Land use/cover classification in the Brazilian Amazon using satellite images

Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical regions, due to the complex biophysical environment and limitations of remote sensing data per se. This paper reviews experiments related to land use/cover classification in the Brazilian Amazon for a decade. Through comprehensive analysis of the classification results, it is concluded that spatial information inherent in remote sensing data plays an essential role in improving land use/cover classification. Incorporation of suitable textural images into multispectral bands and use of segmentation‑based method are valuable ways to improve land use/cover classification, especially for high spatial resolution images. Data fusion of multi‑resolution images within optical sensor data is vital for visual interpretation, but may not improve classification performance. In contrast, integration of optical and radar data did improve classification performance when the proper data fusion method was used. Among the classification algorithms available, the maximum likelihood classifier is still an important method for providing reasonably good accuracy, but nonparametric algorithms, such as classification tree analysis, have the potential to provide better results. However, they often require more time to achieve parametric optimization. Proper use of hierarchical‑based methods is fundamental for developing accurate land use/cover classification, mainly from historical remotely sensed data.

Color of smoked loin from animals fed with bioactive compounds added to forage

The objective of this work was to evaluate the influence of the breed and of the addition of bioactive substances to forage on the color of smoked pork loin. Two pig breeds (Polish Landrace and the crossbreed Polish Landrace x Duroc), three types of bioactive components (organic selenium; 2% of canola oil and 1% of flaxseed oil; and 2% of flaxseed oil and 1% of canola oil), and a control treatment were evaluated. Computer image analysis included the color assessment of muscle, fat, connective tissues, and smoked loin surface. For Polish Landrace, selenium supplementation caused higher values of red, green, and blue color components of the muscle tissue, which were lower for the crossbreed. However, there was no difference in the color components of loin fat tissue of the Polish Landrace breed due to selenium supplementation. In the case of oil supplementation, values of the color components of the muscle tissue for the Polish Landrace x Duroc crossbreed were also lower. The color components of muscle, fat, connective tissues, and smoked loin surface depend on the pig breed and on the bioactive compounds added to the forage.

Classification and fingerprinting of different berries based on biochemical profiling and antioxidant capacity

The objective of this work was to evaluate the biochemical composition of six berry types belonging to Fragaria, Rubus, Vaccinium and Ribes genus. Fruit samples were collected in triplicate (50 fruit each) from 18 different species or cultivars of the mentioned genera, during three years (2008 to 2010). Content of individual sugars, organic acids, flavonols, and phenolic acids were determined by high performance liquid chromatography (HPLC) analysis, while total phenolics (TPC) and total antioxidant capacity (TAC), by using spectrophotometry. Principal component analysis (PCA) and hierarchical cluster analysis (CA) were performed to evaluate the differences in fruit biochemical profile. The highest contents of bioactive components were found in Ribes nigrum and in Fragaria vesca, Rubus plicatus, and Vaccinium myrtillus. PCA and CA were able to partially discriminate between berries on the basis of their biochemical composition. Individual and total sugars, myricetin, ellagic acid, TPC and TAC showed the highest impact on biochemical composition of the berry fruits. CA separated blackberry, raspberry, and blueberry as isolate groups, while classification of strawberry, black and red currant in a specific group has not occurred. There is a large variability both between and within the different types of berries. Metabolite fingerprinting of the evaluated berries showed unique biochemical profiles and specific combination of bioactive compound contents.

Transmission of MRSA and MSSA between humans and farm animals

Human nares are the main niche of Staphylococcus aureus, but farm animals can be also infected (cows) or colonized (pigs) constituting significant reservoir of this pathogen. Previous studies indicated that human and animal strains are quite distinct but the extent of cross-species specialization and transmission remains largely unknown. However, recent reports from several European countries as well as USA and Canada have indicated that employment in farming is an emerging risk factor for MRSA carriage. Pigs were found to be frequently colonized with MRSA, usually with a strain belonging to CC398. It is not known whether animal-human transmission was specific to this particular MRSA strain. S. aureus isolates from cow mastitis and pig colonization isolates were collected in parallel to nasal swab isolates from the animals' caretakers. The isolates were genotyped by AFLP, spatyping, and when appropriate by MLST. The isolates from cow mastitis were genetically uniform in comparison with human isolates. They were quite distinct from farmers\' carriage isolates, indicating pronounced hostspecialization. However, several cases where an infected cow and a colonized farmer had the same strain were detected, including one farm where two farmers were colonized and two cows were infected with MRSA belonging to CC398. Pig isolates were genetically more diverse than cow isolates. They were different from both human and cow isolates with one notable exception. Large fraction of pigs (20%) and pig caretakers (50%) were colonized with isolates belonging to CC398, majority of which were MSSA (2 cases of MRSA). These results indicate that host specialization in S. aureus is quite pronounced. Transmission between humans and farm animals was consequently quite rare. Both MSSA and MRSA strains belonging to otherwise pig-specific CC398 had increased capacity to colonize humans. Study of the genetic factors responsible for host specialization is underway.

Bayesian classification of forest ecological type from satellite data

The main objective of this study was todo a statistical analysis of ecological type from optical satellite data, using Tipping's sparse Bayesian algorithm. This thesis uses "the Relevence Vector Machine" algorithm in ecological classification betweenforestland and wetland. Further this bi-classification technique was used to do classification of many other different species of trees and produces hierarchical classification of entire subclasses given as a target class. Also, we carried out an attempt to use airborne image of same forest area. Combining it with image analysis, using different image processing operation, we tried to extract good features and later used them to perform classification of forestland and wetland.

Cluster-based active learning for compact image classification

In this paper, we consider active sampling to label pixels grouped with hierarchical clustering. The objective of the method is to match the data relationships discovered by the clustering algorithm with the user's desired class semantics. The first is represented as a complete tree to be pruned and the second is iteratively provided by the user. The active learning algorithm proposed searches the pruning of the tree that best matches the labels of the sampled points. By choosing the part of the tree to sample from according to current pruning's uncertainty, sampling is focused on most uncertain clusters. This way, large clusters for which the class membership is already fixed are no longer queried and sampling is focused on division of clusters showing mixed labels. The model is tested on a VHR image in a multiclass classification setting. The method clearly outperforms random sampling in a transductive setting, but cannot generalize to unseen data, since it aims at optimizing the classification of a given cluster structure.

Current Issues in the Diagnosis and Classification of Peripheral T-Cell Lymphomas

Mature T-cell and T/NK-cell neoplasms are both uncommon and heterogeneous, among the broad category of non-Hodgkin's lymphomas. Due to the lack of specific genetic alterations in the vast majority of cases, most currently defined entities show overlapping morphologic and immunophenotypic features and therefore pose a challenge to the diagnostic pathologist. The goal of the symposium is to address current criteria for the recognition of specific subtypes of T-cell lymphoma, and to highlight new data regarding emerging immunophenotypic or molecular markers. This activity has been designed to meet the needs of practicing pathologists, and residents and fellows enrolled in training programs in anatomic and clinical pathology. It should be a particular benefit to those with an interest in hematopathology. Upon completion of this activity, participants should be better able to: -To be able to state the basis for the classification of mature T-cell malignancies involving nodal and extranodal sites. -To recognize and accurately diagnose the various subtypes of nodal and extranodal peripheral T-cell lymphomas. -To utilize immunohistochemical and molecular tests to characterize atypical T-cell proliferations. -To recognize and accurately diagnose T-cell lymphoproliferative lesions involving the skin and gastrointestinal tract, and be able to provide guidance regarding their clinical aggressiveness and management -To be able to utilize flow cytometric data to identify diverse functional T-cell subsets.

Image-Based Coral Reef Classification and Thematic Mapping

This paper presents a novel image classification scheme for benthic coral reef images that can be applied to both single image and composite mosaic datasets. The proposed method can be configured to the characteristics (e.g., the size of the dataset, number of classes, resolution of the samples, color information availability, class types, etc.) of individual datasets. The proposed method uses completed local binary pattern (CLBP), grey level co-occurrence matrix (GLCM), Gabor filter response, and opponent angle and hue channel color histograms as feature descriptors. For classification, either k-nearest neighbor (KNN), neural network (NN), support vector machine (SVM) or probability density weighted mean distance (PDWMD) is used. The combination of features and classifiers that attains the best results is presented together with the guidelines for selection. The accuracy and efficiency of our proposed method are compared with other state-of-the-art techniques using three benthic and three texture datasets. The proposed method achieves the highest overall classification accuracy of any of the tested methods and has moderate execution time. Finally, the proposed classification scheme is applied to a large-scale image mosaic of the Red Sea to create a completely classified thematic map of the reef benthos

Partial protection and intrathecal invasion of CD8(+) T cells in acute canine distemper virus infection.

Initial non-inflammatory demyelination in canine distemper virus infection (CDV) develops against a background of severe immunosuppression and is therefore, thought to be virus-induced. However, recently we found a marked invasion of T cells throughout the central nervous system (CNS) in dogs with acute distemper despite drastic damage to the immune system. In the present study, this apparent paradox was further investigated by immunophenotyping of lymphocytes, following experimental CDV challenge in vaccinated and non-vaccinated dogs. In contrast to CDV infected, unprotected dogs, vaccinated dogs did not become immunosuppressed and exhibited a strong antiviral immune response following challenge with virulent CDV. In unprotected dogs rapid and drastic lymphopenia was initially due to depletion of T cells. In peripheral blood, CD4(+) T cells were more sensitive and depleted earlier and for a longer time than CD8(+) cells which recovered soon. In the cerebrospinal fluid (CSF) we could observe an increase in the T cell to B cell and CD8(+) to CD4(+) ratios. Thus, partial protection of the CD8(+) cell population could explain why part of the immune function in acute distemper is preserved. As found earlier, T cells invaded the CNS parenchyma in these dogs but also in the protected challenged dogs, which did not develop any CNS disease at all. Since markers of T cell activation were upregulated in both groups of animals, this phenomenon could in part be related to non-specific penetration of activated T cells through the blood brain barrier. However, in diseased animals much larger numbers of T cells were found in the CNS than in the protected dogs, suggesting that massive invasion of T cells in the brain requires CDV expression in the CNS.

Signature polymorphisms in the internal transcribed spacer region relevant for the differentiation of zoophilic and anthropophilic strains of Trichophyton interdigitale and other species of T. mentagrophytes sensu lato.

Summary Background Dermatophytes are the main cause of superficial mycoses in humans and animals. Molecular research has given useful insights into the phylogeny and taxonomy of the dermatophytes to overcome the difficulties with conventional diagnostics. Objectives The Trichophyton mentagrophytes complex consists of anthropophilic as well as zoophilic species. Although several molecular markers have been developed for the differentiation of strains belonging to T. mentagrophytes sensu lato, correct identification still remains problematic, especially concerning the delineation of anthropophilic and zoophilic strains of T. interdigitale. This differentiation is not academic but is essential for selection of the correct antimycotic therapy to treat infected patients. Methods One hundred and thirty isolates identified by morphological characteristics as T. mentagrophytes sensu lato were investigated using restriction fragment length polymorphism (RFLP) and sequence analysis of the polymerase chain reaction-amplified internal transcribed spacer (ITS) region of the rDNA. Results Species of this complex produced individual RFLP patterns obtained by the restriction enzyme MvaI. Subsequent sequence analysis of the ITS1, 5.8S and ITS2 region of all strains, but of T. interdigitale in particular, revealed single unique polymorphisms in anthropophilic and zoophilic strains. Conclusions Signature polymorphisms were observed to be useful for the differentiation of these strains and epidemiological data showed a host specificity among zoophilic strains of T. interdigitale/Arthroderma vanbreuseghemii compared with A. benhamiae as well as characteristic clinical pictures in humans when caused by zoophilic or anthropophilic strains. The delineation is relevant because it helps in determining the correct treatment and provides clues regarding the source of the infection.

Similarity measure based classification

Luokittelujärjestelmää suunniteltaessa tarkoituksena on rakentaa systeemi, joka pystyy ratkaisemaan mahdollisimman tarkasti tutkittavan ongelma-alueen. Hahmontunnistuksessa tunnistusjärjestelmän ydin on luokitin. Luokittelun sovellusaluekenttä on varsin laaja. Luokitinta tarvitaan mm. hahmontunnistusjärjestelmissä, joista kuvankäsittely toimii hyvänä esimerkkinä. Myös lääketieteen parissa tarkkaa luokittelua tarvitaan paljon. Esimerkiksi potilaan oireiden diagnosointiin tarvitaan luokitin, joka pystyy mittaustuloksista päättelemään mahdollisimman tarkasti, onko potilaalla kyseinen oire vai ei. Väitöskirjassa on tehty similaarisuusmittoihin perustuva luokitin ja sen toimintaa on tarkasteltu mm. lääketieteen paristatulevilla data-aineistoilla, joissa luokittelutehtävänä on tunnistaa potilaan oireen laatu. Väitöskirjassa esitetyn luokittimen etuna on sen yksinkertainen rakenne, josta johtuen se on helppo tehdä sekä ymmärtää. Toinen etu on luokittimentarkkuus. Luokitin saadaan luokittelemaan useita eri ongelmia hyvin tarkasti. Tämä on tärkeää varsinkin lääketieteen parissa, missä jo pieni tarkkuuden parannus luokittelutuloksessa on erittäin tärkeää. Väitöskirjassa ontutkittu useita eri mittoja, joilla voidaan mitata samankaltaisuutta. Mitoille löytyy myös useita parametreja, joille voidaan etsiä juuri kyseiseen luokitteluongelmaan sopivat arvot. Tämä parametrien optimointi ongelma-alueeseen sopivaksi voidaan suorittaa mm. evoluutionääri- algoritmeja käyttäen. Kyseisessä työssä tähän on käytetty geneettistä algoritmia ja differentiaali-evoluutioalgoritmia. Luokittimen etuna on sen joustavuus. Ongelma-alueelle on helppo vaihtaa similaarisuusmitta, jos kyseinen mitta ei ole sopiva tutkittavaan ongelma-alueeseen. Myös eri mittojen parametrien optimointi voi parantaa tuloksia huomattavasti. Kun käytetään eri esikäsittelymenetelmiä ennen luokittelua, tuloksia pystytään parantamaan.

Stratification of the severity of critically ill patients with classification trees

Background: Development of three classification trees (CT) based on the CART (Classification and Regression Trees), CHAID (Chi-Square Automatic Interaction Detection) and C4.5 methodologies for the calculation of probability of hospital mortality; the comparison of the results with the APACHE II, SAPS II and MPM II-24 scores, and with a model based on multiple logistic regression (LR). Methods: Retrospective study of 2864 patients. Random partition (70:30) into a Development Set (DS) n = 1808 and Validation Set (VS) n = 808. Their properties of discrimination are compared with the ROC curve (AUC CI 95%), Percent of correct classification (PCC CI 95%); and the calibration with the Calibration Curve and the Standardized Mortality Ratio (SMR CI 95%). Results: CTs are produced with a different selection of variables and decision rules: CART (5 variables and 8 decision rules), CHAID (7 variables and 15 rules) and C4.5 (6 variables and 10 rules). The common variables were: inotropic therapy, Glasgow, age, (A-a)O2 gradient and antecedent of chronic illness. In VS: all the models achieved acceptable discrimination with AUC above 0.7. CT: CART (0.75(0.71-0.81)), CHAID (0.76(0.72-0.79)) and C4.5 (0.76(0.73-0.80)). PCC: CART (72(69- 75)), CHAID (72(69-75)) and C4.5 (76(73-79)). Calibration (SMR) better in the CT: CART (1.04(0.95-1.31)), CHAID (1.06(0.97-1.15) and C4.5 (1.08(0.98-1.16)). Conclusion: With different methodologies of CTs, trees are generated with different selection of variables and decision rules. The CTs are easy to interpret, and they stratify the risk of hospital mortality. The CTs should be taken into account for the classification of the prognosis of critically ill patients.