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1.
Sensors (Basel) ; 19(19)2019 Sep 29.
Artigo em Inglês | MEDLINE | ID: mdl-31569596

RESUMO

Infrared and visible image matching methods have been rising in popularity with the emergence of more kinds of sensors, which provide more applications in visual navigation, precision guidance, image fusion, and medical image analysis. In such applications, image matching is utilized for location, fusion, image analysis, and so on. In this paper, an infrared and visible image matching approach, based on distinct wavelength phase congruency (DWPC) and log-Gabor filters, is proposed. Furthermore, this method is modified for non-linear image matching with different physical wavelengths. Phase congruency (PC) theory is utilized to obtain PC images with intrinsic and affluent image features for images containing complex intensity changes or noise. Then, the maximum and minimum moments of the PC images are computed to obtain the corners in the matched images. In order to obtain the descriptors, log-Gabor filters are utilized and overlapping subregions are extracted in a neighborhood of certain pixels. In order to improve the accuracy of the algorithm, the moments of PCs in the original image and a Gaussian smoothed image are combined to detect the corners. Meanwhile, it is improper that the two matched images have the same PC wavelengths, due to the images having different physical wavelengths. Thus, in the experiment, the wavelength of the PC is changed for different physical wavelengths. For realistic application, BiDimRegression method is proposed to compute the similarity between two points set in infrared and visible images. The proposed approach is evaluated on four data sets with 237 pairs of visible and infrared images, and its performance is compared with state-of-the-art approaches: the edge-oriented histogram descriptor (EHD), phase congruency edge-oriented histogram descriptor (PCEHD), and log-Gabor histogram descriptor (LGHD) algorithms. The experimental results indicate that the accuracy rate of the proposed approach is 50% higher than the traditional approaches in infrared and visible images.

2.
Bioresour Technol ; 293: 122016, 2019 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-31473375

RESUMO

Pretreatment is a key step in the energy utilization of lignocellulosic biomass. Different types of pretreatments (ultrafine grinding pretreatment, alkaline hydroxide peroxide pretreatment, dilute acid pretreatment, and ammonia fiber expansion pretreatment) were conducted on corn stover. The lignocellulosic composition, microstructural parameters, and glucose yield of differently pretreated corn stover were characterized and compared. Then qualitative and quantitative correlation analyses of the parameters were carried out to explore the correlations among the composition, microstructure properties, and enzymatic hydrolysis efficacy of corn stover after different types of pretreatments and identify the main properties affecting enzymatic hydrolysis. Qualitative correlation analysis found that cellulose content, specific surface area, pore volume, enzyme-accessible pore volume, and surface area of cellulose had significant positive correlations with glucose yield. The results of quantitative correlation analysis were GY = 15.01 × cellulose content-339.05, GY = 13.06 × SSA + 172.35, GY = 7226.27 × PV + 129.14, GY = 8628.61 × EAPV + 125.61, and GY = 1.18 × SAC-287.21.


Assuntos
Celulose , Zea mays , Biomassa , Carboidratos , Hidrólise
3.
Bioresour Technol ; 282: 384-389, 2019 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-30884458

RESUMO

To investigate the effect of two-step kinetics on enzyme adsorption and hydrolytic properties of different structural substrates at low enzyme doses. The two-step kinetic experiments of ultrafine grinding (UGCS) and sieve-based grinding corn stover (SGCS) were performed respectively with enzyme loading of 2.5 + 2.5 FPU/g and 5 + 5 FPU/g. The different performance of these two samples were illustrated by characterizing the particle size distribution, SEM and XPS. The results showed that ultrafine grinding can promote the structural properties which is beneficial to adsorption and hydrolysis. The main factors influencing adsorption kinetics are enzyme concentration and the surface cellulose amount. Pre-adsorbed enzyme has no effects on the subsequent enzyme adsorption quantity but produces some small competitive and impeditive effects. The hydrolysis kinetics mainly depend on the structure of the substrate and its complexity of hydrolysis. The two-step hydrolysis didn't promote the total sugar yield under the same enzyme concentration, but the first step contributed more to the total sugar yield.


Assuntos
Zea mays/química , Zea mays/metabolismo , Adsorção , Celulose/química , Celulose/metabolismo , Hidrólise , Cinética
4.
Bioresour Technol ; 273: 1-7, 2018 Oct 17.
Artigo em Inglês | MEDLINE | ID: mdl-30368157

RESUMO

This study evaluated the effects of physicochemical properties of a series of ball-milled cellulose on cellulase adsorption and glucose yield. The relationship between cellulase adsorption and initial hydrolysis rate was also discussed. We found that hydrophobicity and surface charge are the key factors affecting cellulase adsorption on ball-milled cellulose. The results demonstrated that glucose yield had a positive correlation with specific surface area, while showed a negative correlation with particle size, degree of polymerization and crystallinity. Among these properties, specific surface area and crystallinity are the key factors affecting glucose yield. As ball milling progressed, cellulose showed lower enzyme adsorption capacity/amount of bound enzyme during initial stage of hydrolysis, but had higher initial hydrolysis rate. The enhanced rate is attributed to the fact that the amorphous region produced by ball milling reduces the free energy required for decrystallization thus increases the catalytic efficiency of the bound enzyme.

5.
Environ Sci Technol ; 52(15): 8408-8418, 2018 Aug 07.
Artigo em Inglês | MEDLINE | ID: mdl-29984574

RESUMO

Nitrous oxide (N2O) emission during composting causes nitrogen loss and air pollution. The interpretation of N2O emission mechanisms will help to customize composting strategies that mitigate climate change. At pile and particle scales, this study characterized N2O emission-related variables (gases, ions, and microbes) and their correlations during pig manure-wheat straw aerobic composting. Pile-scale results showed that N2O emission mainly occurred in mesophilic, thermophilic, and cooling phases; the nitrification by ammonia-oxidizing bacteria ( AOB) and nitrite-oxidizing bacteria ( NOB) coexisted with the denitrification by denitrificans ( DEN); the major NOB and DEN were Nitrobacter ( NOB_Nba) and Thiobacillus denitrificans ( DEN_Tb), respectively. The mechanisms of nitrification, nitrifier denitrification, and anaerobic denitrification in composting particles were initially visualized by confocal laser scanning microscopy: Betaproteobacteria ( AOB_ Beta) sporadically distributed on the outer area of the particles, NOB_Nba internally attached to AOB_ Beta, and Nitrosomonas europea/ Nitrosomonas eutropha ( AOB_eu) and DEN_Tb concentrated in the interior. Correlation analysis of the variables showed that the distribution area of AOB_eu was proportional to N2O emission ( R2 = 0.84); AOB not only participated in nitrification but also nitrifier denitrification, and N2O formation was mainly from nitrifier denitrification by AOB_eu during the mesophilic-thermophilic phase and from denitrification by AOB_eu and DEN during the cooling phase.

6.
Bioresour Technol ; 264: 327-334, 2018 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-29885582

RESUMO

A thorough assessment of the microstructural changes and synergistic effects of hydrothermal and/or ultrafine grinding pretreatment on the subsequent enzymatic hydrolysis of corn stover was performed in this study. The mechanism of pretreatment was elucidated by characterizing the particle size, specific surface area (SSA), pore volume (PV), average pore size, cellulose crystallinity (CrI) and surface morphology of the pretreated samples. In addition, the underlying relationships between the structural parameters and final glucose yields were elucidated, and the relative significance of the factors influencing enzymatic hydrolyzability were assessed by principal component analysis (PCA). Hydrothermal pretreatment at a lower temperature (170 °C) combined with ultrafine grinding achieved a high glucose yield (80.36%) at a low enzyme loading (5 filter paper unit (FPU)/g substrate) which is favorable. The relative significance of structural parameters in enzymatic hydrolyzability was SSA > PV > average pore size > CrI/cellulose > particle size. PV and SSA exhibited logarithmic correlations with the final enzymatic hydrolysis yield.


Assuntos
Zea mays/metabolismo , Reatores Biológicos , Celulose , Enzimas/metabolismo , Glucose , Hidrólise , Temperatura Ambiente
7.
Bioresour Technol ; 265: 1-7, 2018 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-29860078

RESUMO

The alkaline hydrogen peroxide (AHP) pretreatment (0.5 g H2O2/g corn stover, 30 °C, 24 h) removed 91.53% of the initial lignin and 55.77% of the initial hemicellulose in corn stover and afforded a considerable glucose yield (88.34%) through enzymatic hydrolysis. A combination of chemical and microstructural analyses was used to illustrate the mechanism of the effect of AHP pretreatment on enzymatic hydrolysis. During pretreatment, H2O2-derived radicals effectively spread into and destroyed the cell wall of various parts (vascular bundle sheath, xylem vessels, tracheid, phloem, and parenchyma) of corn stover to remove most of the lignin, acetyl group, and partial hemicellulose. They destroyed the compact structure of the cellulose-hemicellulose-lignin network, increased the cellulase-accessible pore volume by 6 times, doubled the area of exposed cellulose, and decreased the unproductive adsorption of enzymes onto lignin. Combining all the effects, AHP pretreatment effectively improved the cellulose accessibility to enhance the subsequent enzymatic hydrolysis efficiency.


Assuntos
Peróxido de Hidrogênio , Lignina , Zea mays , Celulase , Celulose , Hidrólise , Eliminação de Resíduos
8.
Rev Sci Instrum ; 88(10): 104706, 2017 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-29092528

RESUMO

With the development of deep learning, research on image target recognition has made great progress in recent years. Remote sensing detection urgently requires target recognition for military, geographic, and other scientific research. This paper aims to solve the synthetic aperture radar image target recognition problem by combining deep and kernel learning. The model, which has a multilayer multiple kernel structure, is optimized layer by layer with the parameters of Support Vector Machine and a gradient descent algorithm. This new deep kernel learning method improves accuracy and achieves competitive recognition results compared with other learning methods.

9.
Rev Sci Instrum ; 88(6): 065004, 2017 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-28668006

RESUMO

Hyperspectral remote sensing has a strong ability of object information expression, so it provides better support for object classification. Many methods are proposed for the hyperspectral data classification. The spectrum classification is a classical nonlinear problem, and a kernel-based machine is feasible to classify the spectrum data. In the nonlinear kernel-based space, the spectrum data are more discriminative. The kernel functions determine the data distribution in the feature space. In this paper, we propose the quasiconformal multiple kernels-based machine learning for the hyperspectral data classification. In the framework, the structure of hyperspectral data is adaptively adjusted for classification. The multiple kernels extract the multiple features of hyperspectral data for classification. Multiple features-based machine learning exhibits a great potential on the classification of hyperspectral data. Two public datasets, India Pines dataset and Pavia University dataset, are used to test the proposed algorithm. Experimental results demonstrate that the proposed quasiconformal multiple kernels-based hyperspectral data classification method can show competitive performance.

10.
Bioresour Technol ; 234: 23-32, 2017 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-28315601

RESUMO

Quantitative analysis of enzyme adsorption and hydrolysis were performed for sieve-based grinding corn stover (SGCS) and ultrafine grinding corn stover (UGCS)1 with different enzyme consumptions. The UGCS presented significantly higher enzyme adsorption quantity (5.15mg/g for UGCS, 1.33mg/g for SGCS), higher glucose yield (49.75% for UGCS, 28.75% for SGCS) under 20FPU/g and higher binding enzyme proportion (41.32% for UGCS, 10.64% for SGCS under 5FPU/g) which can be attributed to the more accessible microstructure properties. The relationship between enzyme adsorption and hydrolytic production was directly proportional for SGCS (GY1=21.04×AQ1+1.86 (R2=0.95)) while was exponential for UGCS (GY2=49.42×(1-e-0.57×AQ2) (R2=0.99)),2 indicating that overmuch enzyme consumption was not advisable for UGCS at economical aspect.


Assuntos
Celulase/metabolismo , Zea mays/química , Adsorção , Hidrólise
11.
Rev Sci Instrum ; 88(1): 015006, 2017 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-28147685

RESUMO

Sensor-based monitoring systems use multiple sensors to identify high-level information based on the events that take place in a monitored environment. Identification and health care are important tasks in the smart environment. This paper presents a framework for multisensory multimedia data analysis using a kernel optimization-based principal analysis for identification and health care in a smart environment. Images of faces, palmprints, and fingerprints are used to identify a person, and a wrist pulse signal is used to analyze the person's health condition. The recognition performance evaluations are implemented on the complex dataset of face, palmprint, fingerprint, and wrist pulse signals. The experimental results show that the proposed algorithms perform well for identification and heath analysis.


Assuntos
Algoritmos , Aprendizado de Máquina , Reconhecimento Automatizado de Padrão/métodos , Dermatoglifia , Nível de Saúde , Humanos , Pulso Arterial
12.
Biotechnol Biofuels ; 9(1): 181, 2016.
Artigo em Inglês | MEDLINE | ID: mdl-27579144

RESUMO

BACKGROUND: Ultrafine grinding is an environmentally friendly pretreatment that can alter the degree of polymerization, the porosity and the specific surface area of lignocellulosic biomass and can, thus, enhance cellulose hydrolysis. Enzyme adsorption onto the substrate is a prerequisite for the enzymatic hydrolysis process. Therefore, it is necessary to investigate the enzyme adsorption properties of corn stover pretreated by ultrafine grinding. RESULTS: The ultrafine grinding pretreatment was executed on corn stover. The results showed that ultrafine grinding pretreatment can significantly decrease particle size [from 218.50 µm of sieve-based grinding corn stover (SGCS) to 17.45 µm of ultrafine grinding corn stover (UGCS)] and increase the specific surface area (SSA), pore volume (PV) and surface composition (SSA: from 1.71 m(2)/g of SGCS to 2.63 m(2)/g of UGCS, PV: from 0.009 cm(3)/g of SGCS to 0.024 m(3)/g of UGCS, cellulose surface area: from 168.69 m(2)/g of SGCS to 290.76 m(2)/g of UGCS, lignin surface area: from 91.46 m(2)/g of SGCS to 106.70 m(2)/g of UGCS). The structure and surface composition changes induced by ultrafine grinding increase the enzyme adsorption capacity from 2.83 mg/g substrate of SGCS to 5.61 mg/g substrate of UGCS. A film-pore-surface diffusion model was developed to simultaneously predict the enzyme adsorption kinetics of both the SGCS and UGCS. Satisfactory predictions could be made with the model based on high R (2) and low RMSE values (R (2) = 0.95 and RMSE = 0.16 mg/g for the UGCS, R (2) = 0.93 and RMSE = 0.09 mg/g for the SGCS). The model was further employed to analyze the rate-limiting steps in the enzyme adsorption process. Although both the external-film and internal-pore mass transfer are important for enzyme adsorption on the SGCS and UGCS, the UGCS has a lower internal-pore resistance compared to the SGCS. CONCLUSIONS: Ultrafine grinding pretreatment can enhance the enzyme adsorption onto corn stover by altering structure and surface composition. The film-pore-surface diffusion model successfully captures features on enzyme adsorption on ultrafine grinding pretreated corn stover. These findings identify wherein the probable rate-limiting factors for the enzyme adsorption reside and could, therefore, provide a basis for enhanced cellulose hydrolysis processes.

13.
Exp Ther Med ; 11(6): 2209-2212, 2016 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-27284302

RESUMO

The aim of the present study was to evaluate the efficacy of targeted nursing for patients with systemic lupus erythematosus (SLE). A total of 114 patients clinically diagnosed with stable SLE were prospectively selected. The patients were randomly divided into the regular special nursing group, comprising 56 patients and the targeted nursing group (i.e., taylor made according to different pathogenic conditions and treatment period), comprising 58 patients. The patients received standard medical treatment for SLE, irrespective of their group, and the efficacy of targeted nursing on disease activity, incidence of complications, therapeutic compliance, quality of life and nursing satisfaction was compared with regular special nursing. The patients were followed up for a period of 20 months. The results showed that, disease activity and injury index score and incidence of complications were significantly less in the targeted nursing group than in the regular special nursing group (P<0.05). Additionally, therapeutic compliance, quality of life score and nursing content satisfaction were significantly higher in the targeted nursing group in comparison with the regular special nursing group (P<0.05). Thus, the results indicated that targeted nursing significantly improved therapeutic compliance and quality of life, and simultaneously, reduced complications and disease activity in patients receiving standard treatment for SLE.

14.
Carbohydr Polym ; 141: 1-9, 2016 May 05.
Artigo em Inglês | MEDLINE | ID: mdl-26876990

RESUMO

Corn stover was pretreated with acid under moderate conditions (1.5%, w/w, 121°C, 60min), and kinetic enzymolysis experiments were performed on the pretreated substrate using a mixture of Celluclast 1.5L (20FPU/g dry substrate) and Novozyme 188 (40CBU/g dry substrate). Integrated chemical and multi-scale structural methods were then used to characterize both processes. Chemical analysis showed that acid pretreatment removed considerable hemicellulose (from 19.7% in native substrate to 9.28% in acid-pretreated substrate) and achieved a reasonably high conversion efficiency (58.63% of glucose yield) in the subsequent enzymatic hydrolysis. Multi-scale structural analysis indicated that acid pretreatment caused structural changes via cleaving acetyl linkages, solubilizing hemicellulose, relocating cell wall surfaces and enlarging substrate porosity (pore volume increased from 0.0067cm(3)/g in native substrate to 0.019cm(3)/g in acid-pretreated substrate), thereby improving the polysaccharide digestibility.


Assuntos
Ácidos/química , Ração Animal , Polissacarídeos/química , Zea mays/química , Biocatálise , Glucose/química , Temperatura Alta , Hidrólise
15.
Bioresour Technol ; 177: 8-16, 2015 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-25479388

RESUMO

Kinetic experiments on the dilute sulfuric acid pretreatment of corn stover were performed. A high xylan removal and a low inhibitor concentration were achieved by acid pretreatment. A novel diffusion-hydrolysis coupled kinetic model was proposed. The contribution to the xylose yield was analyzed by the kinetic model. Compared with the inhibitor furfural negatively affecting xylose yield, the fast and slow-hydrolyzing xylan significantly contributed to the xylose yield, however, their dominant roles were dependent on reaction temperature and time. The impact of particle size and acid concentration on the xylose yield were also investigated. The diffusion process may significantly influence the hydrolysis of large particles. Increasing the acid concentration from 0.15 M to 0.30 M significantly improved the xylose yield, whereas the extent of improvement decreased to near-quantitative when further increasing acid loading. These findings shed some light on the mechanism for dilute sulfuric acid hydrolysis of corn stover.


Assuntos
Modelos Químicos , Ácidos Sulfúricos/farmacologia , Resíduos , Zea mays/química , Zea mays/efeitos dos fármacos , Difusão , Furaldeído/metabolismo , Hidrólise/efeitos dos fármacos , Cinética , Tamanho da Partícula , Temperatura Ambiente , Xilanos/metabolismo , Xilose/metabolismo
16.
Clin Imaging ; 37(2): 273-82, 2013 Mar-Apr.
Artigo em Inglês | MEDLINE | ID: mdl-23465979

RESUMO

This paper presents a novel approach to detect and discriminate abnormal and cueing signatures in mammography through enhancing the imaging contrast. Partial gland and adipose tissues are removed, and thus, the visual effect of mammography will be enhanced. Inspired by single image haze removal, we remove the majority of background tissues by introducing the idea of image matting. Experimental results show the feasibility and performance on distinguishing focuses from healthy tissues in the enhanced mammography. The method has potential applications on breast cancer diagnosis in computer-aided detection.


Assuntos
Algoritmos , Neoplasias da Mama/diagnóstico por imagem , Diagnóstico por Computador/métodos , Mamografia , Intensificação de Imagem Radiográfica/métodos , Feminino , Humanos , Técnica de Subtração
17.
Clin Imaging ; 36(6): 710-6, 2012 Nov-Dec.
Artigo em Inglês | MEDLINE | ID: mdl-23153999

RESUMO

Mammogram-based classification is an important and effective way for computer-aided diagnosis (CAD)-based breast cancer diagnosis. In this paper, we present a novel discriminant fusing analysis (DFA)-based mammogram classification CAD-based breast cancer diagnosis. The discriminative breast tissue features are exacted and fused by DFA, and DFA achieves the optimal fusion coefficients. The largest class discriminant in the fused feature space is achieved by DFA for classification. Beside the detailed theory derivation, many experimental evaluations are implemented on Mammography Image Analysis Society mammogram database for breast cancer diagnosis.


Assuntos
Algoritmos , Inteligência Artificial , Neoplasias da Mama/diagnóstico por imagem , Mamografia/métodos , Reconhecimento Automatizado de Padrão/métodos , Interpretação de Imagem Radiográfica Assistida por Computador/métodos , Técnica de Subtração , Análise Discriminante , Feminino , Humanos , Intensificação de Imagem Radiográfica/métodos , Reprodutibilidade dos Testes , Sensibilidade e Especificidade
18.
J Med Syst ; 36(4): 2235-44, 2012 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-21476083

RESUMO

Breast tissue classification is an important and effective way for computer aided diagnosis of breast cancer with digital mammogram. Current methods endure two problems, firstly pectoral muscle influences the classification performance owing to its texture similar to parenchyma, and secondly classification algorithms fail to deal with the nonlinear problem from the digital mammogram. For these problems, we propose a novel framework of breast tissue classification based on kernel self-optimized discriminant analysis combined with the artifacts and pectoral muscle removal with multi-level segmentation based Connected Component Labeling analysis. Experiments on mini-MIAS database are implemented to testify and evaluate the performance of proposed algorithm.


Assuntos
Neoplasias da Mama/classificação , Neoplasias da Mama/diagnóstico por imagem , Diagnóstico por Computador , Processamento de Imagem Assistida por Computador/métodos , Mamografia , Algoritmos , Análise Discriminante , Feminino , Humanos
19.
J Med Syst ; 36(5): 2779-86, 2012 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-21735250

RESUMO

Breast tissue classification is an important and effective way for computer aided diagnosis of breast cancer. We present Semi-supervised Locality Discriminant Projections with Kernels for breast cancer classification. The contributions of this work lie in: 1) Semi-supervised learning is used into Locality Preserving Projections (LPP) to enhance its performance using side-information together with the unlabelled training samples, while current algorithms only consider the side-information but ignoring the unlabeled training samples. 2) Kernel trick is applied into Semi-supervised LPP to improve its ability in the nonlinear classification. 3) The framework of breast cancer classification with Semi-supervised LPP with kernels is presented. Many experiments are implemented on four breast tissue databases to testify and evaluate the feasibility and affectivity of the proposed scheme.


Assuntos
Neoplasias da Mama/classificação , Interpretação de Imagem Assistida por Computador/métodos , Algoritmos , Inteligência Artificial , Neoplasias da Mama/diagnóstico , Neoplasias da Mama/diagnóstico por imagem , Humanos , Modelos Lineares , Análise de Componente Principal , Radiografia
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