Formal and philological inquiries into the nature of interrogatives, indefinites, disjunction, and focus in Sinhala and other languages

In this thesis I examine a variety of linguistic elements which involve ``alternative'' semantic values---a class arguably including focus, interrogatives, indefinites, and disjunctions---and the connections between these elements. This study focusses on the analysis of such elements in Sinhala, with comparison to Malayalam, Tlingit, and Japanese. The central part of the study concerns the proper syntactic and semantic analysis of Q[uestion]-particles (including Sinhala "da", Malayalam "-oo", Japanese "ka"), which, in many languages, appear not only in interrogatives, but also in the formation of indefinites, disjunctions, and relative clauses. This set of contexts is syntactically-heterogeneous, and so syntax does not offer an explanation for the appearance of Q-particles in this particular set of environments. I propose that these contexts can be united in terms of semantics, as all involving some element which denotes a set of ``alternatives''. Both wh-words and disjunctions can be analysed as creating Hamblin-type sets of ``alternatives''. Q-particles can be treated as uniformly denoting variables over choice functions which apply to the aforementioned Hamblin-type sets, thus ``restoring'' the derivation to normal Montagovian semantics. The treatment of Q-particles as uniformly denoting variables over choice functions provides an explanation for why these particles appear in just this set of contexts: they all include an element with Hamblin-type semantics. However, we also find variation in the use of Q-particles; including, in some languages, the appearance of multiple morphologically-distinct Q-particles in different syntactic contexts. Such variation can be handled largely by positing that Q-particles may vary in their formal syntactic feature specifications, determining which syntactic contexts they are licensed in. The unified analysis of Q-particles as denoting variables over choice functions also raises various questions about the proper analysis of interrogatives, indefinites, and disjunctions, including issues concerning the nature of the semantics of wh-words and the syntactic structure of disjunction. As well, I observe that indefinites involving Q-particles have a crosslinguistic tendency to be epistemic indefinites, i.e. indefinites which explicitly signal ignorance of details regarding who or what satisfies the existential claim. I provide an account of such indefinites which draws on the analysis of Q-particles as variables over choice functions. These pragmatic ``signals of ignorance'' (which I argue to be presuppositions) also have a further role to play in determining the distribution of Q-particles in disjunctions. The final section of this study investigates the historical development of focus constructions and Q-particles in Sinhala. This diachronic study allows us not only to observe the origin and development of such elements, but also serves to delimit the range of possible synchronic analyses, thus providing us with further insights into the formal syntactic and semantic properties of Q-particles. This study highlights both the importance of considering various components of the grammar (e.g. syntax, semantics, pragmatics, morphology) and the use of philology in developing plausible formal analyses of complex linguistic phenomena such as the crosslinguistic distribution of Q-particles.

Comparing global land cover datasets through the Eagle matrix land cover components for continental Portugal

Global land cover maps play an important role in the understanding of the Earth's ecosystem dynamic. Several global land cover maps have been produced recently namely, Global Land Cover Share (GLC-Share) and GlobeLand30. These datasets are very useful sources of land cover information and potential users and producers are many times interested in comparing these datasets. However these global land cover maps are produced based on different techniques and using different classification schemes making their interoperability in a standardized way a challenge. The Environmental Information and Observation Network (EIONET) Action Group on Land Monitoring in Europe (EAGLE) concept was developed in order to translate the differences in the classification schemes into a standardized format which allows a comparison between class definitions. This is done by elaborating an EAGLE matrix for each classification scheme, where a bar code is assigned to each class definition that compose a certain land cover class. Ahlqvist (2005) developed an overlap metric to cope with semantic uncertainty of geographical concepts, providing this way a measure of how geographical concepts are more related to each other. In this paper, the comparison of global land cover datasets is done by translating each land cover legend into the EAGLE bar coding for the Land Cover Components of the EAGLE matrix. The bar coding values assigned to each class definition are transformed in a fuzzy function that is used to compute the overlap metric proposed by Ahlqvist (2005) and overlap matrices between land cover legends are elaborated. The overlap matrices allow the semantic comparison between the classification schemes of each global land cover map. The proposed methodology is tested on a case study where the overlap metric proposed by Ahlqvist (2005) is computed in the comparison of two global land cover maps for Continental Portugal. The study resulted with the overlap spatial distribution among the two global land cover maps, Globeland30 and GLC-Share. These results shows that Globeland30 product overlap with a degree of 77% with GLC-Share product in Continental Portugal.

Applying Least Absolute Shrinkage Selection Operator and Akaike Information Criterion Analysis to Find the Best Multiple Linear Regression Models between Climate Indices and Components of Cow’s Milk

This study focuses on multiple linear regression models relating six climate indices (temperature humidity THI, environmental stress ESI, equivalent temperature index ETI, heat load HLI, modified HLI (HLI new), and respiratory rate predictor RRP) with three main components of cow’s milk (yield, fat, and protein) for cows in Iran. The least absolute shrinkage selection operator (LASSO) and the Akaike information criterion (AIC) techniques are applied to select the best model for milk predictands with the smallest number of climate predictors. Uncertainty estimation is employed by applying bootstrapping through resampling. Cross validation is used to avoid over-fitting. Climatic parameters are calculated from the NASA-MERRA global atmospheric reanalysis. Milk data for the months from April to September, 2002 to 2010 are used. The best linear regression models are found in spring between milk yield as the predictand and THI, ESI, ETI, HLI, and RRP as predictors with p-value < 0.001 and R2 (0.50, 0.49) respectively. In summer, milk yield with independent variables of THI, ETI, and ESI show the highest relation (p-value < 0.001) with R2 (0.69). For fat and protein the results are only marginal. This method is suggested for the impact studies of climate variability/change on agriculture and food science fields when short-time series or data with large uncertainty are available.

The Effect of Climate Variability on Main Components of Cow Milk in Iran

The main purpose of this study is to assess the relationship between six bioclimatic indices for cattle (temperature humidity (THI), environmental stress (ESI), equivalent temperature (ESI), heat load (HLI), modified heat load (HLInew) and respiratory rate predictor(RRP)) and fundamental milk components (fat, protein, and milk yield) considering uncertainty. The climate parameters used to calculate the climate indices were taken from the NASA-Modern Era Retrospective-Analysis for Research and Applications (NASA-MERRA) reanalysis from 2002 to 2010. Cow milk data were considered for the same period from April to September when cows use natural pasture, with possibility for cows to choose to stay in the barn or to graze on the pasture in the pasturing system. The study is based on a linear regression analysis using correlations as a summarizing diagnostic. Bootstrapping is used to represent uncertainty estimation through resampling in the confidence intervals. To find the relationships between climate indices (THI, ETI, HLI, HLInew, ESI and RRP) and main components of cow milk (fat, protein and yield), multiple liner regression is applied. The least absolute shrinkage selection operator (LASSO) and the Akaike information criterion (AIC) techniques are applied to select the best model for milk predictands with the smallest number of climate predictors. Cross validation is used to avoid over-fitting. Based on results of investigation the effect of heat stress indices on milk compounds separately, we suggest the use of ESI and RRP in the summer and ESI in the spring. THI and HLInew are suggested for fat content and HLInew also is suggested for protein content in the spring season. The best linear models are found in spring between milk yield as predictands and THI, ESI,HLI, ETI and RRP as predictors with p-value < 0.001 and R2 0.50, 0.49. In summer, milk yield with independent variables of THI, ETI and ESI show the highest relation (p-value < 0.001) with R2 (0.69). For fat and protein the results are only marginal. It is strongly suggested that new and significant indices are needed to control critical heat stress conditions that consider more predictors of the effect of climate variability on animal products, such as sunshine duration, quality of pasture, the number of days of stress (NDS), the color of skin with attention to large black spots, and categorical predictors such as breed, welfare facility, and management system. This methodology is suggested for studies investigating the impacts of climate variability/change on food quality/security, animal science and agriculture using short term data considering uncertainty or data collection is expensive, difficult, or data with gaps.

Comparisons of an aerosol transport model with a 4-year analysis of summer aerosol optical depth retrievals over the Canadian Arctic

Abstract : This is a study concerning comparisons between the Dubovik Aerosol optical depth (AOD) retrievals from AEROCAN (ARONET) stations and AOD estimates from simulations provided by a chemical transport model (GEOS-Chem : Goddard Earth Observing System Chemistry). The AOD products associated with the Dubovik product are divided into total, fine and coarse mode components. The retrieval period is from January 2009 to January 2013 for 5 Arctic stations (Barrow, Alaska; Resolute Bay, Nunavut; 0PAL and PEARL (Eureka), Nunavut; and Thule, Greenland). We also employed AOD retrievals from 10 other mid-latitude Canadian stations for comparisons with the Arctic stations. The results of our investigation were submitted to Atmosphere-Ocean. To briefly summarize those results, the model generally but not always tended to underestimate the (monthly) averaged AOD and its components. We found that the subdivision into fine and coarse mode components could provide unique signatures of particular events (Asian dust) and that the means of characterizing the statistics (log-normal frequency distributions versus normal distributions) was an attribute that was common to both the retrievals and the model.

Reinforcement learning over encrypted data

Reinforcement learning is a particular paradigm of machine learning that, recently, has proved times and times again to be a very effective and powerful approach. On the other hand, cryptography usually takes the opposite direction. While machine learning aims at analyzing data, cryptography aims at maintaining its privacy by hiding such data. However, the two techniques can be jointly used to create privacy preserving models, able to make inferences on the data without leaking sensitive information. Despite the numerous amount of studies performed on machine learning and cryptography, reinforcement learning in particular has never been applied to such cases before. Being able to successfully make use of reinforcement learning in an encrypted scenario would allow us to create an agent that efficiently controls a system without providing it with full knowledge of the environment it is operating in, leading the way to many possible use cases. Therefore, we have decided to apply the reinforcement learning paradigm to encrypted data. In this project we have applied one of the most well-known reinforcement learning algorithms, called Deep Q-Learning, to simple simulated environments and studied how the encryption affects the training performance of the agent, in order to see if it is still able to learn how to behave even when the input data is no longer readable by humans. The results of this work highlight that the agent is still able to learn with no issues whatsoever in small state spaces with non-secure encryptions, like AES in ECB mode. For fixed environments, it is also able to reach a suboptimal solution even in the presence of secure modes, like AES in CBC mode, showing a significant improvement with respect to a random agent; however, its ability to generalize in stochastic environments or big state spaces suffers greatly.

Catalytic reduction of levulinic acid derivatives to bio-fuel components

Levulinic Acid and its esters are polyfunctional molecules obtained by biomass conversion. The most investigated strategy for the valorization of LA is its hydrogenation towards fuel additives, solvents and other added-value bio-based chemicals and, in this context, heterogeneous and homogeneous catalysts are widely used. Most commonly, it is typically performed with molecular hydrogen (H2) in batch systems, with high H2 pressures and noble metal catalysts. Several works reported the batch liquid-phase hydrogenation of LA and its esters by heterogenous catalysts which contained support with Brønsted acidity in order to obtain valeric acid and its esters. Furthermore, bimetallic and monometallic systems composed by both a metal for hydrogen activation and a promoter were demonstrated to be suitable catalysts for reduction of carboxylic group. However, there were no studies in the literature reporting the hydrogenation of alkyl levulinates to 1-pentanol (1-PAO). Therefore, bimetallic and monometallic catalysts were tested for one-pot hydrogenation of methyl levulinate to 1-PAO. Re-based catalysts were investigated, this way proving the crucial role of the support for promoting the ring-opening of GVL and its consecutive reduction to valeric compounds. All the reactions were performed in neat without the need of any additional solvents. In these conditions, bimetallic Re-Ru-O/HZSM-5 afforded methyl valerate and valeric acid (VA) with a productivity of 512 mmol gmetal-1 h-1, one of the highest reported in literature to date. Rhenium can also promote the reduction of valeric acid/esters to PV through the formation of 1-pentanol and its efficient esterification/transesterification with the starting material. However, it was proved that Re-based catalysts may undergo leaching of active phase in presence of carboxylic acids, especially by working in neat with VA. Furthermore, the over-reduction of rhenium affects catalytic performance, suggesting not only that a pre-reduction step is unnecessary but also that it could be detrimental for catalyst’s activity.

Quantum Dots As Biophotonics Tools.

This chapter provides a short review of quantum dots (QDs) physics, applications, and perspectives. The main advantage of QDs over bulk semiconductors is the fact that the size became a control parameter to tailor the optical properties of new materials. Size changes the confinement energy which alters the optical properties of the material, such as absorption, refractive index, and emission bands. Therefore, by using QDs one can make several kinds of optical devices. One of these devices transforms electrons into photons to apply them as active optical components in illumination and displays. Other devices enable the transformation of photons into electrons to produce QDs solar cells or photodetectors. At the biomedical interface, the application of QDs, which is the most important aspect in this book, is based on fluorescence, which essentially transforms photons into photons of different wavelengths. This chapter introduces important parameters for QDs' biophotonic applications such as photostability, excitation and emission profiles, and quantum efficiency. We also present the perspectives for the use of QDs in fluorescence lifetime imaging (FLIM) and Förster resonance energy transfer (FRET), so useful in modern microscopy, and how to take advantage of the usually unwanted blinking effect to perform super-resolution microscopy.

Neck Circumference As A New Anthropometric Indicator For Prediction Of Insulin Resistance And Components Of Metabolic Syndrome In Adolescents: Brazilian Metabolic Syndrome Study.

To evaluate the correlation between neck circumference and insulin resistance and components of metabolic syndrome in adolescents with different adiposity levels and pubertal stages, as well as to determine the usefulness of neck circumference to predict insulin resistance in adolescents. Cross-sectional study with 388 adolescents of both genders from ten to 19 years old. The adolescents underwent anthropometric and body composition assessment, including neck and waist circumferences, and biochemical evaluation. The pubertal stage was obtained by self-assessment, and the blood pressure, by auscultation. Insulin resistance was evaluated by the Homeostasis Model Assessment-Insulin Resistance. The correlation between two variables was evaluated by partial correlation coefficient adjusted for the percentage of body fat and pubertal stage. The performance of neck circumference to identify insulin resistance was tested by Receiver Operating Characteristic Curve. After the adjustment for percentage body fat and pubertal stage, neck circumference correlated with waist circumference, blood pressure, triglycerides and markers of insulin resistance in both genders. The results showed that the neck circumference is a useful tool for the detection of insulin resistance and changes in the indicators of metabolic syndrome in adolescents. The easiness of application and low cost of this measure may allow its use in Public Health services.

Beam-energy Dependence Of Charge Separation Along The Magnetic Field In Au+au Collisions At Rhic.

Local parity-odd domains are theorized to form inside a quark-gluon plasma which has been produced in high-energy heavy-ion collisions. The local parity-odd domains manifest themselves as charge separation along the magnetic field axis via the chiral magnetic effect. The experimental observation of charge separation has previously been reported for heavy-ion collisions at the top RHIC energies. In this Letter, we present the results of the beam-energy dependence of the charge correlations in Au+Au collisions at midrapidity for center-of-mass energies of 7.7, 11.5, 19.6, 27, 39, and 62.4 GeV from the STAR experiment. After background subtraction, the signal gradually reduces with decreased beam energy and tends to vanish by 7.7 GeV. This implies the dominance of hadronic interactions over partonic ones at lower collision energies.

Classification Of Frankfurters By Ft-raman Spectroscopy And Chemometric Methods.

Frankfurters are widely consumed all over the world, and the production requires a wide range of meat and non-meat ingredients. Due to these characteristics, frankfurters are products that can be easily adulterated with lower value meats, and the presence of undeclared species. Adulterations are often still difficult to detect, due the fact that the adulterant components are usually very similar to the authentic product. In this work, FT-Raman spectroscopy was employed as a rapid technique for assessing the quality of frankfurters. Based on information provided by the Raman spectra, a multivariate classification model was developed to identify the frankfurter type. The aim was to study three types of frankfurters (chicken, turkey and mixed meat) according to their Raman spectra, based on the fatty vibrational bands. Classification model was built using partial least square discriminant analysis (PLS-DA) and the performance model was evaluated in terms of sensitivity, specificity, accuracy, efficiency and Matthews's correlation coefficient. The PLS-DA models give sensitivity and specificity values on the test set in the ranges of 88%-100%, showing good performance of the classification models. The work shows the Raman spectroscopy with chemometric tools can be used as an analytical tool in quality control of frankfurters.

A New Platinum Complex With Tryptophan: Synthesis, Structural Characterization, Dft Studies And Biological Assays In Vitro Over Human Tumorigenic Cells.

A new platinum(II) complex with the amino acid L-tryptophan (trp), named Pt-trp, was synthesized and characterized. Elemental, thermogravimetric and ESI-QTOF mass spectrometric analyses led to the composition [Pt(C11H11N2O2)2]⋅6H2O. Infrared spectroscopic data indicate the coordination of trp to Pt(II) through the oxygen of the carboxylate group and also through the nitrogen atom of the amino group. The (13)C CP/MAS NMR spectroscopic data confirm coordination through the oxygen atom of the carboxylate group, while the (15)N CP/MAS NMR data confirm coordination of the nitrogen of the NH2 group to the metal. Density functional theory (DFT) studies were applied to evaluate the cis and trans coordination modes of trp to platinum(II). The trans isomer was shown to be energetically more stable than the cis one. The Pt-trp complex was evaluated as a cytotoxic agent against SK-Mel 103 (human melanoma) and Panc-1 (human pancreatic carcinoma) cell lines. The complex was shown to be cytotoxic over the considered cells.

Key Participants Of The Tumor Microenvironment Of The Prostate: An Approach Of The Structural Dynamic Of Cellular Elements And Extracellular Matrix Components During Epithelial-stromal Transition.

Cancer is a multistep process that begins with the transformation of normal epithelial cells and continues with tumor growth, stromal invasion and metastasis. The remodeling of the peritumoral environment is decisive for the onset of tumor invasiveness. This event is dependent on epithelial-stromal interactions, degradation of extracellular matrix components and reorganization of fibrillar components. Our research group has studied in a new proposed rodent model the participation of cellular and molecular components in the prostate microenvironment that contributes to cancer progression. Our group adopted the gerbil Meriones unguiculatus as an alternative experimental model for prostate cancer study. This model has presented significant responses to hormonal treatments and to development of spontaneous and induced neoplasias. The data obtained indicate reorganization of type I collagen fibers and reticular fibers, synthesis of new components such as tenascin and proteoglycans, degradation of basement membrane components and elastic fibers and increased expression of metalloproteinases. Fibroblasts that border the region, apparently participate in the stromal reaction. The roles of each of these events, as well as some signaling molecules, participants of neoplastic progression and factors that promote genetic reprogramming during epithelial-stromal transition are also discussed.

Folhas verdes, folhas secas, fibra do colmo e a clarificação do caldo de cana-de-açúcar

The presence of vegetal impurities in sugarcane delivered to sugarmills as green and dry leaves is a problem not only because they are non-value materials to be processed along with sugarcane stalks, but also because they can rise the color of the clarified juice and, consequently, the color of the sugar produced, with a reduction of its quality for the market. Another problem is the mud volume sedimented in the clarifiers, which also can result in a larger recirculation and greater volume of filtrate juice, with higher losses of sucrose and utilization of the vacuum rotary filters. The objective of this work was to observe the effect of the presence of green and dry leaves on sugarcane juice clarification, related to a control treatment with the addition of fiber extracted from the stalks. The experiments were planned based on the addition of quantities of fibrous sources in order to formulate samples with absolute increase of 0.25 , 0.50 and 0.75 percentual points over the fiber content of the sugarcane stalks (control treatment). The juice clarification was conducted with a laboratory clarifier. The clarified juice color and the mud volume were evaluated. The presence of green leaves caused higher color and mud volume due to the extraction of non-sucrose components of the leaves. Soluble compounds of dry leaves were also extracted, though not detected by juice analysis. The addition of the fiber extracted from the stalks did not induce alterations in the clarification process.

Análise cinemática tridimensional do salto em distância de atletas de alto nível em competição

Universidade Estadual de Campinas . Faculdade de Educação Física