scholarly journals Qualitative SAR Dark Spot Analysis for Oil Anomaly Characterization

2019 ◽  
Vol 7 (5) ◽  
pp. 22-29
Author(s):  
Chituru Dike Obowu ◽  
Tamunoene Kingdom Abam ◽  
Sabastian Ngah
Keyword(s):  
Noise Suppression ◽  
Satellite Image ◽  
Primary Objective ◽  
Dark Spot ◽  
Logarithmic Scale ◽  
Physical Processes ◽  
Noise Filter ◽  
Amplitude Data

The characterization of the morphology of a dark spot event in a SAR image is crucial to determining the nature, fate and classification of a potential oil on water anomaly. Hence the need to adequately analyze SAR backscatter values from an amplitude power image were darks spots have been identified and extracted. The dark spots are potential areas of oil on water events and it is imperative that they are understood sufficiently for the purpose of assigning the level of confidence in the processing of oil analysis, understanding the type of oil on water event, classifying the extent of weathering impacting the detected anomaly and relating the oil anomaly to a potential source. In order to generate high quality datasets for anomaly characterization, it is imperative to transform satellite image amplitude data into power values in units of dB and represented on a logarithmic scale. This new power dataset is corrected radiometrically and requisite speckle to noise filter applied for data cleaning and noise suppression. Oil anomaly or darks spot extraction, representative of a potential oil on water is event which is the primary objective of the pre-processing is done. Gamma enhancement was applied on the dark spots in order to characterize their radiometric, textural and geometric properties. This is predominantly for estimating the confidence level of each anomaly detected, and their properties which are indicative of the type, fate, age and physical processes relating to each anomaly.

scholarly journals Morphological and Ultrastructural Characterization of Hemocytes in an Insect Model, the Hematophagous Dipetalogaster maxima (Hemiptera: Reduviidae)

Insects ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 640
Author(s):  
Natalia R. Moyetta ◽  
Fabián O. Ramos ◽  
Jimena Leyria ◽  
Lilián E. Canavoso ◽  
Leonardo L. Fruttero
Keyword(s):  
Cell Biology ◽  
Cell Types ◽  
Transmission Electron ◽  
Ultrastructural Characterization ◽  
Current Classification ◽  
Contrast Microscopy ◽  
First Time ◽  
Controversial Aspect

Hemocytes, the cells present in the hemolymph of insects and other invertebrates, perform several physiological functions, including innate immunity. The current classification of hemocyte types is based mostly on morphological features; however, divergences have emerged among specialists in triatomines, the insect vectors of Chagas’ disease (Hemiptera: Reduviidae). Here, we have combined technical approaches in order to characterize the hemocytes from fifth instar nymphs of the triatomine Dipetalogaster maxima. Moreover, in this work we describe, for the first time, the ultrastructural features of D. maxima hemocytes. Using phase contrast microscopy of fresh preparations, five hemocyte populations were identified and further characterized by immunofluorescence, flow cytometry and transmission electron microscopy. The plasmatocytes and the granulocytes were the most abundant cell types, although prohemocytes, adipohemocytes and oenocytes were also found. This work sheds light on a controversial aspect of triatomine cell biology and physiology setting the basis for future in-depth studies directed to address hemocyte classification using non-microscopy-based markers.

scholarly journals Semi-automated regional classification of the style of activity of slow rock-slope deformations using PS InSAR and SqueeSAR velocity data

Landslides ◽  
2021 ◽  
Author(s):  
Chiara Crippa ◽  
Elena Valbuzzi ◽  
Paolo Frattini ◽  
Giovanni B. Crosta ◽  
Margherita C. Spreafico ◽  
...  
Keyword(s):  
Rock Slope ◽  
Progressive Failure ◽  
Principal Component ◽  
Cost Effective ◽  
Displacement Rate ◽  
Machine Learning Classification ◽  
Management Perspective ◽  
Alpine Environments

AbstractLarge slow rock-slope deformations, including deep-seated gravitational slope deformations and large landslides, are widespread in alpine environments. They develop over thousands of years by progressive failure, resulting in slow movements that impact infrastructures and can eventually evolve into catastrophic rockslides. A robust characterization of their style of activity is thus required in a risk management perspective. We combine an original inventory of slow rock-slope deformations with different PS-InSAR and SqueeSAR datasets to develop a novel, semi-automated approach to characterize and classify 208 slow rock-slope deformations in Lombardia (Italian Central Alps) based on their displacement rate, kinematics, heterogeneity and morphometric expression. Through a peak analysis of displacement rate distributions, we characterize the segmentation of mapped landslides and highlight the occurrence of nested sectors with differential activity and displacement rates. Combining 2D decomposition of InSAR velocity vectors and machine learning classification, we develop an automatic approach to characterize the kinematics of each landslide. Then, we sequentially combine principal component and K-medoids cluster analyses to identify groups of slow rock-slope deformations with consistent styles of activity. Our methodology is readily applicable to different landslide datasets and provides an objective and cost-effective support to land planning and the prioritization of local-scale studies aimed at granting safety and infrastructure integrity.

scholarly journals The Underlying Order Induced by Orthogonality and the Quantum Speed Limit

2021 ◽  
Vol 3 (3) ◽  
pp. 376-388
Author(s):  
Francisco J. Sevilla ◽  
Andrea Valdés-Hernández ◽  
Alan J. Barrios
Keyword(s):  
Energy Spectrum ◽  
Energy Distribution ◽  
Finite Time ◽  
Complete Characterization ◽  
Comprehensive Analysis ◽  
Orthogonality Condition ◽  
Speed Limit ◽  
Physical Quantities

We perform a comprehensive analysis of the set of parameters {ri} that provide the energy distribution of pure qutrits that evolve towards a distinguishable state at a finite time τ, when evolving under an arbitrary and time-independent Hamiltonian. The orthogonality condition is exactly solved, revealing a non-trivial interrelation between τ and the energy spectrum and allowing the classification of {ri} into families organized in a 2-simplex, δ2. Furthermore, the states determined by {ri} are likewise analyzed according to their quantum-speed limit. Namely, we construct a map that distinguishes those ris in δ2 correspondent to states whose orthogonality time is limited by the Mandelstam–Tamm bound from those restricted by the Margolus–Levitin one. Our results offer a complete characterization of the physical quantities that become relevant in both the preparation and study of the dynamics of three-level states evolving towards orthogonality.

scholarly journals Molecular Classification and Tumor Microenvironment Characterization of Gallbladder Cancer by Comprehensive Genomic and Transcriptomic Analysis

Cancers ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 733
Author(s):  
Nobutaka Ebata ◽  
Masashi Fujita ◽  
Shota Sasagawa ◽  
Kazuhiro Maejima ◽  
Yuki Okawa ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Gallbladder Cancer ◽  
Epithelial To Mesenchymal Transition ◽  
Molecular Classification ◽  
Mesenchymal Transition ◽  
Elevated Expression ◽  
Fresh Frozen ◽  
Therapeutic Decision Making

Gallbladder cancer (GBC), a rare but lethal disease, is often diagnosed at advanced stages. So far, molecular characterization of GBC is insufficient, and a comprehensive molecular portrait is warranted to uncover new targets and classify GBC. We performed a transcriptome analysis of both coding and non-coding RNAs from 36 GBC fresh-frozen samples. The results were integrated with those of comprehensive mutation profiling based on whole-genome or exome sequencing. The clustering analysis of RNA-seq data facilitated the classification of GBCs into two subclasses, characterized by high or low expression levels of TME (tumor microenvironment) genes. A correlation was observed between gene expression and pathological immunostaining. TME-rich tumors showed significantly poor prognosis and higher recurrence rate than TME-poor tumors. TME-rich tumors showed overexpression of genes involved in epithelial-to-mesenchymal transition (EMT) and inflammation or immune suppression, which was validated by immunostaining. One non-coding RNA, miR125B1, exhibited elevated expression in stroma-rich tumors, and miR125B1 knockout in GBC cell lines decreased its invasion ability and altered the EMT pathway. Mutation profiles revealed TP53 (47%) as the most commonly mutated gene, followed by ELF3 (13%) and ARID1A (11%). Mutations of ARID1A, ERBB3, and the genes related to the TGF-β signaling pathway were enriched in TME-rich tumors. This comprehensive analysis demonstrated that TME, EMT, and TGF-β pathway alterations are the main drivers of GBC and provides a new classification of GBCs that may be useful for therapeutic decision-making.

scholarly journals Practical classification of triple-negative breast cancer: intratumoral heterogeneity, mechanisms of drug resistance, and novel therapies

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Antonio Marra ◽  
Dario Trapani ◽  
Giulia Viale ◽  
Carmen Criscitiello ◽  
Giuseppe Curigliano
Keyword(s):  
Breast Cancer ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Residual Disease ◽  
Therapeutic Approaches ◽  
Minimal Residual Disease Monitoring ◽  
Anticancer Treatment ◽  
Immune Contexture

Abstract Triple-negative breast cancer (TNBC) is not a unique disease, encompassing multiple entities with marked histopathological, transcriptomic and genomic heterogeneity. Despite several efforts, transcriptomic and genomic classifications have remained merely theoretic and most of the patients are being treated with chemotherapy. Driver alterations in potentially targetable genes, including PIK3CA and AKT, have been identified across TNBC subtypes, prompting the implementation of biomarker-driven therapeutic approaches. However, biomarker-based treatments as well as immune checkpoint inhibitor-based immunotherapy have provided contrasting and limited results so far. Accordingly, a better characterization of the genomic and immune contexture underpinning TNBC, as well as the translation of the lessons learnt in the metastatic disease to the early setting would improve patients’ outcomes. The application of multi-omics technologies, biocomputational algorithms, assays for minimal residual disease monitoring and novel clinical trial designs are strongly warranted to pave the way toward personalized anticancer treatment for patients with TNBC.

scholarly journals Land Cover Classification of Nine Perennial Crops Using Sentinel-1 and -2 Data

2019 ◽  
Vol 12 (1) ◽  
pp. 96 ◽  
Author(s):  
James Brinkhoff ◽  
Justin Vardanega ◽  
Andrew J. Robson
Keyword(s):  
Land Cover ◽  
Large Scale ◽  
Satellite Image ◽  
Resource Planning ◽  
Support Vector ◽  
Perennial Crop ◽  
Perennial Crops ◽  
Object Based ◽  
Rbf Kernel

Land cover mapping of intensive cropping areas facilitates an enhanced regional response to biosecurity threats and to natural disasters such as drought and flooding. Such maps also provide information for natural resource planning and analysis of the temporal and spatial trends in crop distribution and gross production. In this work, 10 meter resolution land cover maps were generated over a 6200 km2 area of the Riverina region in New South Wales (NSW), Australia, with a focus on locating the most important perennial crops in the region. The maps discriminated between 12 classes, including nine perennial crop classes. A satellite image time series (SITS) of freely available Sentinel-1 synthetic aperture radar (SAR) and Sentinel-2 multispectral imagery was used. A segmentation technique grouped spectrally similar adjacent pixels together, to enable object-based image analysis (OBIA). K-means unsupervised clustering was used to filter training points and classify some map areas, which improved supervised classification of the remaining areas. The support vector machine (SVM) supervised classifier with radial basis function (RBF) kernel gave the best results among several algorithms trialled. The accuracies of maps generated using several combinations of the multispectral and radar bands were compared to assess the relative value of each combination. An object-based post classification refinement step was developed, enabling optimization of the tradeoff between producers’ accuracy and users’ accuracy. Accuracy was assessed against randomly sampled segments, and the final map achieved an overall count-based accuracy of 84.8% and area-weighted accuracy of 90.9%. Producers’ accuracies for the perennial crop classes ranged from 78 to 100%, and users’ accuracies ranged from 63 to 100%. This work develops methods to generate detailed and large-scale maps that accurately discriminate between many perennial crops and can be updated frequently.

Characterization of Electroencephalographic Findings at an Electrodiagnostic Unit of a Tertiary Hospital, North-central Nigeria

2021 ◽  
Vol 2 (1) ◽  
pp. 49-55
Author(s):  
E U Iwuozo ◽  
J O Enyikwola ◽  
I O Obekpa ◽  
O O Ijachi ◽  
A A Godwin ◽  
...  
Keyword(s):  
Tertiary Hospital ◽  
Seizure Disorder ◽  
Cross Sectional ◽  
North Central ◽  
Younger Age ◽  
High Prevalence ◽  
Diagnosis And Classification ◽  
Age Range

Electroencephalography (EEG) remains an important investigative tool in supporting the diagnosis and classification of various seizure types. We sought to examine and characterize the EEG findings from all patients referred for the procedure. This cross-sectional retrospective study was carried out at an EEG unit in Federal Medical Centre, Makurdi, Benue State, North Central Nigeria from May 2016 to December 2020. Relevant patients' information were extracted and analysed using SPSS version 21. A total of 484 patients were seen over the study period with age range of 1-87 years and median age of 23 years. They comprised of 254 (52.5%) male and 230 (47.5%) female. The psychiatrist and the Physicians/Neurologist referred most of them for EEG, 201 (41.5%) and 124 (25.6%) respectively. The most reported indication for EEG was clinical suspicion of seizure disorder 291 (60.1%), whilst some did not have a clear indication 111 (22.9%). About 417 (86.2%) of our patients had abnormal EEG finding out of which 414 (99.3%) were diagnostic of seizure disorder made up of generalized seizure in 255 (61.6%) and focal seizure in 159 (38.4%). About 237 (48.9%) of them were already on antiepileptic drugs (AEDs) at referral of which 190 (80.2%0 were taking carbamazepine. This study showed a high prevalence of abnormal EEG with most of them diagnostic of seizure disorder especially generalized seizure. They were mostly of younger age group with about half of them already on AEDs at referral, majority of who were sent by the Psychiatrist.

scholarly journals Soil–landform–plant-community relationships of a periglacial landscape on Potter Peninsula, maritime Antarctica

Solid Earth ◽  
2015 ◽  
Vol 6 (2) ◽  
pp. 583-594 ◽  
Author(s):  
E. L. Poelking ◽  
C. E. R. Schaefer ◽  
E. I. Fernandes Filho ◽  
A. M. de Andrade ◽  
A. A. Spielmann
Keyword(s):  
Climate Change ◽  
Plant Communities ◽  
Terrestrial Ecosystems ◽  
Maritime Antarctica ◽  
Climate Change Effects ◽  
Ornithogenic Soils ◽  
Physical Environmental Factors ◽  
Potter Peninsula

Abstract. Integrated studies on the interplay between soils, periglacial geomorphology and plant communities are crucial for the understanding of climate change effects on terrestrial ecosystems of maritime Antarctica, one of the most sensitive areas to global warming. Knowledge on physical environmental factors that influence plant communities can greatly benefit studies on the monitoring of climate change in maritime Antarctica, where new ice-free areas are being constantly exposed, allowing plant growth and organic carbon inputs. The relationship between topography, plant communities and soils was investigated on Potter Peninsula, King George Island, maritime Antarctica. We mapped the occurrence and distribution of plant communities and identified soil–landform–vegetation relationships. The vegetation map was obtained by classification of a QuickBird image, coupled with detailed landform and characterization of 18 soil profiles. The sub-formations were identified and classified, and we also determined the total elemental composition of lichens, mosses and grasses. Plant communities on Potter Peninsula occupy 23% of the ice-free area, at different landscape positions, showing decreasing diversity and biomass from the coastal zone to inland areas where sub-desert conditions prevail. There is a clear dependency between landform and vegetated soils. Soils that have greater moisture or are poorly drained, and with acid to neutral pH, are favourable for moss sub-formations. Saline, organic-matter-rich ornithogenic soils of former penguin rookeries have greater biomass and diversity, with mixed associations of mosses and grasses, while stable felsenmeers and flat rocky cryoplanation surfaces are the preferred sites for Usnea and Himantormia lugubris lichens at the highest surface. Lichens sub-formations cover the largest vegetated area, showing varying associations with mosses.

scholarly journals An Application of Spherical Geometry to Hyperkähler Slices

2020 ◽  
pp. 1-30
Author(s):  
Peter Crooks ◽  
Maarten van Pruijssen
Keyword(s):  
Sufficient Conditions ◽  
Compact Subgroup ◽  
Spherical Geometry ◽  
Spherical Subgroup ◽  
Cotangent Bundles ◽  
Complex Semisimple ◽  
Reductive Subgroup ◽  
Necessary And Sufficient

Abstract This work is concerned with Bielawski’s hyperkähler slices in the cotangent bundles of homogeneous affine varieties. One can associate such a slice with the data of a complex semisimple Lie group  $G$ , a reductive subgroup $H\subseteq G$ , and a Slodowy slice $S\subseteq \mathfrak{g}:=\text{Lie}(G)$ , defining it to be the hyperkähler quotient of $T^{\ast }(G/H)\times (G\times S)$ by a maximal compact subgroup of  $G$ . This hyperkähler slice is empty in some of the most elementary cases (e.g., when $S$ is regular and $(G,H)=(\text{SL}_{n+1},\text{GL}_{n})$ , $n\geqslant 3$ ), prompting us to seek necessary and sufficient conditions for non-emptiness. We give a spherical-geometric characterization of the non-empty hyperkähler slices that arise when $S=S_{\text{reg}}$ is a regular Slodowy slice, proving that non-emptiness is equivalent to the so-called $\mathfrak{a}$ -regularity of $(G,H)$ . This $\mathfrak{a}$ -regularity condition is formulated in several equivalent ways, one being a concrete condition on the rank and complexity of $G/H$ . We also provide a classification of the $\mathfrak{a}$ -regular pairs $(G,H)$ in which $H$ is a reductive spherical subgroup. Our arguments make essential use of Knop’s results on moment map images and Losev’s algorithm for computing Cartan spaces.

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