Granular computing, rough entropy and object extraction

The problem of image object extraction in the framework of rough sets and granular computing is addressed. A measure called "rough entropy of image" is defined based on the concept of image granules. Its maximization results in minimization of roughness in both object and background regions; thereby determining the threshold of partitioning. Methods of selecting the appropriate granule size and efficient computation of rough entropy are described

“EVALUATION OF GALPHIMIA GLAUCA STEM METHANOL EXTRACT FRACTIONS FOR ANALGESIC AND ANTI-INFLAMMATORY ACTIVITIES”

Objective: This current investigation assesses in vivo central and peripheral analgesic effects and anti-inflammatory properties of fractions obtained from Galphimia glauca (GG) stem methanol extract. Methods: The laboratory models such as Swiss albino mice and Wistar albino rats were employed in the studies. The GG stem methanol extract was subjected to fractionation with solvents such as hexane, chloroform, ethyl acetate, and methanol. Orally, the dose range of 100, 200, and 400 mg/kg was given for 1 day for evaluating analgesic (hotplate test, tail clip test, writhing test, and formalin test) and weekdays for assessing anti-inflammatory activity (carrageenan and cotton pellet test methods), respectively. The experimental studies were further conducted for determining the involvement of central and peripheral receptor actions in the analgesic activity of the extract by prechallenging it with naloxone and acetic acid, respectively. The in vivo anti-inflammatory studies were conducted using carrageenan-induced rat paw edema model and cotton pellet granuloma test. Results: The LD50 of the extract was found to be >2000 mg/kg b.w. The methanol fraction of 400 mg/kg dose exhibited significant (p≤0.001) and dose-dependent analgesic and anti-inflammatory activity. It also exhibited central and peripheral analgesic actions when treated with naloxone and acetic acid, respectively. Conclusion: The results revealed that the stem methanol fraction has more potential in terms of analgesic and anti-inflammatory properties

Robust Radiomics Feature Quantification Using Semiautomatic Volumetric Segmentation

Due to advances in the acquisition and analysis of medical imaging, it is currently possible to quantify the tumor phenotype. The emerging field of Radiomics addresses this issue by converting medical images into minable data by extracting a large number of quantitative imaging features. One of the main challenges of Radiomics is tumor segmentation. Where manual delineation is time consuming and prone to inter-observer variability, it has been shown that semi-automated approaches are fast and reduce inter-observer variability. In this study, a semiautomatic region growing volumetric segmentation algorithm, implemented in the free and publicly available 3D-Slicer platform, was investigated in terms of its robustness for quantitative imaging feature extraction. Fifty-six 3D-radiomic features, quantifying phenotypic differences based on tumor intensity, shape and texture, were extracted from the computed tomography images of twenty lung cancer patients. These radiomic features were derived from the 3D-tumor volumes defined by three independent observers twice using 3D-Slicer, and compared to manual slice-by-slice delineations of five independent physicians in terms of intra-class correlation coefficient (ICC) and feature range. Radiomic features extracted from 3D-Slicer segmentations had significantly higher reproducibility (ICC = 0.85±0.15, p = 0.0009) compared to the features extracted from the manual segmentations (ICC = 0.77±0.17). Furthermore, we found that features extracted from 3D-Slicer segmentations were more robust, as the range was significantly smaller across observers (p = 3.819e-07), and overlapping with the feature ranges extracted from manual contouring (boundary lower: p = 0.007, higher: p = 5.863e-06). Our results show that 3D-Slicer segmented tumor volumes provide a better alternative to the manual delineation for feature quantification, as they yield more reproducible imaging descriptors. Therefore, 3D-Slicer can be employed for quantitative image feature extraction and image data mining research in large patient cohorts

Integrating livelihoods and conservation in protected areas: Understanding the role and stakeholder views on prospects for non-timber forest products, a Bangladesh case study

Protected areas (PAs) represent a key global strategy in biodiversity conservation. In tropical developing countries, the management of PAs is a great challenge as many contain resources on which local communities rely. Collection and trading of non-timber forest products (NTFPs) is a well-established forest-based livelihood strategy, which has been promoted as a potential means for enhanced conservation and improved rural livelihoods in recent years, even though the sustainability or ecological implications have rarely been tested. We conducted an exploratory survey to understand the role and stakeholder views on conservation prospects and perceived ecological feasibility of NTFPs and harvesting schemes in a northeastern PA of Bangladesh, namely the Satchari National Park. Households (n = 101) were interviewed from three different forest dependency categories, adopting a stratified random sampling approach and using a semi-structured questionnaire. The study identified 13 locally important NTFPs, with five being critically important to supporting local livelihoods. Our study suggests that collection, processing and trading in NTFPs constitutes the primary occupation for about 18% of local inhabitants and account for an estimated 19% of their cash annual income. The household consensus on issues relating to NTFPs and their prospective role in conservation was surprisingly high, with 48% of respondents believing that promotion of NTFPs in the PA could have positive conservation value. The majority (71%) of households also had some understanding of the ecological implications of NTFP harvesting, sustainability (53%) and possible management and monitoring regimes (100%). With little known about their real application in the field, our study suggests further investigations are required to understand the ecological compatibility of traditional NTFP harvesting patterns and management. © 2010 Taylor & Francis

Structure-Activity Determinants in Antifungal Plant Defensins MsDef1 and MtDef4 with Different Modes of Action against Fusarium graminearum

Plant defensins are small cysteine-rich antimicrobial proteins. Their three-dimensional structures are similar in that they consist of an α-helix and three anti-parallel β-strands stabilized by four disulfide bonds. Plant defensins MsDef1 and MtDef4 are potent inhibitors of the growth of several filamentous fungi including Fusarium graminearum. However, they differ markedly in their antifungal properties as well as modes of antifungal action. MsDef1 induces prolific hyperbranching of fungal hyphae, whereas MtDef4 does not. Both defensins contain a highly conserved γ-core motif (GXCX3–9C), a hallmark signature present in the disulfide-stabilized antimicrobial peptides, composed of β2 and β3 strands and the interposed loop. The γ-core motifs of these two defensins differ significantly in their primary amino acid sequences and in their net charge. In this study, we have found that the major determinants of the antifungal activity and morphogenicity of these defensins reside in their γ-core motifs. The MsDef1-γ4 variant in which the γ-core motif of MsDef1 was replaced by that of MtDef4 was almost as potent as MtDef4 and also failed to induce hyperbranching of fungal hyphae. Importantly, the γ-core motif of MtDef4 alone was capable of inhibiting fungal growth, but that of MsDef1 was not. The analysis of synthetic γ-core variants of MtDef4 indicated that the cationic and hydrophobic amino acids were important for antifungal activity. Both MsDef1 and MtDef4 induced plasma membrane permeabilization; however, kinetic studies revealed that MtDef4 was more efficient in permeabilizing fungal plasma membrane than MsDef1. Furthermore, the in vitro antifungal activity of MsDef1, MsDef1-γ4, MtDef4 and peptides derived from the γ-core motif of each defensin was not solely dependent on their ability to permeabilize the fungal plasma membrane. The data reported here indicate that the γ-core motif defines the unique antifungal properties of each defensin and may facilitate de novo design of more potent antifungal peptides

Slow slip source characterized by lithological and geometric heterogeneity

Slow slip events (SSEs) accommodate a significant proportion of tectonic plate motion at subduction zones, yet little is known about the faults that actually host them. The shallow depth (<2 km) of well-documented SSEs at the Hikurangi subduction zone offshore New Zealand offers a unique opportunity to link geophysical imaging of the subduction zone with direct access to incoming material that represents the megathrust fault rocks hosting slow slip. Two recent International Ocean Discovery Program Expeditions sampled this incoming material before it is entrained immediately down-dip along the shallow plate interface. Drilling results, tied to regional seismic reflection images, reveal heterogeneous lithologies with highly variable physical properties entering the SSE source region. These observations suggest that SSEs and associated slow earthquake phenomena are promoted by lithological, mechanical, and frictional heterogeneity within the fault zone, enhanced by geometric complexity associated with subduction of rough crust

Conservation strategies for Srirangapatna Town: evaluation of heritage buildings

There is large number of heritage sites in India and Srirangapatna is one of the prominent heritage sites.It isan island town, situated on Bangalore-Mysore highway, encircled by the river Cauvery. There are many significant heritage areas/precincts and monuments located within the fort, which is one of the principal,elements that add up to the character of Srirangapatna. Over the years, the ever increasing developmental pressures and neglect of monuments/ heritage areas and their environs resulted in decay factors, which call for evolving harmonious strategies and conservation measures.The conservation measures, if taken in time, it will save Srirangapatna from gradual but imminent destruction for sustainable development. The paper presents the historical background of heritage areas and monuments of Srirangapatana and their significance. Significance Assessment is carried-out using mapping procedure for delineating the heritage areas. It suggests the conservation measures by reinvigorating the heritage areas within the fort

Change Detection in Multispectral Remote Sensing Images with Leader Intelligence PSO and NSCT Feature Fusion

Change detection (CD) using Remote sensing images have been a challenging problem over the years. Particularly in the unsupervised domain it is even more difficult. A novel automatic change detection technique in the unsupervised framework is proposed to address the real challenges involved in remote sensing change detection. As the accuracy of change map is highly dependent on quality of difference image (DI), a set of Normalized difference images and a complementary set of Normalized Ratio images are fused in the Nonsubsampled Contourlet Transform (NSCT) domain to generate high quality difference images. The NSCT is chosen as it is efficient in suppressing noise by utilizing its unique characteristics such as multidirectionality and shift-invariance that are suitable for change detection. The low frequency sub bands are fused by averaging to combine the complementary information in the two DIs, and, the higher frequency sub bands are merged by minimum energy rule, for preserving the edges and salient features in the image. By employing a novel Particle Swarm Optimization algorithm with Leader Intelligence (LIPSO), change maps are generated from fused sub bands in two different ways: (i) single spectral band, and (ii) combination of spectral bands. In LIPSO, the concept of leader and followers has been modified with intelligent particles performing L&eacute;vy flight randomly for better exploration, to achieve global optima. The proposed method achieved an overall accuracy of 99.64%, 98.49% and 97.66% on the three datasets considered, which is very high. The results have been compared with relevant algorithms. The quantitative metrics demonstrate the superiority of the proposed techniques over the other methods and are found to be statistically significant with McNemar&rsquo;s test. Visual quality of the results also corroborate the superiority of the proposed method