ESTIMATION OF CORK PRODUCTION USINGAERIAL IMAGERY1

ABSTRACT Inventory and prediction of cork harvest over time and space is important to forest managers who must plan and organize harvest logistics (transport, storage, etc.). Common field inventory methods including the stem density, diameter and height structure are costly and generally point (plot) based. Furthermore, the irregular horizontal structure of cork oak stands makes it difficult, if not impossible, to interpolate between points. We propose a new method to estimate cork production using digital multispectral aerial imagery. We study the spectral response of individual trees in visible and near infrared spectra and then correlate that response with cork production prior to harvest. We use ground measurements of individual trees production to evaluate the model’s predictive capacity. We propose 14 candidate variables to predict cork production based on crown size in combination with different NDVI index derivates. We use Akaike Information Criteria to choose the best among them. The best model is composed of combinations of different NDVI derivates that include red, green, and blue channels. The proposed model is 15% more accurate than a model that includes only a crown projection without any spectral information.

Correlation between the oropharyngo-laryngoscopic findings and the severity of obstructive sleep apnea

Objective: To correlate anatomical and functional changes of the oral cavity, pharynx and larynx to the severity of obstructive sleep apnea syndrome (OSAS). Methods : We conducted a cross-sectional study of 66 patients of both genders, aged between 21 and 59 years old with complaints of snoring and / or apnea. All underwent full clinical evaluation, including physical examination, nasolarybgoscopy and polisonography. We classified individuals into groups by the value of the apnea-hypopnea index (AHI), calculated measures of association and analyzed differences by the Kruskal-Wallis and chi-square tests. Results : all patients with obesity type 2 had OSAS. We found a relationship between the uvula projection during nasoendoscopy and OSAS (OR: 4.9; p-value: 0.008; CI: 1.25-22.9). In addition, there was a major strength of association between the circular shape of the pharynx and the presence of moderate or severe OSAS (OR: 9.4, p-value: 0.002), although the CI was wide (1.80-53.13). The septal deviation and lower turbinate hypertrophy were the most frequent nasal alterations, however unrelated to gravity. Nasal obstruction was four times more common in patients without daytime sleepiness. The other craniofacial anatomical changes were not predictors for the occurrence of OSAS. Conclusion : oral, pharyngeal and laryngeal disorders participate in the pathophysiology of OSAS. The completion of the endoscopic examination is of great value to the evaluation of these patients.

Saimiri sciureus' hard palate morphology

Primate order includes around 180 species. Morphological aspects of New World non-human primates (NHP) have been extensively investigated since last century. General commonsense describes oral cavity adaptations according to diet and feeding, dentition, tongue projection and head shape. Morphological appearance and dimension of the hard palate have been outstanding as interest in many species including man. Six young Saimiri sciureus hard palate were investigated. We measured the hard palate distance (HL), intercanine distance (ICD), intermolar distance (IMD), and interpremolar distance (IPD). Complete and incomplete palatine crests were quantified. We believe that better understanding of the mouth roof morphology will contribute to improve the management of captive animal's diet in order to re-introduce the animals in its habitat.

Real-time Image-based RGB-D Camera Motion Tracking and Environment Mapping

In this work, image based estimation methods, also known as direct methods, are studied which avoid feature extraction and matching completely. Cost functions use raw pixels as measurements and the goal is to produce precise 3D pose and structure estimates. The cost functions presented minimize the sensor error, because measurements are not transformed or modified. In photometric camera pose estimation, 3D rotation and translation parameters are estimated by minimizing a sequence of image based cost functions, which are non-linear due to perspective projection and lens distortion. In image based structure refinement, on the other hand, 3D structure is refined using a number of additional views and an image based cost metric. Image based estimation methods are particularly useful in conditions where the Lambertian assumption holds, and the 3D points have constant color despite viewing angle. The goal is to improve image based estimation methods, and to produce computationally efficient methods which can be accomodated into real-time applications. The developed image-based 3D pose and structure estimation methods are finally demonstrated in practise in indoor 3D reconstruction use, and in a live augmented reality application.

Scalable algorithms for height field illumination

Global illumination algorithms are at the center of realistic image synthesis and account for non-trivial light transport and occlusion within scenes, such as indirect illumination, ambient occlusion, and environment lighting. Their computationally most difficult part is determining light source visibility at each visible scene point. Height fields, on the other hand, constitute an important special case of geometry and are mainly used to describe certain types of objects such as terrains and to map detailed geometry onto object surfaces. The geometry of an entire scene can also be approximated by treating the distance values of its camera projection as a screen-space height field. In order to shadow height fields from environment lights a horizon map is usually used to occlude incident light. We reduce the per-receiver time complexity of generating the horizon map on N N height fields from O(N) of the previous work to O(1) by using an algorithm that incrementally traverses the height field and reuses the information already gathered along the path of traversal. We also propose an accurate method to integrate the incident light within the limits given by the horizon map. Indirect illumination in height fields requires information about which other points are visible to each height field point. We present an algorithm to determine this intervisibility in a time complexity that matches the space complexity of the produced visibility information, which is in contrast to previous methods which scale in the height field size. As a result the amount of computation is reduced by two orders of magnitude in common use cases. Screen-space ambient obscurance methods approximate ambient obscurance from the depth bu er geometry and have been widely adopted by contemporary real-time applications. They work by sampling the screen-space geometry around each receiver point but have been previously limited to near- field effects because sampling a large radius quickly exceeds the render time budget. We present an algorithm that reduces the quadratic per-pixel complexity of previous methods to a linear complexity by line sweeping over the depth bu er and maintaining an internal representation of the processed geometry from which occluders can be efficiently queried. Another algorithm is presented to determine ambient obscurance from the entire depth bu er at each screen pixel. The algorithm scans the depth bu er in a quick pre-pass and locates important features in it, which are then used to evaluate the ambient obscurance integral accurately. We also propose an evaluation of the integral such that results within a few percent of the ray traced screen-space reference are obtained at real-time render times.

Serotonergic neurons in the caudal raphe nuclei discharge in association with activity of masticatory muscles

There is a dense serotonergic projection from nucleus raphe pallidus and nucleus raphe obscurus to the trigeminal motor nucleus and serotonin exerts a strong facilitatory action on the trigeminal motoneurons. Some serotonergic neurons in these caudal raphe nuclei increase their discharge during feeding. The objective of the present study was to investigate the possibility that the activity of these serotonergic neurons is related to activity of masticatory muscles. Cats were implanted with microelectrodes and gross electrodes. Caudal raphe single neuron activity, electrocorticographic activity, and splenius, digastric and masseter electromyographic activities were recorded during active behaviors (feeding and grooming), during quiet waking and during sleep. Seven presumed serotonergic neurons were identified. These neurons showed a long duration action potential (>2.0 ms), and discharged slowly (2-7 Hz) and very regularly (interspike interval coefficient of variation <0.3) during quiet waking. The activity of these neurons decreased remarkably during fast wave sleep (78-100%). Six of these neurons showed tonic changes in their activity positively related to digastric and/or masseter muscle activity but not to splenius muscle activity during waking. These data are consistent with the hypothesis that serotonergic neurons in the caudal raphe nuclei play an important role in the control of jaw movements

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Nimeke- ja tekijätiedot nimiönkehyksissä

Efficient Optimization Algorithms for Nonlinear Data Analysis

Identification of low-dimensional structures and main sources of variation from multivariate data are fundamental tasks in data analysis. Many methods aimed at these tasks involve solution of an optimization problem. Thus, the objective of this thesis is to develop computationally efficient and theoretically justified methods for solving such problems. Most of the thesis is based on a statistical model, where ridges of the density estimated from the data are considered as relevant features. Finding ridges, that are generalized maxima, necessitates development of advanced optimization methods. An efficient and convergent trust region Newton method for projecting a point onto a ridge of the underlying density is developed for this purpose. The method is utilized in a differential equation-based approach for tracing ridges and computing projection coordinates along them. The density estimation is done nonparametrically by using Gaussian kernels. This allows application of ridge-based methods with only mild assumptions on the underlying structure of the data. The statistical model and the ridge finding methods are adapted to two different applications. The first one is extraction of curvilinear structures from noisy data mixed with background clutter. The second one is a novel nonlinear generalization of principal component analysis (PCA) and its extension to time series data. The methods have a wide range of potential applications, where most of the earlier approaches are inadequate. Examples include identification of faults from seismic data and identification of filaments from cosmological data. Applicability of the nonlinear PCA to climate analysis and reconstruction of periodic patterns from noisy time series data are also demonstrated. Other contributions of the thesis include development of an efficient semidefinite optimization method for embedding graphs into the Euclidean space. The method produces structure-preserving embeddings that maximize interpoint distances. It is primarily developed for dimensionality reduction, but has also potential applications in graph theory and various areas of physics, chemistry and engineering. Asymptotic behaviour of ridges and maxima of Gaussian kernel densities is also investigated when the kernel bandwidth approaches infinity. The results are applied to the nonlinear PCA and to finding significant maxima of such densities, which is a typical problem in visual object tracking.

Targeted measures bring the greatest benefits for environmental protection in agriculture final report of the TEHO Plus project (2011–2014)

Targeted measures bring the greatest benefits for environmental protection in agriculture final report of the TEHO Plus project (2011–2014). Particular priority areas of the project activities included creating a training package for agri-environment advisers and testing it, farm-specific advisory services and exploitation of experiences of advice provision, putting together an information package of agri-environment issues, farm-level experiments, and development of water quality monitoring. The recommendations issued by advisers on targeting environmental measures were based on utilising geographical information material and nutrient balances. The project was implemented in cooperation by Southwest Finland Centre for Economic Development, Transport and the Environment, MTK-Satakunta and MTK-Varsinais-Suomi. The project received funding from the Ministry of Agriculture and Forestry and the Ministry of the Environment. Participating farmers, with whom environmental advice was developed and experiments were carried out, were important partners for the project. The operating area of the project was Satakunta and Varsinais-Suomi in Southwest Finland, but its outcomes can be exploited nationally. A national perspective was ensured by close cooperation with actors in different provinces. This final report describes project experiences and outcomes including environmental advisory services, training of agri-environmental advisers, farm visits and the feedback received from farmers on agri-environmental advice, development of water quality monitoring, experiments and project work.

Expression of neuronal nitric oxide synthase in the developing superficial layers of the rat superior colliculus

We investigated the level of expression of neuronal nitric oxide synthase (nNOS) in the retinorecipient layers of the rat superior colliculus during early postnatal development. Male and female Lister rats ranging in age between the day of birth (P0) and the fourth postnatal week were used in the present study. Two biochemical methods were used, i.e., in vitro measurement of NOS specific activity by the conversion of [³H]-arginine to [³H]-citrulline, and analysis of Western blotting immunoreactive bands from superior colliculus homogenates. As revealed by Western blotting, very weak immunoreactive bands were observed as early as P0-2, and their intensity increased progressively at least until P21. The analysis of specific activity of NOS showed similar results. There was a progressive increase in enzymatic activity until near the end of the second postnatal week, and a nonsignificant tendency to an increase until the end of the third week was also observed. Thus, these results indicated an increase in the amount of nNOS during the first weeks after birth. Our results confirm and extend previous reports using histochemistry for NADPH-diaphorase and immunocytochemistry for nNOS, which showed a progressive increase in the number of stained cells in the superficial layers during the first two postnatal weeks, reaching an adult pattern at the end of the third week. Furthermore, our results suggested that nNOS is present in an active form in the rat superior colliculus during the period of refinement of the retinocollicular pathway.

Intrinsic bent DNA sites in the chromosomal replication origin of Xylella fastidiosa 9a5c

The features of the nucleotide sequences in both replication and promoter regions have been investigated in many organisms. Intrinsically bent DNA sites associated with transcription have been described in several prokaryotic organisms. The aim of the present study was to investigate intrinsic bent DNA sites in the segment that holds the chromosomal replication origin, oriC, of Xylella fastidiosa 9a5c. Electrophoretic behavior analyses, as well as in silico analyses of both the 2-D projection and helical parameters, were performed. The chromosomal segment analyzed contains the initial sequence of the rpmH gene, an intergenic region, the dnaA gene, the oriC sequence, and the 5' partial sequence of the dnaN gene. The analysis revealed fragments with reduced electrophoretic mobility, which indicates the presence of curved DNA segments. The analysis of the helical parameter ENDS ratio revealed three bent DNA sites (b1, b2, and b3) located in the rpmH-dnaA intergenic region, the dnaA gene, and the oriC 5' end, respectively. The chromosomal segment of X. fastidiosa analyzed here is rich in phased AT tracts and in CAnT motifs. The 2-D projection indicated a segment whose structure was determined by the cumulative effect of all bent DNA sites. Further, the in silico analysis of the three different bacterial oriC sequences indicated similar negative roll and twist >34.00° values. The DnaA box sequences, and other motifs in them, may be associated with the intrinsic DNA curvature.

Method for automatic detection of wheezing in lung sounds

The present report describes the development of a technique for automatic wheezing recognition in digitally recorded lung sounds. This method is based on the extraction and processing of spectral information from the respiratory cycle and the use of these data for user feedback and automatic recognition. The respiratory cycle is first pre-processed, in order to normalize its spectral information, and its spectrogram is then computed. After this procedure, the spectrogram image is processed by a two-dimensional convolution filter and a half-threshold in order to increase the contrast and isolate its highest amplitude components, respectively. Thus, in order to generate more compressed data to automatic recognition, the spectral projection from the processed spectrogram is computed and stored as an array. The higher magnitude values of the array and its respective spectral values are then located and used as inputs to a multi-layer perceptron artificial neural network, which results an automatic indication about the presence of wheezes. For validation of the methodology, lung sounds recorded from three different repositories were used. The results show that the proposed technique achieves 84.82% accuracy in the detection of wheezing for an isolated respiratory cycle and 92.86% accuracy for the detection of wheezes when detection is carried out using groups of respiratory cycles obtained from the same person. Also, the system presents the original recorded sound and the post-processed spectrogram image for the user to draw his own conclusions from the data.

Methodological approaches to planar and volumetric scintigraphic imaging of small volume targets with high spatial resolution and sensitivity

Single-photon emission computed tomography (SPECT) is a non-invasive imaging technique, which provides information reporting the functional states of tissues. SPECT imaging has been used as a diagnostic tool in several human disorders and can be used in animal models of diseases for physiopathological, genomic and drug discovery studies. However, most of the experimental models used in research involve rodents, which are at least one order of magnitude smaller in linear dimensions than man. Consequently, images of targets obtained with conventional gamma-cameras and collimators have poor spatial resolution and statistical quality. We review the methodological approaches developed in recent years in order to obtain images of small targets with good spatial resolution and sensitivity. Multipinhole, coded mask- and slit-based collimators are presented as alternative approaches to improve image quality. In combination with appropriate decoding algorithms, these collimators permit a significant reduction of the time needed to register the projections used to make 3-D representations of the volumetric distribution of target’s radiotracers. Simultaneously, they can be used to minimize artifacts and blurring arising when single pinhole collimators are used. Representation images are presented, which illustrate the use of these collimators. We also comment on the use of coded masks to attain tomographic resolution with a single projection, as discussed by some investigators since their introduction to obtain near-field images. We conclude this review by showing that the use of appropriate hardware and software tools adapted to conventional gamma-cameras can be of great help in obtaining relevant functional information in experiments using small animals.

Serum metabolic profiling of human gastric cancer based on gas chromatography/mass spectrometry

Research on molecular mechanisms of carcinogenesis plays an important role in diagnosing and treating gastric cancer. Metabolic profiling may offer the opportunity to understand the molecular mechanism of carcinogenesis and help to non-invasively identify the potential biomarkers for the early diagnosis of human gastric cancer. The aims of this study were to explore the underlying metabolic mechanisms of gastric cancer and to identify biomarkers associated with morbidity. Gas chromatography/mass spectrometry (GC/MS) was used to analyze the serum metabolites of 30 Chinese gastric cancer patients and 30 healthy controls. Diagnostic models for gastric cancer were constructed using orthogonal partial least squares discriminant analysis (OPLS-DA). Acquired metabolomic data were analyzed by the nonparametric Wilcoxon test to find serum metabolic biomarkers for gastric cancer. The OPLS-DA model showed adequate discrimination between cancer and non-cancer cohorts while the model failed to discriminate different pathological stages (I-IV) of gastric cancer patients. A total of 44 endogenous metabolites such as amino acids, organic acids, carbohydrates, fatty acids, and steroids were detected, of which 18 differential metabolites were identified with significant differences. A total of 13 variables were obtained for their greatest contribution in the discriminating OPLS-DA model [variable importance in the projection (VIP) value >1.0], among which 11 metabolites were identified using both VIP values (VIP >1) and the Wilcoxon test. These metabolites potentially revealed perturbations of glycolysis and of amino acid, fatty acid, cholesterol, and nucleotide metabolism of gastric cancer patients. These results suggest that gastric cancer serum metabolic profiling has great potential in detecting this disease and helping to understand its metabolic mechanisms.

Performance assessment of the single photon emission microscope: high spatial resolution SPECT imaging of small animal organs

The single photon emission microscope (SPEM) is an instrument developed to obtain high spatial resolution single photon emission computed tomography (SPECT) images of small structures inside the mouse brain. SPEM consists of two independent imaging devices, which combine a multipinhole collimator, a high-resolution, thallium-doped cesium iodide [CsI(Tl)] columnar scintillator, a demagnifying/intensifier tube, and an electron-multiplying charge-coupling device (CCD). Collimators have 300- and 450-µm diameter pinholes on tungsten slabs, in hexagonal arrays of 19 and 7 holes. Projection data are acquired in a photon-counting strategy, where CCD frames are stored at 50 frames per second, with a radius of rotation of 35 mm and magnification factor of one. The image reconstruction software tool is based on the maximum likelihood algorithm. Our aim was to evaluate the spatial resolution and sensitivity attainable with the seven-pinhole imaging device, together with the linearity for quantification on the tomographic images, and to test the instrument in obtaining tomographic images of different mouse organs. A spatial resolution better than 500 µm and a sensitivity of 21.6 counts·s-1·MBq-1 were reached, as well as a correlation coefficient between activity and intensity better than 0.99, when imaging 99mTc sources. Images of the thyroid, heart, lungs, and bones of mice were registered using 99mTc-labeled radiopharmaceuticals in times appropriate for routine preclinical experimentation of <1 h per projection data set. Detailed experimental protocols and images of the aforementioned organs are shown. We plan to extend the instrument's field of view to fix larger animals and to combine data from both detectors to reduce the acquisition time or applied activity.