Leaf nutritional levels in peach and nectarine grown in subtropical climate

The study evaluated the leaf nutritional levels of peach and nectarine trees under subtropical climate in order to improve the fertilization practices. The experiment was carried out in São Paulo state University, Botucatu, São Paulo State, Brazil. The experimental design consisted of subdivided plots, in which plots corresponded to cultivars and subplots to the leaf sample periods. The evaluated peach cultivars were: Marli, Turmalina, Precocinho, Jubileu, Cascata 968, Cascata 848, CP 951C, CP 9553CYN, and Tropic Beauty, and that of nectarine was 'Sun Blaze'. The sample periods were: after harvest, plants in vegetative period; dormancy; beginning of flowering and fruiting (standard sample). Results indicated significant variations in the levels of N, P, K, Ca, Mg, S, B, Cu, Fe, Mn and Zn for the sampling period and in N, Ca, Mg, S, B, Fe and Mn levels for the cultivars.

Effect of gibberellic acid and the biostimulant stimulate® on the initial growth of tamarind

Plant growth regulators and biostimulants have been used as an agronomic technique to optimize the production of seedlings in various crops. This study aimed to evaluate the influence of gibberellic acid and the biostimulant Stimulate® on the initial growth of tamarind (Tamarindus indica L.). The experiments were conducted in a nursery with 50% shading, in a randomized block design with five replications and five plants per plot. Thirty eight days after sowing, the leaves were sprayed seven times a day with 0.0 (control), 0.8, 1.6, 2.4 and 3.2 mL of gibberellic acid L-1 aqueous solution and with 0.0 (control), 6.0,12.0, 18.0, and 24.0 mL Stimulate® L-1 aqueous solution. Stem diameter (SD), plant height (PH), longest root length (LRL), shoot dry mass (SDM), root dry mass (RDM) and RDM:SDM ratio were evaluated ninety days after sowing. Variance and regression analysis showed that GA3 at 4% promoted plant growth (height), but had no significant effect on stem diameter, longest root length, shoot and root dry mass and the RDM:SDM ratio. On the other hand, all concentrations of Stimulate® significantly increased plant height and shoot and root dry mass of tamarind seedlings.

The Sottunga-Jurmo shear zone : structure and deformation history of a crustal-scale ductile shear zone in SW Finland

The aim of this study is to gain a better understanding of the structure and the deformation history of a NW-SE trending regional, crustal-scale shear structure in the Åland archipelago, SW Finland, called the Sottunga-Jurmo shear zone (SJSZ). Approaches involving e.g. structural geology, geochronology, geochemistry and metamorphic petrology were utilised in order to reconstruct the overall deformation history of the study area. The study therefore describes several features of the shear zone including structures, kinematics and lithologies within the study area, the ages of the different deformation phases (ductile to brittle) within the shear zone, as well as some geothermobarometric results. The results indicate that the SJSZ outlines a major crustal discontinuity between the extensively migmatized rocks NE of the shear zone and the unmigmatised, amphibolite facies rocks SW of the zone. The main SJSZ shows overall dextral lateral kinematics with a SW-side up vertical component and deformation partitioning into pure shear and simple shear dominated deformation styles that was intensified toward later stages of the deformation history. The deformation partitioning resulted in complex folding and refolding against the SW margin of the SJSZ, including conical and sheath folds, and in a formation of several minor strike-slip shear zones both parallel and conjugate to the main SJSZ in order to accommodate the regional transpressive stresses. Different deformation phases within the study area were dated by SIMS (zircon U-Pb), ID-TIMS (titanite U-Pb) and 40Ar/39Ar (pseudotachylyte wholerock) methods. The first deformation phase within the ca. 1.88 Ga rocks of the study area is dated at ca. 1.85 Ga, and the shear zone was reactivated twice within the ductile regime (at ca. 1.83 Ga and 1.79 Ga), during which the strain was successively increasingly partitioned into the main SJSZ and the minor shear zones. The age determinations suggest that the orogenic processes within the study area did not occur in a temporal continuum; instead, the metamorphic zircon rims and titanites show distinct, 10-20 Ma long breaks in deformation between phases of active deformation. The results of this study further imply slow cooling of the rocks through 600-700ºC so that at 1.79 Ga, 2 the temperature was still at least 600ºC. The highest recorded metamorphic pressures are 6.4-7.1 kbar. At the late stages or soon after the last ductile phase (ca. 1.79 Ga), relatively high-T mylonites and ultramylonites were formed, witnessing extreme deformation partitioning and high strain rates. After the rocks reached lower amphibolite facies to amphibolite-greenschist facies transitional conditions (ca. 500-550ºC), they cooled rapidly, probably due to crustal uplift and exhumation. The shear zone was reactivated at least once within the semi-brittle to brittle regime between ca. 1.79 Ga and 1.58 Ga, as evidenced by cataclasites and pseudotachylytes. In summary, the results of this study suggest that the Sottunga-Jurmo shear zone (and the South Finland shear zone) defines a major crustal discontinuity, and played a central role in accommodating the regional stresses during and after the Svecofennian orogeny.

The long run impact of mergers and acquisitions on performance – empirical study in the pulp and paper industry

Mergers and acquisitions (M&A) have played very important role in restructuring the pulp and paper industry (PPI). The poor performance and fragmented nature of the industry, overcapacity problems, and globalisation have driven companies to consolidate. The objective of this thesis was to examine how PPI acquirers’ have performed subsequent M&As and whether the deal characteristics have had any impact on performance. Based on the results it seems that PPI companies have not been able to enhance their performance in the long run after M&As although the per-formance of acquiring firms has remained above the industry median, and deal characteristics or the amount of premiums paid do not seem to have had any effect. The statistical significance of the results was tested with change model and regression analysis. Performance was assessed with accrual, cash flow, and market based indicators. Results are congruent with behavioural theory: managers and investors seem to be overoptimistic in determining the synergies from M&As.

Resilience and unmet supportive care needs in patients with cancer during early treatment: A descriptive study.

PURPOSE: The concept of resilience is gaining increasing importance as a key component of supportive care but to date has rarely been addressed in studies with adult cancer patients. The purpose of our study was to describe resilience and its potential predictors and supportive care needs in cancer patients during early treatment and to explore associations between both concepts. METHODS: This descriptive study included adult cancer patients under treatment in ambulatory cancer services of a Swiss hospital. Subjects completed the 25-item Connor-Davidson-Resilience Scale and the 34-item Supportive Care Needs Survey. Descriptive, correlational and regression analysis were performed. RESULTS: 68 patients with cancer were included in the study. Compared to general population, resilience scores were significantly lower (74.4 ± 12.6 vs. 80.4 ± 12.8, p = .0002). Multiple regression analysis showed predictors ("age", "metastasis", "recurrence" and "living alone") of resilience (adjusted R2 = .19, p < .001). Highest unmet needs were observed in the domain of psychological needs. Lower resilience scores were significantly and strongly associated with higher levels of unmet psychological needs (Rho = -.68, p < .001), supportive care needs (Rho = -.49, p < .001) and information needs (Rho = -.42, p = .001). CONCLUSION: Ambulatory patients with higher levels of resilience express fewer unmet needs. Further work is needed to elucidate the mechanism of the observed relationships and if interventions facilitating resilience have a positive effect on unmet needs.

Reuse of information for selection of methods and operating conditions for drying of pharmaceutical materials

Drying is a major step in the manufacturing process in pharmaceutical industries, and the selection of dryer and operating conditions are sometimes a bottleneck. In spite of difficulties, the bottlenecks are taken care of with utmost care due to good manufacturing practices (GMP) and industries' image in the global market. The purpose of this work is to research the use of existing knowledge for the selection of dryer and its operating conditions for drying of pharmaceutical materials with the help of methods like case-based reasoning and decision trees to reduce time and expenditure for research. The work consisted of two major parts as follows: Literature survey on the theories of spray dying, case-based reasoning and decision trees; working part includes data acquisition and testing of the models based on existing and upgraded data. Testing resulted in a combination of two models, case-based reasoning and decision trees, leading to more specific results when compared to conventional methods.

Consequences of lineage-specific gene loss on functional evolution of surviving paralogs: ALDH1A and retinoic acid signaling in vertebrate genomes

Genome duplications increase genetic diversity and may facilitate the evolution of gene subfunctions. Little attention, however, has focused on the evolutionary impact of lineage-specific gene loss. Here, we show that identifying lineage-specific gene loss after genome duplication is important for understanding the evolution of gene subfunctions in surviving paralogs and for improving functional connectivity among human and model organism genomes. We examine the general principles of gene loss following duplication, coupled with expression analysis of the retinaldehyde dehydrogenase Aldh1a gene family during retinoic acid signaling in eye development as a case study. Humans have three ALDH1A genes, but teleosts have just one or two. We used comparative genomics and conserved syntenies to identify loss of ohnologs (paralogs derived from genome duplication) and to clarify uncertain phylogenies. Analysis showed that Aldh1a1 and Aldh1a2 form a clade that is sister to Aldh1a3-related genes. Genome comparisons showed secondarily loss of aldh1a1 in teleosts, revealing that Aldh1a1 is not a tetrapod innovation and that aldh1a3 was recently lost in medaka, making it the first known vertebrate with a single aldh1a gene. Interestingly, results revealed asymmetric distribution of surviving ohnologs between co-orthologous teleost chromosome segments, suggesting that local genome architecture can influence ohnolog survival. We propose a model that reconstructs the chromosomal history of the Aldh1a family in the ancestral vertebrate genome, coupled with the evolution of gene functions in surviving Aldh1a ohnologs after R1, R2, and R3 genome duplications. Results provide evidence for early subfunctionalization and late subfunction-partitioning and suggest a mechanistic model based on altered regulation leading to heterochronic gene expression to explain the acquisition or modification of subfunctions by surviving ohnologs that preserve unaltered ancestral developmental programs in the face of gene loss.

Machine Learning and Clinical Text. Supporting Health Information Flow

Fluent health information flow is critical for clinical decision-making. However, a considerable part of this information is free-form text and inabilities to utilize it create risks to patient safety and cost-­effective hospital administration. Methods for automated processing of clinical text are emerging. The aim in this doctoral dissertation is to study machine learning and clinical text in order to support health information flow.First, by analyzing the content of authentic patient records, the aim is to specify clinical needs in order to guide the development of machine learning applications.The contributions are a model of the ideal information flow,a model of the problems and challenges in reality, and a road map for the technology development. Second, by developing applications for practical cases,the aim is to concretize ways to support health information flow. Altogether five machine learning applications for three practical cases are described: The first two applications are binary classification and regression related to the practical case of topic labeling and relevance ranking.The third and fourth application are supervised and unsupervised multi-class classification for the practical case of topic segmentation and labeling.These four applications are tested with Finnish intensive care patient records.The fifth application is multi-label classification for the practical task of diagnosis coding. It is tested with English radiology reports.The performance of all these applications is promising. Third, the aim is to study how the quality of machine learning applications can be reliably evaluated.The associations between performance evaluation measures and methods are addressed,and a new hold-out method is introduced.This method contributes not only to processing time but also to the evaluation diversity and quality. The main conclusion is that developing machine learning applications for text requires interdisciplinary, international collaboration. Practical cases are very different, and hence the development must begin from genuine user needs and domain expertise. The technological expertise must cover linguistics,machine learning, and information systems. Finally, the methods must be evaluated both statistically and through authentic user-feedback.

Thermodynamic quantities of solvation and dilution for some acetanilide derivatives in octanol and water mutually saturateds

Based on published thermodynamic quantities for solution, partitioning and sublimation of acetanilide (ACN), acetaminophen (ACP) and Phenacetin (PNC), the thermodynamic quantities for drugs solvation in octanol-saturated water (W(ROH)) and water-saturated octanol (ROH(W)) as well as the drugs dilution in ROH(W) were calculated. The Gibbs energies of solvation were favourable in all cases. The respective enthalpies and entropies were negative indicating an enthalpy-driving for the solvation process in all cases. On the other hand, the Gibbs energies of dilution were favourable for ACP and PNC but unfavourable for ACN, whereas the respective enthalpies and entropies were negative for ACP and PNC but positive for ACN indicating enthalpy-driving for the dilution process in the case of the former drugs and entropy-driving for the latter. From the obtained values for the transfer processes, an interpretation based on solute-solvent interactions was developed.

The Sottunga-Jurmo shear zone : structure and deformation history of a crustal-scale ductile shear zone in SW Finland

The aim of this study is to gain a better understanding of the structure and the deformation history of a NW-SE trending regional, crustal-scale shear structure in the Åland archipelago, SW Finland, called the Sottunga-Jurmo shear zone (SJSZ). Approaches involving e.g. structural geology, geochronology, geochemistry and metamorphic petrology were utilised in order to reconstruct the overall deformation history of the study area. The study therefore describes several features of the shear zone including structures, kinematics and lithologies within the study area, the ages of the different deformation phases (ductile to brittle) within the shear zone, as well as some geothermobarometric results. The results indicate that the SJSZ outlines a major crustal discontinuity between the extensively migmatized rocks NE of the shear zone and the unmigmatised, amphibolite facies rocks SW of the zone. The main SJSZ shows overall dextral lateral kinematics with a SW-side up vertical component and deformation partitioning into pure shear and simple shear dominated deformation styles that was intensified toward later stages of the deformation history. The deformation partitioning resulted in complex folding and refolding against the SW margin of the SJSZ, including conical and sheath folds, and in a formation of several minor strike-slip shear zones both parallel and conjugate to the main SJSZ in order to accommodate the regional transpressive stresses. Different deformation phases within the study area were dated by SIMS (zircon U-Pb), ID-TIMS (titanite U-Pb) and 40Ar/39Ar (pseudotachylyte wholerock) methods. The first deformation phase within the ca. 1.88 Ga rocks of the study area is dated at ca. 1.85 Ga, and the shear zone was reactivated twice within the ductile regime (at ca. 1.83 Ga and 1.79 Ga), during which the strain was successively increasingly partitioned into the main SJSZ and the minor shear zones. The age determinations suggest that the orogenic processes within the study area did not occur in a temporal continuum; instead, the metamorphic zircon rims and titanites show distinct, 10-20 Ma long breaks in deformation between phases of active deformation. The results of this study further imply slow cooling of the rocks through 600-700ºC so that at 1.79 Ga, 2 the temperature was still at least 600ºC. The highest recorded metamorphic pressures are 6.4-7.1 kbar. At the late stages or soon after the last ductile phase (ca. 1.79 Ga), relatively high-T mylonites and ultramylonites were formed, witnessing extreme deformation partitioning and high strain rates. After the rocks reached lower amphibolite facies to amphibolite-greenschist facies transitional conditions (ca. 500-550ºC), they cooled rapidly, probably due to crustal uplift and exhumation. The shear zone was reactivated at least once within the semi-brittle to brittle regime between ca. 1.79 Ga and 1.58 Ga, as evidenced by cataclasites and pseudotachylytes. In summary, the results of this study suggest that the Sottunga-Jurmo shear zone (and the South Finland shear zone) defines a major crustal discontinuity, and played a central role in accommodating the regional stresses during and after the Svecofennian orogeny.

Tree structure and richness in an Atlantic Forest fragment: distance from anthropogenic and natural edges

Approximately 7.2% of the Atlantic rainforest remains in Brazil, with only 16% of this forest remaining in the State of Rio de Janeiro, all of it distributed in fragments. This forest fragmentation can produce biotic and abiotic differences between edges and the fragment interior. In this study, we compared the structure and richness of tree communities in three habitats - an anthropogenic edge (AE), a natural edge (NE) and the fragment interior (FI) - of a fragment of Atlantic forest in the State of Rio de Janeiro, Brazil (22°50'S and 42°28'W). One thousand and seventy-six trees with a diameter at breast height > 4.8 cm, belonging to 132 morphospecies and 39 families, were sampled in a total study area of 0.75 ha. NE had the greatest basal area and the trees in this habitat had the greatest diameter:height allometric coefficient, whereas AE had a lower richness and greater variation in the height of the first tree branch. Tree density, diameter, height and the proportion of standing dead trees did not differ among the habitats. There was marked heterogeneity among replicates within each habitat. These results indicate that the forest interior and the fragment edges (natural or anthropogenic) do not differ markedly considering the studied parameters. Other factors, such as the age from the edge, type of matrix and proximity of gaps, may play a more important role in plant community structure than the proximity from edges.

Kernel-Based Ranking. Methods for Learning and Performance Estimation

Machine learning provides tools for automated construction of predictive models in data intensive areas of engineering and science. The family of regularized kernel methods have in the recent years become one of the mainstream approaches to machine learning, due to a number of advantages the methods share. The approach provides theoretically well-founded solutions to the problems of under- and overfitting, allows learning from structured data, and has been empirically demonstrated to yield high predictive performance on a wide range of application domains. Historically, the problems of classification and regression have gained the majority of attention in the field. In this thesis we focus on another type of learning problem, that of learning to rank. In learning to rank, the aim is from a set of past observations to learn a ranking function that can order new objects according to how well they match some underlying criterion of goodness. As an important special case of the setting, we can recover the bipartite ranking problem, corresponding to maximizing the area under the ROC curve (AUC) in binary classification. Ranking applications appear in a large variety of settings, examples encountered in this thesis include document retrieval in web search, recommender systems, information extraction and automated parsing of natural language. We consider the pairwise approach to learning to rank, where ranking models are learned by minimizing the expected probability of ranking any two randomly drawn test examples incorrectly. The development of computationally efficient kernel methods, based on this approach, has in the past proven to be challenging. Moreover, it is not clear what techniques for estimating the predictive performance of learned models are the most reliable in the ranking setting, and how the techniques can be implemented efficiently. The contributions of this thesis are as follows. First, we develop RankRLS, a computationally efficient kernel method for learning to rank, that is based on minimizing a regularized pairwise least-squares loss. In addition to training methods, we introduce a variety of algorithms for tasks such as model selection, multi-output learning, and cross-validation, based on computational shortcuts from matrix algebra. Second, we improve the fastest known training method for the linear version of the RankSVM algorithm, which is one of the most well established methods for learning to rank. Third, we study the combination of the empirical kernel map and reduced set approximation, which allows the large-scale training of kernel machines using linear solvers, and propose computationally efficient solutions to cross-validation when using the approach. Next, we explore the problem of reliable cross-validation when using AUC as a performance criterion, through an extensive simulation study. We demonstrate that the proposed leave-pair-out cross-validation approach leads to more reliable performance estimation than commonly used alternative approaches. Finally, we present a case study on applying machine learning to information extraction from biomedical literature, which combines several of the approaches considered in the thesis. The thesis is divided into two parts. Part I provides the background for the research work and summarizes the most central results, Part II consists of the five original research articles that are the main contribution of this thesis.

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.

Liquidity levels of Finnish SME’s from 2007 to 2013 and a closer analysis of the IC sector

TAVOITTEET: Tämän tutkielman tarkoitus on tarkastella eri toimialojen likviditeettitasoja vuosien 2007 ja 2013 välillä. Se tarkastelee myös kassanhallinnan ja likviditeetin kirjallisuutta, erilaisia likviditeettiä kuvaavia tunnuslukuja sekä asioita, joilla on vaikutusta likviditeettiin. Tämän lisäksi se tutkii informaatio ja kommunikaatio sektoria tarkemmin. DATA: Data on kerätty Orbis tietokannasta. Toimialakohtaiset keskiarvot on laskettu joko kappaleen 2 esittämillä kaavoilla tai noudettu suoraan tietokannasta. Hajonta kuvaajat on tehty Excelillä ja korrelaatio matriisi ja regressioanalyysit SAS EG:llä. TULOKSET: Tämä tutkimus esittää toimialakohtaiset keskiarvot liquidity ratiosta, solvency ratiosta sekä gearingista, kuten monista muista likviditeettiä kuvaavista tai siihen vaikuttavista tunnusluvuista. Tutkimus osoittaa, että keskimäärin likviditeetti ja maksuvalmius ovat säilyneet melko samana, mutta toimialakohtaiset muutokset ovat voimakkaita. IC sektorilla likviditeettiin vaikuttaa katetuotto, työntekijöiden määrä, liikevaihto, taseen määrä sekä maksuaika.

Sea Level Variations during the Late Quaternary and Coastal Evolution along the Northern Kerala, South West of India

In the present investigation, an attempt is made to document various episodes of transgression and regression during the late Quaternary period from the study of coastal and shelf sequences extending from the inland across the beach to the shelf domain. Shore parallel beach ridges with alternating swales and occurrence of strand line deposits on the shelf make the northern Kerala coast an ideal natural laboratory for documenting the morpho-dynamic response of the coast to the changing sea level. The objectives of the study are lithographic reconstruction of environments of deposition from the coastal plain and shelf sequences; documentation of episodes of transgression and regression by studying different coastal plain sequences and shelf deposits and evolve a comprehensive picture of late Quaternary coastal evolution and sea level changes along the northern Kerala coast by collating morphological, lithological and geochronological evidences from the coastal plain and shelf sequences. The present study is confined to two shore-normal east-west trending transects, Viz. Punjavi and Onakkunnu, in the northern Kerala coast.