990 resultados para Nekrassov–Mehmke 2 method – (NM2)
Resumo:
Spatially-explicit modelling of grassland classes is important to site-specific planning for improving grassland and environmental management over large areas. In this study, a climate-based grassland classification model, the Comprehensive and Sequential Classification System (CSCS) was integrated with spatially interpolated climate data to classify grassland in Gansu province, China. The study area is characterized by complex topographic features imposed by plateaus, high mountains, basins and deserts. To improve the quality of the interpolated climate data and the quality of the spatial classification over this complex topography, three linear regression methods, namely an analytic method based on multiple regression and residues (AMMRR), a modification of the AMMRR method through adding the effect of slope and aspect to the interpolation analysis (M-AMMRR) and a method which replaces the IDW approach for residue interpolation in M-AMMRR with an ordinary kriging approach (I-AMMRR), for interpolating climate variables were evaluated. The interpolation outcomes from the best interpolation method were then used in the CSCS model to classify the grassland in the study area. Climate variables interpolated included the annual cumulative temperature and annual total precipitation. The results indicated that the AMMRR and M-AMMRR methods generated acceptable climate surfaces but the best model fit and cross validation result were achieved by the I-AMMRR method. Twenty-six grassland classes were classified for the study area. The four grassland vegetation classes that covered more than half of the total study area were "cool temperate-arid temperate zonal semi-desert", "cool temperate-humid forest steppe and deciduous broad-leaved forest", "temperate-extra-arid temperate zonal desert", and "frigid per-humid rain tundra and alpine meadow". The vegetation classification map generated in this study provides spatial information on the locations and extents of the different grassland classes. This information can be used to facilitate government agencies' decision-making in land-use planning and environmental management, and for vegetation and biodiversity conservation. The information can also be used to assist land managers in the estimation of safe carrying capacities which will help to prevent overgrazing and land degradation.
Resumo:
Pyrido[1,2-a]benzimidazoles1, 2a are interesting compounds both from the viewpoint of medicinal chemistry2–7 (solubility,7 DNA intercalation3) and materials chemistry8 (fluorescence). Of note among the former is the antibiotic drug Rifaximin,5 which contains this heteroaromatic core. The classical synthetic approach for the assembly of pyrido[1,2-a]benzimidazoles is by [3+3] cyclocondensation of benzimidazoles containing a methylene group at C2 with appropriate bielectrophiles.2a However, these procedures are often low-yielding, involve indirect/lengthy sequences, and/or provide access to a limited range of products, primarily providing derivatives with substituents located on the pyridine ring (A ring, Scheme 1).2–4 Theoretically, a good alternative synthetic method for the synthesis of pyrido[1,2-a]benzimidazoles with substituents in the benzene ring (C ring) should be accessible by intramolecular transition-metal-catalyzed CN bond formation in N-(2-chloroaryl)pyridin-2-amines, based on chemistry recently developed in our research group.9 These substrates themselves are easily available through SNAr or selective Pd-catalyzed amination10 of 2-chloropyridine with 2-chloroanilines.11 If a synthetic procedure that eliminated the need for preactivation of the 2-position of the 2-chloroarylamino entity could be developed, this would be even more powerful, as anilines are more readily commercially available than 2-chloroanilines. Therefore the synthesis of pyrido[1,2-a]benzimidazoles (4) by a transition-metal-catalyzed intramolecular CH amination approach from N-arylpyridin-2-amines (3) was explored (Scheme 1).
Resumo:
Recently, botnet, a network of compromised computers, has been recognized as the biggest threat to the Internet. The bots in a botnet communicate with the botnet owner via a communication channel called Command and Control (C & C) channel. There are three main C & C channels: Internet Relay Chat (IRC), Peer-to-Peer (P2P) and web-based protocols. By exploiting the flexibility of the Web 2.0 technology, the web-based botnet has reached a new level of sophistication. In August 2009, such botnet was found on Twitter, one of the most popular Web 2.0 services. In this paper, we will describe a new type of botnet that uses Web 2.0 service as a C & C channel and a temporary storage for their stolen information. We will then propose a novel approach to thwart this type of attack. Our method applies a unique identifier of the computer, an encryption algorithm with session keys and a CAPTCHA verification.
Resumo:
This study reports that treatment of osseous defects with different growth factors initiates distinct rates of repair. We developed a new method for monitoring the progression of repair, based upon measuring the in vivo mechanical properties of healing bone. Two different members of the bone morphogenetic protein (BMP) family were chosen to initiate defect healing: BMP-2 to induce osteogenesis, and growth-and-differentiation factor (GDF)-5 to induce chondrogenesis. To evaluate bone healing, BMPs were implanted into stabilised 5 mm bone defects in rat femurs and compared to controls. During the first two weeks, in vivo biomechanical measurements showed similar values regardless of the treatment used. However, 2 weeks after surgery, the rhBMP-2 group had a substantial increase in stiffness, which was supported by the imaging modalities. Although the rhGDF-5 group showed comparable mechanical properties at 6 weeks as the rhBMP-2 group, the temporal development of regenerating tissues appeared different with rhGDF-5, resulting in a smaller callus and delayed tissue mineralisation. Moreover, histology showed the presence of cartilage in the rhGDF-5 group whereas the rhBMP-2 group had no cartilaginous tissue. Therefore, this study shows that rhBMP-2 and rhGDF-5 treated defects, under the same conditions, use distinct rates of bone healing as shown by the tissue mechanical properties. Furthermore, results showed that in vivo biomechanical method is capable of detecting differences in healing rate by means of change in callus stiffness due to tissue mineralisation.
Resumo:
The aim of this study was to use lipidomics to determine if the lipid composition of apolipoprotein-B-containing lipoproteins is modified by dyslipidaemia in type 2 diabetes and if any of the identified changes potentially have biological relevance in the pathophysiology of type 2 diabetes. VLDL and LDL from normolipidaemic and dyslipidaemic type 2 diabetic women and controls were isolated and quantified with HPLC and mass spectrometry. A detailed molecular characterisation of VLDL triacylglycerols (TAG) was also performed using the novel ozone-induced dissociation method, which allowed us to distinguish vaccenic acid (C18:1 n-7) from oleic acid (C18:1 n-9) in specific TAG species. Lipid class composition was very similar in VLDL and LDL from normolipidaemic type 2 diabetic and control participants. By contrast, dyslipidaemia was associated with significant changes in both lipid classes (e.g. increased diacylglycerols) and lipid species (e.g. increased C16:1 and C20:3 in phosphatidylcholine and cholesteryl ester and increased C16:0 [palmitic acid] and vaccenic acid in TAG). Levels of palmitic acid in VLDL and LDL TAG correlated with insulin resistance, and VLDL TAG enriched in palmitic acid promoted increased secretion of proinflammatory mediators from human smooth muscle cells. We showed that dyslipidaemia is associated with major changes in both lipid class and lipid species composition in VLDL and LDL from women with type 2 diabetes. In addition, we identified specific molecular lipid species that both correlate with clinical variables and are proinflammatory. Our study thus shows the potential of advanced lipidomic methods to further understand the pathophysiology of type 2 diabetes.
Resumo:
MicroRNAs (miRNAs) are a class of small non-coding RNAs with a critical role in development and environmental responses. Efficient and reliable detection of miRNAs is an essential step towards understanding their roles in specific cells and tissues. However, gel-based assays currently used to detect miRNAs are very limited in terms of throughput, sensitivity and specificity. Here we provide protocols for detection and quantification of miRNAs by RT-PCR. We describe an end-point and real-time looped RT-PCR procedure and demonstrate detection of miRNAs from as little as 20 pg of plant tissue total RNA and from total RNA isolated from as little as 0.1 l of phloem sap. In addition, we have developed an alternative real-time PCR assay that can further improve specificity when detecting low abundant miRNAs. Using this assay, we have demonstrated that miRNAs are differentially expressed in the phloem sap and the surrounding vascular tissue. This method enables fast, sensitive and specific miRNA expression profiling and is suitable for facilitation of high-throughput detection and quantification of miRNA expression.
Resumo:
This paper describes a novel system for automatic classification of images obtained from Anti-Nuclear Antibody (ANA) pathology tests on Human Epithelial type 2 (HEp-2) cells using the Indirect Immunofluorescence (IIF) protocol. The IIF protocol on HEp-2 cells has been the hallmark method to identify the presence of ANAs, due to its high sensitivity and the large range of antigens that can be detected. However, it suffers from numerous shortcomings, such as being subjective as well as time and labour intensive. Computer Aided Diagnostic (CAD) systems have been developed to address these problems, which automatically classify a HEp-2 cell image into one of its known patterns (eg. speckled, homogeneous). Most of the existing CAD systems use handpicked features to represent a HEp-2 cell image, which may only work in limited scenarios. We propose a novel automatic cell image classification method termed Cell Pyramid Matching (CPM), which is comprised of regional histograms of visual words coupled with the Multiple Kernel Learning framework. We present a study of several variations of generating histograms and show the efficacy of the system on two publicly available datasets: the ICPR HEp-2 cell classification contest dataset and the SNPHEp-2 dataset.
Resumo:
Background Accelerometers have become one of the most common methods of measuring physical activity (PA). Thus, validity of accelerometer data reduction approaches remains an important research area. Yet, few studies directly compare data reduction approaches and other PA measures in free-living samples. Objective To compare PA estimates provided by 3 accelerometer data reduction approaches, steps, and 2 self-reported estimates: Crouter's 2-regression model, Crouter's refined 2-regression model, the weighted cut-point method adopted in the National Health and Nutrition Examination Survey (NHANES; 2003-2004 and 2005-2006 cycles), steps, IPAQ, and 7-day PA recall. Methods A worksite sample (N = 87) completed online-surveys and wore ActiGraph GT1M accelerometers and pedometers (SW-200) during waking hours for 7 consecutive days. Daily time spent in sedentary, light, moderate, and vigorous intensity activity and percentage of participants meeting PA recommendations were calculated and compared. Results Crouter's 2-regression (161.8 +/- 52.3 minutes/day) and refined 2-regression (137.6 +/- 40.3 minutes/day) models provided significantly higher estimates of moderate and vigorous PA and proportions of those meeting PA recommendations (91% and 92%, respectively) as compared with the NHANES weighted cut-point method (39.5 +/- 20.2 minutes/day, 18%). Differences between other measures were also significant. Conclusions When comparing 3 accelerometer cut-point methods, steps, and self-report measures, estimates of PA participation vary substantially.
Resumo:
This thesis developed a new method for measuring extremely low amounts of organic and biological molecules, using Surface enhanced Raman Spectroscopy. This method has many potential applications, e.g. medical diagnosis, public health, food provenance, antidoping, forensics and homeland security. The method development used caffeine as the small molecule example, and erythropoietin (EPO) as the large molecule. This method is much more sensitive and specific than currently used methods; rapid, simple and cost effective. The method can be used to detect target molecules in beverages and biological fluids without the usual preparation steps.
Resumo:
The basic principles and equations are developed for elementary finance, based on the concept of compound interest. The five quantities of interest in such problems are present value, future value, amount of periodic payment, number of periods and the rate of interest per period. We consider three distinct means of computing each of these five quantities in Excel 2007: (i) use of algebraic equations, (ii) by recursive schedule and the Goal Seek facility, and (iii) use of Excel's intrinsic financial functions. The paper is intended to be used as the basis for a lesson plan and contains many examples and solved problems. Comment is made regarding the relative difficulty of each approach, and a prominent theme is the systematic use of more than one method to increase student understanding and build confidence in the answer obtained. Full instructions to build each type of model are given and a complete set of examples and solutions may be downloaded (Examples.xlsx and Solutions.xlsx).
Resumo:
In this paper the renormalization group (RG) method of Chen, Goldenfeld, and Oono [Phys. Rev. Lett., 73 (1994), pp.1311-1315; Phys. Rev. E, 54 (1996), pp.376-394] is presented in a pedagogical way to increase its visibility in applied mathematics and to argue favorably for its incorporation into the corresponding graduate curriculum.The method is illustrated by some linear and nonlinear singular perturbation problems. Key word. © 2012 Society for Industrial and Applied Mathematics.
Resumo:
Background Obtaining single parasite clones is required for many techniques in malaria research. Cloning by limiting dilution using microscopy-based assessment for parasite growth is an arduous and labor-intensive process. An alternative method for the detection of parasite growth in limiting dilution assays is using a commercial ELISA histidine-rich protein II (HRP2) detection kit. Methods Detection of parasite growth was undertaken using HRP2 ELISA and compared to thick film microscopy. An HRP2 protein standard was used to determine the detection threshold of the HRP2 ELISA assay, and a HRP2 release model was used to extrapolate the amount of parasite growth required for a positive result. Results The HRP2 ELISA was more sensitive than microscopy for detecting parasite growth. The minimum level of HRP2 protein detection of the ELISA was 0.11ng/ml. Modeling of HRP2 release determined that 2,116 parasites are required to complete a full erythrocytic cycle to produce sufficient HRP2 to be detected by the ELISA. Under standard culture conditions this number of parasites is likely to be reached between 8 to 14 days of culture. Conclusions This method provides an accurate and simple way for the detection of parasite growth in limiting dilution assays, reducing time and resources required in traditional methods. Furthermore the method uses spent culture media instead of the parasite-infected red blood cells, enabling culture to continue.
Resumo:
In this paper, we have synthesized two novel diketopyrrolopyrrole (DPP) based donor-acceptor (D-A) copolymers poly{3,6-dithiophene-2-yl-2,5-di(2-octyl)- pyrrolo[3,4-c]pyrrole-1,4-dione-alt-1,5-bis(dodecyloxy)naphthalene} (PDPPT-NAP) and poly{3,6-dithiophene-2-yl-2,5-di(2-butyldecyl)-pyrrolo[3,4-c]pyrrole-1,4- dione-alt-2-dodecyl-2H-benzo[d][1,2,3]triazole} (PDPPT-BTRZ) via direct arylation organometallic coupling. Both copolymers contain a common electron withdrawing DPP building block which is combined with electron donating alkoxy naphthalene and electron withdrawing alkyl-triazole comonomers. The number average molecular weight (Mn) determined by gel permeation chromatography (GPC) for polymer PDPPT-NAP is around 23 400 g mol-1 whereas for polymer PDPPT-BTRZ it is 18 600 g mol-1. The solid state absorption spectra of these copolymers show a wide range of absorption from 400 nm to 1000 nm with optical band gaps calculated from absorption cut off values in the range of 1.45-1.30 eV. The HOMO values determined for PDPPT-NAP and PDPPT-BTRZ copolymers from photoelectron spectroscopy in air (PESA) data are 5.15 eV and 5.25 eV respectively. These polymers exhibit promising p-channel and ambipolar behaviour when used as an active layer in organic thin-film transistor (OTFT) devices. The highest hole mobility measured for polymer PDPPT-NAP is around 0.0046 cm2 V-1 s-1 whereas the best ambipolar performance was calculated for PDPPT-BTRZ with a hole and electron mobility of 0.01 cm2 V-1 s-1 and 0.006 cm2 V-1 s-1.