Protocolo para la zonificación intraparcelaria de la viña para vendimia selectiva a partir de imágenes multiespectratrales

En este trabajo se presenta un protocolo para la zonificación intraparcelaria de la viña con la finalidad de vendimia selectiva. Se basa en la adquisición de una imagen multiespectral detallada en el momento del envero, a partir de la cual se obtiene el índice de vegetación de la diferencia normalizada (NDVI). Este índice se clasifica en áreas de vigor alto y bajo mediante un proceso de clasificación no supervisada (algoritmo ISODATA). Las zonas resultantes se generalizan y se transfieren al monitor de cosecha de una máquina vendimiadora para realizar la recolección selectiva. La uva recolectada según este protocolo en parcelas control ha mostrado diferenciación en cuanto a parámetros de calidad como el pH, la acidez total, el contenido de polifenoles y el color. La imagen multiespectral utilizada fue adquirida por el satélite Quickbird-2. Los datos de calidad de la uva fueron muestreados según una malla regular de 5 filas por 10 cepas, procediendo a un test estadístico de rangos múltiples para analizar la separación de medias de las variables analizadas en cada zona de NDVI.

Forest cover and its change in Unguja Island, Zanzibar

Tropical forests are sources of many ecosystem services, but these forests are vanishing rapidly. The situation is severe in Sub-Saharan Africa and especially in Tanzania. The causes of change are multidimensional and strongly interdependent, and only understanding them comprehensively helps to change the ongoing unsustainable trends of forest decline. Ongoing forest changes, their spatiality and connection to humans and environment can be studied with the methods of Land Change Science. The knowledge produced with these methods helps to make arguments about the actors, actions and causes that are behind the forest decline. In this study of Unguja Island in Zanzibar the focus is in the current forest cover and its changes between 1996 and 2009. The cover and changes are measured with often used remote sensing methods of automated land cover classification and post-classification comparison from medium resolution satellite images. Kernel Density Estimation is used to determine the clusters of change, sub-area –analysis provides information about the differences between regions, while distance and regression analyses connect changes to environmental factors. These analyses do not only explain the happened changes, but also allow building quantitative and spatial future scenarios. Similar study has not been made for Unguja and therefore it provides new information, which is beneficial for the whole society. The results show that 572 km2 of Unguja is still forested, but 0,82–1,19% of these forests are disappearing annually. Besides deforestation also vertical degradation and spatial changes are significant problems. Deforestation is most severe in the communal indigenous forests, but also agroforests are decreasing. Spatially deforestation concentrates to the areas close to the coastline, population and Zanzibar Town. Biophysical factors on the other hand do not seem to influence the ongoing deforestation process. If the current trend continues there should be approximately 485 km2 of forests remaining in 2025. Solutions to these deforestation problems should be looked from sustainable land use management, surveying and protection of the forests in risk areas and spatially targeted self-sustainable tree planting schemes.

Image analysis and definition of nuclear phenotypes

Some basic topics concerned with the extraction of textural and geometric information from cell nucleus images as well as description and characterization of chromatin supraorganization and consequent classification of nuclear phenotypes are presented.

Evaluation of radioinduced damage and repair capacity in blood lymphocytes of breast cancer patients

Genetic damage caused by ionizing radiation and repair capacity of blood lymphocytes from 3 breast cancer patients and 3 healthy donors were investigated using the comet assay. The comets were analyzed by two parameters: comet tail length and visual classification. Blood samples from the donors were irradiated in vitro with a 60Co source at a dose rate of 0.722 Gy/min, with a dose range of 0.2 to 4.0 Gy and analyzed immediately after the procedure and 3 and 24 h later. The basal level of damage and the radioinduced damage were higher in lymphocytes from breast cancer patients than in lymphocytes from healthy donors. The radioinduced damage showed that the two groups had a similar response when analyzed immediately after the irradiations. Therefore, while the healthy donors presented a considerable reduction of damage after 3 h, the patients had a higher residual damage even 24 h after exposure. The repair capacity of blood lymphocytes from the patients was slower than that of lymphocytes from healthy donors. The possible influence of age, disease stage and mutations in the BRCA1 and BRCA2 genes are discussed. Both parameters adopted proved to be sensitive and reproducible: the dose-response curves for DNA migration can be used not only for the analysis of cellular response but also for monitoring therapeutic interventions. Lymphocytes from the breast cancer patients presented an initial radiosensitivity similar to that of healthy subjects but a deficient repair mechanism made them more vulnerable to the genotoxic action of ionizing radiation. However, since lymphocytes from only 3 patients and 3 normal subjects were analyzed in the present paper, additional donors will be necessary for a more accurate evaluation.

Ethnicity and glutathione S-transferase (GSTM1/GSTT1) polymorphisms in a Brazilian population

The distribution of polymorphisms related to glutathione S-transferases (GST) has been described in different populations, mainly for white individuals. We evaluated the distribution of GST mu (GSTM1) and theta (GSTT1) genotypes in 594 individuals, by multiplex PCR-based methods, using amplification of the exon 7 of CYP1A1 gene as an internal control. In São Paulo, 233 whites, 87 mulattos, and 137 blacks, all healthy blood-donor volunteers, were tested. In Bahia, where black and mulatto populations are more numerous, 137 subjects were evaluated. The frequency of the GSTM1 null genotype was significantly higher among whites (55.4%) than among mulattos (41.4%; P = 0.03) and blacks (32.8%; P < 0.0001) from São Paulo, or Bahian subjects in general (35.7%; P = 0.0003). There was no statistically different distribution among any non-white groups. The distribution of GSTT1 null genotype among groups did not differ significantly. The agreement between self-reported and interviewer classification of skin color in the Bahian group was low. The interviewer classification indicated a gradient of distribution of the GSTM1 null genotype from whites (55.6%) to light mulattos (40.4%), dark mulattos (32.0%) and blacks (28.6%). However, any information about race or ethnicity should be considered with caution regarding the bias introduced by different data collection techniques, specially in countries where racial admixture is intense, and ethnic definition boundaries are loose. Because homozygous deletions of GST gene might be associated with cancer risk, a better understanding of chemical metabolizing gene distribution can contribute to risk assessment of humans exposed to environmental carcinogens.

p53 immunostaining is correlated with reduced survival and is not correlated with gene mutations in resected pulmonary large cell carcinomas

Malignancy of pulmonary large cell carcinomas (LCC) increases from classic LCC through LCC with neuroendocrine morphology (LCCNM) to large cell neuroendocrine carcinomas (LCNEC). However, the histological classification has sometimes proved to be difficult. Because the malignancy of LCC is highly dependent on proteins with functions in the cell cycle, DNA repair, and apoptosis, p53 has been targeted as a potentially useful biological marker. p53 mutations in lung cancers have been shown to result in expression and protein expression also occurs in the absence of mutations. To validate the importance of both p53 protein expression (by immunostaining) and p53 gene mutations in lung LCC (by PCR-single strand conformational polymorphism analysis of exons 5, 6, 7, and 8) and to study their relationships with clinical factors and sub-classification we investigated the correlation of p53 abnormalities in 15 patients with LCC (5 classic LCC, 5 LCNEC, and 5 LCCNM) who had undergone resection with curative intent. Of these patients, 5/15 expressed p53 and none had mutant p53 sequences. There was a negative survival correlation with positive p53 immunostaining (P = 0.05). After adjustment for stage, age, gender, chemotherapy, radiotherapy, and histological subtypes by multivariate analysis, p53 expression had an independent impact on survival. The present study indicates that p53 assessment may provide an objective marker for the prognosis of LCC irrespective of morphological variants and suggests that p53 expression is important for outcome prediction in patients with the early stages of LCC. The results reported here should be considered to be initial results because tumors from only 15 patients were studied: 5 each from LCC, LCNEC and LCCNM. This was due to the rarity of these specific diseases.

Anti-cyclic citrullinated peptide antibodies and rheumatoid factor in leprosy patients with articular involvement

The objective of the present research was to evaluate the usefulness of anti-cyclic citrullinated peptide (anti-CCP) antibodies and the IgM rheumatoid factor (IgM RF) test for the differential diagnosis of leprosy with articular involvement and rheumatoid arthritis (RA). Anti-CCP antibodies and IgM RF were measured in the sera of 158 leprosy patients (76 with and 82 without articular involvement), 69 RA patients and 89 healthy controls. Leprosy diagnosis was performed according to Ridley and Jopling classification criteria and clinical and demographic characteristics of leprosy patients were collected by a standard questionnaire. Leprosy patients with any concomitant rheumatic disease were excluded. Serum samples were obtained from all participants and frozen at _20°C. Measurement of anti-CCP antibodies and IgM RF were performed by ELISA, using a commercial second-generation kit, and the latex agglutination test, respectively. Anti-CCP antibodies and IgM RF were detected in low frequencies (2.6 and 1.3%, respectively) in leprosy patients and were not associated with articular involvement. Among healthy individuals both anti-CCP antibodies and IgM RF were each detected in 3.4% of the subjects. In contrast, in the RA group, anti-CCP antibodies were present in 81.2% and IgM RF in 62.3%. In the present study, both anti-CCP antibodies and IgM RF showed good positive predictive value for RA, helping to discriminate between RA and leprosy patients with articular involvement. However, anti-CCP antibodies were more specific for RA diagnosis in the population under study.

A safety and feasibility study of cell therapy in dilated cardiomyopathy

The aim of this study was to determine if bone marrow mononuclear cell (BMMC) transplantation is safe for moderate to severe idiopathic dilated cardiomyopathy (IDC). Clinical trials have shown that this procedure is safe and effective for ischemic patients, but little information is available regarding non-ischemic patients. Twenty-four patients with IDC, optimized therapy, age 46 ± 11.6 years, 17 males, NYHA classes II-IV, and left ventricular ejection fraction <35% were enrolled in the study. Clinical evaluation at baseline and 6 months after stem cell therapy to assess heart function included echocardiogram, magnetic resonance imaging, cardiopulmonary test, Minnesota Quality of Life Questionnaire, and NYHA classification. After cell transplantation 1 patient showed a transient increase in enzyme levels and 2 patients presented arrhythmias that were reversed within 72 h. Four patients died during follow-up, between 6 and 12 weeks after therapy. Clinical evaluation showed improvement in most patients as reflected by statistically significant decreases in Minnesota Quality of Life Questionnaire (63 ± 17.9 baseline vs 28.8 ± 16.75 at 6 months) and in class III-IV NYHA patients (18/24 baseline vs 2/20 at 6 months). Cardiopulmonary exercise tests demonstrated increased peak oxygen consumption (12.2 ± 2.4 at baseline vs 15.8 ± 7.1 mL·kg-1·min-1 at 6 months) and walked distance (377.2 ± 85.4 vs 444.1 ± 77.9 m at 6 months) in the 6-min walk test, which was not accompanied by increased left ventricular ejection fraction. Our findings indicate that BMMC therapy in IDC patients with severe ventricular dysfunction is feasible and that larger, randomized and placebo-controlled trials are warranted.

Blue and Uv-Emitting Upconversion Nanoparticles: Synthesis and (Bio) Analytical Applications.

Rare-earth based upconverting nanoparticles (UCNPs) have attracted much attention due to their unique luminescent properties. The ability to convert multiple photons of lower energy to ones with higher energy through an upconversion (UC) process offers a wide range of applications for UCNPs. The emission intensities and wavelengths of UCNPs are important performance characteristics, which determine the appropriate applications. However, insufficient intensities still limit the use of UCNPs; especially the efficient emission of blue and ultraviolet (UV) light via upconversion remains challenging, as these events require three or more near-infrared (NIR) photons. The aim of the study was to enhance the blue and UV upconversion emission intensities of Tm3+ doped NaYF4 nanoparticles and to demonstrate their utility in in vitro diagnostics. As the distance between the sensitizer and the activator significantly affect the energy transfer efficiency, different strategies were explored to change the local symmetry around the doped lanthanides. One important strategy is the intentional co-doping of active (participate in energy transfer) or passive (do not participate in energy transfer) impurities into the host matrix. The roles of doped passive impurities (K+ and Sc3+) in enhancing the blue and UV upconversions, as well as in influencing the intense UV upconversion emission through excess sensitization (active impurity) were studied. Additionally, the effects of both active and passive impurity doping on the morphological and optical performance of UCNPs were investigated. The applicability of UV emitting UCNPs as an internal light source for glucose sensing in a dry chemistry test strip was demonstrated. The measurements were in agreement with the traditional method based on reflectance measurements using an external UV light source. The use of UCNPs in the glucose test strip offers an alternative detection method with advantages such as control signals for minimizing errors and high penetration of the NIR excitation through the blood sample, which gives more freedom for designing the optical setup. In bioimaging, the excitation of the UCNPs in the transparent IR region of the tissue permits measurements, which are free of background fluorescence and have a high signal-to-background ratio. In addition, the narrow emission bandwidth of the UCNPs enables multiplexed detections. An array-in-well immunoassay was developed using two different UC emission colours. The differentiation between different viral infections and the classification of antibody responses were achieved based on both the position and colour of the signal. The study demonstrates the potential of spectral and spatial multiplexing in the imaging based array-in-well assays.

Algorithmes d'apprentissage pour la recommandation

L'ère numérique dans laquelle nous sommes entrés apporte une quantité importante de nouveaux défis à relever dans une multitude de domaines. Le traitement automatique de l'abondante information à notre disposition est l'un de ces défis, et nous allons ici nous pencher sur des méthodes et techniques adaptées au filtrage et à la recommandation à l'utilisateur d'articles adaptés à ses goûts, dans le contexte particulier et sans précédent notable du jeu vidéo multi-joueurs en ligne. Notre objectif est de prédire l'appréciation des niveaux par les joueurs. Au moyen d'algorithmes d'apprentissage machine modernes tels que les réseaux de neurones profonds avec pré-entrainement non-supervisé, que nous décrivons après une introduction aux concepts nécessaires à leur bonne compréhension, nous proposons deux architectures aux caractéristiques différentes bien que basées sur ce même concept d'apprentissage profond. La première est un réseau de neurones multi-couches pour lequel nous tentons d'expliquer les performances variables que nous rapportons sur les expériences menées pour diverses variations de profondeur, d'heuristique d'entraînement, et des méthodes de pré-entraînement non-supervisé simple, débruitant et contractant. Pour la seconde architecture, nous nous inspirons des modèles à énergie et proposons de même une explication des résultats obtenus, variables eux aussi. Enfin, nous décrivons une première tentative fructueuse d'amélioration de cette seconde architecture au moyen d'un fine-tuning supervisé succédant le pré-entrainement, puis une seconde tentative où ce fine-tuning est fait au moyen d'un critère d'entraînement semi-supervisé multi-tâches. Nos expériences montrent des performances prometteuses, notament avec l'architecture inspirée des modèles à énergie, justifiant du moins l'utilisation d'algorithmes d'apprentissage profonds pour résoudre le problème de la recommandation.

Mechanism and Prediction of Post-Operative Atrial Fibrillation Based on Atrial Electrograms

La fibrillation auriculaire (FA) est une arythmie touchant les oreillettes. En FA, la contraction auriculaire est rapide et irrégulière. Le remplissage des ventricules devient incomplet, ce qui réduit le débit cardiaque. La FA peut entraîner des palpitations, des évanouissements, des douleurs thoraciques ou l’insuffisance cardiaque. Elle augmente aussi le risque d'accident vasculaire. Le pontage coronarien est une intervention chirurgicale réalisée pour restaurer le flux sanguin dans les cas de maladie coronarienne sévère. 10% à 65% des patients qui n'ont jamais subi de FA, en sont victime le plus souvent lors du deuxième ou troisième jour postopératoire. La FA est particulièrement fréquente après une chirurgie de la valve mitrale, survenant alors dans environ 64% des patients. L'apparition de la FA postopératoire est associée à une augmentation de la morbidité, de la durée et des coûts d'hospitalisation. Les mécanismes responsables de la FA postopératoire ne sont pas bien compris. L'identification des patients à haut risque de FA après un pontage coronarien serait utile pour sa prévention. Le présent projet est basé sur l'analyse d’électrogrammes cardiaques enregistrées chez les patients après pontage un aorte-coronaire. Le premier objectif de la recherche est d'étudier si les enregistrements affichent des changements typiques avant l'apparition de la FA. Le deuxième objectif est d'identifier des facteurs prédictifs permettant d’identifier les patients qui vont développer une FA. Les enregistrements ont été réalisés par l'équipe du Dr Pierre Pagé sur 137 patients traités par pontage coronarien. Trois électrodes unipolaires ont été suturées sur l'épicarde des oreillettes pour enregistrer en continu pendant les 4 premiers jours postopératoires. La première tâche était de développer un algorithme pour détecter et distinguer les activations auriculaires et ventriculaires sur chaque canal, et pour combiner les activations des trois canaux appartenant à un même événement cardiaque. L'algorithme a été développé et optimisé sur un premier ensemble de marqueurs, et sa performance évaluée sur un second ensemble. Un logiciel de validation a été développé pour préparer ces deux ensembles et pour corriger les détections sur tous les enregistrements qui ont été utilisés plus tard dans les analyses. Il a été complété par des outils pour former, étiqueter et valider les battements sinusaux normaux, les activations auriculaires et ventriculaires prématurées (PAA, PVA), ainsi que les épisodes d'arythmie. Les données cliniques préopératoires ont ensuite été analysées pour établir le risque préopératoire de FA. L’âge, le niveau de créatinine sérique et un diagnostic d'infarctus du myocarde se sont révélés être les plus importants facteurs de prédiction. Bien que le niveau du risque préopératoire puisse dans une certaine mesure prédire qui développera la FA, il n'était pas corrélé avec le temps de l'apparition de la FA postopératoire. Pour l'ensemble des patients ayant eu au moins un épisode de FA d’une durée de 10 minutes ou plus, les deux heures précédant la première FA prolongée ont été analysées. Cette première FA prolongée était toujours déclenchée par un PAA dont l’origine était le plus souvent sur l'oreillette gauche. Cependant, au cours des deux heures pré-FA, la distribution des PAA et de la fraction de ceux-ci provenant de l'oreillette gauche était large et inhomogène parmi les patients. Le nombre de PAA, la durée des arythmies transitoires, le rythme cardiaque sinusal, la portion basse fréquence de la variabilité du rythme cardiaque (LF portion) montraient des changements significatifs dans la dernière heure avant le début de la FA. La dernière étape consistait à comparer les patients avec et sans FA prolongée pour trouver des facteurs permettant de discriminer les deux groupes. Cinq types de modèles de régression logistique ont été comparés. Ils avaient une sensibilité, une spécificité et une courbe opérateur-receveur similaires, et tous avaient un niveau de prédiction des patients sans FA très faible. Une méthode de moyenne glissante a été proposée pour améliorer la discrimination, surtout pour les patients sans FA. Deux modèles ont été retenus, sélectionnés sur les critères de robustesse, de précision, et d’applicabilité. Autour 70% patients sans FA et 75% de patients avec FA ont été correctement identifiés dans la dernière heure avant la FA. Le taux de PAA, la fraction des PAA initiés dans l'oreillette gauche, le pNN50, le temps de conduction auriculo-ventriculaire, et la corrélation entre ce dernier et le rythme cardiaque étaient les variables de prédiction communes à ces deux modèles.

Design And Development Of A Named Entity Based Question Answering System For Malayalam Language

This is a Named Entity Based Question Answering System for Malayalam Language. Although a vast amount of information is available today in digital form, no effective information access mechanism exists to provide humans with convenient information access. Information Retrieval and Question Answering systems are the two mechanisms available now for information access. Information systems typically return a long list of documents in response to a user’s query which are to be skimmed by the user to determine whether they contain an answer. But a Question Answering System allows the user to state his/her information need as a natural language question and receives most appropriate answer in a word or a sentence or a paragraph. This system is based on Named Entity Tagging and Question Classification. Document tagging extracts useful information from the documents which will be used in finding the answer to the question. Question Classification extracts useful information from the question to determine the type of the question and the way in which the question is to be answered. Various Machine Learning methods are used to tag the documents. Rule-Based Approach is used for Question Classification. Malayalam belongs to the Dravidian family of languages and is one of the four major languages of this family. It is one of the 22 Scheduled Languages of India with official language status in the state of Kerala. It is spoken by 40 million people. Malayalam is a morphologically rich agglutinative language and relatively of free word order. Also Malayalam has a productive morphology that allows the creation of complex words which are often highly ambiguous. Document tagging tools such as Parts-of-Speech Tagger, Phrase Chunker, Named Entity Tagger, and Compound Word Splitter are developed as a part of this research work. No such tools were available for Malayalam language. Finite State Transducer, High Order Conditional Random Field, Artificial Immunity System Principles, and Support Vector Machines are the techniques used for the design of these document preprocessing tools. This research work describes how the Named Entity is used to represent the documents. Single sentence questions are used to test the system. Overall Precision and Recall obtained are 88.5% and 85.9% respectively. This work can be extended in several directions. The coverage of non-factoid questions can be increased and also it can be extended to include open domain applications. Reference Resolution and Word Sense Disambiguation techniques are suggested as the future enhancements

Unconstrained Handwritten Malayalam Character Recognition using Wavelet Transform and Support vector Machine Classifier

This paper presents the application of wavelet processing in the domain of handwritten character recognition. To attain high recognition rate, robust feature extractors and powerful classifiers that are invariant to degree of variability of human writing are needed. The proposed scheme consists of two stages: a feature extraction stage, which is based on Haar wavelet transform and a classification stage that uses support vector machine classifier. Experimental results show that the proposed method is effective

Estimation of Effective Impervious Surface Area of Cochin using Satellite Images

Urbanization refers to the process in which an increasing proportion of a population lives in cities and suburbs. Urbanization fuels the alteration of the Land use/Land cover pattern of the region including increase in built-up area, leading to imperviousness of the ground surface. With increasing urbanization and population pressures; the impervious areas in the cities are increasing fast. An impervious surface refers to an anthropogenic ally modified surface that prevents water from infiltrating into the soil. Surface imperviousness mapping is important for the studies related to water cycling, water quality, soil erosion, flood water drainage, non-point source pollution, urban heat island effect and urban hydrology. The present study estimates the Total Impervious Area (TIA) of the city of Kochi using high resolution satellite image (LISS IV, 5m. resolution). Additionally the study maps the Effective Impervious Area (EIA) by coupling the capabilities of GIS and Remote Sensing. Land use/Land cover map of the study area was prepared from the LISS IV image acquired for the year 2012. The classes were merged to prepare a map showing pervious and impervious area. Supervised Maximum Likelihood Classification (Supervised MLC),which is a simple but accurate method for image classification, is used in calculating TIA and an overall classification accuracy of 86.33% was obtained. Water bodies are 100% pervious, whereas urban built up area are 100% impervious. Further based on percentage of imperviousness, the Total Impervious Area is categorized into various classes

KAM: Automatic Planning and Interpretation of Numerical Experiments Using Geometrical Methods

KAM is a computer program that can automatically plan, monitor, and interpret numerical experiments with Hamiltonian systems with two degrees of freedom. The program has recently helped solve an open problem in hydrodynamics. Unlike other approaches to qualitative reasoning about physical system dynamics, KAM embodies a significant amount of knowledge about nonlinear dynamics. KAM's ability to control numerical experiments arises from the fact that it not only produces pictures for us to see, but also looks at (sic---in its mind's eye) the pictures it draws to guide its own actions. KAM is organized in three semantic levels: orbit recognition, phase space searching, and parameter space searching. Within each level spatial properties and relationships that are not explicitly represented in the initial representation are extracted by applying three operations ---(1) aggregation, (2) partition, and (3) classification--- iteratively.