Development of the femur - Implications for age and sex determination.

Growth of four variables of the femur (diapyseal length, diaphyseal length plus distal epiphysis, maximum length and vertical diameter of the head) was analyzed by polynomial regression for the purpose of evaluating its significance and capacity for age and sex determination throughout the entire life continuum. Materials included in analysis consisted of 346 specimens ranging from birth to 97 years of age from five documented osteological collections of Western European descent. Linear growth was displayed by each of the four variables. Significant sexual dimorphism was identified in two of the femoral measurements, including maximum length and vertical diameter of the head, from age 15 onward. These results indicate that the two variables may be of use in the determination of sex in sex determination from that age onward. Strong correlation coefficients were identified between femoral size and age for each of the four metric variables. These results indicate that any of the femoral measurements is likely to serve as a useful source to estimate sub-adult age in both archaeological and forensic samples.

Domain Adaptation in remote sensing: increasing the portability of land-cover classifiers

Among the types of remote sensing acquisitions, optical images are certainly one of the most widely relied upon data sources for Earth observation. They provide detailed measurements of the electromagnetic radiation reflected or emitted by each pixel in the scene. Through a process termed supervised land-cover classification, this allows to automatically yet accurately distinguish objects at the surface of our planet. In this respect, when producing a land-cover map of the surveyed area, the availability of training examples representative of each thematic class is crucial for the success of the classification procedure. However, in real applications, due to several constraints on the sample collection process, labeled pixels are usually scarce. When analyzing an image for which those key samples are unavailable, a viable solution consists in resorting to the ground truth data of other previously acquired images. This option is attractive but several factors such as atmospheric, ground and acquisition conditions can cause radiometric differences between the images, hindering therefore the transfer of knowledge from one image to another. The goal of this Thesis is to supply remote sensing image analysts with suitable processing techniques to ensure a robust portability of the classification models across different images. The ultimate purpose is to map the land-cover classes over large spatial and temporal extents with minimal ground information. To overcome, or simply quantify, the observed shifts in the statistical distribution of the spectra of the materials, we study four approaches issued from the field of machine learning. First, we propose a strategy to intelligently sample the image of interest to collect the labels only in correspondence of the most useful pixels. This iterative routine is based on a constant evaluation of the pertinence to the new image of the initial training data actually belonging to a different image. Second, an approach to reduce the radiometric differences among the images by projecting the respective pixels in a common new data space is presented. We analyze a kernel-based feature extraction framework suited for such problems, showing that, after this relative normalization, the cross-image generalization abilities of a classifier are highly increased. Third, we test a new data-driven measure of distance between probability distributions to assess the distortions caused by differences in the acquisition geometry affecting series of multi-angle images. Also, we gauge the portability of classification models through the sequences. In both exercises, the efficacy of classic physically- and statistically-based normalization methods is discussed. Finally, we explore a new family of approaches based on sparse representations of the samples to reciprocally convert the data space of two images. The projection function bridging the images allows a synthesis of new pixels with more similar characteristics ultimately facilitating the land-cover mapping across images.

Dielectric constant obtained from TDR and volumetric moisture of soils in southern Brazil

Soil moisture is the property which most greatly influences the soil dielectric constant, which is also influenced by soil mineralogy. The aim of this study was to determine mathematical models for soil moisture and the dielectric constant (Ka) for a Hapludalf, two clayey Hapludox and a very clayey Hapludox and test the reliability of universal models, such as those proposed by Topp and Ledieu and their co-workers in the 80's, and specific models to estimate soil moisture with a TDR. Soil samples were collected from the 0 to 0.30 m layer, sieved through a mesh of 0.002 m diameter and packed in PVC cylinders with a 0.1 m diameter and 0.3 m height. Seven samples of each soil class were saturated by capillarity and a probe composed of two rods was inserted in each one of them. Moisture readings began with the saturated soil and concluded when the soil was near permanent wilting point. In each step, the samples were weighed on a precision scale to calculate volumetric moisture. Linear and polynomial models were adjusted for each soil class and for all soils together between soil moisture and the dielectric constant. Accuracy of the models was evaluated by the coefficient of determination, the standard error of estimate and the 1:1 line. The models proposed by Topp and Ledieu and their co-workers were not adequate for estimating the moisture in the soil classes studied. The adjusted linear and polynomial models for the entire set of data of the four soil classes did not have sufficient accuracy for estimating soil moisture. The greater the soil clay and Fe oxide content, the greater the dielectric constant of the medium for a given volumetric moisture. The specific models, θ = 0.40283 - 0.04231 Ka + 0.00194 Ka² - 0.000022 Ka³ (Hapludox) θ = 0.01971 + 0.02902 Ka - 0.00086 Ka² + 0.000012 Ka³ (Hapludox -PF), θ = 0.01692 - 0.00507 Ka (Hapludalf) and θ = 0.08471 + 0.01145 Ka (Hapludox-CA), show greater accuracy and reliability for estimating soil moisture in the soil classes studied.

Chronofunctions of Heilu soil developed from Loess in Luochuan, on the chinese Loess plateau

Soil chronofunctions are an alternative for the quantification of soil-forming processes and underlie the modeling of soil genesis. To establish soil chronofunctions of a Heilu soil profile on Loess in Luochuan, selected soil properties and the 14C ages in the Holocene were studied. Linear, logarithmic, and third-order polynomial functions were selected to fit the relationships between soil properties and ages. The results indicated that third-order polynomial function fit best for the relationships between clay (< 0.002 mm), silt (0.002-0.02 mm), sand (0.02-2 mm) and soil ages, and a trend of an Ah horizon ocurrence in the profile. The logarithmic function indicated mainly variations of soil organic carbon and pH with time (soil age). The variation in CaCO3 content, Mn/Zr, Fe/Zr, K/Zr, Mg/Zr, Ca/Zr, P/Zr, and Na/Zr ratios with soil age were best described by three-order polynomial functions, in which the trend line showed migration of CaCO3 and some elements.

Influence of organic-mineral fertilization of an oxisol on soil chemical properties and Bracharia brizantha production

The use of organic-mineral fertilizer produced by the manufacturing industry of lysine and threonine amino acids can improve the fertility of tropical soils. The objective of this study was to evaluate the influence of different doses of the organic-mineral fertilizer named Ajifer L-14 on chemical properties and on the response with increased production of a forage on a Red Latosol in the northwestern region of São Paulo State, Brazil. A randomized block design was used with seven treatments and four replications. The treatments consisted of: T1- control (without application of Ajifer L-14); T2- control (natural vegetation); T3- mineral fertilization according to crop requirements and soil analysis (application of 1.35 kg plot-1 of urea, 2.20 single superphosphate, and 0.51 KCl, corresponding to 60 of N, 40 P2O5 and 30 kg ha-1 of K2O); T4- fertilization with Ajifer L-14 according to the recommendation resulting from the soil chemical analysis (40 L plot-1, corresponding to 60 kg ha-1 N); T5- fertilization with Ajifer L-14, at a rate of 150 % of the recommended values (60 L plot-1, corresponding to 90 kg ha-1 N); T6- fertilization with Ajifer L-14 at a rate of 50 % of the recommended values (20 L plot-1, corresponding to 30 kg ha-1 N); T7- fertilization with Ajifer L-14 at a rate of 125 % of the recommended values (50 L plot-1, corresponding to 75 kg ha-1 N); T8- fertilization with Ajifer L-14 at a rate of 75 % of the recommended values (30 L plot-1, corresponding to 45 kg ha-1 N). The following soil chemical properties were evaluated (layers 0.0-0.1 and 0.1-0.2 m): P, organic matter, pH, K+, Ca2+, Mg2+, cation exchange capacity, potential acidity, and base saturation. The application of this organic-mineral fertilizer does not influence the soil chemical properties. Regression analysis indicated a polynomial relationship between the application rates of organic-mineral fertilizer and the production of dry matter and crude protein of Bracharia Brizantha.

Assessment of the occurrence of nanoparticles in Swiss industry and evaluation of the appropriatenesss of the measurement devices to determine the workforce exposure

Abstract : The occupational health risk involved with handling nanoparticles is the probability that a worker will experience an adverse health effect: this is calculated as a function of the worker's exposure relative to the potential biological hazard of the material. Addressing the risks of nanoparticles requires therefore knowledge on occupational exposure and the release of nanoparticles into the environment as well as toxicological data. However, information on exposure is currently not systematically collected; therefore this risk assessment lacks quantitative data. This thesis aimed at, first creating the fundamental data necessary for a quantitative assessment and, second, evaluating methods to measure the occupational nanoparticle exposure. The first goal was to determine what is being used where in Swiss industries. This was followed by an evaluation of the adequacy of existing measurement methods to assess workplace nanopaiticle exposure to complex size distributions and concentration gradients. The study was conceived as a series of methodological evaluations aimed at better understanding nanoparticle measurement devices and methods. lt focused on inhalation exposure to airborne particles, as respiration is considered to be the most important entrance pathway for nanoparticles in the body in terms of risk. The targeted survey (pilot study) was conducted as a feasibility study for a later nationwide survey on the handling of nanoparticles and the applications of specific protection means in industry. The study consisted of targeted phone interviews with health and safety officers of Swiss companies that were believed to use or produce nanoparticles. This was followed by a representative survey on the level of nanoparticle usage in Switzerland. lt was designed based on the results of the pilot study. The study was conducted among a representative selection of clients of the Swiss National Accident Insurance Fund (SUVA), covering about 85% of Swiss production companies. The third part of this thesis focused on the methods to measure nanoparticles. Several pre- studies were conducted studying the limits of commonly used measurement devices in the presence of nanoparticle agglomerates, This focus was chosen, because several discussions with users and producers of the measurement devices raised questions about their accuracy measuring nanoparticle agglomerates and because, at the same time, the two survey studies revealed that such powders are frequently used in industry. The first preparatory experiment focused on the accuracy of the scanning mobility particle sizer (SMPS), which showed an improbable size distribution when measuring powders of nanoparticle agglomerates. Furthermore, the thesis includes a series of smaller experiments that took a closer look at problems encountered with other measurement devices in the presence of nanoparticle agglomerates: condensation particle counters (CPC), portable aerosol spectrometer (PAS) a device to estimate the aerodynamic diameter, as well as diffusion size classifiers. Some initial feasibility tests for the efficiency of filter based sampling and subsequent counting of carbon nanotubes (CNT) were conducted last. The pilot study provided a detailed picture of the types and amounts of nanoparticles used and the knowledge of the health and safety experts in the companies. Considerable maximal quantities (> l'000 kg/year per company) of Ag, Al-Ox, Fe-Ox, SiO2, TiO2, and ZnO (mainly first generation particles) were declared by the contacted Swiss companies, The median quantity of handled nanoparticles, however, was 100 kg/year. The representative survey was conducted by contacting by post mail a representative selection of l '626 SUVA-clients (Swiss Accident Insurance Fund). It allowed estimation of the number of companies and workers dealing with nanoparticles in Switzerland. The extrapolation from the surveyed companies to all companies of the Swiss production sector suggested that l'309 workers (95%-confidence interval l'073 to l'545) of the Swiss production sector are potentially exposed to nanoparticles in 586 companies (145 to l'027). These numbers correspond to 0.08% (0.06% to 0.09%) of all workers and to 0.6% (0.2% to 1.1%) of companies in the Swiss production sector. To measure airborne concentrations of sub micrometre-sized particles, a few well known methods exist. However, it was unclear how well the different instruments perform in the presence of the often quite large agglomerates of nanostructured materials. The evaluation of devices and methods focused on nanoparticle agglomerate powders. lt allowed the identification of the following potential sources of inaccurate measurements at workplaces with considerable high concentrations of airborne agglomerates: - A standard SMPS showed bi-modal particle size distributions when measuring large nanoparticle agglomerates. - Differences in the range of a factor of a thousand were shown between diffusion size classifiers and CPC/SMPS. - The comparison between CPC/SMPS and portable aerosol Spectrometer (PAS) was much better, but depending on the concentration, size or type of the powders measured, the differences were still of a high order of magnitude - Specific difficulties and uncertainties in the assessment of workplaces were identified: the background particles can interact with particles created by a process, which make the handling of background concentration difficult. - Electric motors produce high numbers of nanoparticles and confound the measurement of the process-related exposure. Conclusion: The surveys showed that nanoparticles applications exist in many industrial sectors in Switzerland and that some companies already use high quantities of them. The representative survey demonstrated a low prevalence of nanoparticle usage in most branches of the Swiss industry and led to the conclusion that the introduction of applications using nanoparticles (especially outside industrial chemistry) is only beginning. Even though the number of potentially exposed workers was reportedly rather small, it nevertheless underscores the need for exposure assessments. Understanding exposure and how to measure it correctly is very important because the potential health effects of nanornaterials are not yet fully understood. The evaluation showed that many devices and methods of measuring nanoparticles need to be validated for nanoparticles agglomerates before large exposure assessment studies can begin. Zusammenfassung : Das Gesundheitsrisiko von Nanopartikel am Arbeitsplatz ist die Wahrscheinlichkeit dass ein Arbeitnehmer einen möglichen Gesundheitsschaden erleidet wenn er diesem Stoff ausgesetzt ist: sie wird gewöhnlich als Produkt von Schaden mal Exposition gerechnet. Für eine gründliche Abklärung möglicher Risiken von Nanomaterialien müssen also auf der einen Seite Informationen über die Freisetzung von solchen Materialien in die Umwelt vorhanden sein und auf der anderen Seite solche über die Exposition von Arbeitnehmenden. Viele dieser Informationen werden heute noch nicht systematisch gesarnmelt und felilen daher für Risikoanalysen, Die Doktorarbeit hatte als Ziel, die Grundlagen zu schaffen für eine quantitative Schatzung der Exposition gegenüber Nanopartikel am Arbeitsplatz und die Methoden zu evaluieren die zur Messung einer solchen Exposition nötig sind. Die Studie sollte untersuchen, in welchem Ausmass Nanopartikel bereits in der Schweizer Industrie eingesetzt werden, wie viele Arbeitnehrner damit potentiel] in Kontakt komrrien ob die Messtechnologie für die nötigen Arbeitsplatzbelastungsmessungen bereits genügt, Die Studie folcussierte dabei auf Exposition gegenüber luftgetragenen Partikel, weil die Atmung als Haupteintrittspforte iïlr Partikel in den Körper angesehen wird. Die Doktorarbeit besteht baut auf drei Phasen auf eine qualitative Umfrage (Pilotstudie), eine repräsentative, schweizerische Umfrage und mehrere technische Stndien welche dem spezitischen Verständnis der Mëglichkeiten und Grenzen einzelner Messgeräte und - teclmikeri dienen. Die qualitative Telephonumfrage wurde durchgeführt als Vorstudie zu einer nationalen und repräsentativen Umfrage in der Schweizer Industrie. Sie zielte auf Informationen ab zum Vorkommen von Nanopartikeln, und den angewendeten Schutzmassnahmen. Die Studie bestand aus gezielten Telefoninterviews mit Arbeit- und Gesundheitsfachpersonen von Schweizer Unternehmen. Die Untemehmen wurden aufgrund von offentlich zugànglichen lnformationen ausgewählt die darauf hinwiesen, dass sie mit Nanopartikeln umgehen. Der zweite Teil der Dolctorarbeit war die repräsentative Studie zur Evalniernng der Verbreitnng von Nanopaitikelanwendungen in der Schweizer lndustrie. Die Studie baute auf lnformationen der Pilotstudie auf und wurde mit einer repräsentativen Selektion von Firmen der Schweizerischen Unfall Versicherungsanstalt (SUVA) durchgeüihxt. Die Mehrheit der Schweizerischen Unternehmen im lndustrieselctor wurde damit abgedeckt. Der dritte Teil der Doktorarbeit fokussierte auf die Methodik zur Messung von Nanopartikeln. Mehrere Vorstudien wurden dnrchgefîihrt, um die Grenzen von oft eingesetzten Nanopartikelmessgeräten auszuloten, wenn sie grösseren Mengen von Nanopartikel Agglomeraten ausgesetzt messen sollen. Dieser F okns wurde ans zwei Gründen gewählt: weil mehrere Dislcussionen rnit Anwendem und auch dem Produzent der Messgeràte dort eine Schwachstelle vermuten liessen, welche Zweifel an der Genauigkeit der Messgeräte aufkommen liessen und weil in den zwei Umfragestudien ein häufiges Vorkommen von solchen Nanopartikel-Agglomeraten aufgezeigt wurde. i Als erstes widmete sich eine Vorstndie der Genauigkeit des Scanning Mobility Particle Sizer (SMPS). Dieses Messgerät zeigte in Präsenz von Nanopartikel Agglorneraten unsinnige bimodale Partikelgrössenverteilung an. Eine Serie von kurzen Experimenten folgte, welche sich auf andere Messgeräte und deren Probleme beim Messen von Nanopartikel-Agglomeraten konzentrierten. Der Condensation Particle Counter (CPC), der portable aerosol spectrometer (PAS), ein Gerät zur Schàtzung des aerodynamischen Durchniessers von Teilchen, sowie der Diffusion Size Classifier wurden getestet. Einige erste Machbarkeitstests zur Ermittlnng der Effizienz von tilterbasierter Messung von luftgetragenen Carbon Nanotubes (CNT) wnrden als letztes durchgeiührt. Die Pilotstudie hat ein detailliiertes Bild der Typen und Mengen von genutzten Nanopartikel in Schweizer Unternehmen geliefert, und hat den Stand des Wissens der interviewten Gesundheitsschntz und Sicherheitsfachleute aufgezeigt. Folgende Typen von Nanopaitikeln wurden von den kontaktierten Firmen als Maximalmengen angegeben (> 1'000 kg pro Jahr / Unternehrnen): Ag, Al-Ox, Fe-Ox, SiO2, TiO2, und ZnO (hauptsächlich Nanopartikel der ersten Generation). Die Quantitäten von eingesetzten Nanopartikeln waren stark verschieden mit einem ein Median von 100 kg pro Jahr. ln der quantitativen Fragebogenstudie wurden l'626 Unternehmen brieflich kontaktiert; allesamt Klienten der Schweizerischen Unfallversicherringsanstalt (SUVA). Die Resultate der Umfrage erlaubten eine Abschätzung der Anzahl von Unternehmen und Arbeiter, welche Nanopartikel in der Schweiz anwenden. Die Hochrechnung auf den Schweizer lndnstriesektor hat folgendes Bild ergeben: ln 586 Unternehmen (95% Vertrauensintervallz 145 bis 1'027 Unternehmen) sind 1'309 Arbeiter potentiell gegenüber Nanopartikel exponiert (95%-Vl: l'073 bis l'545). Diese Zahlen stehen für 0.6% der Schweizer Unternehmen (95%-Vl: 0.2% bis 1.1%) und 0.08% der Arbeiternehmerschaft (95%-V1: 0.06% bis 0.09%). Es gibt einige gut etablierte Technologien um die Luftkonzentration von Submikrometerpartikel zu messen. Es besteht jedoch Zweifel daran, inwiefern sich diese Technologien auch für die Messurrg von künstlich hergestellten Nanopartikeln verwenden lassen. Aus diesem Grund folcussierten die vorbereitenden Studien für die Arbeitsplatzbeurteilnngen auf die Messung von Pulverri, welche Nan0partike1-Agg10merate enthalten. Sie erlaubten die ldentifikation folgender rnöglicher Quellen von fehlerhaften Messungen an Arbeitsplätzen mit erhöhter Luft-K0nzentrati0n von Nanopartikel Agglomeratenz - Ein Standard SMPS zeigte eine unglaubwürdige bimodale Partikelgrössenverteilung wenn er grössere Nan0par'til<e1Agg10merate gemessen hat. - Grosse Unterschiede im Bereich von Faktor tausend wurden festgestellt zwischen einem Diffusion Size Classiîier und einigen CPC (beziehungsweise dem SMPS). - Die Unterschiede zwischen CPC/SMPS und dem PAS waren geringer, aber abhängig von Grosse oder Typ des gemessenen Pulvers waren sie dennoch in der Grössenordnung von einer guten Grössenordnung. - Spezifische Schwierigkeiten und Unsicherheiten im Bereich von Arbeitsplatzmessungen wurden identitiziert: Hintergrundpartikel können mit Partikeln interagieren die während einem Arbeitsprozess freigesetzt werden. Solche Interaktionen erschweren eine korrekte Einbettung der Hintergrunds-Partikel-Konzentration in die Messdaten. - Elektromotoren produzieren grosse Mengen von Nanopartikeln und können so die Messung der prozessbezogenen Exposition stören. Fazit: Die Umfragen zeigten, dass Nanopartikel bereits Realitàt sind in der Schweizer Industrie und dass einige Unternehmen bereits grosse Mengen davon einsetzen. Die repräsentative Umfrage hat diese explosive Nachricht jedoch etwas moderiert, indem sie aufgezeigt hat, dass die Zahl der Unternehmen in der gesamtschweizerischen Industrie relativ gering ist. In den meisten Branchen (vor allem ausserhalb der Chemischen Industrie) wurden wenig oder keine Anwendungen gefunden, was schliessen last, dass die Einführung dieser neuen Technologie erst am Anfang einer Entwicklung steht. Auch wenn die Zahl der potentiell exponierten Arbeiter immer noch relativ gering ist, so unterstreicht die Studie dennoch die Notwendigkeit von Expositionsmessungen an diesen Arbeitsplätzen. Kenntnisse um die Exposition und das Wissen, wie solche Exposition korrekt zu messen, sind sehr wichtig, vor allem weil die möglichen Auswirkungen auf die Gesundheit noch nicht völlig verstanden sind. Die Evaluation einiger Geräte und Methoden zeigte jedoch, dass hier noch Nachholbedarf herrscht. Bevor grössere Mess-Studien durgefîihrt werden können, müssen die Geräte und Methodem für den Einsatz mit Nanopartikel-Agglomeraten validiert werden.

Comparison between artificial neural networks and maximum likelihood classification in digital soil mapping

Soil surveys are the main source of spatial information on soils and have a range of different applications, mainly in agriculture. The continuity of this activity has however been severely compromised, mainly due to a lack of governmental funding. The purpose of this study was to evaluate the feasibility of two different classifiers (artificial neural networks and a maximum likelihood algorithm) in the prediction of soil classes in the northwest of the state of Rio de Janeiro. Terrain attributes such as elevation, slope, aspect, plan curvature and compound topographic index (CTI) and indices of clay minerals, iron oxide and Normalized Difference Vegetation Index (NDVI), derived from Landsat 7 ETM+ sensor imagery, were used as discriminating variables. The two classifiers were trained and validated for each soil class using 300 and 150 samples respectively, representing the characteristics of these classes in terms of the discriminating variables. According to the statistical tests, the accuracy of the classifier based on artificial neural networks (ANNs) was greater than of the classic Maximum Likelihood Classifier (MLC). Comparing the results with 126 points of reference showed that the resulting ANN map (73.81 %) was superior to the MLC map (57.94 %). The main errors when using the two classifiers were caused by: a) the geological heterogeneity of the area coupled with problems related to the geological map; b) the depth of lithic contact and/or rock exposure, and c) problems with the environmental correlation model used due to the polygenetic nature of the soils. This study confirms that the use of terrain attributes together with remote sensing data by an ANN approach can be a tool to facilitate soil mapping in Brazil, primarily due to the availability of low-cost remote sensing data and the ease by which terrain attributes can be obtained.

Computational problems in perfect phylogeny haplotyping: typing without calling the allele.

A haplotype is an m-long binary vector. The XOR-genotype of two haplotypes is the m-vector of their coordinate-wise XOR. We study the following problem: Given a set of XOR-genotypes, reconstruct their haplotypes so that the set of resulting haplotypes can be mapped onto a perfect phylogeny (PP) tree. The question is motivated by studying population evolution in human genetics, and is a variant of the perfect phylogeny haplotyping problem that has received intensive attention recently. Unlike the latter problem, in which the input is "full" genotypes, here we assume less informative input, and so may be more economical to obtain experimentally. Building on ideas of Gusfield, we show how to solve the problem in polynomial time, by a reduction to the graph realization problem. The actual haplotypes are not uniquely determined by that tree they map onto, and the tree itself may or may not be unique. We show that tree uniqueness implies uniquely determined haplotypes, up to inherent degrees of freedom, and give a sufficient condition for the uniqueness. To actually determine the haplotypes given the tree, additional information is necessary. We show that two or three full genotypes suffice to reconstruct all the haplotypes, and present a linear algorithm for identifying those genotypes.

Auditory perceptual decision-making based on semantic categorization of environmental sounds.

Discriminating complex sounds relies on multiple stages of differential brain activity. The specific roles of these stages and their links to perception were the focus of the present study. We presented 250ms duration sounds of living and man-made objects while recording 160-channel electroencephalography (EEG). Subjects categorized each sound as that of a living, man-made or unknown item. We tested whether/when the brain discriminates between sound categories even when not transpiring behaviorally. We applied a single-trial classifier that identified voltage topographies and latencies at which brain responses are most discriminative. For sounds that the subjects could not categorize, we could successfully decode the semantic category based on differences in voltage topographies during the 116-174ms post-stimulus period. Sounds that were correctly categorized as that of a living or man-made item by the same subjects exhibited two periods of differences in voltage topographies at the single-trial level. Subjects exhibited differential activity before the sound ended (starting at 112ms) and on a separate period at ~270ms post-stimulus onset. Because each of these periods could be used to reliably decode semantic categories, we interpreted the first as being related to an implicit tuning for sound representations and the second as being linked to perceptual decision-making processes. Collectively, our results show that the brain discriminates environmental sounds during early stages and independently of behavioral proficiency and that explicit sound categorization requires a subsequent processing stage.

Plant-available soil water capacity: estimation methods and implications

The plant-available water capacity of the soil is defined as the water content between field capacity and wilting point, and has wide practical application in planning the land use. In a representative profile of the Cerrado Oxisol, methods for estimating the wilting point were studied and compared, using a WP4-T psychrometer and Richards chamber for undisturbed and disturbed samples. In addition, the field capacity was estimated by the water content at 6, 10, 33 kPa and by the inflection point of the water retention curve, calculated by the van Genuchten and cubic polynomial models. We found that the field capacity moisture determined at the inflection point was higher than by the other methods, and that even at the inflection point the estimates differed, according to the model used. By the WP4-T psychrometer, the water content was significantly lower found the estimate of the permanent wilting point. We concluded that the estimation of the available water holding capacity is markedly influenced by the estimation methods, which has to be taken into consideration because of the practical importance of this parameter.

Pedotransfer functions to predict water retention for soils of the humid tropics: a review

Over the past three decades, pedotransfer functions (PTFs) have been widely used by soil scientists to estimate soils properties in temperate regions in response to the lack of soil data for these regions. Several authors indicated that little effort has been dedicated to the prediction of soil properties in the humid tropics, where the need for soil property information is of even greater priority. The aim of this paper is to provide an up-to-date repository of past and recently published articles as well as papers from proceedings of events dealing with water-retention PTFs for soils of the humid tropics. Of the 35 publications found in the literature on PTFs for prediction of water retention of soils of the humid tropics, 91 % of the PTFs are based on an empirical approach, and only 9 % are based on a semi-physical approach. Of the empirical PTFs, 97 % are continuous, and 3 % (one) is a class PTF; of the empirical PTFs, 97 % are based on multiple linear and polynomial regression of n th order techniques, and 3 % (one) is based on the k-Nearest Neighbor approach; 84 % of the continuous PTFs are point-based, and 16 % are parameter-based; 97 % of the continuous PTFs are equation-based PTFs, and 3 % (one) is based on pattern recognition. Additionally, it was found that 26 % of the tropical water-retention PTFs were developed for soils in Brazil, 26 % for soils in India, 11 % for soils in other countries in America, and 11 % for soils in other countries in Africa.

Artificial neural networks applied for soil class prediction in mountainous landscape of the Serra do Mar¹

Soil information is needed for managing the agricultural environment. The aim of this study was to apply artificial neural networks (ANNs) for the prediction of soil classes using orbital remote sensing products, terrain attributes derived from a digital elevation model and local geology information as data sources. This approach to digital soil mapping was evaluated in an area with a high degree of lithologic diversity in the Serra do Mar. The neural network simulator used in this study was JavaNNS and the backpropagation learning algorithm. For soil class prediction, different combinations of the selected discriminant variables were tested: elevation, declivity, aspect, curvature, curvature plan, curvature profile, topographic index, solar radiation, LS topographic factor, local geology information, and clay mineral indices, iron oxides and the normalized difference vegetation index (NDVI) derived from an image of a Landsat-7 Enhanced Thematic Mapper Plus (ETM+) sensor. With the tested sets, best results were obtained when all discriminant variables were associated with geological information (overall accuracy 93.2 - 95.6 %, Kappa index 0.924 - 0.951, for set 13). Excluding the variable profile curvature (set 12), overall accuracy ranged from 93.9 to 95.4 % and the Kappa index from 0.932 to 0.948. The maps based on the neural network classifier were consistent and similar to conventional soil maps drawn for the study area, although with more spatial details. The results show the potential of ANNs for soil class prediction in mountainous areas with lithological diversity.

Advanced Kernel Methods For Remote Sensing Image Classification

Résumé Suite aux recentes avancées technologiques, les archives d'images digitales ont connu une croissance qualitative et quantitative sans précédent. Malgré les énormes possibilités qu'elles offrent, ces avancées posent de nouvelles questions quant au traitement des masses de données saisies. Cette question est à la base de cette Thèse: les problèmes de traitement d'information digitale à très haute résolution spatiale et/ou spectrale y sont considérés en recourant à des approches d'apprentissage statistique, les méthodes à noyau. Cette Thèse étudie des problèmes de classification d'images, c'est à dire de catégorisation de pixels en un nombre réduit de classes refletant les propriétés spectrales et contextuelles des objets qu'elles représentent. L'accent est mis sur l'efficience des algorithmes, ainsi que sur leur simplicité, de manière à augmenter leur potentiel d'implementation pour les utilisateurs. De plus, le défi de cette Thèse est de rester proche des problèmes concrets des utilisateurs d'images satellite sans pour autant perdre de vue l'intéret des méthodes proposées pour le milieu du machine learning dont elles sont issues. En ce sens, ce travail joue la carte de la transdisciplinarité en maintenant un lien fort entre les deux sciences dans tous les développements proposés. Quatre modèles sont proposés: le premier répond au problème de la haute dimensionalité et de la redondance des données par un modèle optimisant les performances en classification en s'adaptant aux particularités de l'image. Ceci est rendu possible par un système de ranking des variables (les bandes) qui est optimisé en même temps que le modèle de base: ce faisant, seules les variables importantes pour résoudre le problème sont utilisées par le classifieur. Le manque d'information étiquétée et l'incertitude quant à sa pertinence pour le problème sont à la source des deux modèles suivants, basés respectivement sur l'apprentissage actif et les méthodes semi-supervisées: le premier permet d'améliorer la qualité d'un ensemble d'entraînement par interaction directe entre l'utilisateur et la machine, alors que le deuxième utilise les pixels non étiquetés pour améliorer la description des données disponibles et la robustesse du modèle. Enfin, le dernier modèle proposé considère la question plus théorique de la structure entre les outputs: l'intègration de cette source d'information, jusqu'à présent jamais considérée en télédétection, ouvre des nouveaux défis de recherche. Advanced kernel methods for remote sensing image classification Devis Tuia Institut de Géomatique et d'Analyse du Risque September 2009 Abstract The technical developments in recent years have brought the quantity and quality of digital information to an unprecedented level, as enormous archives of satellite images are available to the users. However, even if these advances open more and more possibilities in the use of digital imagery, they also rise several problems of storage and treatment. The latter is considered in this Thesis: the processing of very high spatial and spectral resolution images is treated with approaches based on data-driven algorithms relying on kernel methods. In particular, the problem of image classification, i.e. the categorization of the image's pixels into a reduced number of classes reflecting spectral and contextual properties, is studied through the different models presented. The accent is put on algorithmic efficiency and the simplicity of the approaches proposed, to avoid too complex models that would not be used by users. The major challenge of the Thesis is to remain close to concrete remote sensing problems, without losing the methodological interest from the machine learning viewpoint: in this sense, this work aims at building a bridge between the machine learning and remote sensing communities and all the models proposed have been developed keeping in mind the need for such a synergy. Four models are proposed: first, an adaptive model learning the relevant image features has been proposed to solve the problem of high dimensionality and collinearity of the image features. This model provides automatically an accurate classifier and a ranking of the relevance of the single features. The scarcity and unreliability of labeled. information were the common root of the second and third models proposed: when confronted to such problems, the user can either construct the labeled set iteratively by direct interaction with the machine or use the unlabeled data to increase robustness and quality of the description of data. Both solutions have been explored resulting into two methodological contributions, based respectively on active learning and semisupervised learning. Finally, the more theoretical issue of structured outputs has been considered in the last model, which, by integrating outputs similarity into a model, opens new challenges and opportunities for remote sensing image processing.

Quantitative Assessment of Soil Physical Quality in Northern China Based on S-theory

ABSTRACT Quantitative assessment of soil physical quality is of great importance for eco-environmental pollution and soil quality studies. In this paper, based on the S-theory, data from 16 collection sites in the Haihe River Basin in northern China were used, and the effects of soil particle size distribution and bulk density on three important indices of theS-theory were investigated on a regional scale. The relationships between unsaturated hydraulic conductivityKi at the inflection point and S values (S/hi) were also studied using two different types of fitting equations. The results showed that the polynomial equation was better than the linear equation for describing the relationships between -log Ki and -logS, and -log Kiand -log (S/hi)2; and clay content was the most important factor affecting the soil physical quality index (S). The variation in the S index according to soil clay content was able to be fitted using a double-linear-line approach, with decrease in the S index being much faster for clay content less than 20 %. In contrast, the bulk density index was found to be less important than clay content. The average S index was 0.077, indicating that soil physical quality in the Haihe River Basin was good.

Rgtsp: a generalized top scoring pairs package for class prediction.

SUMMARY: A top scoring pair (TSP) classifier consists of a pair of variables whose relative ordering can be used for accurately predicting the class label of a sample. This classification rule has the advantage of being easily interpretable and more robust against technical variations in data, as those due to different microarray platforms. Here we describe a parallel implementation of this classifier which significantly reduces the training time, and a number of extensions, including a multi-class approach, which has the potential of improving the classification performance. AVAILABILITY AND IMPLEMENTATION: Full C++ source code and R package Rgtsp are freely available from http://lausanne.isb-sib.ch/~vpopovic/research/. The implementation relies on existing OpenMP libraries.