069

Detection of Gene Rearrangements in Circulating Tumor Cells: Examples of ALK-, ROS1-, RET-Rearrangements in Non-Small-Cell Lung Cancer and ERG-Rearrangements in Prostate Cancer.

PubMed

Catelain, Cyril; Pailler, Emma; Oulhen, Marianne; Faugeroux, Vincent; Pommier, Anne-Laure; Farace, Françoise

2017-01-01

Circulating tumor cells (CTCs) hold promise as biomarkers to aid in patient treatment stratification and disease monitoring. Because the number of cells is a critical parameter for exploiting CTCs for predictive biomarker's detection, we developed a FISH (fluorescent in situ hybridization) method for CTCs enriched on filters (filter-adapted FISH [FA-FISH]) that was optimized for high cell recovery. To increase the feasibility and reliability of the analyses, we combined fluorescent staining and FA-FISH and developed a semi-automated microscopy method for optimal FISH signal identification in filtration-enriched CTCs . Here we present these methods and their use for the detection and characterization of ALK-, ROS1-, RET-rearrangement in CTCs from non-small-cell lung cancer and ERG-rearrangements in CTCs from prostate cancer patients.

A new technique for simulating composite material

NASA Technical Reports Server (NTRS)

Volakis, John L.

1991-01-01

This project dealt with the development on new methodologies and algorithms for the multi-spectrum electromagnetic characterization of large scale nonmetallic airborne vehicles and structures. A robust, low memory, and accurate methodology was developed which is particularly suited for modern machine architectures. This is a hybrid finite element method that combines two well known numerical solution approaches. That of the finite element method for modeling volumes and the boundary integral method which yields exact boundary conditions for terminating the finite element mesh. In addition, a variety of high frequency results were generated (such as diffraction coefficients for impedance surfaces and material layers) and a class of boundary conditions were developed which hold promise for more efficient simulations. During the course of this project, nearly 25 detailed research reports were generated along with an equal number of journal papers. The reports, papers, and journal articles are listed in the appendices along with their abstracts.

Pretreatment of agricultural biomass for anaerobic digestion: Current state and challenges.

PubMed

Paudel, Shukra Raj; Banjara, Sushant Prasad; Choi, Oh Kyung; Park, Ki Young; Kim, Young Mo; Lee, Jae Woo

2017-12-01

The anaerobic digestion (AD) of agricultural biomass is an attractive second generation biofuel with potential environmental and economic benefits. Most agricultural biomass contains lignocellulose which requires pretreatment prior to AD. For optimization, the pretreatment methods need to be specific to the characteristics of the biomass feedstock. In this review, cereal residue, fruit and vegetable wastes, grasses and animal manure were selected as the agricultural biomass candidates, and the fundamentals and current state of various pretreatment methods used for AD of these feedstocks were investigated. Several nonconventional methods (electrical, ionic liquid-based chemicals, ruminant biological pretreatment) offer potential as targeted pretreatments of lignocellulosic biomass, but each comes with its own challenges. Pursuing an energy-intensive route, a combined bioethanol-biogas production could be a promising a second biofuel refinery option, further emphasizing the importance of pretreatment when lignocellulosic feedstock is used. Copyright © 2017 Elsevier Ltd. All rights reserved.

Petri net-based dependability modeling methodology for reconfigurable field programmable gate arrays

NASA Astrophysics Data System (ADS)

Graczyk, Rafał; Orleański, Piotr; Poźniak, Krzysztof

2015-09-01

Dependability modeling is an important issue for aerospace and space equipment designers. From system level perspective, one has to choose from multitude of possible architectures, redundancy levels, component combinations in a way to meet desired properties and dependability and finally fit within required cost and time budgets. Modeling of such systems is getting harder as its levels of complexity grow together with demand for more functional and flexible, yet more available systems that govern more and more crucial parts of our civilization's infrastructure (aerospace transport systems, telecommunications, exploration probes). In this article promising method of modeling complex systems using Petri networks is introduced in context of qualitative and quantitative dependability analysis. This method, although with some limitation and drawback offer still convenient visual formal method of describing system behavior on different levels (functional, timing, random events) and offers straight correspondence to underlying mathematical engine, perfect for simulations and engineering support.

Discrimination of inflammatory bowel disease using Raman spectroscopy and linear discriminant analysis methods

NASA Astrophysics Data System (ADS)

Ding, Hao; Cao, Ming; DuPont, Andrew W.; Scott, Larry D.; Guha, Sushovan; Singhal, Shashideep; Younes, Mamoun; Pence, Isaac; Herline, Alan; Schwartz, David; Xu, Hua; Mahadevan-Jansen, Anita; Bi, Xiaohong

2016-03-01

Inflammatory bowel disease (IBD) is an idiopathic disease that is typically characterized by chronic inflammation of the gastrointestinal tract. Recently much effort has been devoted to the development of novel diagnostic tools that can assist physicians for fast, accurate, and automated diagnosis of the disease. Previous research based on Raman spectroscopy has shown promising results in differentiating IBD patients from normal screening cases. In the current study, we examined IBD patients in vivo through a colonoscope-coupled Raman system. Optical diagnosis for IBD discrimination was conducted based on full-range spectra using multivariate statistical methods. Further, we incorporated several feature selection methods in machine learning into the classification model. The diagnostic performance for disease differentiation was significantly improved after feature selection. Our results showed that improved IBD diagnosis can be achieved using Raman spectroscopy in combination with multivariate analysis and feature selection.

Modification of chemical reactivity of enzymatic hydrolysis lignin by ultrasound treatment in dilute alkaline solutions.

PubMed

Ma, Zhuoming; Li, Shujun; Fang, Guizhen; Patil, Nikhil; Yan, Ning

2016-12-01

In this study, we have explored various ultrasound treatment conditions for structural modification of enzymatic hydrolysis lignin (EHL) for enhanced chemical reactivity. The key structural modifications were characterized by using a combination of analytical methods, including, Fourier Transform-Infrared spectroscopy (FTIR), Proton Nuclear Magnetic Resonance ( 1 H NMR), Gel permeation chromatography (GPC), X-ray photoelectron spectroscopy (XPS), and Folin-Ciocalteu (F-C) method. Chemical reactivity of the modified EHL samples was determined by both 1,1-diphenyl-2-picrylhydrazyl (DPPH) free radical scavenging activity and their reactivity towards formaldehyde. It was observed that the modified EHL had a higher phenolic hydroxyl group content, a lower molecular weight, a higher reactivity towards formaldehyde, and a greater antioxidant property. The higher reactivity demonstrated by the samples after treatment suggesting that ultrasound is a promising method for modifying enzymatic hydrolysis lignin for value-added applications. Copyright © 2016 Elsevier B.V. All rights reserved.

A detailed comparison of analysis processes for MCC-IMS data in disease classification—Automated methods can replace manual peak annotations

PubMed Central

Horsch, Salome; Kopczynski, Dominik; Kuthe, Elias; Baumbach, Jörg Ingo; Rahmann, Sven

2017-01-01

Motivation Disease classification from molecular measurements typically requires an analysis pipeline from raw noisy measurements to final classification results. Multi capillary column—ion mobility spectrometry (MCC-IMS) is a promising technology for the detection of volatile organic compounds in the air of exhaled breath. From raw measurements, the peak regions representing the compounds have to be identified, quantified, and clustered across different experiments. Currently, several steps of this analysis process require manual intervention of human experts. Our goal is to identify a fully automatic pipeline that yields competitive disease classification results compared to an established but subjective and tedious semi-manual process. Method We combine a large number of modern methods for peak detection, peak clustering, and multivariate classification into analysis pipelines for raw MCC-IMS data. We evaluate all combinations on three different real datasets in an unbiased cross-validation setting. We determine which specific algorithmic combinations lead to high AUC values in disease classifications across the different medical application scenarios. Results The best fully automated analysis process achieves even better classification results than the established manual process. The best algorithms for the three analysis steps are (i) SGLTR (Savitzky-Golay Laplace-operator filter thresholding regions) and LM (Local Maxima) for automated peak identification, (ii) EM clustering (Expectation Maximization) and DBSCAN (Density-Based Spatial Clustering of Applications with Noise) for the clustering step and (iii) RF (Random Forest) for multivariate classification. Thus, automated methods can replace the manual steps in the analysis process to enable an unbiased high throughput use of the technology. PMID:28910313

In vitro glucose measurement using tunable mid-infrared laser spectroscopy combined with fiber-optic sensor

PubMed Central

Yu, Songlin; Li, Dachao; Chong, Hao; Sun, Changyue; Yu, Haixia; Xu, Kexin

2013-01-01

Because mid-infrared (mid-IR) spectroscopy is not a promising method to noninvasively measure glucose in vivo, a method for minimally invasive high-precision glucose determination in vivo by mid-IR laser spectroscopy combined with a tunable laser source and small fiber-optic attenuated total reflection (ATR) sensor is introduced. The potential of this method was evaluated in vitro. This research presents a mid-infrared tunable laser with a broad emission spectrum band of 9.19 to 9.77μm(1024~1088 cm−1) and proposes a method to control and stabilize the laser emission wavelength and power. Moreover, several fiber-optic ATR sensors were fabricated and investigated to determine glucose in combination with the tunable laser source, and the effective sensing optical length of these sensors was determined for the first time. In addition, the sensitivity of this system was four times that of a Fourier transform infrared (FT-IR) spectrometer. The noise-equivalent concentration (NEC) of this laser measurement system was as low as 3.8 mg/dL, which is among the most precise glucose measurements using mid-infrared spectroscopy. Furthermore, a partial least-squares regression and Clarke error grid were used to quantify the predictability and evaluate the prediction accuracy of glucose concentration in the range of 5 to 500 mg/dL (physiologically relevant range: 30~400 mg/dL). The experimental results were clinically acceptable. The high sensitivity, tunable laser source, low NEC and small fiber-optic ATR sensor demonstrate an encouraging step in the work towards precisely monitoring glucose levels in vivo. PMID:24466493

Sequencing Larger Intact Proteins (30-70 kDa) with Activated Ion Electron Transfer Dissociation

NASA Astrophysics Data System (ADS)

Riley, Nicholas M.; Westphall, Michael S.; Coon, Joshua J.

2018-01-01

The analysis of intact proteins via mass spectrometry can offer several benefits to proteome characterization, although the majority of top-down experiments focus on proteoforms in a relatively low mass range (<30 kDa). Recent studies have focused on improving the analysis of larger intact proteins (up to 75 kDa), but they have also highlighted several challenges to be addressed. One major hurdle is the efficient dissociation of larger protein ions, which often to do not yield extensive fragmentation via conventional tandem MS methods. Here we describe the first application of activated ion electron transfer dissociation (AI-ETD) to proteins in the 30-70 kDa range. AI-ETD leverages infrared photo-activation concurrent to ETD reactions to improve sequence-informative product ion generation. This method generates more product ions and greater sequence coverage than conventional ETD, higher-energy collisional dissociation (HCD), and ETD combined with supplemental HCD activation (EThcD). Importantly, AI-ETD provides the most thorough protein characterization for every precursor ion charge state investigated in this study, making it suitable as a universal fragmentation method in top-down experiments. Additionally, we highlight several acquisition strategies that can benefit characterization of larger proteins with AI-ETD, including combination of spectra from multiple ETD reaction times for a given precursor ion, multiple spectral acquisitions of the same precursor ion, and combination of spectra from two different dissociation methods (e.g., AI-ETD and HCD). In all, AI-ETD shows great promise as a method for dissociating larger intact protein ions as top-down proteomics continues to advance into larger mass ranges. [Figure not available: see fulltext.

Development and Validation of an NPSS Model of a Small Turbojet Engine

NASA Astrophysics Data System (ADS)

Vannoy, Stephen Michael

Recent studies have shown that integrated gas turbine engine (GT)/solid oxide fuel cell (SOFC) systems for combined propulsion and power on aircraft offer a promising method for more efficient onboard electrical power generation. However, it appears that nobody has actually attempted to construct a hybrid GT/SOFC prototype for combined propulsion and electrical power generation. This thesis contributes to this ambition by developing an experimentally validated thermodynamic model of a small gas turbine (˜230 N thrust) platform for a bench-scale GT/SOFC system. The thermodynamic model is implemented in a NASA-developed software environment called Numerical Propulsion System Simulation (NPSS). An indoor test facility was constructed to measure the engine's performance parameters: thrust, air flow rate, fuel flow rate, engine speed (RPM), and all axial stage stagnation temperatures and pressures. The NPSS model predictions are compared to the measured performance parameters for steady state engine operation.

Determining SAFOD area microearthquake locations solely with the Pilot Hole seismic array data

NASA Astrophysics Data System (ADS)

Oye, Volker; Chavarria, J. Andres; Malin, Peter E.

2004-05-01

In August 2002, an array of 32 three-component geophones was installed in the San Andreas Fault Observatory at Depth (SAFOD) Pilot Hole (PH) at Parkfield, CA. As an independent test of surface-observation-based microearthquake locations, we have located such events using only data recorded on the PH array. We then compared these locations with locations from a combined set of PH and Parkfield High Resolution Seismic Network (HRSN) observations. We determined the uncertainties in the locations as they relate to errors in the travel time picks and the velocity model by the bootstrap method. Based on the PH and combined locations, we find that the ``C2'' cluster to the northeast of the PH has the smallest location uncertainties. Events in this cluster also have the most similar waveforms and largest magnitudes. This confirms earlier suggestions that the C2 cluster is a promising target for the SAFOD Main Hole.

A progress report on estuary modeling by the finite-element method

USGS Publications Warehouse

Gray, William G.

1978-01-01

Various schemes are investigated for finite-element modeling of two-dimensional surface-water flows. The first schemes investigated combine finite-element spatial discretization with split-step time stepping schemes that have been found useful in finite-difference computations. Because of the large number of numerical integrations performed in space and the large sparse matrices solved, these finite-element schemes were found to be economically uncompetitive with finite-difference schemes. A very promising leapfrog scheme is proposed which, when combined with a novel very fast spatial integration procedure, eliminates the need to solve any matrices at all. Additional problems attacked included proper propagation of waves and proper specification of the normal flow-boundary condition. This report indicates work in progress and does not come to a definitive conclusion as to the best approach for finite-element modeling of surface-water problems. The results presented represent findings obtained between September 1973 and July 1976. (Woodard-USGS)

Raman Spectroscopy of Optically Trapped Single Biological Micro-Particles

PubMed Central

Redding, Brandon; Schwab, Mark J.; Pan, Yong-le

2015-01-01

The combination of optical trapping with Raman spectroscopy provides a powerful method for the study, characterization, and identification of biological micro-particles. In essence, optical trapping helps to overcome the limitation imposed by the relative inefficiency of the Raman scattering process. This allows Raman spectroscopy to be applied to individual biological particles in air and in liquid, providing the potential for particle identification with high specificity, longitudinal studies of changes in particle composition, and characterization of the heterogeneity of individual particles in a population. In this review, we introduce the techniques used to integrate Raman spectroscopy with optical trapping in order to study individual biological particles in liquid and air. We then provide an overview of some of the most promising applications of this technique, highlighting the unique types of measurements enabled by the combination of Raman spectroscopy with optical trapping. Finally, we present a brief discussion of future research directions in the field. PMID:26247952

Sonochemotherapy: from bench to bedside

PubMed Central

Lammertink, Bart H. A.; Bos, Clemens; Deckers, Roel; Storm, Gert; Moonen, Chrit T. W.; Escoffre, Jean-Michel

2015-01-01

The combination of microbubbles and ultrasound has emerged as a promising method for local drug delivery. Microbubbles can be locally activated by a targeted ultrasound beam, which can result in several bio-effects. For drug delivery, microbubble-assisted ultrasound is used to increase vascular- and plasma membrane permeability for facilitating drug extravasation and the cellular uptake of drugs in the treated region, respectively. In the case of drug-loaded microbubbles, these two mechanisms can be combined with local release of the drug following destruction of the microbubble. The use of microbubble-assisted ultrasound to deliver chemotherapeutic agents is also referred to as sonochemotherapy. In this review, the basic principles of sonochemotherapy are discussed, including aspects such as the type of (drug-loaded) microbubbles used, the routes of administration used in vivo, ultrasound devices and parameters, treatment schedules and safety issues. Finally, the clinical translation of sonochemotherapy is discussed, including the first clinical study using sonochemotherapy. PMID:26217226

Virtual screening of B-Raf kinase inhibitors: A combination of pharmacophore modelling, molecular docking, 3D-QSAR model and binding free energy calculation studies.

PubMed

Zhang, Wen; Qiu, Kai-Xiong; Yu, Fang; Xie, Xiao-Guang; Zhang, Shu-Qun; Chen, Ya-Juan; Xie, Hui-Ding

2017-10-01

B-Raf kinase has been identified as an important target in recent cancer treatment. In order to discover structurally diverse and novel B-Raf inhibitors (BRIs), a virtual screening of BRIs against ZINC database was performed by using a combination of pharmacophore modelling, molecular docking, 3D-QSAR model and binding free energy (ΔG bind ) calculation studies in this work. After the virtual screening, six promising hit compounds were obtained, which were then tested for inhibitory activities of A375 cell lines. In the result, five hit compounds show good biological activities (IC 50 <50μM). The present method of virtual screening can be applied to find structurally diverse inhibitors, and the obtained five structurally diverse compounds are expected to develop novel BRIs. Copyright © 2017. Published by Elsevier Ltd.

Beyond Brainstorming: Exploring Convergence in Teams.

PubMed

Seeber, Isabella; de Vreede, Gert-Jan; Maier, Ronald; Weber, Barbara

2017-01-01

Collaborative brainstorming is often followed by a convergence activity where teams extract the most promising ideas on a useful level of detail from the brainstorming results. Contrary to the wealth of research on electronic brainstorming, there is a dearth of research on convergence. We used experimental methods for an in-depth exploration of two facilitation-based interventions in a convergence activity: attention guidance (focusing participants on procedures to execute a convergence task) and discussion encouragement (engaging participants in conversations to combine knowledge on ideas). Our findings show that both attention guidance and discussion encouragement are correlated with higher convergence quality. We argue that attention guidance's contribution is in its support of coordination, information processing, and goal specification. Similar, we argue that discussion encouragement's contribution is in its stimulation of idea clarification and idea combination. Contrary to past research, our findings further show that satisfaction was higher after convergence than after brainstorming.

Zipping, entanglement, and the elastic modulus of aligned single-walled carbon nanotube films

PubMed Central

Won, Yoonjin; Gao, Yuan; Panzer, Matthew A.; Xiang, Rong; Maruyama, Shigeo; Kenny, Thomas W.; Cai, Wei; Goodson, Kenneth E.

2013-01-01

Reliably routing heat to and from conversion materials is a daunting challenge for a variety of innovative energy technologies––from thermal solar to automotive waste heat recovery systems––whose efficiencies degrade due to massive thermomechanical stresses at interfaces. This problem may soon be addressed by adhesives based on vertically aligned carbon nanotubes, which promise the revolutionary combination of high through-plane thermal conductivity and vanishing in-plane mechanical stiffness. Here, we report the data for the in-plane modulus of aligned single-walled carbon nanotube films using a microfabricated resonator method. Molecular simulations and electron microscopy identify the nanoscale mechanisms responsible for this property. The zipping and unzipping of adjacent nanotubes and the degree of alignment and entanglement are shown to govern the spatially varying local modulus, thereby providing the route to engineered materials with outstanding combinations of mechanical and thermal properties. PMID:24309375

A variational eigenvalue solver on a photonic quantum processor

PubMed Central

Peruzzo, Alberto; McClean, Jarrod; Shadbolt, Peter; Yung, Man-Hong; Zhou, Xiao-Qi; Love, Peter J.; Aspuru-Guzik, Alán; O’Brien, Jeremy L.

2014-01-01

Quantum computers promise to efficiently solve important problems that are intractable on a conventional computer. For quantum systems, where the physical dimension grows exponentially, finding the eigenvalues of certain operators is one such intractable problem and remains a fundamental challenge. The quantum phase estimation algorithm efficiently finds the eigenvalue of a given eigenvector but requires fully coherent evolution. Here we present an alternative approach that greatly reduces the requirements for coherent evolution and combine this method with a new approach to state preparation based on ansätze and classical optimization. We implement the algorithm by combining a highly reconfigurable photonic quantum processor with a conventional computer. We experimentally demonstrate the feasibility of this approach with an example from quantum chemistry—calculating the ground-state molecular energy for He–H+. The proposed approach drastically reduces the coherence time requirements, enhancing the potential of quantum resources available today and in the near future. PMID:25055053

Beyond Brainstorming: Exploring Convergence in Teams

PubMed Central

Seeber, Isabella; de Vreede, Gert-Jan; Maier, Ronald; Weber, Barbara

2017-01-01

Abstract Collaborative brainstorming is often followed by a convergence activity where teams extract the most promising ideas on a useful level of detail from the brainstorming results. Contrary to the wealth of research on electronic brainstorming, there is a dearth of research on convergence. We used experimental methods for an in-depth exploration of two facilitation-based interventions in a convergence activity: attention guidance (focusing participants on procedures to execute a convergence task) and discussion encouragement (engaging participants in conversations to combine knowledge on ideas). Our findings show that both attention guidance and discussion encouragement are correlated with higher convergence quality. We argue that attention guidance’s contribution is in its support of coordination, information processing, and goal specification. Similar, we argue that discussion encouragement’s contribution is in its stimulation of idea clarification and idea combination. Contrary to past research, our findings further show that satisfaction was higher after convergence than after brainstorming. PMID:29399005

Preparing the MAX IV storage rings for timing-based experiments

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

Stråhlman, C., E-mail: Christian.Strahlman@maxlab.lu.se; Olsson, T., E-mail: Teresia.Olsson@maxlab.lu.se; Leemann, S. C.

2016-07-27

Time-resolved experimental techniques are increasingly abundant at storage ring facilities. Recent developments in accelerator technology and beamline instrumentation allow for simultaneous operation of high-intensity and timing-based experiments. The MAX IV facility is a state-of-the-art synchrotron light source in Lund, Sweden, that will come into operation in 2016. As many storage ring facilities are pursuing upgrade programs employing strong-focusing multibend achromats and passive harmonic cavities (HCs) in high-current operation, it is of broad interest to study the accelerator and instrumentation developments required to enable timing-based experiments at such machines. In particular, the use of hybrid filling modes combined with pulse pickingmore » by resonant excitation or pseudo single bunch has shown promising results. These methods can be combined with novel beamline instrumentation, such as choppers and instrument gating. In this paper we discuss how these techniques can be implemented and employed at MAX IV.« less

Strategies and limitations for fluorescence detection of XAFS at high flux beamlines

DOE PAGES

Heald, Steve M.

2015-02-17

The issue of detecting the XAFS signal from dilute samples is discussed in detail with the aim of making best use of high flux beamlines that provide up to 10 13 photons -1. Various detection methods are compared, including filters with slits, solid state detectors, crystal analyzers and combinations of these. These comparisons rely on simulations that use experimentally determined parameters. It is found that inelastic scattering places a fundamental limit on detection, and that it is important to take proper account of the polarization dependence of the signals. The combination of a filter–slit system with a solid state detectormore » is a promising approach. With an optimized system good performance can be obtained even if the total count rate is limited to 10 7 Hz. Detection schemes with better energy resolution can help at the largest dilutions if their collection efficiency and count rate limits can be improved.« less

Strategies and limitations for fluorescence detection of XAFS at high flux beamlines

PubMed Central

Heald, Steve M.

2015-01-01

The issue of detecting the XAFS signal from dilute samples is discussed in detail with the aim of making best use of high flux beamlines that provide up to 1013 photons s−1. Various detection methods are compared, including filters with slits, solid state detectors, crystal analyzers and combinations of these. These comparisons rely on simulations that use experimentally determined parameters. It is found that inelastic scattering places a fundamental limit on detection, and that it is important to take proper account of the polarization dependence of the signals. The combination of a filter–slit system with a solid state detector is a promising approach. With an optimized system good performance can be obtained even if the total count rate is limited to 107 Hz. Detection schemes with better energy resolution can help at the largest dilutions if their collection efficiency and count rate limits can be improved. PMID:25723945

Application of Multiple Categories of Unmanned Aircraft Systems (uas) in Different Airspaces for Bushfire Monitoring and Response

NASA Astrophysics Data System (ADS)

Homainejad, N.; Rizos, C.

2015-08-01

Demand and interest in Unmanned Aircraft Systems (UAS) for civilian applications, and advances in technology such as development of sense-and-avoid systems, will soon allow UAS to be flown alongside manned aircrafts in non-segregated airspace. An area that can benefit from the application of UAS is the bushfire services sector. Currently such services rely on watchtowers, fixed-wing manned aircrafts and satellite data for reliable information. UAS are a promising alternative to traditional methods of collecting bushfire data. There are several varieties of UAS and each category has certain limitations, hence a combination of multiple UAS with features appropriate for bushfire emergencies can be used simultaneously for collecting valuable data. This paper will describe the general UAS categories, some characteristics of Australian bushfires, and speculate on how a combination of several UAS operating in different airspaces can be of benefit for bushfire response personnel and firefighters.

A chemical family-based strategy for uncovering hidden bioactive molecules and multicomponent interactions in herbal medicines.

PubMed

Song, Hui-Peng; Wu, Si-Qi; Hao, Haiping; Chen, Jun; Lu, Jun; Xu, Xiaojun; Li, Ping; Yang, Hua

2016-03-30

Two concepts involving natural products were proposed and demonstrated in this paper. (1) Natural product libraries (e.g. herbal extract) are not perfect for bioactivity screening because of the vast complexity of compound compositions, and thus a library reconstruction procedure is necessary before screening. (2) The traditional mode of "screening single compound" could be improved to "screening single compound, drug combination and multicomponent interaction" due to the fact that herbal medicines work by integrative effects of multi-components rather than single effective constituents. Based on the two concepts, we established a novel strategy aiming to make screening easier and deeper. Using thrombin as the model enzyme, we firstly uncovered the minor lead compounds, potential drug combinations and multicomponent interactions in an herbal medicine of Dan-Qi pair, showing a significant advantage over previous methods. This strategy was expected to be a new and promising mode for investigation of herbal medicines.

Energy intensity of computer manufacturing: hybrid assessment combining process and economic input-output methods.

PubMed

Williams, Eric

2004-11-15

The total energy and fossil fuels used in producing a desktop computer with 17-in. CRT monitor are estimated at 6400 megajoules (MJ) and 260 kg, respectively. This indicates that computer manufacturing is energy intensive: the ratio of fossil fuel use to product weight is 11, an order of magnitude larger than the factor of 1-2 for many other manufactured goods. This high energy intensity of manufacturing, combined with rapid turnover in computers, results in an annual life cycle energy burden that is surprisingly high: about 2600 MJ per year, 1.3 times that of a refrigerator. In contrast with many home appliances, life cycle energy use of a computer is dominated by production (81%) as opposed to operation (19%). Extension of usable lifespan (e.g. by reselling or upgrading) is thus a promising approach to mitigating energy impacts as well as other environmental burdens associated with manufacturing and disposal.

Removal of oxalic acid, oxamic acid and aniline by a combined photolysis and ozonation process.

PubMed

Orge, C A; Faria, J L; Pereira, M F R

2015-01-01

Aniline (ANL), an aromatic amine, oxalic acid (OXA) and oxamic acid (OMA), short-chain carboxylic acids, were chosen as model organic pollutants for testing the combined effect of neat photolysis and ozonation in the treatment of aqueous effluents. In order to better understand the results, single ozonation and neat photolysis were also carried out. OXA has a high refractory character relatively to single ozonation and neat photolysis only accounted for 26% conversion of OXA after 2 h of reaction. On the other hand, OXA complete degradation was observed in less than an hour when ozone and light were used simultaneously. Despite OMA, a compound never studied before by a combined ozonation and photolysis treatment, being highly refractory to oxidation, more than 50% was removed by photo-ozonation after 3 h of reaction. In the case of ANL, both single ozonation and photo-ozonation resulted in 100% removal in a short reaction period due to the high reactivity of ozone to attack this type of molecules; however, only the combined method leads to efficient mineralization (89%) after 3 h of reaction. A significant synergetic effect was observed in the degradation of the selected contaminants by the simultaneous use of ozone and light, since the mineralization rate of combined method is higher than the sum of the mineralization rates of the individual treatments. The promising results observed in the degradation of the selected contaminants are paving the way to the application of photo-ozonation in the treatment of wastewater containing this type of pollutants.

Radiation and Anti-Cancer Vaccines: A Winning Combination.

PubMed

Cadena, Alexandra; Cushman, Taylor R; Anderson, Clark; Barsoumian, Hampartsoum B; Welsh, James W; Cortez, Maria Angelica

2018-01-30

The emerging combination of radiation therapy with vaccines is a promising new treatment plan in the fight against cancer. While many cancer vaccines such as MUC1, p53 CpG oligodeoxynucleotide, and SOX2 may be great candidates for antitumor vaccination, there still remain many investigations to be done into possible vaccine combinations. One fruitful partnership that has emerged are anti-tumor vaccines in combination with radiation. Radiation therapy was previously thought to be only a tool for directly or indirectly damaging DNA and therefore causing cancer cell death. Now, with much preclinical and clinical data, radiation has taken on the role of an in situ vaccine. With both cancer vaccines and radiation at our disposal, more and more studies are looking to combining vaccine types such as toll-like receptors, viral components, dendritic-cell-based, and subunit vaccines with radiation. While the outcomes of these combinatory efforts are promising, there is still much work to be covered. This review sheds light on the current state of affairs in cancer vaccines and how radiation will bring its story into the future.

Quality Assessment of Kumu Injection, a Traditional Chinese Medicine Preparation, Using HPLC Combined with Chemometric Methods and Qualitative and Quantitative Analysis of Multiple Alkaloids by Single Marker.

PubMed

Wang, Ning; Li, Zhi-Yong; Zheng, Xiao-Li; Li, Qiao; Yang, Xin; Xu, Hui

2018-04-09

Kumu injection (KMI) is a common-used traditional Chinese medicine (TCM) preparation made from Picrasma quassioides (D. Don) Benn. rich in alkaloids. An innovative technique for quality assessment of KMI was developed using high performance liquid chromatography (HPLC) combined with chemometric methods and qualitative and quantitative analysis of multi-components by single marker (QAMS). Nigakinone (PQ-6, 5-hydroxy-4-methoxycanthin-6-one), one of the most abundant alkaloids responsible for the major pharmacological activities of Kumu, was used as a reference substance. Six alkaloids in KMI were quantified, including 6-hydroxy- β -carboline-1-carboxylic acid (PQ-1), 4,5-dimethoxycanthin-6-one (PQ-2), β -carboline-1-carboxylic acid (PQ-3), β -carboline-1-propanoic acid (PQ-4), 3-methylcanthin-5,6-dione (PQ-5), and PQ-6. Based on the outcomes of twenty batches of KMI samples, the contents of six alkaloids were used for further chemometric analysis. By hierarchical cluster analysis (HCA), radar plots, and principal component analysis (PCA), all the KMI samples could be categorized into three groups, which were closely related to production date and indicated the crucial influence of herbal raw material on end products of KMI. QAMS combined with chemometric analysis could accurately measure and clearly distinguish the different quality samples of KMI. Hence, QAMS is a feasible and promising method for the quality control of KMI.

Rain radar measurement error estimation using data assimilation in an advection-based nowcasting system

NASA Astrophysics Data System (ADS)

Merker, Claire; Ament, Felix; Clemens, Marco

2017-04-01

The quantification of measurement uncertainty for rain radar data remains challenging. Radar reflectivity measurements are affected, amongst other things, by calibration errors, noise, blocking and clutter, and attenuation. Their combined impact on measurement accuracy is difficult to quantify due to incomplete process understanding and complex interdependencies. An improved quality assessment of rain radar measurements is of interest for applications both in meteorology and hydrology, for example for precipitation ensemble generation, rainfall runoff simulations, or in data assimilation for numerical weather prediction. Especially a detailed description of the spatial and temporal structure of errors is beneficial in order to make best use of the areal precipitation information provided by radars. Radar precipitation ensembles are one promising approach to represent spatially variable radar measurement errors. We present a method combining ensemble radar precipitation nowcasting with data assimilation to estimate radar measurement uncertainty at each pixel. This combination of ensemble forecast and observation yields a consistent spatial and temporal evolution of the radar error field. We use an advection-based nowcasting method to generate an ensemble reflectivity forecast from initial data of a rain radar network. Subsequently, reflectivity data from single radars is assimilated into the forecast using the Local Ensemble Transform Kalman Filter. The spread of the resulting analysis ensemble provides a flow-dependent, spatially and temporally correlated reflectivity error estimate at each pixel. We will present first case studies that illustrate the method using data from a high-resolution X-band radar network.

On-line crack prognosis in attachment lug using Lamb wave-deterministic resampling particle filter-based method

NASA Astrophysics Data System (ADS)

Yuan, Shenfang; Chen, Jian; Yang, Weibo; Qiu, Lei

2017-08-01

Fatigue crack growth prognosis is important for prolonging service time, improving safety, and reducing maintenance cost in many safety-critical systems, such as in aircraft, wind turbines, bridges, and nuclear plants. Combining fatigue crack growth models with the particle filter (PF) method has proved promising to deal with the uncertainties during fatigue crack growth and reach a more accurate prognosis. However, research on prognosis methods integrating on-line crack monitoring with the PF method is still lacking, as well as experimental verifications. Besides, the PF methods adopted so far are almost all sequential importance resampling-based PFs, which usually encounter sample impoverishment problems, and hence performs poorly. To solve these problems, in this paper, the piezoelectric transducers (PZTs)-based active Lamb wave method is adopted for on-line crack monitoring. The deterministic resampling PF (DRPF) is proposed to be used in fatigue crack growth prognosis, which can overcome the sample impoverishment problem. The proposed method is verified through fatigue tests of attachment lugs, which are a kind of important joint component in aerospace systems.

Comparing electrochemical performance of transition metal silicate cathodes and chevrel phase Mo6S8 in the analogous rechargeable Mg-ion battery system

NASA Astrophysics Data System (ADS)

Chen, Xinzhi; Bleken, Francesca L.; Løvvik, Ole Martin; Vullum-Bruer, Fride

2016-07-01

Polyanion based silicate materials, MgMSiO4 (M = Fe, Mn, Co), previously reported to be promising cathode materials for Mg-ion batteries, have been re-examined. Both the sol-gel and molten salt methods are employed to synthesize MgMSiO4 composites. Mo6S8 is synthesized by a molten salt method combined with Cu leaching and investigated in the equivalent electrochemical system as a bench mark. Electrochemical measurements for Mo6S8 performed using the 2nd generation electrolyte show similar results to those reported in literature. Electrochemical performance of the silicate materials on the other hand, do not show the promising results previously reported. A thorough study of these published results are presented here, and compared to the current experimental data on the same material system. It appears that there are certain inconsistencies in the published results which cannot be explained. To further corroborate the present experimental results, atomic-scale calculations from first principles are performed, demonstrating that diffusion barriers are very high for Mg diffusion in MgMSiO4. In conclusion, MgMSiO4 (M = Fe, Mn, Co) olivine materials do not seem to be such good candidates for cathode materials in Mg-ion batteries as previously reported.

Simple and cost-effective method of highly conductive and elastic carbon nanotube/polydimethylsiloxane composite for wearable electronics.

PubMed

Kim, Jeong Hun; Hwang, Ji-Young; Hwang, Ha Ryeon; Kim, Han Seop; Lee, Joong Hoon; Seo, Jae-Won; Shin, Ueon Sang; Lee, Sang-Hoon

2018-01-22

The development of various flexible and stretchable materials has attracted interest for promising applications in biomedical engineering and electronics industries. This interest in wearable electronics, stretchable circuits, and flexible displays has created a demand for stable, easily manufactured, and cheap materials. However, the construction of flexible and elastic electronics, on which commercial electronic components can be mounted through simple and cost-effective processing, remains challenging. We have developed a nanocomposite of carbon nanotubes (CNTs) and polydimethylsiloxane (PDMS) elastomer. To achieve uniform distributions of CNTs within the polymer, an optimized dispersion process was developed using isopropyl alcohol (IPA) and methyl-terminated PDMS in combination with ultrasonication. After vaporizing the IPA, various shapes and sizes can be easily created with the nanocomposite, depending on the mold. The material provides high flexibility, elasticity, and electrical conductivity without requiring a sandwich structure. It is also biocompatible and mechanically stable, as demonstrated by cytotoxicity assays and cyclic strain tests (over 10,000 times). We demonstrate the potential for the healthcare field through strain sensor, flexible electric circuits, and biopotential measurements such as EEG, ECG, and EMG. This simple and cost-effective fabrication method for CNT/PDMS composites provides a promising process and material for various applications of wearable electronics.

Differences in the Policies, Programs, and Practices (PPPs) and Combination of PPPs across Turnaround, Moderately Improving, and Not Improving Schools

ERIC Educational Resources Information Center

Herman, Rebecca; Huberman, Mette

2012-01-01

The TALPS study aims to build on the existing research base to develop promising methodologies to identify chronically low-performing and turnaround schools, as well as to identify promising strategies for turning around chronically low-performing schools. By looking specifically at schools identified as turnaround, in comparison to nonturnaround…

Deep-learning networks and the functional architecture of executive control.

PubMed

Cooper, Richard P

2017-01-01

Lake et al. underrate both the promise and the limitations of contemporary deep learning techniques. The promise lies in combining those techniques with broad multisensory training as experienced by infants and children. The limitations lie in the need for such systems to possess functional subsystems that generate, monitor, and switch goals and strategies in the absence of human intervention.

Quantitative lung perfusion evaluation using Fourier decomposition perfusion MRI.

PubMed

Kjørstad, Åsmund; Corteville, Dominique M R; Fischer, Andre; Henzler, Thomas; Schmid-Bindert, Gerald; Zöllner, Frank G; Schad, Lothar R

2014-08-01

To quantitatively evaluate lung perfusion using Fourier decomposition perfusion MRI. The Fourier decomposition (FD) method is a noninvasive method for assessing ventilation- and perfusion-related information in the lungs, where the perfusion maps in particular have shown promise for clinical use. However, the perfusion maps are nonquantitative and dimensionless, making follow-ups and direct comparisons between patients difficult. We present an approach to obtain physically meaningful and quantifiable perfusion maps using the FD method. The standard FD perfusion images are quantified by comparing the partially blood-filled pixels in the lung parenchyma with the fully blood-filled pixels in the aorta. The percentage of blood in a pixel is then combined with the temporal information, yielding quantitative blood flow values. The values of 10 healthy volunteers are compared with SEEPAGE measurements which have shown high consistency with dynamic contrast enhanced-MRI. All pulmonary blood flow (PBF) values are within the expected range. The two methods are in good agreement (mean difference = 0.2 mL/min/100 mL, mean absolute difference = 11 mL/min/100 mL, mean PBF-FD = 150 mL/min/100 mL, mean PBF-SEEPAGE = 151 mL/min/100 mL). The Bland-Altman plot shows a good spread of values, indicating no systematic bias between the methods. Quantitative lung perfusion can be obtained using the Fourier Decomposition method combined with a small amount of postprocessing. Copyright © 2013 Wiley Periodicals, Inc.

Nonintrusive multibiometrics on a mobile device: a comparison of fusion techniques

NASA Astrophysics Data System (ADS)

Allano, Lorene; Morris, Andrew C.; Sellahewa, Harin; Garcia-Salicetti, Sonia; Koreman, Jacques; Jassim, Sabah; Ly-Van, Bao; Wu, Dalei; Dorizzi, Bernadette

2006-04-01

In this article we test a number of score fusion methods for the purpose of multimodal biometric authentication. These tests were made for the SecurePhone project, whose aim is to develop a prototype mobile communication system enabling biometrically authenticated users to deal legally binding m-contracts during a mobile phone call on a PDA. The three biometrics of voice, face and signature were selected because they are all traditional non-intrusive and easy to use means of authentication which can readily be captured on a PDA. By combining multiple biometrics of relatively low security it may be possible to obtain a combined level of security which is at least as high as that provided by a PIN or handwritten signature, traditionally used for user authentication. As the relative success of different fusion methods depends on the database used and tests made, the database we used was recorded on a suitable PDA (the Qtek2020) and the test protocol was designed to reflect the intended application scenario, which is expected to use short text prompts. Not all of the fusion methods tested are original. They were selected for their suitability for implementation within the constraints imposed by the application. All of the methods tested are based on fusion of the match scores output by each modality. Though computationally simple, the methods tested have shown very promising results. All of the 4 fusion methods tested obtain a significant performance increase.

Combining XCO2 Measurements Derived from SCIAMACHY and GOSAT for Potentially Generating Global CO2 Maps with High Spatiotemporal Resolution

PubMed Central

Wang, Tianxing; Shi, Jiancheng; Jing, Yingying; Zhao, Tianjie; Ji, Dabin; Xiong, Chuan

2014-01-01

Global warming induced by atmospheric CO2 has attracted increasing attention of researchers all over the world. Although space-based technology provides the ability to map atmospheric CO2 globally, the number of valid CO2 measurements is generally limited for certain instruments owing to the presence of clouds, which in turn constrain the studies of global CO2 sources and sinks. Thus, it is a potentially promising work to combine the currently available CO2 measurements. In this study, a strategy for fusing SCIAMACHY and GOSAT CO2 measurements is proposed by fully considering the CO2 global bias, averaging kernel, and spatiotemporal variations as well as the CO2 retrieval errors. Based on this method, a global CO2 map with certain UTC time can also be generated by employing the pattern of the CO2 daily cycle reflected by Carbon Tracker (CT) data. The results reveal that relative to GOSAT, the global spatial coverage of the combined CO2 map increased by 41.3% and 47.7% on a daily and monthly scale, respectively, and even higher when compared with that relative to SCIAMACHY. The findings in this paper prove the effectiveness of the combination method in supporting the generation of global full-coverage XCO2 maps with higher temporal and spatial sampling by jointly using these two space-based XCO2 datasets. PMID:25119468

Phonological outcome of laryngeal framework surgery by different anesthesia protocols: a single-surgeon experience.

PubMed

Kanazawa, Takeharu; Watanabe, Yusuke; Komazawa, Daigo; Indo, Kanako; Misawa, Kiyoshi; Nagatomo, Takafumi; Shimada, Mari; Iino, Yukiko; Ichimura, Keiichi

2014-02-01

Similar to combined arytenoid adduction and medialization laryngoplasty (i.e. combined surgery) under local anesthesia, general anesthesia by intubation or by the laryngeal mask airway (LMA) method significantly improves phonological outcome. Thus, laryngeal framework surgery under general anesthesia is a promising surgical approach for selected patients with unilateral vocal cord paralysis (UVCP). The advantages of laryngeal framework surgery under local anesthesia have been described, but no studies exist concerning the difference in phonological outcome of laryngeal framework surgery performed under general anesthesia. To add new information, we retrospectively investigated the phonological outcome of the combined surgery performed under three different anesthesia protocols. Thirty-nine consecutive patients with severe UVCP underwent the combined surgery under three anesthesia protocols performed by a single surgeon: (1) under general anesthesia by intubation, (2) under general anesthesia using LMA, and (3) under local anesthesia. Under all anesthesia protocols, the vocal cords of most patients could be positioned such that the best vocal outcome could be expected. Statistical analyses demonstrated improved maximum phonation time and mean airflow rate, and grade, roughness, breathiness, asthenia, and strain (GRBAS) scale in all patients, regardless of their anesthesia protocol. Furthermore, of the three protocols, local anesthesia had the shortest operation time.

Improved Discrimination for Brassica Vegetables Treated with Agricultural Fertilizers Using a Combined Chemometric Approach.

PubMed

Yuan, Yuwei; Hu, Guixian; Chen, Tianjin; Zhao, Ming; Zhang, Yongzhi; Li, Yong; Xu, Xiahong; Shao, Shengzhi; Zhu, Jiahong; Wang, Qiang; Rogers, Karyne M

2016-07-20

Multielement and stable isotope (δ(13)C, δ(15)N, δ(2)H, δ(18)O, (207)Pb/(206)Pb, and (208)Pb/(206)Pb) analyses were combined to provide a new chemometric approach to improve the discrimination between organic and conventional Brassica vegetable production. Different combinations of organic and conventional fertilizer treatments were used to demonstrate this authentication approach using Brassica chinensis planted in experimental test pots. Stable isotope analyses (δ(15)N and δ(13)C) of B. chinensis using elemental analyzer-isotope ratio mass spectrometry easily distinguished organic and chemical fertilizer treatments. However, for low-level application fertilizer treatments, this dual isotope approach became indistinguishable over time. Using a chemometric approach (combined isotope and elemental approach), organic and chemical fertilizer mixes and low-level applications of synthetic and organic fertilizers were detectable in B. chinensis and their associated soils, improving the detection limit beyond the capacity of individual isotopes or elemental characterization. LDA shows strong promise as an improved method to discriminate genuine organic Brassica vegetables from produce treated with chemical fertilizers and could be used as a robust test for organic produce authentication.

Combination of vildagliptin and rosiglitazone ameliorates nonalcoholic fatty liver disease in C57BL/6 mice

PubMed Central

Mookkan, Jeyamurugan; De, Soumita; Shetty, Pranesha; Kulkarni, Nagaraj M.; Devisingh, Vijayaraj; Jaji, Mallikarjun S.; Lakshmi, Vinitha P.; Chaudhary, Shilpee; Kulathingal, Jayanarayan; Rajesh, Navin B.; Narayanan, Shridhar

2014-01-01

Objectives: To evaluate the effect of vildagliptin alone and in combination with metformin or rosiglitazone on murine hepatic steatosis in diet-induced nonalcoholic fatty liver disease (NAFLD). Materials and Methods: Male C57BL/6 mice were fed with high fat diet (60 Kcal %) and fructose (40%) in drinking water for 60 days to induce NAFLD. After the induction period, animals were divided into different groups and treated with vildagliptin (10 mg/kg), metformin (350 mg/kg), rosiglitazone (10 mg/kg), vildagliptin (10 mg/kg) + metformin (350 mg/kg), or vildagliptin (10 mg/kg) + rosiglitazone (10 mg/kg) orally for 28 days. Following parameters were measured: body weight, food intake, plasma glucose, triglyceride (TG), total cholesterol, liver function tests, and liver TG. Liver histopathology was also examined. Results: Oral administration of vildagliptin and rosiglitazone in combination showed a significant reduction in fasting plasma glucose, hepatic steatosis, and liver TGs. While other treatments showed less or no improvement in the measured parameters. Conclusions: These preliminary results demonstrate that administration of vildagliptin in combination with rosiglitazone could be a promising therapeutic strategy for the treatment of NAFLD. PMID:24550584

Synergy of a combination of nisin and citric acid against Staphylococcus aureus and Listeria monocytogenes.

PubMed

Zhao, Xingchen; Zhen, Zhen; Wang, Xinyang; Guo, Na

2017-12-01

Food-borne diseases caused by pathogens, such as Staphylococcus aureus and Listeria monocytogenes, have long attracted attention globally from researchers, food industries, and food safety authorities. Nisin (NS) is the only bacteriocin used worldwide as a generally recognised as safe (GRAS) food preservative, while citric acid (CA) has an unrestricted use in foods since it has GRAS status. In this study, synergistic interactions of NS combined with CA against S. aureus and L. monocytogenes were studied by the chequerboard microdilution method, with fractional inhibitory concentration index values ranging from 0.25 to 0.375 and 0.19 to 0.375, respectively. The positive interactions were verified by time-kill studies in pasteurised milk and disk diffusion assays. The mechanism of the synergistic antibacterial of NS and CA is proposed following SEM analysis and the determination of release of cell constituents. These results suggest that the cell walls and membrane are the probable main targets of this antimicrobial combination. These findings indicated that the combination of NS and CA not only could be used as a new promising naturally sourced food preservative, but may also reduce the problem of bacterial resistance.

Photodynamic Therapy Combined with Terbinafine Against Chromoblastomycosis and the Effect of PDT on Fonsecaea monophora In Vitro

PubMed Central

Hu, Yongxuan; Huang, Xiaowen; Lu, Sha; Hamblin, Michael R.; Mylonakis, Eleftherios; Zhang, Junmin

2014-01-01

Chromoblastomycosis, a chronic fungal infection of skin and subcutaneous tissue caused by dematiaceous fungi, is associated with low cure and high relapse rates. Among all factors affecting clinical outcome, etiological agents have an important position. In southern China, Fonsecaea pedrosoi and Fonsecaea monophora are main causative agents causing Chromoblastomycosis. We treated one case of chromoblastomycosis by photodynamic therapy (PDT) of 5-aminolevulinic acid (ALA) irradiation combined with terbinafine 250 mg a day. The lesions were improved after two sessions of ALA-PDT treatment, each including nine times, at an interval of 1 week, combined with terbinafine 250 mg/day oral, and clinical improvement could be observed. In the following study, based on the clinical treatment, the effect of PDT and antifungal drugs on this isolate was detected in vitro. It showed sensitivity to terbinafine, itraconazole or voriconazole, and PDT inhibited the growth. Both the clinic and experiments in vitro confirm the good outcome of ALA-PDT applied in the inhibition of F. monophora. It demonstrated that combination of antifungal drugs with ALA-PDT arises as a promising alternative method for the treatment of these refractory cases of chromoblastomycosis. PMID:25366276

Synergistic Effect of TPD7 and Berberine against Leukemia Jurkat Cell Growth through Regulating Ephrin-B2 Signaling.

PubMed

Ma, Weina; Zhu, Man; Yang, Liu; Yang, Tianfeng; Zhang, Yanmin

2017-09-01

TPD7, a novel biphenyl urea taspine derivative, and berberine have presented inhibition on VEGFR2 that can be regulated by ephrin-B2 reverse signaling through interactions with the PDZ domain. The purpose of this study is to investigate the inhibitory effect of the combination of TPD7 and berberine (TAB) on T-cell acute lymphoblastic leukemia cell growth. TPD7 and berberine together synergistically inhibited the proliferation of Jurkat cells. Also, the combination of TAB induced G 1 -phase cell-cycle arrest by downregulating the level of cyclin D1, cyclin E, and CDC2. Furthermore, the combination of TAB significantly enhanced apoptosis in Jurkat cells, and the apoptosis most likely resulted from the modulation of the level of Bcl-2 family members. Most importantly, the concomitant treatment simultaneously regulated the ephrin-B2 and VEGFR2 signaling, as well as modulated the MEK/ERK and PTEN/PI3K/AKT/mTOR signaling. Therefore, the combination treatment of TAB may be a promising therapeutic method in treating T-cell acute lymphoblastic leukemia. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Laser-ablative engineering of phase singularities in plasmonic metamaterial arrays for biosensing applications

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

Aristov, Andrey I.; Kabashin, Andrei V., E-mail: kabashin@lp3.univ-mrs.fr; Zywietz, Urs

2014-02-17

By using methods of laser-induced transfer combined with nanoparticle lithography, we design and fabricate large-area gold nanoparticle-based metamaterial arrays exhibiting extreme Heaviside-like phase jumps in reflected light due to a strong diffractive coupling of localized plasmons. When employed in sensing schemes, these phase singularities provide the sensitivity of 5 × 10{sup 4} deg. of phase shift per refractive index unit change that is comparable with best values reported for plasmonic biosensors. The implementation of sensor platforms on the basis of such metamaterial arrays promises a drastic improvement of sensitivity and cost efficiency of plasmonic biosensing devices.

Adaptive hybrid optimal quantum control for imprecisely characterized systems.

PubMed

Egger, D J; Wilhelm, F K

2014-06-20

Optimal quantum control theory carries a huge promise for quantum technology. Its experimental application, however, is often hindered by imprecise knowledge of the input variables, the quantum system's parameters. We show how to overcome this by adaptive hybrid optimal control, using a protocol named Ad-HOC. This protocol combines open- and closed-loop optimal control by first performing a gradient search towards a near-optimal control pulse and then an experimental fidelity estimation with a gradient-free method. For typical settings in solid-state quantum information processing, adaptive hybrid optimal control enhances gate fidelities by an order of magnitude, making optimal control theory applicable and useful.

Porous dendritic copper: an electrocatalyst for highly selective CO2 reduction to formate in water/ionic liquid electrolyte.

PubMed

Huan, Tran Ngoc; Simon, Philippe; Rousse, Gwenaëlle; Génois, Isabelle; Artero, Vincent; Fontecave, Marc

2017-01-01

Copper is currently extensively studied because it provides promising electrodes for carbon dioxide electroreduction. The original combination, reported here, of a nanostructured porous dendritic Cu-based material, characterized by electron microcopy (SEM, TEM) and X-ray diffraction methods, and a water/ionic liquid mixture as the solvent, contributing to CO 2 solubilization and activation, results in a remarkably efficient (large current densities at low overpotentials), stable and selective (large faradic yields) electrocatalytic system for the conversion of CO 2 into formic acid, a product with a variety of uses. These results provide new directions for the further improvement of Cu electrodes.

Using simulation to interpret experimental data in terms of protein conformational ensembles.

PubMed

Allison, Jane R

2017-04-01

In their biological environment, proteins are dynamic molecules, necessitating an ensemble structural description. Molecular dynamics simulations and solution-state experiments provide complimentary information in the form of atomically detailed coordinates and averaged or distributions of structural properties or related quantities. Recently, increases in the temporal and spatial scale of conformational sampling and comparison of the more diverse conformational ensembles thus generated have revealed the importance of sampling rare events. Excitingly, new methods based on maximum entropy and Bayesian inference are promising to provide a statistically sound mechanism for combining experimental data with molecular dynamics simulations. Copyright © 2016 Elsevier Ltd. All rights reserved.

Computational method for multi-modal microscopy based on transport of intensity equation

NASA Astrophysics Data System (ADS)

Li, Jiaji; Chen, Qian; Sun, Jiasong; Zhang, Jialin; Zuo, Chao

2017-02-01

In this paper, we develop the requisite theory to describe a hybrid virtual-physical multi-modal imaging system which yields quantitative phase, Zernike phase contrast, differential interference contrast (DIC), and light field moment imaging simultaneously based on transport of intensity equation(TIE). We then give the experimental demonstration of these ideas by time-lapse imaging of live HeLa cell mitosis. Experimental results verify that a tunable lens based TIE system, combined with the appropriate post-processing algorithm, can achieve a variety of promising imaging modalities in parallel with the quantitative phase images for the dynamic study of cellular processes.

Fluorescence quenching by TEMPO: a sub-30 A single-molecule ruler.

PubMed

Zhu, Peizhi; Clamme, Jean-Pierre; Deniz, Ashok A

2005-11-01

A series of DNA molecules labeled with 5-carboxytetramethylrhodamine (5-TAMRA) and the small nitroxide radical TEMPO were synthesized and tested to investigate whether the intramolecular quenching efficiency can be used to measure short intramolecular distances in small ensemble and single-molecule experiments. In combination with distance calculations using molecular mechanics modeling, the experimental results from steady-state ensemble fluorescence and fluorescence correlation spectroscopy measurements both show an exponential decrease in the quenching rate constant with the dye-quencher distance in the 10-30 A range. The results demonstrate that TEMPO-5-TAMRA fluorescence quenching is a promising method to measure short distance changes within single biomolecules.

Onyx, a New Liquid Embolic Material for Peripheral Interventions: Preliminary Experience in Aneurysm, Pseudoaneurysm, and Pulmonary Arteriovenous Malformation Embolization

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

Vanninen, Ritva L., E-mail: ritva.vanninen@kuh.fi; Manninen, I.

Purpose. To describe our preliminary experience with a new liquid embolization agent, Onyx, in peripheral interventions. Methods and results. We successfully treated two peripheral aneurysms (one in an internal iliac artery, one in a thoracic collateral artery of an aortic coarctation), two peripheral pseudoaneurysms (one in a lumbar artery, one in a renal artery), and one pulmonary arteriovenous malformation. Conclusion. Onyx is a promising alternative embolic material for peripheral interventions. It can be combined with coils in selected cases, and balloon catheters can be effectively used during slow injection of embolic material to control flow and protect the aneurysm neck.

The Water-Energy-Food Nexus: A systematic review of methods for nexus assessment

NASA Astrophysics Data System (ADS)

Albrecht, Tamee R.; Crootof, Arica; Scott, Christopher A.

2018-04-01

The water-energy-food (WEF) nexus is rapidly expanding in scholarly literature and policy settings as a novel way to address complex resource and development challenges. The nexus approach aims to identify tradeoffs and synergies of water, energy, and food systems, internalize social and environmental impacts, and guide development of cross-sectoral policies. However, while the WEF nexus offers a promising conceptual approach, the use of WEF nexus methods to systematically evaluate water, energy, and food interlinkages or support development of socially and politically-relevant resource policies has been limited. This paper reviews WEF nexus methods to provide a knowledge base of existing approaches and promote further development of analytical methods that align with nexus thinking. The systematic review of 245 journal articles and book chapters reveals that (a) use of specific and reproducible methods for nexus assessment is uncommon (less than one-third); (b) nexus methods frequently fall short of capturing interactions among water, energy, and food—the very linkages they conceptually purport to address; (c) assessments strongly favor quantitative approaches (nearly three-quarters); (d) use of social science methods is limited (approximately one-quarter); and (e) many nexus methods are confined to disciplinary silos—only about one-quarter combine methods from diverse disciplines and less than one-fifth utilize both quantitative and qualitative approaches. To help overcome these limitations, we derive four key features of nexus analytical tools and methods—innovation, context, collaboration, and implementation—from the literature that reflect WEF nexus thinking. By evaluating existing nexus analytical approaches based on these features, we highlight 18 studies that demonstrate promising advances to guide future research. This paper finds that to address complex resource and development challenges, mixed-methods and transdisciplinary approaches are needed that incorporate social and political dimensions of water, energy, and food; utilize multiple and interdisciplinary approaches; and engage stakeholders and decision-makers.

Direct Identification of On-Bead Peptides Using Surface-Enhanced Raman Spectroscopic Barcoding System for High-Throughput Bioanalysis

PubMed Central

Kang, Homan; Jeong, Sinyoung; Koh, Yul; Geun Cha, Myeong; Yang, Jin-Kyoung; Kyeong, San; Kim, Jaehi; Kwak, Seon-Yeong; Chang, Hye-Jin; Lee, Hyunmi; Jeong, Cheolhwan; Kim, Jong-Ho; Jun, Bong-Hyun; Kim, Yong-Kweon; Hong Jeong, Dae; Lee, Yoon-Sik

2015-01-01

Recently, preparation and screening of compound libraries remain one of the most challenging tasks in drug discovery, biomarker detection, and biomolecular profiling processes. So far, several distinct encoding/decoding methods such as chemical encoding, graphical encoding, and optical encoding have been reported to identify those libraries. In this paper, a simple and efficient surface-enhanced Raman spectroscopic (SERS) barcoding method using highly sensitive SERS nanoparticles (SERS ID) is presented. The 44 kinds of SERS IDs were able to generate simple codes and could possibly generate more than one million kinds of codes by incorporating combinations of different SERS IDs. The barcoding method exhibited high stability and reliability under bioassay conditions. The SERS ID encoding based screening platform can identify the peptide ligand on the bead and also quantify its binding affinity for specific protein. We believe that our SERS barcoding technology is a promising method in the screening of one-bead-one-compound (OBOC) libraries for drug discovery. PMID:26017924

Direct identification of on-bead peptides using surface-enhanced Raman spectroscopic barcoding system for high-throughput bioanalysis.

PubMed

Kang, Homan; Jeong, Sinyoung; Koh, Yul; Geun Cha, Myeong; Yang, Jin-Kyoung; Kyeong, San; Kim, Jaehi; Kwak, Seon-Yeong; Chang, Hye-Jin; Lee, Hyunmi; Jeong, Cheolhwan; Kim, Jong-Ho; Jun, Bong-Hyun; Kim, Yong-Kweon; Hong Jeong, Dae; Lee, Yoon-Sik

2015-05-28

Recently, preparation and screening of compound libraries remain one of the most challenging tasks in drug discovery, biomarker detection, and biomolecular profiling processes. So far, several distinct encoding/decoding methods such as chemical encoding, graphical encoding, and optical encoding have been reported to identify those libraries. In this paper, a simple and efficient surface-enhanced Raman spectroscopic (SERS) barcoding method using highly sensitive SERS nanoparticles (SERS ID) is presented. The 44 kinds of SERS IDs were able to generate simple codes and could possibly generate more than one million kinds of codes by incorporating combinations of different SERS IDs. The barcoding method exhibited high stability and reliability under bioassay conditions. The SERS ID encoding based screening platform can identify the peptide ligand on the bead and also quantify its binding affinity for specific protein. We believe that our SERS barcoding technology is a promising method in the screening of one-bead-one-compound (OBOC) libraries for drug discovery.

Learning challenges and sustainable development: A methodological perspective.

PubMed

Seppänen, Laura

2017-01-01

Sustainable development requires learning, but the contents of learning are often complex and ambiguous. This requires new integrated approaches from research. It is argued that investigation of people's learning challenges in every-day work is beneficial for research on sustainable development. The aim of the paper is to describe a research method for examining learning challenges in promoting sustainable development. This method is illustrated with a case example from organic vegetable farming in Finland. The method, based on Activity Theory, combines historical analysis with qualitative analysis of need expressions in discourse data. The method linking local and subjective need expressions with general historical analysis is a promising way to overcome the gap between the individual and society, so much needed in research for sustainable development. Dialectically informed historical frameworks have practical value as tools in collaborative negotiations and participatory designs for sustainable development. The simultaneous use of systemic and subjective perspectives allows researchers to manage the complexity of practical work activities and to avoid too simplistic presumptions about sustainable development.

A new direct growth method of graphene on Si-face of 6H-SiC by synergy of the inner and external carbon sources

NASA Astrophysics Data System (ADS)

Yang, Zhiyuan; Xu, Shicai; Zhao, Lili; Zhang, Jing; Wang, Zhengping; Chen, Xiufang; Cheng, Xiufeng; Yu, Fapeng; Zhao, Xian

2018-04-01

Graphene is a promising two-dimensional material that has possible application in various disciplines, due to its super properties, including high carrier mobility, chemical stability, and optical transparency etc. In this paper, we report an inner and external carbon synergy (IECS) method to grow graphene on Si-face of 6H-SiC. This method combined the advantages of chemical vapor deposition (CVD) and traditional epitaxial growth (EG) based on silicon carbide, which providing a feasible approach for growing graphene on the SiC substrates. The graphene was synthesized within just 3 min, which was more than one order of magnitude faster than the graphene grown on 6H-SiC substrates by the traditional EG method. The growth temperature was ∼200 °C lower than the EG process. The directly grown graphene maintained the compatibility with the semiconductor technique, which is benefit for use in graphene-based microelectronic devices.

A novel application of artificial neural network for wind speed estimation

NASA Astrophysics Data System (ADS)

Fang, Da; Wang, Jianzhou

2017-05-01

Providing accurate multi-steps wind speed estimation models has increasing significance, because of the important technical and economic impacts of wind speed on power grid security and environment benefits. In this study, the combined strategies for wind speed forecasting are proposed based on an intelligent data processing system using artificial neural network (ANN). Generalized regression neural network and Elman neural network are employed to form two hybrid models. The approach employs one of ANN to model the samples achieving data denoising and assimilation and apply the other to predict wind speed using the pre-processed samples. The proposed method is demonstrated in terms of the predicting improvements of the hybrid models compared with single ANN and the typical forecasting method. To give sufficient cases for the study, four observation sites with monthly average wind speed of four given years in Western China were used to test the models. Multiple evaluation methods demonstrated that the proposed method provides a promising alternative technique in monthly average wind speed estimation.

Fabrication of high quality aspheric microlens array by dose-modulated lithography and surface thermal reflow

NASA Astrophysics Data System (ADS)

Huang, Shengzhou; Li, Mujun; Shen, Lianguan; Qiu, Jinfeng; Zhou, Youquan

2018-03-01

A novel fabrication method for high quality aspheric microlens array (MLA) was developed by combining the dose-modulated DMD-based lithography and surface thermal reflow process. In this method, the complex shape of aspheric microlens is pre-modeled via dose modulation in a digital micromirror device (DMD) based maskless projection lithography. And the dose modulation mainly depends on the distribution of exposure dose of photoresist. Then the pre-shaped aspheric microlens is polished by a following non-contact thermal reflow (NCTR) process. Different from the normal process, the reflow process here is investigated to improve the surface quality while keeping the pre-modeled shape unchanged, and thus will avoid the difficulties in generating the aspheric surface during reflow. Fabrication of a designed aspheric MLA with this method was demonstrated in experiments. Results showed that the obtained aspheric MLA was good in both shape accuracy and surface quality. The presented method may be a promising approach in rapidly fabricating high quality aspheric microlens with complex surface.

Wavelet images and Chou's pseudo amino acid composition for protein classification.

PubMed

Nanni, Loris; Brahnam, Sheryl; Lumini, Alessandra

2012-08-01

The last decade has seen an explosion in the collection of protein data. To actualize the potential offered by this wealth of data, it is important to develop machine systems capable of classifying and extracting features from proteins. Reliable machine systems for protein classification offer many benefits, including the promise of finding novel drugs and vaccines. In developing our system, we analyze and compare several feature extraction methods used in protein classification that are based on the calculation of texture descriptors starting from a wavelet representation of the protein. We then feed these texture-based representations of the protein into an Adaboost ensemble of neural network or a support vector machine classifier. In addition, we perform experiments that combine our feature extraction methods with a standard method that is based on the Chou's pseudo amino acid composition. Using several datasets, we show that our best approach outperforms standard methods. The Matlab code of the proposed protein descriptors is available at http://bias.csr.unibo.it/nanni/wave.rar .

Hypericin-bearing magnetic iron oxide nanoparticles for selective drug delivery in photodynamic therapy

PubMed Central

Unterweger, Harald; Subatzus, Daniel; Tietze, Rainer; Janko, Christina; Poettler, Marina; Stiegelschmitt, Alfons; Schuster, Matthias; Maake, Caroline; Boccaccini, Aldo R; Alexiou, Christoph

2015-01-01

Combining the concept of magnetic drug targeting and photodynamic therapy is a promising approach for the treatment of cancer. A high selectivity as well as significant fewer side effects can be achieved by this method, since the therapeutic treatment only takes place in the area where accumulation of the particles by an external electromagnet and radiation by a laser system overlap. In this article, a novel hypericin-bearing drug delivery system has been developed by synthesis of superparamagnetic iron oxide nanoparticles (SPIONs) with a hypericin-linked functionalized dextran coating. For that, sterically stabilized dextran-coated SPIONs were produced by coprecipitation and crosslinking with epichlorohydrin to enhance stability. Carboxymethylation of the dextran shell provided a functionalized platform for linking hypericin via glutaraldehyde. Particle sizes obtained by dynamic light scattering were in a range of 55–85 nm, whereas investigation of single magnetite or maghemite particle diameter was performed by transmission electron microscopy and X-ray diffraction and resulted in approximately 4.5–5.0 nm. Surface chemistry of those particles was evaluated by Fourier transform infrared spectroscopy and ζ potential measurements, indicating successful functionalization and dispersal stabilization due to a mixture of steric and electrostatic repulsion. Flow cytometry revealed no toxicity of pure nanoparticles as well as hypericin without exposure to light on Jurkat T-cells, whereas the combination of hypericin, alone or loaded on particles, with light-induced cell death in a concentration and exposure time-dependent manner due to the generation of reactive oxygen species. In conclusion, the combination of SPIONs’ targeting abilities with hypericin’s phototoxic properties represents a promising approach for merging magnetic drug targeting with photodynamic therapy for the treatment of cancer. PMID:26648714

Hypericin-bearing magnetic iron oxide nanoparticles for selective drug delivery in photodynamic therapy.

PubMed

Unterweger, Harald; Subatzus, Daniel; Tietze, Rainer; Janko, Christina; Poettler, Marina; Stiegelschmitt, Alfons; Schuster, Matthias; Maake, Caroline; Boccaccini, Aldo R; Alexiou, Christoph

2015-01-01

Combining the concept of magnetic drug targeting and photodynamic therapy is a promising approach for the treatment of cancer. A high selectivity as well as significant fewer side effects can be achieved by this method, since the therapeutic treatment only takes place in the area where accumulation of the particles by an external electromagnet and radiation by a laser system overlap. In this article, a novel hypericin-bearing drug delivery system has been developed by synthesis of superparamagnetic iron oxide nanoparticles (SPIONs) with a hypericin-linked functionalized dextran coating. For that, sterically stabilized dextran-coated SPIONs were produced by coprecipitation and crosslinking with epichlorohydrin to enhance stability. Carboxymethylation of the dextran shell provided a functionalized platform for linking hypericin via glutaraldehyde. Particle sizes obtained by dynamic light scattering were in a range of 55-85 nm, whereas investigation of single magnetite or maghemite particle diameter was performed by transmission electron microscopy and X-ray diffraction and resulted in approximately 4.5-5.0 nm. Surface chemistry of those particles was evaluated by Fourier transform infrared spectroscopy and ζ potential measurements, indicating successful functionalization and dispersal stabilization due to a mixture of steric and electrostatic repulsion. Flow cytometry revealed no toxicity of pure nanoparticles as well as hypericin without exposure to light on Jurkat T-cells, whereas the combination of hypericin, alone or loaded on particles, with light-induced cell death in a concentration and exposure time-dependent manner due to the generation of reactive oxygen species. In conclusion, the combination of SPIONs' targeting abilities with hypericin's phototoxic properties represents a promising approach for merging magnetic drug targeting with photodynamic therapy for the treatment of cancer.

Construction of doxycycline-mediated BMP-2 transgene combining with APA microcapsules for bone repair.

PubMed

Qian, Dongyang; Bai, Bo; Yan, Guangbin; Zhang, Shujiang; Liu, Qi; Chen, Yi; Tan, Xiaobo; Zeng, Yanjun

2016-01-01

The repairing of large segmental bone defects is difficult for clinical orthopedists at present. Gene therapy is regarded as a promising method for bone defects repair. The present study aimed to construct an effective and controllable Tet-On expression system for transferring hBMP-2 gene into bone marrow mesenchymal progenitor cells (BMSCs). Meanwhile, with combination of alginate-poly-L-lysine-alginate (APA) microencapsulation technology, we attempted to reduce the influence of immunologic rejection and examine the effect of the Tet-On expression system on osteogenesis of BMSCs. The adenovirus encoding hBMP-2 (ADV-hBMP2) was constructed using the means of molecular cloning. The ADV-hBMP2 and Adeno-X Tet-On virus was respectively transfected to the HEK293 for amplification and afterward BMSCs were co-infected with the virus of ADV-hBMP2 and the Adeno-X Tet-On. The expression of hBMP-2 was measured with induction by doxycycline (DOX) at different concentration by means of RT-PCR and ELISA. Combining Tet-On expression system and APA microcapsules with the use of the pulsed high-voltage electrostatic microcapsule instrument, we examined the expression level of hBMP-2 in APA microcapsules by ELISA as well as the osteogenesis by alizarin red S staining. An effective Tet-On expression system for transferring hBMP-2 gene into BMSCs was constructed successfully. Also, the expression of hBMP-2 could be regulated by concentration of DOX. The data exhibited that BMSCs in APA microcapsules maintained the capability of proliferation and differentiation. The combination of Tet-On expression system and APA microcapsules could promote the osteogenesis of BMSCs. According to the results, microencapsulated Tet-On expression system showed the effective characteristics of secreting hBMP-2 and enhancing osteogenesis, which would provide a promising way for bone repair.

A novel method for extraction of neural response from single channel cochlear implant auditory evoked potentials.

PubMed

Sinkiewicz, Daniel; Friesen, Lendra; Ghoraani, Behnaz

2017-02-01

Cortical auditory evoked potentials (CAEP) are used to evaluate cochlear implant (CI) patient auditory pathways, but the CI device produces an electrical artifact, which obscures the relevant information in the neural response. Currently there are multiple methods, which attempt to recover the neural response from the contaminated CAEP, but there is no gold standard, which can quantitatively confirm the effectiveness of these methods. To address this crucial shortcoming, we develop a wavelet-based method to quantify the amount of artifact energy in the neural response. In addition, a novel technique for extracting the neural response from single channel CAEPs is proposed. The new method uses matching pursuit (MP) based feature extraction to represent the contaminated CAEP in a feature space, and support vector machines (SVM) to classify the components as normal hearing (NH) or artifact. The NH components are combined to recover the neural response without artifact energy, as verified using the evaluation tool. Although it needs some further evaluation, this approach is a promising method of electrical artifact removal from CAEPs. Copyright © 2016 IPEM. Published by Elsevier Ltd. All rights reserved.

Point-of-care testing in the early diagnosis of acute pesticide intoxication: The example of paraquat.

PubMed

Wei, Ting-Yen; Yen, Tzung-Hai; Cheng, Chao-Min

2018-01-01

Acute pesticide intoxication is a common method of suicide globally. This article reviews current diagnostic methods and makes suggestions for future development. In the case of paraquat intoxication, it is characterized by multi-organ failure, causing substantial mortality and morbidity. Early diagnosis may save the life of a paraquat intoxication patient. Conventional paraquat intoxication diagnostic methods, such as symptom review and urine sodium dithionite assay, are time-consuming and impractical in resource-scarce areas where most intoxication cases occur. Several experimental and clinical studies have shown the potential of portable Surface Enhanced Raman Scattering (SERS), paper-based devices, and machine learning for paraquat intoxication diagnosis. Portable SERS and new SERS substrates maintain the sensitivity of SERS while being less costly and more convenient than conventional SERS. Paper-based devices provide the advantages of price and portability. Machine learning algorithms can be implemented as a mobile phone application and facilitate diagnosis in resource-limited areas. Although these methods have not yet met all features of an ideal diagnostic method, the combination and development of these methods offer much promise.

Intraoperative on-the-fly organ-mosaicking for laparoscopic surgery

PubMed Central

Reichard, Daniel; Bodenstedt, Sebastian; Suwelack, Stefan; Mayer, Benjamin; Preukschas, Anas; Wagner, Martin; Kenngott, Hannes; Müller-Stich, Beat; Dillmann, Rüdiger; Speidel, Stefanie

2015-01-01

Abstract. The goal of computer-assisted surgery is to provide the surgeon with guidance during an intervention, e.g., using augmented reality. To display preoperative data, soft tissue deformations that occur during surgery have to be taken into consideration. Laparoscopic sensors, such as stereo endoscopes, can be used to create a three-dimensional reconstruction of stereo frames for registration. Due to the small field of view and the homogeneous structure of tissue, reconstructing just one frame, in general, will not provide enough detail to register preoperative data, since every frame only contains a part of an organ surface. A correct assignment to the preoperative model is possible only if the patch geometry can be unambiguously matched to a part of the preoperative surface. We propose and evaluate a system that combines multiple smaller reconstructions from different viewpoints to segment and reconstruct a large model of an organ. Using graphics processing unit-based methods, we achieved four frames per second. We evaluated the system with in silico, phantom, ex vivo, and in vivo (porcine) data, using different methods for estimating the camera pose (optical tracking, iterative closest point, and a combination). The results indicate that the proposed method is promising for on-the-fly organ reconstruction and registration. PMID:26693166

Association between abnormal brain functional connectivity in children and psychopathology: A study based on graph theory and machine learning.

PubMed

Sato, João Ricardo; Biazoli, Claudinei Eduardo; Salum, Giovanni Abrahão; Gadelha, Ary; Crossley, Nicolas; Vieira, Gilson; Zugman, André; Picon, Felipe Almeida; Pan, Pedro Mario; Hoexter, Marcelo Queiroz; Amaro, Edson; Anés, Mauricio; Moura, Luciana Monteiro; Del'Aquilla, Marco Antonio Gomes; Mcguire, Philip; Rohde, Luis Augusto; Miguel, Euripedes Constantino; Jackowski, Andrea Parolin; Bressan, Rodrigo Affonseca

2018-03-01

One of the major challenges facing psychiatry is how to incorporate biological measures in the classification of mental health disorders. Many of these disorders affect brain development and its connectivity. In this study, we propose a novel method for assessing brain networks based on the combination of a graph theory measure (eigenvector centrality) and a one-class support vector machine (OC-SVM). We applied this approach to resting-state fMRI data from 622 children and adolescents. Eigenvector centrality (EVC) of nodes from positive- and negative-task networks were extracted from each subject and used as input to an OC-SVM to label individual brain networks as typical or atypical. We hypothesised that classification of these subjects regarding the pattern of brain connectivity would predict the level of psychopathology. Subjects with atypical brain network organisation had higher levels of psychopathology (p < 0.001). There was a greater EVC in the typical group at the bilateral posterior cingulate and bilateral posterior temporal cortices; and significant decreases in EVC at left temporal pole. The combination of graph theory methods and an OC-SVM is a promising method to characterise neurodevelopment, and may be useful to understand the deviations leading to mental disorders.

An identification method of orbit responses rooting in vibration analysis of rotor during touchdowns of active magnetic bearings

NASA Astrophysics Data System (ADS)

Liu, Tao; Lyu, Mindong; Wang, Zixi; Yan, Shaoze

2018-02-01

Identification of orbit responses can make the active protection operation more easily realize for active magnetic bearings (AMB) in case of touchdowns. This paper presents an identification method of the orbit responses rooting on signal processing of rotor displacements during touchdowns. The recognition method consists of two major steps. Firstly, the combined rub and bouncing is distinguished from the other orbit responses by the mathematical expectation of axis displacements of the rotor. Because when the combined rub and bouncing occurs, the rotor of AMB will not be always close to the touchdown bearings (TDB). Secondly, we recognize the pendulum vibration and the full rub by the Fourier spectrum of displacement in horizontal direction, as the frequency characteristics of the two responses are different. The principle of the whole identification algorithm is illustrated by two sets of signal generated by a dynamic model of the specific rotor-TDB system. The universality of the method is validated by other four sets of signal. Besides, the adaptability of noise is also tested by adding white noises with different strengths, and the result is promising. As the mathematical expectation and Discrete Fourier transform are major calculations of the algorithm, the calculation quantity of the algorithm is low, so it is fast, easily realized and embedded in the AMB controller, which has an important engineering value for the protection of AMBs during touchdowns.

Machine learning for predicting the response of breast cancer to neoadjuvant chemotherapy

PubMed Central

Mani, Subramani; Chen, Yukun; Li, Xia; Arlinghaus, Lori; Chakravarthy, A Bapsi; Abramson, Vandana; Bhave, Sandeep R; Levy, Mia A; Xu, Hua; Yankeelov, Thomas E

2013-01-01

Objective To employ machine learning methods to predict the eventual therapeutic response of breast cancer patients after a single cycle of neoadjuvant chemotherapy (NAC). Materials and methods Quantitative dynamic contrast-enhanced MRI and diffusion-weighted MRI data were acquired on 28 patients before and after one cycle of NAC. A total of 118 semiquantitative and quantitative parameters were derived from these data and combined with 11 clinical variables. We used Bayesian logistic regression in combination with feature selection using a machine learning framework for predictive model building. Results The best predictive models using feature selection obtained an area under the curve of 0.86 and an accuracy of 0.86, with a sensitivity of 0.88 and a specificity of 0.82. Discussion With the numerous options for NAC available, development of a method to predict response early in the course of therapy is needed. Unfortunately, by the time most patients are found not to be responding, their disease may no longer be surgically resectable, and this situation could be avoided by the development of techniques to assess response earlier in the treatment regimen. The method outlined here is one possible solution to this important clinical problem. Conclusions Predictive modeling approaches based on machine learning using readily available clinical and quantitative MRI data show promise in distinguishing breast cancer responders from non-responders after the first cycle of NAC. PMID:23616206

Enhanced the enzymatic hydrolysis efficiency of wheat straw after combined steam explosion and laccase pretreatment.

PubMed

Qiu, Weihua; Chen, Hongzhang

2012-08-01

Laccase, capable of selectively degrading lignin while keeping cellulose intact, has been widely applied for the modification and bio-bleaching of pulp. In this study Sclerotium sp. laccase (MSLac) was employed in combination with steam explosion to evaluate the effect of this treatment on cellulose hydrolysis. Combined steam explosion with laccase pretreatment enhanced the cellulose conversion rate of wheat straw no matter in the case of successive (MSLac-Cel) and simultaneous (MSLac+Cel) MSLac and cellulase hydrolysis. The highest cellulose conversion rate of 84.23% was obtained when steam-exploded wheat straw (SEWS) (1.3 MPa, 5 min) was treated by MSLac+Cel at a laccase loading of 0.55 U g(-1) substrate. FT-IR and SEM analyses indicated that MSLac oxidized the phenol and changed electron configuration of the ring, which contributed to loosening the compact wrap of lignin-carbohydrate complex and consequently enhancing the enzymatic hydrolysis efficiency of cellulose. This article provided a promising method for lignocellulose bio-pretreatment. Copyright © 2012 Elsevier Ltd. All rights reserved.

Fat Graft, Laser CO₂ and Platelet-Rich-Plasma Synergy in Scars Treatment

PubMed Central

Nita, AC; Orzan, OA; Filipescu, M; Jianu, D

2013-01-01

Abstract Rationale: Many treatments have been proposed for cosmetic or functional improvement of scars. It is known that fat grafts and laser treatment can have beneficial effects on the remodeling of scar tissue, and platelet-rich plasma (PRP) can be effective during the wound-healing process. We hypothesized that laser and PRP can enhance fat graft survival and the combination would be effective in improving scars appearance. Objective: The purpose of this study was to evaluate the efficacy of these combinations in the treatment of atrophic and contractile scars. Methods and Results: From 2008-2013, we treated with this combination 64 patients affected by atrophic and contractile scars involving different body parts. At 6 months the patients’ overall satisfaction rate was excellent for over 50% of the patients. Discussion: The association of an ablative laser CO2 with PRP and autologous fat graft seems to be a promising and effective therapeutic approach for atrophic and contractile scars. Abbreviations: PRP platelet-rich plasma, OTI orotracheal intubation, HLLT high level laser therapy, LLLT low level laser therapy PMID:24868255

Combined Dielectrophoresis and Impedance Systems for Bacteria Analysis in Microfluidic On-Chip Platforms

PubMed Central

Páez-Avilés, Cristina; Juanola-Feliu, Esteve; Punter-Villagrasa, Jaime; del Moral Zamora, Beatriz; Homs-Corbera, Antoni; Colomer-Farrarons, Jordi; Miribel-Català, Pere Lluís; Samitier, Josep

2016-01-01

Bacteria concentration and detection is time-consuming in regular microbiology procedures aimed to facilitate the detection and analysis of these cells at very low concentrations. Traditional methods are effective but often require several days to complete. This scenario results in low bioanalytical and diagnostic methodologies with associated increased costs and complexity. In recent years, the exploitation of the intrinsic electrical properties of cells has emerged as an appealing alternative approach for concentrating and detecting bacteria. The combination of dielectrophoresis (DEP) and impedance analysis (IA) in microfluidic on-chip platforms could be key to develop rapid, accurate, portable, simple-to-use and cost-effective microfluidic devices with a promising impact in medicine, public health, agricultural, food control and environmental areas. The present document reviews recent DEP and IA combined approaches and the latest relevant improvements focusing on bacteria concentration and detection, including selectivity, sensitivity, detection time, and conductivity variation enhancements. Furthermore, this review analyses future trends and challenges which need to be addressed in order to successfully commercialize these platforms resulting in an adequate social return of public-funded investments. PMID:27649201

Optical design of optical synthetic aperture telescope

NASA Astrophysics Data System (ADS)

Zhou, Chenghao; Wang, Zhile

2018-03-01

Optical synthetic aperture (OSA) is a promising solution for very high-resolution imaging while reducing its volume and mass. In this paper, first, the configuration of OSA systems are analyzed and the design methods of two types (Fizeau and Michelson) of OSA systems are summarized and researched. Second, Fizeau and Michelson OSA prototype systems are designed in detail. In the Michelson configuration, the instrument is made of sub-telescopes distributed in entrance pupil and combined by a common telescope via phase delay line. The design of Michelson configuration is more difficult than that of Fizeau configuration. In the design of Fizeau configuration, according to the third aberration theory tworeflective system is designed. Then the primary mirror of the two mirror system is replaced by the synthetic aperture. The whole system was simulated by Zemax software to obtain the Modulation transform function (MTF). In the design of Michelson configuration, the system is first divided into three parts: the afocal interferometric telescopes, beam combiner system and phase delay line. The three parts are designed respectively and then combined in Zemax software to obtain the MTF.

Combined inhibition of BET family proteins and histone deacetylases as a potential epigenetics-based therapy for pancreatic ductal adenocarcinoma

PubMed Central

Mazur, Pawel K; Herner, Alexander; Mello, Stephano S; Wirth, Matthias; Hausmann, Simone; Sánchez-Rivera, Francisco J; Lofgren, Shane M; Kuschma, Timo; Hahn, Stephan A; Vangala, Deepak; Trajkovic-Arsic, Marija; Gupta, Aayush; Heid, Irina; Noël, Peter B; Braren, Rickmer; Erkan, Mert; Kleeff, Jörg; Sipos, Bence; Sayles, Leanne C; Heikenwalder, Mathias; Heßmann, Elisabeth; Ellenrieder, Volker; Esposito, Irene; Jacks, Tyler; Bradner, James E; Khatri, Purvesh; Sweet-Cordero, E Alejandro; Attardi, Laura D; Schmid, Roland M; Schneider, Guenter; Sage, Julien; Siveke, Jens T

2016-01-01

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal human cancers and shows resistance to any therapeutic strategy used. Here we tested small-molecule inhibitors targeting chromatin regulators as possible therapeutic agents in PDAC. We show that JQ1, an inhibitor of the bromodomain and extraterminal (BET) family of proteins, suppresses PDAC development in mice by inhibiting both MYC activity and inflammatory signals. The histone deacetylase (HDAC) inhibitor SAHA synergizes with JQ1 to augment cell death and more potently suppress advanced PDAC. Finally, using a CRISPR-Cas9–based method for gene editing directly in the mouse adult pancreas, we show that de-repression of p57 (also known as KIP2 or CDKN1C) upon combined BET and HDAC inhibition is required for the induction of combination therapy–induced cell death in PDAC. SAHA is approved for human use, and molecules similar to JQ1 are being tested in clinical trials. Thus, these studies identify a promising epigenetic-based therapeutic strategy that may be rapidly implemented in fatal human tumors. PMID:26390243

Durable and mass producible polymer surface structures with different combinations of micro-micro hierarchy

NASA Astrophysics Data System (ADS)

Jiang, Yu; Suvanto, Mika; Pakkanen, Tapani A.

2016-01-01

Extensive studies have been performed with the aim of fabricating hierarchical surface structures inspired by nature. However, synthetic hierarchical structures have to sacrifice mechanical resistance to functionality by introducing finer scaled structures. Therefore, surfaces are less durable. Surface micro-micro hierarchy has been proven to be effective in replacing micro-nano hierarchy in the sense of superhydrophobicity. However, less attention has been paid to the combined micro-micro hierarchies with surface pillars and pits incorporated together. The fabrication of this type of hierarchy may be less straightforward, with the possibility of being a complicated multi-step process. In this study, we present a simple yet mass producible fabrication method for hierarchical structures with different combinations of surface pillars and pits. The fabrication was based on only one aluminum (Al) mold with sequential mountings. The fabricated structures exhibit high mechanical durability and structural stabilities with a normal load up to 100 kg. In addition, the theoretical estimation of the wetting state shows a promising way of stabilizing a water droplet on the surface pit structures with a more stable Cassie-Baxter state.

Bioethanol from Lignocellulosic Biomass: Current Findings Determine Research Priorities

PubMed Central

Kang, Qian; Appels, Lise; Tan, Tianwei

2014-01-01

“Second generation” bioethanol, with lignocellulose material as feedstock, is a promising alternative for first generation bioethanol. This paper provides an overview of the current status and reveals the bottlenecks that hamper its implementation. The current literature specifies a conversion of biomass to bioethanol of 30 to ~50% only. Novel processes increase the conversion yield to about 92% of the theoretical yield. New combined processes reduce both the number of operational steps and the production of inhibitors. Recent advances in genetically engineered microorganisms are promising for higher alcohol tolerance and conversion efficiency. By combining advanced systems and by intensive additional research to eliminate current bottlenecks, second generation bioethanol could surpass the traditional first generation processes. PMID:25614881

Combined multi-pharmacophore, molecular docking and molecular dynamic study for discovery of promising MTH1 inhibitors

NASA Astrophysics Data System (ADS)

Dai, Duoqian; Zhou, Lu; Zhu, Xiaohong; You, Rong; Zhong, Liangliang

2017-06-01

MutT homolog 1 (MTH1), a nudix phosphohydrolase enzyme participates in the process of repairing of DNA damage by hydrolyzing oxidized deoxy-ribonucleoside triphosphate in cancer cells, is regarded as a potential target for anticancer therapy. In order to seek for promising inhibitor of MTH1, structured-based pharmacophore and 3D-QSAR pharmacophore hypotheses combine with the ADMET analysis and Lipinski's rule of five were used for screening the public molecules libraries (Asinex, Ibscreen and Natural). Then molecular docking studies were performed on screened hits via various docking programs (Glide SP, GOLD and Glide XP), five molecules with three scaffolds were picked out as potential inhibitors against MTH1. Eventually, 20 ns molecular dynamics simulation was implemented on the potential inhibitors. The RMSD (Root Mean Square Deviation) values were used to illustrate bind stability between potential molecules and MTH1. Therefore, the five hits may be considered as promising MTH1 inhibitors by all above studies.

Arctigenin in combination with quercetin synergistically enhances the anti-proliferative effect in prostate cancer cells

PubMed Central

Wang, Piwen; Phan, Tien; Gordon, David; Chung, Seyung; Henning, Susanne M.; Vadgama, Jaydutt V.

2014-01-01

Scope We investigated whether a combination of two promising chemopreventive agents arctigenin and quercetin increases the anti-carcinogenic potency at lower concentrations than necessary when used individually in prostate cancer. Methods and results Androgen-dependent LAPC-4 and LNCaP prostate cancer cells were treated with low doses of arctigenin and quercetin alone or in combination for 48h. The anti-proliferative activity of arctigenin was 10-20 fold stronger than quercetin in both cell lines. Their combination synergistically enhanced the anti-proliferative effect, with a stronger effect in androgen receptor (AR) wild-type LAPC-4 cells than in AR mutated LNCaP cells. Arctigenin demonstrated a strong ability to inhibit AR protein expression in LAPC-4 cells. The combination treatment significantly inhibited both AR and PI3K/Akt pathways compared to control. A protein array analysis revealed that the mixture targets multiple pathways particularly in LAPC-4 cells including Stat3 pathway. The mixture significantly inhibited the expression of several oncogenic microRNAs including miR-21, miR-19b, and miR-148a compared to control. The mixture also enhanced the inhibition of cell migration in both cell lines compared to individual compounds tested. Conclusion The combination of arctigenin and quercetin, that target similar pathways, at low physiological doses, provides a novel regimen with enhanced chemoprevention in prostate cancer. PMID:25380086

Melanoma Vaccines: Mixed Past, Promising Future

PubMed Central

Ozao-Choy, Junko; Lee, Delphine J.; Faries, Mark B.

2014-01-01

Synopsis Cancer vaccines were one of the earliest forms of immunotherapy to be investigated. Past attempts to vaccinate against cancer, including melanoma, have mixed results, revealing the complexity of what was thought to be a simple concept. However, several recent successes and the combination of improved knowledge of tumor immunology and the advent of new immunomodulators make vaccination a promising strategy for the future. PMID:25245965

Optical biopsy - a new armamentarium to detect disease using light

NASA Astrophysics Data System (ADS)

Pu, Yang; Alfano, Robert R.

2015-03-01

Optical spectroscopy has been considered a promising method for cancer detection for past thirty years because of its advantages over the conventional diagnostic methods of no tissue removal, minimal invasiveness, rapid diagnoses, less time consumption and reproducibility since the first use in 1984. It offers a new armamentarium. Human tissue is mainly composed of extracellular matrix of collagen fiber, proteins, fat, water, and epithelial cells with key molecules in different structures. Tissues contain a number of key fingerprint native endogenous fluorophore molecules, such as tryptophan, collagen, elastin, reduced nicotinamide adenine dinucleotide (NADH), flavin adenine dinucleotide (FAD) and porphyrins. It is well known that abnormalities in metabolic activity precede the onset of a lot of main diseases: carcinoma, diabetes mellitus, atherosclerosis, Alzheimer, and Parkinson's disease, etc. Optical spectroscopy may help in detecting various disorders. Conceivably the biochemical or morphologic changes that cause the spectra variations would appear earlier than the histological aberration. Therefore, "optical biopsy" holds a great promise as clinical tool for diagnosing early stage of carcinomas and other deceases by combining with available photonic technology (e.g. optical fibers, photon detectors, spectrographs spectroscopic ratiometer, fiber-optic endomicroscope and nasopharyngoscope) for in vivo use. This paper focuses on various methods available to detect spectroscopic changes in tissues, for example to distinguish cancerous prostate tissues and/or cells from normal prostate tissues and/or cells. The methods to be described are fluorescence, stokes shift, scattering, Raman, and time-resolved spectroscopy will be reviewed. The underlying physical and biological basis for these optical approaches will be discussed with examples. The idea is to present some of the salient works to show the usefulness and methods of Optical Biopsy for cancer detection and show new directions.

Essential energy space random walks to accelerate molecular dynamics simulations: Convergence improvements via an adaptive-length self-healing strategy

NASA Astrophysics Data System (ADS)

Zheng, Lianqing; Yang, Wei

2008-07-01

Recently, accelerated molecular dynamics (AMD) technique was generalized to realize essential energy space random walks so that further sampling enhancement and effective localized enhanced sampling could be achieved. This method is especially meaningful when essential coordinates of the target events are not priori known; moreover, the energy space metadynamics method was also introduced so that biasing free energy functions can be robustly generated. Despite the promising features of this method, due to the nonequilibrium nature of the metadynamics recursion, it is challenging to rigorously use the data obtained at the recursion stage to perform equilibrium analysis, such as free energy surface mapping; therefore, a large amount of data ought to be wasted. To resolve such problem so as to further improve simulation convergence, as promised in our original paper, we are reporting an alternate approach: the adaptive-length self-healing (ALSH) strategy for AMD simulations; this development is based on a recent self-healing umbrella sampling method. Here, the unit simulation length for each self-healing recursion is increasingly updated based on the Wang-Landau flattening judgment. When the unit simulation length for each update is long enough, all the following unit simulations naturally run into the equilibrium regime. Thereafter, these unit simulations can serve for the dual purposes of recursion and equilibrium analysis. As demonstrated in our model studies, by applying ALSH, both fast recursion and short nonequilibrium data waste can be compromised. As a result, combining all the data obtained from all the unit simulations that are in the equilibrium regime via the weighted histogram analysis method, efficient convergence can be robustly ensured, especially for the purpose of free energy surface mapping.

Conjugation of Hot-Melt Extrusion with High-Pressure Homogenization: a Novel Method of Continuously Preparing Nanocrystal Solid Dispersions.

PubMed

Ye, Xingyou; Patil, Hemlata; Feng, Xin; Tiwari, Roshan V; Lu, Jiannan; Gryczke, Andreas; Kolter, Karl; Langley, Nigel; Majumdar, Soumyajit; Neupane, Dipesh; Mishra, Sanjay R; Repka, Michael A

2016-02-01

Over the past few decades, nanocrystal formulations have evolved as promising drug delivery systems owing to their ability to enhance the bioavailability and maintain the stability of poorly water-soluble drugs. However, conventional methods of preparing nanocrystal formulations, such as spray drying and freeze drying, have some drawbacks including high cost, time and energy inefficiency, traces of residual solvent, and difficulties in continuous operation. Therefore, new techniques for the production of nanocrystal formulations are necessary. The main objective of this study was to introduce a new technique for the production of nanocrystal solid dispersions (NCSDs) by combining high-pressure homogenization (HPH) and hot-melt extrusion (HME). Efavirenz (EFZ), a Biopharmaceutics Classification System class II drug, which is used for the treatment of human immunodeficiency virus (HIV) type I, was selected as the model drug for this study. A nanosuspension (NS) was first prepared by HPH using sodium lauryl sulfate (SLS) and Kollidon® 30 as a stabilizer system. The NS was then mixed with Soluplus® in the extruder barrel, and the water was removed by evaporation. The decreased particle size and crystalline state of EFZ were confirmed by scanning electron microscopy, zeta particle size analysis, and differential scanning calorimetry. The increased dissolution rate was also determined. EFZ NCSD was found to be highly stable after storage for 6 months. In summary, the conjugation of HPH with HME technology was demonstrated to be a promising novel method for the production of NCSDs.

NANOCRYSTALLINE MATERIALS FOR REMOVAL OF REDUCED SULFUR AND NITROGEN COMPOUNDS FROM FUEL GAS - PHASE II

EPA Science Inventory

Integrated gasification combined cycle (IGCC), which uses a gasilier to convert coal to fuel gas, and then uses a combined cycle power block to generate electricity. is one of the most promising technologies for generating electricity from coal in an environmentally sustainabl...

A digital data acquisition scheme for SPECT and PET small animal imaging detectors for Theranostic applications

NASA Astrophysics Data System (ADS)

Georgiou, M.; Fysikopoulos, E.; Loudos, G.

2017-11-01

Nanoparticle based drug delivery is considered as a new, promising technology for the efficient treatment of various diseases. When nanoparticles are radiolabelled it is possible to image them, using molecular imaging techniques. The use of magnetic nanoparticles in hyperthermia is one of the most promising nanomedicine directions and requires the accurate, non-invasive, monitoring of temperature increase and drug release. The combination of imaging and therapy has opened the very promising Theranostics domain. In this work, we present a digital data acquisition scheme for nuclear medicine dedicated detectors for Theranostic applications.

A pragmatic definition of therapeutic synergy suitable for clinically relevant in vitro multicompound analyses.

PubMed

Kashif, Muhammad; Andersson, Claes; Åberg, Magnus; Nygren, Peter; Sjöblom, Tobias; Hammerling, Ulf; Larsson, Rolf; Gustafsson, Mats G

2014-07-01

For decades, the standard procedure when screening for candidate anticancer drug combinations has been to search for synergy, defined as any positive deviation from trivial cases like when the drugs are regarded as diluted versions of each other (Loewe additivity), independent actions (Bliss independence), or no interaction terms in a response surface model (no interaction). Here, we show that this kind of conventional synergy analysis may be completely misleading when the goal is to detect if there is a promising in vitro therapeutic window. Motivated by this result, and the fact that a drug combination offering a promising therapeutic window seldom is interesting if one of its constituent drugs can provide the same window alone, the largely overlooked concept of therapeutic synergy (TS) is reintroduced. In vitro TS is said to occur when the largest therapeutic window obtained by the best drug combination cannot be achieved by any single drug within the concentration range studied. Using this definition of TS, we introduce a procedure that enables its use in modern massively parallel experiments supported by a statistical omnibus test for TS designed to avoid the multiple testing problem. Finally, we suggest how one may perform TS analysis, via computational predictions of the reference cell responses, when only the target cell responses are available. In conclusion, the conventional error-prone search for promising drug combinations may be improved by replacing conventional (toxicology-rooted) synergy analysis with an analysis focused on (clinically motivated) TS. ©2014 American Association for Cancer Research.

Hydration Free Energy from Orthogonal Space Random Walk and Polarizable Force Field.

PubMed

Abella, Jayvee R; Cheng, Sara Y; Wang, Qiantao; Yang, Wei; Ren, Pengyu

2014-07-08

The orthogonal space random walk (OSRW) method has shown enhanced sampling efficiency in free energy calculations from previous studies. In this study, the implementation of OSRW in accordance with the polarizable AMOEBA force field in TINKER molecular modeling software package is discussed and subsequently applied to the hydration free energy calculation of 20 small organic molecules, among which 15 are positively charged and five are neutral. The calculated hydration free energies of these molecules are compared with the results obtained from the Bennett acceptance ratio method using the same force field, and overall an excellent agreement is obtained. The convergence and the efficiency of the OSRW are also discussed and compared with BAR. Combining enhanced sampling techniques such as OSRW with polarizable force fields is very promising for achieving both accuracy and efficiency in general free energy calculations.

An application of stereoscopy and image processing in forensics: recovering obliterated firearms serial number

NASA Astrophysics Data System (ADS)

da Silva Nunes, L. C.; dos Santos, Paulo Acioly M.

2004-10-01

We present an application of the use of stereoscope to recovering obliterated firearms serial number. We investigate a promising new combined cheap method using both non-destructive and destructive techniques. With the use of a stereomicroscope coupled with a digital camera and a flexible cold light source, we can capture the image of the damaged area, and with continuous polishing and sometimes with the help of image processing techniques we could enhance the observed images and they can also be recorded as evidence. This method has already proven to be useful, in certain cases, in aluminum dotted pistol frames, whose serial number is printed with a laser, when etching techniques are not successful. We can also observe acid treated steel surfaces and enhance the images of recovered serial numbers, which sometimes lack of definition.

Design and Characterisation of Metallic Glassy Alloys of High Neutron Shielding Capability

NASA Astrophysics Data System (ADS)

Khong, J. C.; Daisenberger, D.; Burca, G.; Kockelmann, W.; Tremsin, A. S.; Mi, J.

2016-11-01

This paper reports the design, making and characterisation of a series of Fe-based bulk metallic glass alloys with the aim of achieving the combined properties of high neutron absorption capability and sufficient glass forming ability. Synchrotron X-ray diffraction and pair distribution function methods were used to characterise the crystalline or amorphous states of the samples. Neutron transmission and macroscopic attenuation coefficients of the designed alloys were measured using energy resolved neutron imaging method and the very recently developed microchannel plate detector. The study found that the newly designed alloy (Fe48Cr15Mo14C15B6Gd2 with a glass forming ability of Ø5.8 mm) has the highest neutron absorption capability among all Fe-based bulk metallic glasses so far reported. It is a promising material for neutron shielding applications.

Design and Characterisation of Metallic Glassy Alloys of High Neutron Shielding Capability.

PubMed

Khong, J C; Daisenberger, D; Burca, G; Kockelmann, W; Tremsin, A S; Mi, J

2016-11-16

This paper reports the design, making and characterisation of a series of Fe-based bulk metallic glass alloys with the aim of achieving the combined properties of high neutron absorption capability and sufficient glass forming ability. Synchrotron X-ray diffraction and pair distribution function methods were used to characterise the crystalline or amorphous states of the samples. Neutron transmission and macroscopic attenuation coefficients of the designed alloys were measured using energy resolved neutron imaging method and the very recently developed microchannel plate detector. The study found that the newly designed alloy (Fe 48 Cr 15 Mo 14 C 15 B 6 Gd 2 with a glass forming ability of Ø5.8 mm) has the highest neutron absorption capability among all Fe-based bulk metallic glasses so far reported. It is a promising material for neutron shielding applications.

An efficient abnormal cervical cell detection system based on multi-instance extreme learning machine

NASA Astrophysics Data System (ADS)

Zhao, Lili; Yin, Jianping; Yuan, Lihuan; Liu, Qiang; Li, Kuan; Qiu, Minghui

2017-07-01

Automatic detection of abnormal cells from cervical smear images is extremely demanded in annual diagnosis of women's cervical cancer. For this medical cell recognition problem, there are three different feature sections, namely cytology morphology, nuclear chromatin pathology and region intensity. The challenges of this problem come from feature combination s and classification accurately and efficiently. Thus, we propose an efficient abnormal cervical cell detection system based on multi-instance extreme learning machine (MI-ELM) to deal with above two questions in one unified framework. MI-ELM is one of the most promising supervised learning classifiers which can deal with several feature sections and realistic classification problems analytically. Experiment results over Herlev dataset demonstrate that the proposed method outperforms three traditional methods for two-class classification in terms of well accuracy and less time.

Availability and assessment of fixing additives for the in situ remediation of heavy metal contaminated soils: a review.

PubMed

Guo, Guanlin; Zhou, Qixing; Ma, Lene Q

2006-05-01

The use of low-cost and environmental safety amendments for the in situ immobilization of heavy metals has been investigated as a promising method for contaminated soil remediation. Natural materials and waste products from certain industries with high captive capacity of heavy metals can be obtained and employed. Reduction of extractable metal concentration and phytotoxicity could be evaluated and demonstrated by the feasibility of various amendments in fixing remediation. In this review, an extensive list of references has been compiled to provide a summary of information on a wide range of potentially amendment resources, including organic, inorganic and combined organic-inorganic materials. The assessment based on the economic efficiency and environmental risks brought forth the potential application values and future development directions of this method on solving the soil contamination.

Novel Biomedical Devices Utilizing Light-Emitting Nanostructures

NASA Technical Reports Server (NTRS)

Goldman, Rachel S.

2004-01-01

As part of the NASA project, we are investigating the formation, properties, and performance of QD heterostructures, to be incorporated into a novel biomedical device for detecting bacteria and/or viruses in fluids on board space vehicles. We are presently synthesizing the epitaxial quantum dot structures using molecular beam epitaxy. We recently developed a method for controlling the arrangement of QDs, based upon a combination of buffer layer growth and controlled annealing sequences. This method is promising for producing arrangements of QDs with a locally well-controlled distribution of sizes. In the future, we plan to explore selective pre-patterning of the starting surface using focused ion-beam nanopatterning, which will enable us to precisely tune the compositions, sizes, and placement of the QDs, in order laterally tune the emission and detection wavelengths of QD based devices.

Conceptual design of distillation-based hybrid separation processes.

PubMed

Skiborowski, Mirko; Harwardt, Andreas; Marquardt, Wolfgang

2013-01-01

Hybrid separation processes combine different separation principles and constitute a promising design option for the separation of complex mixtures. Particularly, the integration of distillation with other unit operations can significantly improve the separation of close-boiling or azeotropic mixtures. Although the design of single-unit operations is well understood and supported by computational methods, the optimal design of flowsheets of hybrid separation processes is still a challenging task. The large number of operational and design degrees of freedom requires a systematic and optimization-based design approach. To this end, a structured approach, the so-called process synthesis framework, is proposed. This article reviews available computational methods for the conceptual design of distillation-based hybrid processes for the separation of liquid mixtures. Open problems are identified that must be addressed to finally establish a structured process synthesis framework for such processes.

Good initialization model with constrained body structure for scene text recognition

NASA Astrophysics Data System (ADS)

Zhu, Anna; Wang, Guoyou; Dong, Yangbo

2016-09-01

Scene text recognition has gained significant attention in the computer vision community. Character detection and recognition are the promise of text recognition and affect the overall performance to a large extent. We proposed a good initialization model for scene character recognition from cropped text regions. We use constrained character's body structures with deformable part-based models to detect and recognize characters in various backgrounds. The character's body structures are achieved by an unsupervised discriminative clustering approach followed by a statistical model and a self-build minimum spanning tree model. Our method utilizes part appearance and location information, and combines character detection and recognition in cropped text region together. The evaluation results on the benchmark datasets demonstrate that our proposed scheme outperforms the state-of-the-art methods both on scene character recognition and word recognition aspects.

Split Bregman multicoil accelerated reconstruction technique: A new framework for rapid reconstruction of cardiac perfusion MRI

PubMed Central

Kamesh Iyer, Srikant; Tasdizen, Tolga; Likhite, Devavrat; DiBella, Edward

2016-01-01

Purpose: Rapid reconstruction of undersampled multicoil MRI data with iterative constrained reconstruction method is a challenge. The authors sought to develop a new substitution based variable splitting algorithm for faster reconstruction of multicoil cardiac perfusion MRI data. Methods: The new method, split Bregman multicoil accelerated reconstruction technique (SMART), uses a combination of split Bregman based variable splitting and iterative reweighting techniques to achieve fast convergence. Total variation constraints are used along the spatial and temporal dimensions. The method is tested on nine ECG-gated dog perfusion datasets, acquired with a 30-ray golden ratio radial sampling pattern and ten ungated human perfusion datasets, acquired with a 24-ray golden ratio radial sampling pattern. Image quality and reconstruction speed are evaluated and compared to a gradient descent (GD) implementation and to multicoil k-t SLR, a reconstruction technique that uses a combination of sparsity and low rank constraints. Results: Comparisons based on blur metric and visual inspection showed that SMART images had lower blur and better texture as compared to the GD implementation. On average, the GD based images had an ∼18% higher blur metric as compared to SMART images. Reconstruction of dynamic contrast enhanced (DCE) cardiac perfusion images using the SMART method was ∼6 times faster than standard gradient descent methods. k-t SLR and SMART produced images with comparable image quality, though SMART was ∼6.8 times faster than k-t SLR. Conclusions: The SMART method is a promising approach to reconstruct good quality multicoil images from undersampled DCE cardiac perfusion data rapidly. PMID:27036592

A COMBINED SPECTROSCOPIC AND PHOTOMETRIC STELLAR ACTIVITY STUDY OF EPSILON ERIDANI

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

Giguere, Matthew J.; Fischer, Debra A.; Zhang, Cyril X. Y.

2016-06-20

We present simultaneous ground-based radial velocity (RV) measurements and space-based photometric measurements of the young and active K dwarf Epsilon Eridani. These measurements provide a data set for exploring methods of identifying and ultimately distinguishing stellar photospheric velocities from Keplerian motion. We compare three methods we have used in exploring this data set: Dalmatian, an MCMC spot modeling code that fits photometric and RV measurements simultaneously; the FF′ method, which uses photometric measurements to predict the stellar activity signal in simultaneous RV measurements; and H α analysis. We show that our H α measurements are strongly correlated with the Microvariabilitymore » and Oscillations of STars telescope ( MOST ) photometry, which led to a promising new method based solely on the spectroscopic observations. This new method, which we refer to as the HH′ method, uses H α measurements as input into the FF′ model. While the Dalmatian spot modeling analysis and the FF′ method with MOST space-based photometry are currently more robust, the HH′ method only makes use of one of the thousands of stellar lines in the visible spectrum. By leveraging additional spectral activity indicators, we believe the HH′ method may prove quite useful in disentangling stellar signals.« less

Fabrication of spherical microlens array by combining lapping on silicon wafer and rapid surface molding

NASA Astrophysics Data System (ADS)

Liu, Xiaohua; Zhou, Tianfeng; Zhang, Lin; Zhou, Wenchen; Yu, Jianfeng; Lee, L. James; Yi, Allen Y.

2018-07-01

Silicon is a promising mold material for compression molding because of its properties of hardness and abrasion resistance. Silicon wafers with carbide-bonded graphene coating and micro-patterns were evaluated as molds for the fabrication of microlens arrays. This study presents an efficient but flexible manufacturing method for microlens arrays that combines a lapping method and a rapid molding procedure. Unlike conventional processes for microstructures on silicon wafers, such as diamond machining and photolithography, this research demonstrates a unique approach by employing precision steel balls and diamond slurries to create microlenses with accurate geometry. The feasibility of this method was demonstrated by the fabrication of several microlens arrays with different aperture sizes and pitches on silicon molds. The geometrical accuracy and surface roughness of the microlens arrays were measured using an optical profiler. The measurement results indicated good agreement with the optical profile of the design. The silicon molds were then used to copy the microstructures onto polymer substrates. The uniformity and quality of the samples molded through rapid surface molding were also assessed and statistically quantified. To further evaluate the optical functionality of the molded microlens arrays, the focal lengths of the microlens arrays were measured using a simple optical setup. The measurements showed that the microlens arrays molded in this research were compatible with conventional manufacturing methods. This research demonstrated an alternative low-cost and efficient method for microstructure fabrication on silicon wafers, together with the follow-up optical molding processes.

Numerical Predictions of Wind Turbine Power and Aerodynamic Loads for the NREL Phase II and IV Combined Experiment Rotor

NASA Technical Reports Server (NTRS)

Duque, Earl P. N.; Johnson, Wayne; vanDam, C. P.; Chao, David D.; Cortes, Regina; Yee, Karen

1999-01-01

Accurate, reliable and robust numerical predictions of wind turbine rotor power remain a challenge to the wind energy industry. The literature reports various methods that compare predictions to experiments. The methods vary from Blade Element Momentum Theory (BEM), Vortex Lattice (VL), to variants of Reynolds-averaged Navier-Stokes (RaNS). The BEM and VL methods consistently show discrepancies in predicting rotor power at higher wind speeds mainly due to inadequacies with inboard stall and stall delay models. The RaNS methodologies show promise in predicting blade stall. However, inaccurate rotor vortex wake convection, boundary layer turbulence modeling and grid resolution has limited their accuracy. In addition, the inherently unsteady stalled flow conditions become computationally expensive for even the best endowed research labs. Although numerical power predictions have been compared to experiment. The availability of good wind turbine data sufficient for code validation experimental data that has been extracted from the IEA Annex XIV download site for the NREL Combined Experiment phase II and phase IV rotor. In addition, the comparisons will show data that has been further reduced into steady wind and zero yaw conditions suitable for comparisons to "steady wind" rotor power predictions. In summary, the paper will present and discuss the capabilities and limitations of the three numerical methods and make available a database of experimental data suitable to help other numerical methods practitioners validate their own work.

An Investigation of Mathematically Promising Students' Cognitive Abilities and Their Contributions to Learning Environment

ERIC Educational Resources Information Center

Budak, Ibrahim; Kaygin, Bulent

2015-01-01

In this study, through the observation of mathematically promising students in regular classrooms, relevant learning environments and the learning needs of promising students, teacher approaches and teaching methods, and the differences between the promising students and their normal ability peers in the same classroom were investigated.…

Combining Neutron and Magnetic Resonance Imaging to Study the Interaction of Plant Roots and Soil

NASA Astrophysics Data System (ADS)

Oswald, Sascha E.; Tötzke, Christian; Haber-Pohlmeier, Sabina; Pohlmeier, Andreas; Kaestner, Anders P.; Lehmann, Eberhard

The soil in direct vicinity of the roots, the root-soil interface or so called rhizosphere, is heavily modified by the activity of roots, compared to bulk soil, e.g. in respect to microbiology and soil chemistry. It has turned out that the root-soil interface, though small in size, also plays a decisive role in the hydraulics controlling the water flow from bulk soil into the roots. A promising approach for the non-invasive investigation of water dynamics, water flow and solute transport is the combination of the two imaging techniques magnetic resonance imaging (MRI) and neutron imaging (NI). Both methods are complementary, because NI maps the total proton density, possibly amplified by NI tracers, which usually corresponds to total water content, and is able to detect changes and spatial patterns with high resolution. On the other side, nuclear magnetic resonance relaxation times reflect the interaction between fluid and matrix, while also a mapping of proton spin density and thus water content is possible. Therefore MRI is able to classify different water pools via their relaxation times additionally to the water distribution inside soil as a porous medium. We have started such combined measurements with the approach to use the same samples and perform tomography with each imaging method at different location and short-term sample transfer.

Manifold Learning in MR spectroscopy using nonlinear dimensionality reduction and unsupervised clustering.

PubMed

Yang, Guang; Raschke, Felix; Barrick, Thomas R; Howe, Franklyn A

2015-09-01

To investigate whether nonlinear dimensionality reduction improves unsupervised classification of (1) H MRS brain tumor data compared with a linear method. In vivo single-voxel (1) H magnetic resonance spectroscopy (55 patients) and (1) H magnetic resonance spectroscopy imaging (MRSI) (29 patients) data were acquired from histopathologically diagnosed gliomas. Data reduction using Laplacian eigenmaps (LE) or independent component analysis (ICA) was followed by k-means clustering or agglomerative hierarchical clustering (AHC) for unsupervised learning to assess tumor grade and for tissue type segmentation of MRSI data. An accuracy of 93% in classification of glioma grade II and grade IV, with 100% accuracy in distinguishing tumor and normal spectra, was obtained by LE with unsupervised clustering, but not with the combination of k-means and ICA. With (1) H MRSI data, LE provided a more linear distribution of data for cluster analysis and better cluster stability than ICA. LE combined with k-means or AHC provided 91% accuracy for classifying tumor grade and 100% accuracy for identifying normal tissue voxels. Color-coded visualization of normal brain, tumor core, and infiltration regions was achieved with LE combined with AHC. The LE method is promising for unsupervised clustering to separate brain and tumor tissue with automated color-coding for visualization of (1) H MRSI data after cluster analysis. © 2014 Wiley Periodicals, Inc.

A Non-Destructive Method for Distinguishing Reindeer Antler (Rangifer tarandus) from Red Deer Antler (Cervus elaphus) Using X-Ray Micro-Tomography Coupled with SVM Classifiers

PubMed Central

Lefebvre, Alexandre; Rochefort, Gael Y.; Santos, Frédéric; Le Denmat, Dominique; Salmon, Benjamin; Pétillon, Jean-Marc

2016-01-01

Over the last decade, biomedical 3D-imaging tools have gained widespread use in the analysis of prehistoric bone artefacts. While initial attempts to characterise the major categories used in osseous industry (i.e. bone, antler, and dentine/ivory) have been successful, the taxonomic determination of prehistoric artefacts remains to be investigated. The distinction between reindeer and red deer antler can be challenging, particularly in cases of anthropic and/or taphonomic modifications. In addition to the range of destructive physicochemical identification methods available (mass spectrometry, isotopic ratio, and DNA analysis), X-ray micro-tomography (micro-CT) provides convincing non-destructive 3D images and analyses. This paper presents the experimental protocol (sample scans, image processing, and statistical analysis) we have developed in order to identify modern and archaeological antler collections (from Isturitz, France). This original method is based on bone microstructure analysis combined with advanced statistical support vector machine (SVM) classifiers. A combination of six microarchitecture biomarkers (bone volume fraction, trabecular number, trabecular separation, trabecular thickness, trabecular bone pattern factor, and structure model index) were screened using micro-CT in order to characterise internal alveolar structure. Overall, reindeer alveoli presented a tighter mesh than red deer alveoli, and statistical analysis allowed us to distinguish archaeological antler by species with an accuracy of 96%, regardless of anatomical location on the antler. In conclusion, micro-CT combined with SVM classifiers proves to be a promising additional non-destructive method for antler identification, suitable for archaeological artefacts whose degree of human modification and cultural heritage or scientific value has previously made it impossible (tools, ornaments, etc.). PMID:26901355

Exploring the optimal integration levels between SAR and optical data for better urban land cover mapping in the Pearl River Delta

NASA Astrophysics Data System (ADS)

Zhang, Hongsheng; Xu, Ru

2018-02-01

Integrating synthetic aperture radar (SAR) and optical data to improve urban land cover classification has been identified as a promising approach. However, which integration level is the most suitable remains unclear but important to many researchers and engineers. This study aimed to compare different integration levels for providing a scientific reference for a wide range of studies using optical and SAR data. SAR data from TerraSAR-X and ENVISAT ASAR in both WSM and IMP modes were used to be combined with optical data at pixel level, feature level and decision levels using four typical machine learning methods. The experimental results indicated that: 1) feature level that used both the original images and extracted features achieved a significant improvement of up to 10% compared to that using optical data alone; 2) different levels of fusion required different suitable methods depending on the data distribution and data resolution. For instance, support vector machine was the most stable at both the feature and decision levels, while random forest was suitable at the pixel level but not suitable at the decision level. 3) By examining the distribution of SAR features, some features (e.g., homogeneity) exhibited a close-to-normal distribution, explaining the improvement from the maximum likelihood method at the feature and decision levels. This indicated the benefits of using texture features from SAR data when being combined with optical data for land cover classification. Additionally, the research also shown that combining optical and SAR data does not guarantee improvement compared with using single data source for urban land cover classification, depending on the selection of appropriate fusion levels and fusion methods.

Self-Assembled Nanoparticles from Phenolic Derivatives for Cancer Therapy.

PubMed

Dai, Yunlu; Guo, Junling; Wang, Ting-Yi; Ju, Yi; Mitchell, Andrew J; Bonnard, Thomas; Cui, Jiwei; Richardson, Joseph J; Hagemeyer, Christoph E; Alt, Karen; Caruso, Frank

2017-08-01

Therapeutic nanoparticles hold clinical promise for cancer treatment by avoiding limitations of conventional pharmaceuticals. Herein, a facile and rapid method is introduced to assemble poly(ethylene glycol) (PEG)-modified Pt prodrug nanocomplexes through metal-polyphenol complexation and combined with emulsification, which results in ≈100 nm diameter nanoparticles (PtP NPs) that exhibit high drug loading (0.15 fg Pt per nanoparticle) and low fouling properties. The PtP NPs are characterized for potential use as cancer therapeutics. Mass cytometry is used to quantify uptake of the nanoparticles and the drug concentration in individual cells in vitro. The PtP NPs have long circulation times, with an elimination half-life of ≈18 h in healthy mice. The in vivo antitumor activity of the PtP NPs is systematically investigated in a human prostate cancer xenograft mouse model. Mice treated with the PtP NPs demonstrate four times better inhibition of tumor growth than either free prodrug or cisplatin. This study presents a promising strategy to prepare therapeutic nanoparticles for biomedical applications. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The multifaceted interplay between lipids and epigenetics.

PubMed

Dekkers, Koen F; Slagboom, P Eline; Jukema, J Wouter; Heijmans, Bastiaan T

2016-06-01

The interplay between lipids and epigenetic mechanisms has recently gained increased interest because of its relevance for common diseases and most notably atherosclerosis. This review discusses recent advances in unravelling this interplay with a particular focus on promising approaches and methods that will be able to establish causal relationships. Complementary approaches uncovered close links between circulating lipids and epigenetic mechanisms at multiple levels. A characterization of lipid-associated genetic variants suggests that these variants exert their influence on lipid levels through epigenetic changes in the liver. Moreover, exposure of monocytes to lipids persistently alters their epigenetic makeup resulting in more proinflammatory cells. Hence, epigenetic changes can both impact on and be induced by lipids. It is the combined application of technological advances to probe epigenetic modifications at a genome-wide scale and methodological advances aimed at causal inference (including Mendelian randomization and integrative genomics) that will elucidate the interplay between circulating lipids and epigenetics. Understanding its role in the development of atherosclerosis holds the promise of identifying a new category of therapeutic targets, since epigenetic changes are amenable to reversal.

Utilization of Telehealth Technology to Develop and Implement a Comprehensive Management Initiative for Chronic Diseases

DTIC Science & Technology

2010-10-21

involving oral or injectable regimens for type 2 diabetes, alone or in various combinations . The program indicates which dose or doses of medications...educational access. Virtual diabetes education techniques that combine best educational practices with telehealth technology offer a promising solution to...patterns over time, so we combined these two groups to simplify interpretation of the results. The analyses tested for group differences in

Combination of physical activity, nutrition, or other metabolic factors and vaccine response

PubMed Central

Hance, Kenneth W.; Rogers, Connie J.; Hursting, Stephen D.; Greiner, John W.

2010-01-01

A number of lifestyle factors that reduce cancer risk in the primary prevention setting may be potential new targets for use in combination with cancer vaccines. This review discusses the modulation of energy balance (physical activity, calorie restriction, and obesity prevention), and the supplementation with natural and synthetic analogs of vitamins A and E, as potential interventions for use in combination with cancer vaccines. Additionally, the pharmacologic manipulation of nutrient metabolism in the tumor microenvironment (e.g., arachidonic acid, arginine, tryptophan, and glucose metabolism) is discussed. This review includes a brief overview of the role of each agent in primary cancer prevention; outlines the effects of these agents on immune function, specifically adaptive and/or anti-tumor immune mechanisms, when known; and discusses the potential use of these interventions in combination with therapeutic cancer vaccines. Modulation of energy balance through exercise and strategies targeting nutrient metabolism in the tumor microenvironment represent the most promising interventions to partner with therapeutic cancer vaccines. Additionally, the use of vitamin E succinate and the retinoid X receptor-directed rexinoids in combination with cancer vaccines offer promise. In summary, a number of energy balance- and nutrition-related interventions are viable candidates for further study in combination with cancer vaccines. PMID:17569626

Targeting different pathophysiological events after traumatic brain injury in mice: Role of melatonin and memantine.

PubMed

Kelestemur, Taha; Yulug, Burak; Caglayan, Ahmet Burak; Beker, Mustafa Caglar; Kilic, Ulkan; Caglayan, Berrak; Yalcin, Esra; Gundogdu, Reyhan Zeynep; Kilic, Ertugrul

2016-01-26

The tissue damage that emerges during traumatic brain injury (TBI) is a consequence of a variety of pathophysiological events, including free radical generation and over-activation of N-methyl-d-aspartate-type glutamate receptors (NMDAR). Considering the complex pathophysiology of TBI, we hypothesized that combination of neuroprotective compounds, targeting different events which appear during injury, may be a more promising approach for patients. In this context, both NMDAR antagonist memantine and free radical scavenger melatonin are safe in humans and promising agents for the treatment of TBI. Herein, we examined the effects of melatonin administered alone or in combination with memantine on the activation of signaling pathways, injury development and DNA fragmentation. Both compounds reduced brain injury moderately and the density of DNA fragmentation significantly. Notably, melatonin/memantine combination decreased brain injury and DNA fragmentation significantly, which was associated with reduced p38 and ERK-1/2 phosphorylation. As compared with melatonin and memantine groups, SAPK/JNK-1/2 phosphorylation was also reduced in melatonin/memantine combined animals. In addition, melatonin, memantine and their combination decreased iNOS activity significantly. Here, we provide evidence that melatonin/memantine combination protects brain from traumatic injury, which was associated with decreased DNA fragmentation, p38 phosphorylation and iNOS activity. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Regenerative medicine for the respiratory system: distant future or tomorrow's treatment?

PubMed

Brouwer, Katrien M; Hoogenkamp, Henk R; Daamen, Willeke F; van Kuppevelt, Toin H

2013-03-01

Regenerative medicine (RM) is a new field of biomedical science that focuses on the regeneration of tissues and organs and the restoration of organ function. Although regeneration of organ systems such as bone, cartilage, and heart has attracted intense scientific research over recent decades, RM research regarding the respiratory system, including the trachea, the lung proper, and the diaphragm, has lagged behind. However, the last 5 years have witnessed novel approaches and initial clinical applications of tissue-engineered constructs to restore organ structure and function. In this regard, this article briefly addresses the basics of RM and introduces the key elements necessary for tissue regeneration, including (stem) cells, biomaterials, and extracellular matrices. In addition, the current status of the (clinical) application of RM to the respiratory system is discussed, and bottlenecks and recent approaches are identified. For the trachea, several initial clinical studies have been reported and have used various combinations of cells and scaffolds. Although promising, the methods used in these studies require optimization and standardization. For the lung proper, only (stem) cell-based approaches have been probed clinically, but it is becoming apparent that combinations of cells and scaffolds are required to successfully restore the lung's architecture and function. In the case of the diaphragm, clinical applications have focused on the use of decellularized scaffolds, but novel scaffolds, with or without cells, are clearly needed for true regeneration of diaphragmatic tissue. We conclude that respiratory treatment with RM will not be realized tomorrow, but its future looks promising.

Simulations of defect spin qubits in piezoelectric semiconductors

NASA Astrophysics Data System (ADS)

Seo, Hosung

In recent years, remarkable advances have been reported in the development of defect spin qubits in semiconductors for solid-state quantum information science and quantum metrology. Promising spin qubits include the nitrogen-vacancy center in diamond, dopants in silicon, and the silicon vacancy and divacancy spins in silicon carbide. In this talk, I will highlight some of our recent efforts devoted to defect spin qubits in piezoelectric wide-gap semiconductors for potential applications in mechanical hybrid quantum systems. In particular, I will describe our recent combined theoretical and experimental study on remarkably robust quantum coherence found in the divancancy qubits in silicon carbide. We used a quantum bath model combined with a cluster expansion method to identify the microscopic mechanisms behind the unusually long coherence times of the divacancy spins in SiC. Our study indicates that developing spin qubits in complex crystals with multiple types of atom is a promising route to realize strongly coherent hybrid quantum systems. I will also discuss progress and challenges in computational design of new spin defects for use as qubits in piezoelectric crystals such as AlN and SiC, including a new defect design concept using large metal ion - vacancy complexes. Our first principles calculations include DFT computations using recently developed self-consistent hybrid density functional theory and large-scale many-body GW theory. This work was supported by the National Science Foundation (NSF) through the University of Chicago MRSEC under Award Number DMR-1420709.

Development of ultrahigh resolution alpha particle imaging detector using 1 mm channel size Si-PM array

NASA Astrophysics Data System (ADS)

Yamamoto, Seiichi; Kawaguchi, Wataru

2018-06-01

For precise distribution measurements of alpha particles, a high-resolution alpha particle imaging detector is required. Although combining a thin scintillator with a silicon photomultiplier (Si-PM) array is a promising method for achieving high resolution, the spatial resolution is limited. Reducing the size of the Si-PM array is a possible approach to improving the spatial resolution of the alpha particle imaging detector. Consequently, we employed a 1 mm channel size Si-PM array combined with a thin ZnS(Ag) sheet to form an alpha particle imaging detector and evaluated the performance. For the developed alpha particle imaging detector, an Si-PM array with 1 mm x 1 mm channel size arranged 8 x 8 was optically coupled to a ZnS(Ag) sheet with a 1-mm-thick light guide between them. The size of the alpha particle imaging detector was 9.5 mm x 9.5 mm. The spatial resolution of the developed alpha particle imaging detector was 0.14 mm FWHM, and the energy resolution was 74% FWHM for 5.5 MeV alpha particles. The uniformity of the imaging detector at the central part of the field of view (FOV) was ±4.7%. The background count rate was 0.06 counts/min. We obtained various high-resolution phantom images for alpha particles with the developed system. We conclude that the developed imaging detector is promising for high-resolution distribution measurements of alpha particles.

A multiple distributed representation method based on neural network for biomedical event extraction.

PubMed

Wang, Anran; Wang, Jian; Lin, Hongfei; Zhang, Jianhai; Yang, Zhihao; Xu, Kan

2017-12-20

Biomedical event extraction is one of the most frontier domains in biomedical research. The two main subtasks of biomedical event extraction are trigger identification and arguments detection which can both be considered as classification problems. However, traditional state-of-the-art methods are based on support vector machine (SVM) with massive manually designed one-hot represented features, which require enormous work but lack semantic relation among words. In this paper, we propose a multiple distributed representation method for biomedical event extraction. The method combines context consisting of dependency-based word embedding, and task-based features represented in a distributed way as the input of deep learning models to train deep learning models. Finally, we used softmax classifier to label the example candidates. The experimental results on Multi-Level Event Extraction (MLEE) corpus show higher F-scores of 77.97% in trigger identification and 58.31% in overall compared to the state-of-the-art SVM method. Our distributed representation method for biomedical event extraction avoids the problems of semantic gap and dimension disaster from traditional one-hot representation methods. The promising results demonstrate that our proposed method is effective for biomedical event extraction.

Prosthetic component segmentation with blur compensation: a fast method for 3D fluoroscopy.

PubMed

Tarroni, Giacomo; Tersi, Luca; Corsi, Cristiana; Stagni, Rita

2012-06-01

A new method for prosthetic component segmentation from fluoroscopic images is presented. The hybrid approach we propose combines diffusion filtering, region growing and level-set techniques without exploiting any a priori knowledge of the analyzed geometry. The method was evaluated on a synthetic dataset including 270 images of knee and hip prosthesis merged to real fluoroscopic data simulating different conditions of blurring and illumination gradient. The performance of the method was assessed by comparing estimated contours to references using different metrics. Results showed that the segmentation procedure is fast, accurate, independent on the operator as well as on the specific geometrical characteristics of the prosthetic component, and able to compensate for amount of blurring and illumination gradient. Importantly, the method allows a strong reduction of required user interaction time when compared to traditional segmentation techniques. Its effectiveness and robustness in different image conditions, together with simplicity and fast implementation, make this prosthetic component segmentation procedure promising and suitable for multiple clinical applications including assessment of in vivo joint kinematics in a variety of cases.

Retrieving hydrological connectivity from empirical causality in karst systems

NASA Astrophysics Data System (ADS)

Delforge, Damien; Vanclooster, Marnik; Van Camp, Michel; Poulain, Amaël; Watlet, Arnaud; Hallet, Vincent; Kaufmann, Olivier; Francis, Olivier

2017-04-01

Because of their complexity, karst systems exhibit nonlinear dynamics. Moreover, if one attempts to model a karst, the hidden behavior complicates the choice of the most suitable model. Therefore, both intense investigation methods and nonlinear data analysis are needed to reveal the underlying hydrological connectivity as a prior for a consistent physically based modelling approach. Convergent Cross Mapping (CCM), a recent method, promises to identify causal relationships between time series belonging to the same dynamical systems. The method is based on phase space reconstruction and is suitable for nonlinear dynamics. As an empirical causation detection method, it could be used to highlight the hidden complexity of a karst system by revealing its inner hydrological and dynamical connectivity. Hence, if one can link causal relationships to physical processes, the method should show great potential to support physically based model structure selection. We present the results of numerical experiments using karst model blocks combined in different structures to generate time series from actual rainfall series. CCM is applied between the time series to investigate if the empirical causation detection is consistent with the hydrological connectivity suggested by the karst model.

A fuzzy integral method based on the ensemble of neural networks to analyze fMRI data for cognitive state classification across multiple subjects.

PubMed

Cacha, L A; Parida, S; Dehuri, S; Cho, S-B; Poznanski, R R

2016-12-01

The huge number of voxels in fMRI over time poses a major challenge to for effective analysis. Fast, accurate, and reliable classifiers are required for estimating the decoding accuracy of brain activities. Although machine-learning classifiers seem promising, individual classifiers have their own limitations. To address this limitation, the present paper proposes a method based on the ensemble of neural networks to analyze fMRI data for cognitive state classification for application across multiple subjects. Similarly, the fuzzy integral (FI) approach has been employed as an efficient tool for combining different classifiers. The FI approach led to the development of a classifiers ensemble technique that performs better than any of the single classifier by reducing the misclassification, the bias, and the variance. The proposed method successfully classified the different cognitive states for multiple subjects with high accuracy of classification. Comparison of the performance improvement, while applying ensemble neural networks method, vs. that of the individual neural network strongly points toward the usefulness of the proposed method.

Simultaneous assessment of phase chemistry, phase abundance and bulk chemistry with statistical electron probe micro-analyses: Application to cement clinkers

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

Wilson, William; Krakowiak, Konrad J.; Ulm, Franz-Josef, E-mail: ulm@mit.edu

2014-01-15

According to recent developments in cement clinker engineering, the optimization of chemical substitutions in the main clinker phases offers a promising approach to improve both reactivity and grindability of clinkers. Thus, monitoring the chemistry of the phases may become part of the quality control at the cement plants, along with the usual measurements of the abundance of the mineralogical phases (quantitative X-ray diffraction) and the bulk chemistry (X-ray fluorescence). This paper presents a new method to assess these three complementary quantities with a single experiment. The method is based on electron microprobe spot analyses, performed over a grid located onmore » a representative surface of the sample and interpreted with advanced statistical tools. This paper describes the method and the experimental program performed on industrial clinkers to establish the accuracy in comparison to conventional methods. -- Highlights: •A new method of clinker characterization •Combination of electron probe technique with cluster analysis •Simultaneous assessment of phase abundance, composition and bulk chemistry •Experimental validation performed on industrial clinkers.« less

Robust prediction of protein subcellular localization combining PCA and WSVMs.

PubMed

Tian, Jiang; Gu, Hong; Liu, Wenqi; Gao, Chiyang

2011-08-01

Automated prediction of protein subcellular localization is an important tool for genome annotation and drug discovery, and Support Vector Machines (SVMs) can effectively solve this problem in a supervised manner. However, the datasets obtained from real experiments are likely to contain outliers or noises, which can lead to poor generalization ability and classification accuracy. To explore this problem, we adopt strategies to lower the effect of outliers. First we design a method based on Weighted SVMs, different weights are assigned to different data points, so the training algorithm will learn the decision boundary according to the relative importance of the data points. Second we analyse the influence of Principal Component Analysis (PCA) on WSVM classification, propose a hybrid classifier combining merits of both PCA and WSVM. After performing dimension reduction operations on the datasets, kernel-based possibilistic c-means algorithm can generate more suitable weights for the training, as PCA transforms the data into a new coordinate system with largest variances affected greatly by the outliers. Experiments on benchmark datasets show promising results, which confirms the effectiveness of the proposed method in terms of prediction accuracy. Copyright © 2011 Elsevier Ltd. All rights reserved.

Recent applications of multivariate data analysis methods in the authentication of rice and the most analyzed parameters: A review.

PubMed

Maione, Camila; Barbosa, Rommel Melgaço

2018-01-24

Rice is one of the most important staple foods around the world. Authentication of rice is one of the most addressed concerns in the present literature, which includes recognition of its geographical origin and variety, certification of organic rice and many other issues. Good results have been achieved by multivariate data analysis and data mining techniques when combined with specific parameters for ascertaining authenticity and many other useful characteristics of rice, such as quality, yield and others. This paper brings a review of the recent research projects on discrimination and authentication of rice using multivariate data analysis and data mining techniques. We found that data obtained from image processing, molecular and atomic spectroscopy, elemental fingerprinting, genetic markers, molecular content and others are promising sources of information regarding geographical origin, variety and other aspects of rice, being widely used combined with multivariate data analysis techniques. Principal component analysis and linear discriminant analysis are the preferred methods, but several other data classification techniques such as support vector machines, artificial neural networks and others are also frequently present in some studies and show high performance for discrimination of rice.

Promotional communications for influenza vaccination: a systematic review.

PubMed

Macdonald, Laura; Cairns, Georgina; Angus, Kathryn; de Andrade, Marisa

2013-01-01

The authors conducted a systematic review that aimed to map current practice and identify effective practice in promotional communications for seasonal influenza vaccination in Europe. They identified 22 studies from 7 European countries. Included studies were primarily outcome evaluations of communications promoting vaccination to health care workers and elderly adults. Evidence on communications to improve public acceptance was sparse. A range of communication approaches, methods, materials, and channels were used, frequently in combination. All forms of promotional communications have the potential to increase uptake in health care workers and can also improve uptake among patients. There was promising evidence that mass communication methods, delivered as standalone activities or as one component of a communication mix, can improve uptake in target populations. Education for health care workers and improved service delivery are common adjuncts to promotional communications that were associated with effectiveness. The evidence suggests that personalized communications, combined with improved service delivery, might boost rates of uptake among elderly adults. Future development of good practice could be enhanced by more systematic, theory-based intervention design and more detailed reporting of process and outcome evaluations. Vaccine hesitancy is increasingly prevalent; more policy and research to improve public acceptance should therefore be considered.

A self-sensing magnetorheological damper with power generation

NASA Astrophysics Data System (ADS)

Chen, Chao; Liao, Wei-Hsin

2012-02-01

Magnetorheological (MR) dampers are promising for semi-active vibration control of various dynamic systems. In the current MR damper systems, a separate power supply and dynamic sensor are required. To enable the MR damper to be self-powered and self-sensing in the future, in this paper we propose and investigate a self-sensing MR damper with power generation, which integrates energy harvesting, dynamic sensing and MR damping technologies into one device. This MR damper has self-contained power generation and velocity sensing capabilities, and is applicable to various dynamic systems. It combines the advantages of energy harvesting—reusing wasted energy, MR damping—controllable damping force, and sensing—providing dynamic information for controlling system dynamics. This multifunctional integration would bring great benefits such as energy saving, size and weight reduction, lower cost, high reliability, and less maintenance for the MR damper systems. In this paper, a prototype of the self-sensing MR damper with power generation was designed, fabricated, and tested. Theoretical analyses and experimental studies on power generation were performed. A velocity-sensing method was proposed and experimentally validated. The magnetic-field interference among three functions was prevented by a combined magnetic-field isolation method. Modeling, analysis, and experimental results on damping forces are also presented.

Gland segmentation in prostate histopathological images

PubMed Central

Singh, Malay; Kalaw, Emarene Mationg; Giron, Danilo Medina; Chong, Kian-Tai; Tan, Chew Lim; Lee, Hwee Kuan

2017-01-01

Abstract. Glandular structural features are important for the tumor pathologist in the assessment of cancer malignancy of prostate tissue slides. The varying shapes and sizes of glands combined with the tedious manual observation task can result in inaccurate assessment. There are also discrepancies and low-level agreement among pathologists, especially in cases of Gleason pattern 3 and pattern 4 prostate adenocarcinoma. An automated gland segmentation system can highlight various glandular shapes and structures for further analysis by the pathologist. These objective highlighted patterns can help reduce the assessment variability. We propose an automated gland segmentation system. Forty-three hematoxylin and eosin-stained images were acquired from prostate cancer tissue slides and were manually annotated for gland, lumen, periacinar retraction clefting, and stroma regions. Our automated gland segmentation system was trained using these manual annotations. It identifies these regions using a combination of pixel and object-level classifiers by incorporating local and spatial information for consolidating pixel-level classification results into object-level segmentation. Experimental results show that our method outperforms various texture and gland structure-based gland segmentation algorithms in the literature. Our method has good performance and can be a promising tool to help decrease interobserver variability among pathologists. PMID:28653016

Particle based vaccine formulations for transcutaneous immunization.

PubMed

Mittal, Ankit; Raber, Anne S; Lehr, Claus-Michael; Hansen, Steffi

2013-09-01

Vaccine formulations on the basis of nano- (NP) or microparticles (MP) can solve issues with stabilization, controlled release, and poor immunogenicity of antigens. Likewise transcutaneous immunization (TCI) promises superior immunogenicity as well as the advantages of needle-free application compared with conventional intramuscular injections. Thus the combination of both strategies seems to be a very valuable approach. However, until now TCI using particle based vaccine formulations has made no impact on medical practice. One of the main difficulties is that NPs and MPs cannot penetrate the skin to an extent that would allow the application of the required dose of antigen. This is due to the formidable stratum corneum (SC) barrier, the limited amount of antigen in the formulation and often an insufficient immunogenicity. A multitude of strategies are currently under investigation to overcome these issues. We highlight selected methods presenting a spectrum of solutions ranging from transfollicular delivery, to devices disrupting the SC barrier and the combination of particle based vaccines with adjuvants discussing their advantages and shortcomings. Some of these are currently at an experimental state while others are already in clinical testing. All methods have been shown to be capable of transcutaneous antigen delivery.

Conservative strategy-based ensemble surrogate model for optimal groundwater remediation design at DNAPLs-contaminated sites

NASA Astrophysics Data System (ADS)

Ouyang, Qi; Lu, Wenxi; Lin, Jin; Deng, Wenbing; Cheng, Weiguo

2017-08-01

The surrogate-based simulation-optimization techniques are frequently used for optimal groundwater remediation design. When this technique is used, surrogate errors caused by surrogate-modeling uncertainty may lead to generation of infeasible designs. In this paper, a conservative strategy that pushes the optimal design into the feasible region was used to address surrogate-modeling uncertainty. In addition, chance-constrained programming (CCP) was adopted to compare with the conservative strategy in addressing this uncertainty. Three methods, multi-gene genetic programming (MGGP), Kriging (KRG) and support vector regression (SVR), were used to construct surrogate models for a time-consuming multi-phase flow model. To improve the performance of the surrogate model, ensemble surrogates were constructed based on combinations of different stand-alone surrogate models. The results show that: (1) the surrogate-modeling uncertainty was successfully addressed by the conservative strategy, which means that this method is promising for addressing surrogate-modeling uncertainty. (2) The ensemble surrogate model that combines MGGP with KRG showed the most favorable performance, which indicates that this ensemble surrogate can utilize both stand-alone surrogate models to improve the performance of the surrogate model.

Retreatment Predictions in Odontology by means of CBR Systems.

PubMed

Campo, Livia; Aliaga, Ignacio J; De Paz, Juan F; García, Alvaro Enrique; Bajo, Javier; Villarubia, Gabriel; Corchado, Juan M

2016-01-01

The field of odontology requires an appropriate adjustment of treatments according to the circumstances of each patient. A follow-up treatment for a patient experiencing problems from a previous procedure such as endodontic therapy, for example, may not necessarily preclude the possibility of extraction. It is therefore necessary to investigate new solutions aimed at analyzing data and, with regard to the given values, determine whether dental retreatment is required. In this work, we present a decision support system which applies the case-based reasoning (CBR) paradigm, specifically designed to predict the practicality of performing or not performing a retreatment. Thus, the system uses previous experiences to provide new predictions, which is completely innovative in the field of odontology. The proposed prediction technique includes an innovative combination of methods that minimizes false negatives to the greatest possible extent. False negatives refer to a prediction favoring a retreatment when in fact it would be ineffective. The combination of methods is performed by applying an optimization problem to reduce incorrect classifications and takes into account different parameters, such as precision, recall, and statistical probabilities. The proposed system was tested in a real environment and the results obtained are promising.

Retreatment Predictions in Odontology by means of CBR Systems

PubMed Central

Campo, Livia; Aliaga, Ignacio J.; García, Alvaro Enrique; Villarubia, Gabriel; Corchado, Juan M.

2016-01-01

The field of odontology requires an appropriate adjustment of treatments according to the circumstances of each patient. A follow-up treatment for a patient experiencing problems from a previous procedure such as endodontic therapy, for example, may not necessarily preclude the possibility of extraction. It is therefore necessary to investigate new solutions aimed at analyzing data and, with regard to the given values, determine whether dental retreatment is required. In this work, we present a decision support system which applies the case-based reasoning (CBR) paradigm, specifically designed to predict the practicality of performing or not performing a retreatment. Thus, the system uses previous experiences to provide new predictions, which is completely innovative in the field of odontology. The proposed prediction technique includes an innovative combination of methods that minimizes false negatives to the greatest possible extent. False negatives refer to a prediction favoring a retreatment when in fact it would be ineffective. The combination of methods is performed by applying an optimization problem to reduce incorrect classifications and takes into account different parameters, such as precision, recall, and statistical probabilities. The proposed system was tested in a real environment and the results obtained are promising. PMID:26884749

A novel method for NDT applications using NXCT system at the Missouri University of Science & Technology

NASA Astrophysics Data System (ADS)

Sinha, Vaibhav; Srivastava, Anjali; Koo Lee, Hyoung

2014-06-01

A novel method for non-destructive analysis has been developed using a neutron/X-ray combined computed tomography (NXCT) system at the Missouri University of Science and Technology Reactor (MSTR). This imaging system takes advantage of the fact that neutrons and X-rays have characteristically different interactions with same materials. NXCT fuses the imaging capabilities of both systems at one location and allows instant evaluation for nondestructive testing (NDT) applications. This technique promises viable advances in the field of NDT. In this paper, the complete design criteria and procedures are provided. The described design criteria and procedures can effectively be utilized to design and develop advanced combined computed tomography system. The successful operation of the high resolution X-ray and neutron computed tomography has been demonstrated in this paper. The utility and importance of the NXCT system has been shown by nondestructive evaluation of various phantoms constituting different materials, geometrical, structural and compositional information. The concept of NXCT can be useful for concealed material detection, material characterization, investigation of complex geometries involving different atomic number materials and real time imaging for in-situ studies.

Efficient universal quantum channel simulation in IBM's cloud quantum computer

NASA Astrophysics Data System (ADS)

Wei, Shi-Jie; Xin, Tao; Long, Gui-Lu

2018-07-01

The study of quantum channels is an important field and promises a wide range of applications, because any physical process can be represented as a quantum channel that transforms an initial state into a final state. Inspired by the method of performing non-unitary operators by the linear combination of unitary operations, we proposed a quantum algorithm for the simulation of the universal single-qubit channel, described by a convex combination of "quasi-extreme" channels corresponding to four Kraus operators, and is scalable to arbitrary higher dimension. We demonstrated the whole algorithm experimentally using the universal IBM cloud-based quantum computer and studied the properties of different qubit quantum channels. We illustrated the quantum capacity of the general qubit quantum channels, which quantifies the amount of quantum information that can be protected. The behavior of quantum capacity in different channels revealed which types of noise processes can support information transmission, and which types are too destructive to protect information. There was a general agreement between the theoretical predictions and the experiments, which strongly supports our method. By realizing the arbitrary qubit channel, this work provides a universally- accepted way to explore various properties of quantum channels and novel prospect for quantum communication.

Attention Bias Modification (ABM): Review of Effects of Multisession ABM Training on Anxiety and Threat-Related Attention in High-Anxious Individuals

PubMed Central

Mogg, Karin; Waters, Allison M.; Bradley, Brendan P.

2017-01-01

Attention bias modification (ABM) aims to reduce anxiety by reducing attention bias (AB) to threat; however, effects on anxiety and AB are variable. This review examines 34 studies assessing effects of multisession-ABM on both anxiety and AB in high-anxious individuals. Methods include ABM-threat-avoidance (promoting attention-orienting away from threat), ABM-positive-search (promoting explicit, goal-directed attention-search for positive/nonthreat targets among negative/threat distractors), and comparison conditions (e.g., control-attention training combining threat-cue exposure and attention-task practice without AB-modification). Findings indicate anxiety reduction often occurs during both ABM-threat-avoidance and control-attention training; anxiety reduction is not consistently accompanied by AB reduction; anxious individuals often show no pretraining AB in orienting toward threat; and ABM-positive-search training appears promising in reducing anxiety. Methodological and theoretical issues are discussed concerning ABM paradigms, comparison conditions, and AB assessment. ABM methods combining explicit goal-directed attention-search for nonthreat/positive information and effortful threat-distractor inhibition (promoting top-down cognitive control during threat-cue exposure) warrant further evaluation. PMID:28752017

Auditory processing theories of language disorders: past, present, and future.

PubMed

Miller, Carol A

2011-07-01

The purpose of this article is to provide information that will assist readers in understanding and interpreting research literature on the role of auditory processing in communication disorders. A narrative review was used to summarize and synthesize the literature on auditory processing deficits in children with auditory processing disorder (APD), specific language impairment (SLI), and dyslexia. The history of auditory processing theories of these 3 disorders is described, points of convergence and controversy within and among the different branches of research literature are considered, and the influence of research on practice is discussed. The theoretical and clinical contributions of neurophysiological methods are also reviewed, and suggested approaches for critical reading of the research literature are provided. Research on the role of auditory processing in communication disorders springs from a variety of theoretical perspectives and assumptions, and this variety, combined with controversies over the interpretation of research results, makes it difficult to draw clinical implications from the literature. Neurophysiological research methods are a promising route to better understanding of auditory processing. Progress in theory development and its clinical application is most likely to be made when researchers from different disciplines and theoretical perspectives communicate clearly and combine the strengths of their approaches.

Imaging transcranial direct current stimulation (tDCS) of the prefrontal cortex-correlation or causality in stimulation-mediated effects?

PubMed

Wörsching, Jana; Padberg, Frank; Ertl-Wagner, Birgit; Kumpf, Ulrike; Kirsch, Beatrice; Keeser, Daniel

2016-10-01

Transcranial current stimulation approaches include neurophysiologically distinct non-invasive brain stimulation techniques widely applied in basic, translational and clinical research: transcranial direct current stimulation (tDCS), oscillating transcranial direct current stimulation (otDCS), transcranial alternating current stimulation (tACS) and transcranial random noise stimulation (tRNS). Prefrontal tDCS seems to be an especially promising tool for clinical practice. In order to effectively modulate relevant neural circuits, systematic research on prefrontal tDCS is needed that uses neuroimaging and neurophysiology measures to specifically target and adjust this method to physiological requirements. This review therefore analyses the various neuroimaging methods used in combination with prefrontal tDCS in healthy and psychiatric populations. First, we provide a systematic overview on applications, computational models and studies combining neuroimaging or neurophysiological measures with tDCS. Second, we categorise these studies in terms of their experimental designs and show that many studies do not vary the experimental conditions to the extent required to demonstrate specific relations between tDCS and its behavioural or neurophysiological effects. Finally, to support best-practice tDCS research we provide a methodological framework for orientation among experimental designs. Copyright © 2016 Elsevier Ltd. All rights reserved.

Controlled trials to improve antibiotic utilization: a systematic review of experience, 1984-2004.

PubMed

Parrino, Thomas A

2005-02-01

To review the effectiveness of interventions designed to improve antibiotic prescribing patterns in clinical practice and to draw inferences about the most practical methods for optimizing antibiotic utilization in hospital and ambulatory settings. A literature search using online databases for the years 1975-2004 identified controlled trials of strategies for improving antibiotic utilization. Due to variation in study settings and design, quantitative meta-analysis was not feasible. Therefore, a qualitative literature review was conducted. Forty-one controlled trials met the search criteria. Interventions consisted of education, peer review and feedback, physician participation, rewards and penalties, administrative methods, and combined approaches. Social marketing directed at patients and prescribers was effective in varying contexts, as was implementation of practice guidelines. Authorization systems with structured order entry, formulary restriction, and mandatory consultation were also effective. Peer review and feedback were more effective when combined with dissemination of relevant information or social marketing than when used alone. Several practices were effective in improving antibiotic utilization: social marketing, practice guidelines, authorization systems, and peer review and feedback. Online systems providing clinical information, structured order entry, and decision support may be the most promising approach. Further studies, including economic analyses, are needed to confirm or refute this hypothesis.

Fluorescent labeling of NASBA amplified tmRNA molecules for microarray applications

PubMed Central

Scheler, Ott; Glynn, Barry; Parkel, Sven; Palta, Priit; Toome, Kadri; Kaplinski, Lauris; Remm, Maido; Maher, Majella; Kurg, Ants

2009-01-01

Background Here we present a novel promising microbial diagnostic method that combines the sensitivity of Nucleic Acid Sequence Based Amplification (NASBA) with the high information content of microarray technology for the detection of bacterial tmRNA molecules. The NASBA protocol was modified to include aminoallyl-UTP (aaUTP) molecules that were incorporated into nascent RNA during the NASBA reaction. Post-amplification labeling with fluorescent dye was carried out subsequently and tmRNA hybridization signal intensities were measured using microarray technology. Significant optimization of the labeled NASBA protocol was required to maintain the required sensitivity of the reactions. Results Two different aaUTP salts were evaluated and optimum final concentrations were identified for both. The final 2 mM concentration of aaUTP Li-salt in NASBA reaction resulted in highest microarray signals overall, being twice as high as the strongest signals with 1 mM aaUTP Na-salt. Conclusion We have successfully demonstrated efficient combination of NASBA amplification technology with microarray based hybridization detection. The method is applicative for many different areas of microbial diagnostics including environmental monitoring, bio threat detection, industrial process monitoring and clinical microbiology. PMID:19445684

Smoking cessation programs in occupational settings

PubMed Central

Danaher, Brian G.

1980-01-01

For reasons of health and economics, the business community is displaying a growing interest in providing smoking cessation programs for employees. An examination of the current research on smoking cessation methods has revealed a number of promising directions that smoking cessation programs can take, for example, aversive smoking approaches combined with self-control strategies. A review of current smoking cessation programs in occupational settings revealed some emphasis on physician counseling, but a relatively greater emphasis on use of consultants (especially in proprietary programs) or of contingency programs to encourage nonsmoking. The smoking cessation programs in businesses can move in a number of innovative directions, including (a) increased use of inhouse programs with a variety of smoking cessation strategies; (b) greater emphasis on the training of program participants in nonsmoking behavioral skills, combined with contingency or incentive programs for smoking control; (c) vastly improved research methods, including complete followup assessments of program participants and chemical tests to validate their self-reported abstinence; (d) greater concern about the need for empirically tested procedures for recruitment of participants for the programs; and (e) expanded interchange among behavioral scientists (especially behavioral psychologists), health professionals in occupational health and medicine, union and employee groups, and management. PMID:7360872

Programmable and Bidirectional Bending of Soft Actuators Based on Janus Structure with Sticky Tough PAA-Clay Hydrogel.

PubMed

Zhao, Lei; Huang, Jiahe; Zhang, Yuancheng; Wang, Tao; Sun, Weixiang; Tong, Zhen

2017-04-05

Facile preparation, rapid actuating, and versatile actions are great challenges in exploring new kinds of hydrogel actuators. In this paper, we presented a facile sticking method to prepare Janus bilayer and multilayer hydrogel actuators that benefited from a special tough and adhesive PAA-clay hydrogel. Combining physical and chemical cross-linking reagents, we endowed the PAA gel with both toughness and adhesion. This PAA gel was reinforced by further cross-linking with Fe 3+ . These two hydrogels with different cross-linking densities exhibited different swelling capabilities and moduli in the media manipulated by pH and ionic strength, thus acting as promising candidates for soft actuators. On the basis of these gels, we designed hydrogel actuators of rapid response in several minutes and precisely controlled actuating direction by sticking two hydrogel layers together. Elaborate soft actuators such as bidirectional bending flytrap, gel hand with grasp, open, and gesturing actions as well as word-writing actuator were prepared. This method could be generalized by using other stimuli-responsive hydrogels combined with the adhesive PAA gel, which would open a new way to programmable and versatile soft actuators.

Diagnosis of IBS: symptoms, symptom-based criteria, biomarkers or 'psychomarkers'?

PubMed

Sood, Ruchit; Law, Graham R; Ford, Alexander C

2014-11-01

IBS is estimated to have a prevalence of up to 20% in Western populations and results in substantial costs to health-care services worldwide, estimated to be US$1 billion per year in the USA. IBS remains difficult to diagnose due to its multifactorial aetiology, heterogeneous nature and overlap of symptoms with organic pathologies, such as coeliac disease and IBD. As a result, IBS often continues to be a diagnosis of exclusion, resulting in unnecessary investigations. Available methods for the diagnosis of IBS-including the current gold standard, the Rome III criteria-perform only moderately well. Visceral hypersensitivity and altered pain perception do not discriminate between IBS and other functional gastrointestinal diseases or health with any great accuracy. Attention has now turned to developing novel biomarkers and using psychological markers (so-called psychomarkers) to aid the diagnosis of IBS. This Review describes how useful symptoms, symptom-based criteria, biomarkers and psychomarkers, and indeed combinations of all these approaches, are in the diagnosis of IBS. Future directions in diagnosing IBS could include combining demographic data, gastrointestinal symptoms, biomarkers and psychomarkers using statistical methods. Latent class analysis to distinguish between IBS and non-IBS symptom profiles might also represent a promising avenue for future research.

Temperature Profiles of Different Cooling Methods in Porcine Pancreas Procurement

PubMed Central

Weegman, Brad P.; Suszynski, Thomas M.; Scott, William E.; Ferrer, Joana; Avgoustiniatos, Efstathios S.; Anazawa, Takayuki; O’Brien, Timothy D.; Rizzari, Michael D.; Karatzas, Theodore; Jie, Tun; Sutherland, David ER.; Hering, Bernhard J.; Papas, Klearchos K.

2014-01-01

Background Porcine islet xenotransplantation is a promising alternative to human islet allotransplantation. Porcine pancreas cooling needs to be optimized to reduce the warm ischemia time (WIT) following donation after cardiac death, which is associated with poorer islet isolation outcomes. Methods This study examines the effect of 4 different cooling Methods on core porcine pancreas temperature (n=24) and histopathology (n=16). All Methods involved surface cooling with crushed ice and chilled irrigation. Method A, which is the standard for porcine pancreas procurement, used only surface cooling. Method B involved an intravascular flush with cold solution through the pancreas arterial system. Method C involved an intraductal infusion with cold solution through the major pancreatic duct, and Method D combined all 3 cooling Methods. Results Surface cooling alone (Method A) gradually decreased core pancreas temperature to < 10 °C after 30 minutes. Using an intravascular flush (Method B) improved cooling during the entire duration of procurement, but incorporating an intraductal infusion (Method C) rapidly reduced core temperature 15–20 °C within the first 2 minutes of cooling. Combining all methods (Method D) was the most effective at rapidly reducing temperature and providing sustained cooling throughout the duration of procurement, although the recorded WIT was not different between Methods (p=0.36). Histological scores were different between the cooling Methods (p=0.02) and the worst with Method A. There were differences in histological scores between Methods A and C (p=0.02) and Methods A and D (p=0.02), but not between Methods C and D (p=0.95), which may highlight the importance of early cooling using an intraductal infusion. Conclusions In conclusion, surface cooling alone cannot rapidly cool large (porcine or human) pancreata. Additional cooling with an intravascular flush and intraductal infusion results in improved core porcine pancreas temperature profiles during procurement and histopathology scores. These data may also have implications on human pancreas procurement since use of an intraductal infusion is not common practice. PMID:25040217

The Importance of Role Definition in Combining School and Public Libraries.

ERIC Educational Resources Information Center

Amey, L. J.

Public and school libraries having begun as an outgrowth of each other and then separated, have some overlap in philosophy, function, and public served. Although studies have opposed the combined school and public library, communities continue to attempt mergers largely for promise of dollar savings. There is also a philosophical trend in…

Perspectives Do Matter: "Joint Screen", a Promising Methodology for Multimodal Interaction Analysis

ERIC Educational Resources Information Center

Arend, Béatrice; Sunnen, Patrick; Fixmer, Pierre; Sujbert, Monika

2014-01-01

This paper discusses theoretical and methodological issues arising from a video-based research design and the emergent tool "Joint Screen'"when grasping joint activity. We share our reflections regarding the combined reading of four synchronised camera perspectives combined in one screen. By these means we reconstruct and analyse…

Pairing Script and Dialogue: Combinations that Show Promise for Second or Foreign Language Learning.

ERIC Educational Resources Information Center

Holobow, N. E.; And Others

1984-01-01

Describes a study to determine if the initial advantage of listening to first language dialogs while reading second language scripts (i.e., reversed subtitling) would hold up over time and if a combination of coordinated dialogs and scripts both in the second language would gain effectiveness through usage. (SED)

Development of a biocidal treatment regime to inhibit biological growths on cultural heritage: BIODAM

NASA Astrophysics Data System (ADS)

Young, M. E.; Alakomi, H.-L.; Fortune, I.; Gorbushina, A. A.; Krumbein, W. E.; Maxwell, I.; McCullagh, C.; Robertson, P.; Saarela, M.; Valero, J.; Vendrell, M.

2008-12-01

Existing chemical treatments to prevent biological damage to monuments often involve considerable amounts of potentially dangerous and even poisonous biocides. The scientific approach described in this paper aims at a drastic reduction in the concentration of biocide applications by a polyphasic approach of biocides combined with cell permeabilisers, polysaccharide and pigment inhibitors and a photodynamic treatment. A variety of potential agents were screened to determine the most effective combination. Promising compounds were tested under laboratory conditions with cultures of rock deteriorating bacteria, algae, cyanobacteria and fungi. A subsequent field trial involved two sandstone types with natural biofilms. These were treated with multiple combinations of chemicals and exposed to three different climatic conditions. Although treatments proved successful in the laboratory, field trials were inconclusive and further testing will be required to determine the most effective treatment regime. While the most effective combination of chemicals and their application methodology is still being optimised, results to date indicate that this is a promising and effective treatment for the control of a wide variety of potentially damaging organisms colonising stone substrates.

Optimizing a machine learning based glioma grading system using multi-parametric MRI histogram and texture features

PubMed Central

Hu, Yu-Chuan; Li, Gang; Yang, Yang; Han, Yu; Sun, Ying-Zhi; Liu, Zhi-Cheng; Tian, Qiang; Han, Zi-Yang; Liu, Le-De; Hu, Bin-Quan; Qiu, Zi-Yu; Wang, Wen; Cui, Guang-Bin

2017-01-01

Current machine learning techniques provide the opportunity to develop noninvasive and automated glioma grading tools, by utilizing quantitative parameters derived from multi-modal magnetic resonance imaging (MRI) data. However, the efficacies of different machine learning methods in glioma grading have not been investigated.A comprehensive comparison of varied machine learning methods in differentiating low-grade gliomas (LGGs) and high-grade gliomas (HGGs) as well as WHO grade II, III and IV gliomas based on multi-parametric MRI images was proposed in the current study. The parametric histogram and image texture attributes of 120 glioma patients were extracted from the perfusion, diffusion and permeability parametric maps of preoperative MRI. Then, 25 commonly used machine learning classifiers combined with 8 independent attribute selection methods were applied and evaluated using leave-one-out cross validation (LOOCV) strategy. Besides, the influences of parameter selection on the classifying performances were investigated. We found that support vector machine (SVM) exhibited superior performance to other classifiers. By combining all tumor attributes with synthetic minority over-sampling technique (SMOTE), the highest classifying accuracy of 0.945 or 0.961 for LGG and HGG or grade II, III and IV gliomas was achieved. Application of Recursive Feature Elimination (RFE) attribute selection strategy further improved the classifying accuracies. Besides, the performances of LibSVM, SMO, IBk classifiers were influenced by some key parameters such as kernel type, c, gama, K, etc. SVM is a promising tool in developing automated preoperative glioma grading system, especially when being combined with RFE strategy. Model parameters should be considered in glioma grading model optimization. PMID:28599282

The use of Gram stain and matrix-assisted laser desorption ionization time-of-flight mass spectrometry on positive blood culture: synergy between new and old technology.

PubMed

Fuglsang-Damgaard, David; Nielsen, Camilla Houlberg; Mandrup, Elisabeth; Fuursted, Kurt

2011-10-01

Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS) is promising as an alternative to more costly and cumbersome methods for direct identifications in blood cultures. We wanted to evaluate a simplified pre-treatment method for using MALDI-TOF-MS directly on positive blood cultures using BacT/Alert blood culture system, and to test an algorithm combining the result of the initial microscopy with the result suggested by MALDI-TOF-MS. Using the recommended cut-off score of 1.7 the best results were obtained among Gram-negative rods with correct identifications in 91% of Enterobacteriaceae, 83% in aerobic/non-fermentative Gram-negative rods, whereas results were more modest among Gram-positive cocci with correct identifications in 52% of Staphylococci, 54% in Enterococci and only 20% in Streptococci. Combining the results of Gram stain with the top reports by MALDI-TOF-MS, increased the sensitivity from 91% to 93% in the score range from 1.5 to 1.7 and from 48% to 85% in the score range from 1.3 to 1.5. Thus, using this strategy and accepting a cut-off at 1.3 instead of the suggested 1.7, overall sensitivity could be increased from 88.1% to 96.3%. MALDI-TOF-MS is an efficient method for direct routine identification of bacterial isolates in blood culture, especially when combined with the result of the Gram stain. © 2011 The Authors. APMIS © 2011 APMIS.

Genetic Bee Colony (GBC) algorithm: A new gene selection method for microarray cancer classification.

PubMed

Alshamlan, Hala M; Badr, Ghada H; Alohali, Yousef A

2015-06-01

Naturally inspired evolutionary algorithms prove effectiveness when used for solving feature selection and classification problems. Artificial Bee Colony (ABC) is a relatively new swarm intelligence method. In this paper, we propose a new hybrid gene selection method, namely Genetic Bee Colony (GBC) algorithm. The proposed algorithm combines the used of a Genetic Algorithm (GA) along with Artificial Bee Colony (ABC) algorithm. The goal is to integrate the advantages of both algorithms. The proposed algorithm is applied to a microarray gene expression profile in order to select the most predictive and informative genes for cancer classification. In order to test the accuracy performance of the proposed algorithm, extensive experiments were conducted. Three binary microarray datasets are use, which include: colon, leukemia, and lung. In addition, another three multi-class microarray datasets are used, which are: SRBCT, lymphoma, and leukemia. Results of the GBC algorithm are compared with our recently proposed technique: mRMR when combined with the Artificial Bee Colony algorithm (mRMR-ABC). We also compared the combination of mRMR with GA (mRMR-GA) and Particle Swarm Optimization (mRMR-PSO) algorithms. In addition, we compared the GBC algorithm with other related algorithms that have been recently published in the literature, using all benchmark datasets. The GBC algorithm shows superior performance as it achieved the highest classification accuracy along with the lowest average number of selected genes. This proves that the GBC algorithm is a promising approach for solving the gene selection problem in both binary and multi-class cancer classification. Copyright © 2015 Elsevier Ltd. All rights reserved.

A proposed method to estimate premorbid full scale intelligence quotient (FSIQ) for the Canadian Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) using demographic and combined estimation procedures.

PubMed

Schoenberg, Mike R; Lange, Rael T; Saklofske, Donald H

2007-11-01

Establishing a comparison standard in neuropsychological assessment is crucial to determining change in function. There is no available method to estimate premorbid intellectual functioning for the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV). The WISC-IV provided normative data for both American and Canadian children aged 6 to 16 years old. This study developed regression algorithms as a proposed method to estimate full-scale intelligence quotient (FSIQ) for the Canadian WISC-IV. Participants were the Canadian WISC-IV standardization sample (n = 1,100). The sample was randomly divided into two groups (development and validation groups). The development group was used to generate regression algorithms; 1 algorithm only included demographics, and 11 combined demographic variables with WISC-IV subtest raw scores. The algorithms accounted for 18% to 70% of the variance in FSIQ (standard error of estimate, SEE = 8.6 to 14.2). Estimated FSIQ significantly correlated with actual FSIQ (r = .30 to .80), and the majority of individual FSIQ estimates were within +/-10 points of actual FSIQ. The demographic-only algorithm was less accurate than algorithms combining demographic variables with subtest raw scores. The current algorithms yielded accurate estimates of current FSIQ for Canadian individuals aged 6-16 years old. The potential application of the algorithms to estimate premorbid FSIQ is reviewed. While promising, clinical validation of the algorithms in a sample of children and/or adolescents with known neurological dysfunction is needed to establish these algorithms as a premorbid estimation procedure.

Optimizing a machine learning based glioma grading system using multi-parametric MRI histogram and texture features.

PubMed

Zhang, Xin; Yan, Lin-Feng; Hu, Yu-Chuan; Li, Gang; Yang, Yang; Han, Yu; Sun, Ying-Zhi; Liu, Zhi-Cheng; Tian, Qiang; Han, Zi-Yang; Liu, Le-De; Hu, Bin-Quan; Qiu, Zi-Yu; Wang, Wen; Cui, Guang-Bin

2017-07-18

Current machine learning techniques provide the opportunity to develop noninvasive and automated glioma grading tools, by utilizing quantitative parameters derived from multi-modal magnetic resonance imaging (MRI) data. However, the efficacies of different machine learning methods in glioma grading have not been investigated.A comprehensive comparison of varied machine learning methods in differentiating low-grade gliomas (LGGs) and high-grade gliomas (HGGs) as well as WHO grade II, III and IV gliomas based on multi-parametric MRI images was proposed in the current study. The parametric histogram and image texture attributes of 120 glioma patients were extracted from the perfusion, diffusion and permeability parametric maps of preoperative MRI. Then, 25 commonly used machine learning classifiers combined with 8 independent attribute selection methods were applied and evaluated using leave-one-out cross validation (LOOCV) strategy. Besides, the influences of parameter selection on the classifying performances were investigated. We found that support vector machine (SVM) exhibited superior performance to other classifiers. By combining all tumor attributes with synthetic minority over-sampling technique (SMOTE), the highest classifying accuracy of 0.945 or 0.961 for LGG and HGG or grade II, III and IV gliomas was achieved. Application of Recursive Feature Elimination (RFE) attribute selection strategy further improved the classifying accuracies. Besides, the performances of LibSVM, SMO, IBk classifiers were influenced by some key parameters such as kernel type, c, gama, K, etc. SVM is a promising tool in developing automated preoperative glioma grading system, especially when being combined with RFE strategy. Model parameters should be considered in glioma grading model optimization.

Survey of Material for an Infrared-Opaque Coating

NASA Technical Reports Server (NTRS)

Smith, Sheldon M.; Howitt, Richard V.

1986-01-01

More than 40 reflectance spectra in the range from 20 to 500 microns have been obtained for a variety of coatings, binders, and additives to identify promising components of an infrared-opaque coating for the Space Infrared Telescope Facility. Certain combinations of materials showed a specular reflectance below 0.1 throughout the spectral range measured. In addition to estimating the optical constants of several combination coatings, this survey also supports three qualitative conclusions: (1) promising off-the-shelf binders of different additives are Chemglaze Z-306, ECP-2200, and De Soto Black; (2) carbon black is very effective in reducing far-infrared reflectance; (3) the far-infrared reflectance from coatings containing 80 SiC grit is consistently lower than that from similar coatings containing TiBr powder.

Survey of material for an infrared-opaque coating

NASA Technical Reports Server (NTRS)

Smith, Sheldon M.; Howitt, Richard V.

1986-01-01

More than 40 reflectance spectra in the range from 20 to 500 microns have been obtained of a variety of coatings, binders, and additives to identify promising components of an infrared-opaque coating for the Space Infrared Telescope Facility. Certain combinations of materials showed a specular reflectance below 0.1 throughout the spectral range measured. In addition to estimating the optical constants of several combination coatings, this survey also supports three qualitative conclusions: (1) promising 'off-the-shelf' binders of different additives are Chemglaze Z-306, ECP-2200, and De Soto Black; (2) carbon black is very effective reducing far-infrared reflectance; and (3) the far-infrared reflectance from coatings containing 80 SiC grit is consistently lower than that from similar coatings containing TlBr powder.

A method for modeling co-occurrence propensity of clinical codes with application to ICD-10-PCS auto-coding.

PubMed

Subotin, Michael; Davis, Anthony R

2016-09-01

Natural language processing methods for medical auto-coding, or automatic generation of medical billing codes from electronic health records, generally assign each code independently of the others. They may thus assign codes for closely related procedures or diagnoses to the same document, even when they do not tend to occur together in practice, simply because the right choice can be difficult to infer from the clinical narrative. We propose a method that injects awareness of the propensities for code co-occurrence into this process. First, a model is trained to estimate the conditional probability that one code is assigned by a human coder, given than another code is known to have been assigned to the same document. Then, at runtime, an iterative algorithm is used to apply this model to the output of an existing statistical auto-coder to modify the confidence scores of the codes. We tested this method in combination with a primary auto-coder for International Statistical Classification of Diseases-10 procedure codes, achieving a 12% relative improvement in F-score over the primary auto-coder baseline. The proposed method can be used, with appropriate features, in combination with any auto-coder that generates codes with different levels of confidence. The promising results obtained for International Statistical Classification of Diseases-10 procedure codes suggest that the proposed method may have wider applications in auto-coding. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Application of bacteriophages in sensor development.

PubMed

Peltomaa, Riikka; López-Perolio, Irene; Benito-Peña, Elena; Barderas, Rodrigo; Moreno-Bondi, María Cruz

2016-03-01

Bacteriophage-based bioassays are a promising alternative to traditional antibody-based immunoassays. Bacteriophages, shortened to phages, can be easily conjugated or genetically engineered. Phages are robust, ubiquitous in nature, and harmless to humans. Notably, phages do not usually require inoculation and killing of animals; and thus, the production of phages is simple and economical. In recent years, phage-based biosensors have been developed featuring excellent robustness, sensitivity, and selectivity in combination with the ease of integration into transduction devices. This review provides a critical overview of phage-based bioassays and biosensors developed in the last few years using different interrogation methods such as colorimetric, enzymatic, fluorescence, surface plasmon resonance, quartz crystal microbalance, magnetoelastic, Raman, or electrochemical techniques.

[The reconstruction of two-dimensional distributions of gas concentration in the flat flame based on tunable laser absorption spectroscopy].

PubMed

Jiang, Zhi-Shen; Wang, Fei; Xing, Da-Wei; Xu, Ting; Yan, Jian-Hua; Cen, Ke-Fa

2012-11-01

The experimental method by using the tunable diode laser absorption spectroscopy combined with the model and algo- rithm was studied to reconstruct the two-dimensional distribution of gas concentration The feasibility of the reconstruction program was verified by numerical simulation A diagnostic system consisting of 24 lasers was built for the measurement of H2O in the methane/air premixed flame. The two-dimensional distribution of H2O concentration in the flame was reconstructed, showing that the reconstruction results reflect the real two-dimensional distribution of H2O concentration in the flame. This diagnostic scheme provides a promising solution for combustion control.

Performance Evaluation of the Operational Air Quality Monitor for Water Testing Aboard the International Space Station

NASA Technical Reports Server (NTRS)

Wallace, William T.; Limero, Thomas F.; Gazda, Daniel B.; Minton, John M.; Macatangay, Ariel V.; Dwivedi, Prabha; Fernandez, Facundo M.

2014-01-01

Real-time environmental monitoring on ISS is necessary to provide data in a timely fashion and to help ensure astronaut health. Current real-time water TOC monitoring provides high-quality trending information, but compound-specific data is needed. The combination of ETV with the AQM showed that compounds of interest could be liberated from water and analyzed in the same manner as air sampling. Calibration of the AQM using water samples allowed for the quantitative analysis of ISS archival samples. Some calibration issues remain, but the excellent accuracy of DMSD indicates that ETV holds promise for as a sample introduction method for water analysis in spaceflight.

Development and characterization of lubricants for use near nuclear reactors in space vehicles

NASA Technical Reports Server (NTRS)

Robinson, G. L.; Akawie, R. I.; Gardos, M. N.; Krening, K. C.

1972-01-01

The synthesis and evaluation program was conducted to develop wide-temperature range lubricants suitable for use in space vehicles particularly in the vicinity of nuclear reactors. Synthetic approaches resulted in nonpolymeric, large molecular weight materials, all based on some combination of siloxane and aromatic groups. Evaluation of these materials indicated that certain tetramethyl and hexamethyl disiloxanes containing phenyl thiophenyl substituents are extremely promising with respect to radiation stability, wide temperature range, good lubricity, oxidation resistance and additive acceptance. The synthesis of fluids is discussed, and the equipment and methods used in evaluation are described, some of which were designed to evaluate micro-quantities of the synthesized lubricants.

Gene Therapy for the Treatment of Diabetic Neuropathy

PubMed Central

Mata, Marina; Chattopadhyay, Munmun; Fink, David J

2009-01-01

Neuropathy is a common, untreatable complication of both type 1 and type 2 diabetes. In animal models peptide neurotrophic factors can be used to protect against the development of neuropathy, but the combination of short half-life and off-target effects of these potent pleiotropic peptides has limited translation to human therapy. Gene transfer is a promising strategy that might circumvent these limitations. In this essay we review the basic methods of gene transfer and the preclinical data in rodent models that support the utility of this approach in the treatment of diabetic neuropathy. The path to a clinical applications and potential pitfalls in developing gene therapy for the treatment of diabetic neuropathy are considered. PMID:18990298

Commercial aspects of semi-reusable launch systems

NASA Astrophysics Data System (ADS)

Obersteiner, M. H.; Müller, H.; Spies, H.

2003-07-01

This paper presents a business planning model for a commercial space launch system. The financing model is based on market analyses and projections combined with market capture models. An operations model is used to derive the annual cash income. Parametric cost modeling, development and production schedules are used for quantifying the annual expenditures, the internal rate of return, break even point of positive cash flow and the respective prices per launch. Alternative consortia structures, cash flow methods, capture rates and launch prices are used to examine the sensitivity of the model. Then the model is applied for a promising semi-reusable launcher concept, showing the general achievability of the commercial approach and the necessary pre-conditions.

Fluorescence Quenching by TEMPO: A Sub-30 Å Single-Molecule Ruler

PubMed Central

Zhu, Peizhi; Clamme, Jean-Pierre; Deniz, Ashok A.

2005-01-01

A series of DNA molecules labeled with 5-carboxytetramethylrhodamine (5-TAMRA) and the small nitroxide radical TEMPO were synthesized and tested to investigate whether the intramolecular quenching efficiency can be used to measure short intramolecular distances in small ensemble and single-molecule experiments. In combination with distance calculations using molecular mechanics modeling, the experimental results from steady-state ensemble fluorescence and fluorescence correlation spectroscopy measurements both show an exponential decrease in the quenching rate constant with the dye-quencher distance in the 10–30 Å range. The results demonstrate that TEMPO-5-TAMRA fluorescence quenching is a promising method to measure short distance changes within single biomolecules. PMID:16199509

A Bridging Opportunities Work-frame to develop mobile applications for clinical decision making

PubMed Central

van Rooij, Tibor; Rix, Serena; Moore, James B; Marsh, Sharon

2015-01-01

Background: Mobile applications (apps) providing clinical decision support (CDS) may show the greatest promise when created by and for frontline clinicians. Our aim was to create a generic model enabling healthcare providers to direct the development of CDS apps. Methods: We combined Change Management with a three-tier information technology architecture to stimulate CDS app development. Results: A Bridging Opportunities Work-frame model was developed. A test case was used to successfully develop an app. Conclusion: Healthcare providers can re-use this globally applicable model to actively create and manage regional decision support applications to translate evidence-based medicine in the use of emerging medication or novel treatment regimens. PMID:28031883