No description available.

The Tropical Andes continue to suffer the most radical climatic changes in South America. These changes generate alterations in its ecosystems, and therefore affect local populations, whose livelihoods are dependent on its diversity and functioning. This is particularly true for rural populations who rely on agriculture as their primary source of food and income. Although the biophysical pathways through which climate change can affect these populations have received extensive scientific attention, it is urgent to study the socioeconomic pathways, at scales that allow the development of vulnerability reduction strategies at the local level. The present study is part of the INCA project (International Network on Climate Change), which is a research network that analyses the local strategies of farmers under a changing climate in the Tropical Andes (Lindner et al. 2017). To contribute to this goal this study investigates climate-related vulnerability and climate change adaptation at local scales. First, the current vulnerability of farm household systems (FHSs) to climate-related hazards is assessed. This is done by looking at determinants that are internal (adaptive capital) and external (climate-related hazards) to the FHSs. Based on the recurrence of internal factors, FHSs are categorized into different groups. These groups are validated by observing the effects of climatic events that are specific to each group. The result of the analysis are different typologies or archetypes of climate-related vulnerability. The analysis adopts an archetype approach and develops methods based on multivariate analysis techniques. Second, the study analyzes the impacts of climate change, expressed as an increase in temperature conditions, at local levels. For this purpose, a multi-agent systems model of land-use/cover change is used, specifically the software package MPMAS. The model is the first attempt at a detailed representation of agents-environment interactions in the framework of climate change in the Tropical Andes. The simulation outcomes report on the adaptation of different farm household groups and the effects of climate change on the agricultural landscape. The research was conducted in selected communities in the Central Andes of Peru. The active integration of empirical data with secondary literature in the application of the research methods provided a suitable way to analyze the vulnerability and adaptive capacity of FHSs in the Tropical Andes in a comprehensive manner. Moreover, the use of participatory assessment techniques to obtain empirical data provided an additional perspective for the analysis and improved the understanding of the problem, contributing to deriving analytical generalizations that could hardly be obtained using only quantitative methods. The research results for the study area identify five archetypes of farm household’s vulnerability to climate-related hazards. For each archetype, distinct vulnerability-creating mechanisms are observed. For example, most vulnerable farm households have a very limited amount of adaptive capital: low levels of off-farm employment, few farm animals, small agricultural area, mostly rainfed, and low use of agro-ecological zones. In addition, they occupy predominantly the higher, and therefore less-productive, agro-ecological zones of the watershed. The analysis also makes it possible to derive spatial and thematic priorities for vulnerability reduction that are specific to each archetype. The modeling approach applied proved to be suitable for simulating the impacts of climate change at the local level. In particular, regarding the explicit simulation of FHSs, the productive landscape, and the way in which they interrelate and change in response to an increase in temperature conditions. The incorporation of heterogeneity and dynamics in the modeled population, the use of optimization techniques to simulate decision making, and the multi-periodicity of the model produce non-linearity, uncertainty and trajectory dependence. In addition, the use of vulnerability archetypes is a novel and robust way of creating a heterogeneous population for the initialization of the model. Simulation results show dynamic changes in the agricultural landscape as temperature increases. The area allocated to corn and olluco expands, while potato and oat areas diminish. Investment in tree plantations is largely unaffected. The effects of rising temperatures on farm households’ welfare show a general persistence of poverty in the study area. However, the effect on FHSs income is predominantly positive, allowing some to improve their food poverty position. The FHSs that manage to benefit from an increase in temperature have, on average, larger agricultural and forest areas, a greater amount of savings in the form of animals, hire more salaried labor and practice more mechanized agriculture than the FHSs whose situation did not improve. The results show that, in addition to the effects of climate change on crop productivity, there are other factors influencing land use decisions that deserve more attention in the analysis of vulnerability and climate change impacts. A better understanding of heterogeneity in climate vulnerability and climate impacts is an important step in meeting this demand.

No description available.

No description available.

Thesis (MComm (Business Management))--University of Stellenbosch, 2007. / ENGLISH ABSTRACT: his study aims to investigate whether the phenomena found by Shnoll et al. when applying histogram pattern analysis techniques to stochastic processes from chemistry and physics are also present in financial time series, particularly exchange rate and index data. The phenomena are related to fine structure of non-smoothed frequency distributions drawn from statistically insufficient samples of changes and their patterns in time. Shnoll et al. use the notion of macroscopic fluctuations to explain the behaviour of sequences of histograms. Histogram patterns in time adhere to several laws that could not be detected when using time series analysis methods. In this study general approaches are reviewed that may be used to model financial markets and the volatility of price processes in particular. Special emphasis is placed on the modelling of highfrequency data sets and exchange rate data. Following previous studies of the Shnoll phenomena from other fields, different steps of the histogram sequence analysis are carried out to determine whether the findings of Shnoll et al. could also be applied to financial market data. The findings of this thesis widen the understanding of time varying volatility and can aid in financial risk measurement and management. Outcomes of the study include an investigation of time series characteristics in terms of the formation of discrete states, the detection of the near zone effect as proclaimed by Shnoll et al., the periodic recurrence of histogram shapes as well as the synchronous variation in data sets measured in the same time intervals.

The causes of errors in the angle of impact calculation were investigated including the surface type, falling velocity and the method used to fit an ellipse to a bloodstain. As had been cited previously the angle of impact was generally underestimated, especially at acute angles and the reason for this was determined to be due to an overestimation of the length of a bloodstain. The surface type was found to significantly affect the accuracy of an angle of impact calculation and as the falling velocity increased, the angle of impact calculation became more accurate. High-speed photography was used to further investigate the formation of bloodstains on surfaces. It was found that the formation of the bloodstain varied depending on the surface type and the angle of the surface. Bloodstain pattern analysis involves the application of scientific techniques to reconstruct events that resulted in a bloodstain pattern. The position of the blood source in three-dimensional space is a fundamental element of this application. Currently little is known about the methods used by bloodstain pattern analysts to select bloodstains when determining the region of origin. Fourteen analysts worldwide were surveyed in order to ascertain this information. It was found that the methods used were variable and were often not based on scientific research. Research was therefore undertaken into bloodstain selection and in particular, which bloodstains should be selected for a region of origin analysis. As a result of these experiments, two sets of selection criteria were established, one for use when the region of origin is being calculated manually and one for when directional analysis is being used.

Introduction and objectives In Vietnam, the forest resources have been declining and degrading severely in recent years. The degradation has decreased the natural forest area, changed the forest structure seriously and reduced timber volume and biodiversity. From 1999 to 2005, the rich forest area has decreased 10.2%, whereas the poor secondary forest has increased dramatically by 20.7%. Forest structure plays an important role in forestry research. Understanding forest structure will unlock an understanding of the history, function and future of a forest ecosystem (Spies, 1998). The forest structure is an excellent basis for restoration measures. Therefore, this research is necessary to contribute to improving forest area and quality, reducing difficulties in forest management. The study also enhances the grasp of forest structure, structure changes after harvesting and fills serious gaps in knowledge. In addition, the research results will contribute to improving and rescuing the poor secondary forest and restoring it, approaching the old-growth forest in Vietnam. Material and methods The study was conducted in Kon Ka Kinh national park. The park is located in the Northeastern region of Gia Lai province, 50 km from Pleiku city center to the Northeast. The park is distributed over seven different communes in three districts: K’Bang, Mang Yang and Đăk Đoa. Data were collected from 10 plots of secondary forests (Type IIb) and 10 plots of primeval forests (Type IV). Stratified random sampling was applied to select plot locations. 1 ha plots were used to investigate gaps. 2000 m2 plots were used to measure overstorey trees such as diameter at breast height, total height, crown width and species names. 500 m2 subplots were used to record tree positions. For regeneration, 25 systematic 4 m2 subplots were established inside 1 ha plots. After data were collected in the field, data analyses were conducted by using R and Excel. Firstly, some stand information, such as density, volume and so on, was calculated, and then descriptive statistics were computed for diameter and height variables. Linear mixed effect models were applied to analyze the difference of diameter and height and to check the effect of random factor between the two forest types. Diameter and height frequency distributions were also generated and compared by using permutational analysis of variance (PERMANOVA). Non-linear regression models were analyzed for diameter and height variables. Similar analyses were implemented for gaps. Regarding spatial point patterns of overstorey trees, replicated point pattern analysis techniques were applied in this research. For biodiversity, some calculations were run such as richness and biodiversity indices, comparison of biodiversity indices by using linear mixed models and biodiversity differences between two forest types tested again by permutational analysis of variance. In terms of regeneration, some analyses were implemented such as: height frequency distribution generation, frequency difference testing, biodiversity indices for the regeneration and spatial distribution checking by using a nonrandomness index. Results and discussion After analyzing the data, some essential findings were obtained as follows: Hypothesis H1 “The overstorey structure of secondary forests is more homogeneous and uniform than old-growth forests” is accepted. In other words, the secondary forest density is about 1.8 times higher than the jungle. However, the volume is only 0.56 times as large. The average diameter and height of the secondary forest is smaller by 5.71 cm and 3.73 m than the old-growth forest, respectively. Linear mixed effect model results indicate that this difference is statistically different and the effect of the random factor (Section) is not important. Type IIb has many small trees and the diameter frequency distribution is quite homogeneous. The old-growth forest has more big trees. For both forest stages, the height frequency distribution is positively skewed. PERMANOVA results illustrate that the frequency distribution is statistically different between the two forest types. Regression functions are also more variant and diverse in the old-growth forest, because all standard deviations of the parameters are greater there. Gap analysis results indicate that the number of gaps in the young forest is slightly higher, while the average gap size is much smaller. The gap frequency distribution is statistically different between the two types. In terms of the spatial point pattern of overlayer trees, the G-test and the pair correlation function results show that trees distribute randomly in the secondary forest. In contrast, the spatial point patterns of trees are more regular and diverse in the old-growth forest. The spatial point pattern difference is not significant, and this is proved by a permutational t-test for pair correlation function (pcf). Envelope function results indicate that the variation of pcf in young forests is much lower than in the primary forests. Hypothesis H2 “The overstorey species biodiversity of the secondary forest is less than in the old-growth forest” is rejected. Results show that the number of species of the secondary forest is much greater than in the old-growth forest, especially richness. The richness of the secondary forest is 1.16 times higher. The Simpson and Shannon indices are slightly smaller in the secondary forest. The average Simpson index for both forest stages is 0.898 and 0.920, respectively. However, the difference is not significant. Species accumulation curves become relatively flatter on the right, meaning a reasonable number of plots have been observed. Estimated number of species from accumulation curves in two forest types are 105 and 95/ha. PERMANOVA results show that number of species and proportion of individuals in each species are significantly different between forest types. Hypothesis H3 “The number regenerating species of the secondary forest is less and they distribute more regularly, compared to the old-growth forest” is rejected. There are both similarities and differences between the two types. The regeneration density of the stage IIb is 22,930 seedlings/ha, greater than the old forest by 9,030 seedlings. The height frequency distribution shows a decreasing trend. Similar to overstorey, the richness of the secondary forest is 141 species, higher than the old-growth forest by 9 species. Biodiversity indices are not statistically different between two types. PERMANOVA results indicate that the number of species and the proportion of individuals for each species are also not significantly different from observed forest types. Nonrandomness index results show that the regeneration distributes regularly. Up to 95% of the plots reflect this distribution trend. Hypothesis H4 “Restoration measures (with and without human intervention) could be implemented in the regenerating forest” is accepted. The investigated results show that the secondary forest still has mother trees, and it has enough seedlings to restore. Therefore, restoration solutions with and without human intervention can be implemented. Firstly, forest protection should be applied. This measure is relevant to national park regulations in Vietnam. Rangers and other related organizations will be responsible for carrying out protection activities. These activities will protect forest resources from illegal logging, grazing and tourist activities. Environmental education and awareness-raising activities for indigenous people is also important. Another measure is additional and enrichment planting. It should focus on exclusive species of the overstorey in Type IIb or exclusive species of the primary forest. Selection of these species will lead to species biodiversity increase in the future. This also meets the purpose of the maximum biodiversity solution. Conclusion Forest resources play a very important role in human life as well as maintaining the sustainability of ecosystems. However, at present, they are under serious threat, particularly in Vietnam. Central Highland, Vietnam, where forest resources are still relatively good, is also threatened by illegal logging, lack of knowledge of people and so on. Therefore, it needs the hands of the people, especially foresters and researchers. Through research, scientists can provide the knowledge and understanding of the forest, including the structure and forest restoration. This study has obtained important findings. The secondary forest is more homogeneous and uniform, while the old-growth forest is very diverse. Biodiversity of the overstorey in the secondary forest is more than the primary. The number of regenerating species in the secondary forest is higher, but other indices are not statistically different between two types. The regeneration distribute regularly on the ground. The secondary forest still has mother trees and sufficient regeneration, so some restoration measures can be applied here. Findings of the study contribute to improve people’s understanding of the structure and the structural changes after harvesting in Kon Ka Kinh national park, Gia Lai. That is a key to have better understandings of the history and values of the forests. These findings and the proposed restoration measures address rescuing degraded forests in Central Highland in particular and Vietnam in general. And further, this is a promising basis for the management and sustainable use of forest resources in the future.

Menschen teilen mit vielen Spezies die Fähigkeit, aus einer Menge von Objekten deren Numerosität zu extrahieren. Es wird angenommen, dass diese Fähigkeit die Grundlage für die Menschen eigene, symbolisch-mathematische Fertigkeiten bildet. Daher ist ein besseres Verständnis der neuralen Charakteristiken dieser Fähigkeit von großer Bedeutung. Eines der einflussreichsten Modelle (das Triple Code Modell-TCM) nimmt an, dass dieser evolutionär alte Mechanismus in horizontalen Anteil des intraparietalen Sulcus verortet werden kann, der die Bedeutung von Anzahl in einer format- und modalitätsunabhängigen Art und Weise repräsentiert (d.h., Größencode). Zusätzlich wird angenommen, dass Subtraktion auf eben dieser Fähigkeit aufbaut, wohingegen Multiplikation stärker auf phonologischen Verarbeitungsmechanismen beruht (d.h., verbaler Code). Elektrophysiologische Untersuchungen beim Affen deuten auf einen gewissen Grad an Abstraktion von semantischer Größeninformation im parietalen Kortex hin. Jedoch wurde dies bisher nur für kleine Numerositäten ( / Humans as well as other animals are endowed with the capacity to extract the numerosity (i.e., the number of items) of a given set of objects. This capacity is thought to form the basis of human specific symbolic mathematical abilities. Hence, understanding its nature is of importance. One of the most influential models (The Triple Code Model) suggests that this evolutionarily ancient mechanism resides on the horizontal aspect of the intraparietal sulcus and represents number semantics in a format and modality independent fashion (i.e., magnitude code). In addition, subtraction is thought to rely more on this mechanism whereas multiplication relies more on phonological circuits (i.e., verbal code). Although there is evidence from non-human primate electrophysiology suggesting a certain degree of abstraction for number semantics in the parietal cortex, this was only found for small numerosities (

The goal of the diploma thesis is to design, implement and evaluate classifiers for automatic classification of semantic patterns of English verbs according to a pattern lexicon that draws on the Corpus Pattern Analysis. We use a pilot collection of 30 sample English verbs as training and test data sets. We employ standard methods of machine learning. In our experiments we use decision trees, k-nearest neighbourghs (kNN), support vector machines (SVM) and Adaboost algorithms. Among other things we concentrate on feature design and selection. We experiment with both morpho-syntactic and semantic features. Our results show that the morpho-syntactic features are the most important for statistically-driven semantic disambiguation. Nevertheless, for some verbs the use of semantic features plays an important role.

A neuroimaging feature extraction model is designed to extract region-based image features whose values are predicted by base learners trained on raw neuroimaging morphological variables. The main objectives are to identify Alzheimer’s disease (AD) in its earliest manifestations, and be able to predict and gauge progression of the disease through the stages of mild cognitive impairment (EMCI), late MCI (LMCI) and AD. The model was evaluated on the ADNI database and showed 75.26% accuracy for the challenging EMCI diagnosis based on the 10-fold cross-validation. Our approach also performed well for the other binary classifications: EMCI vs. LMCI (72.3%), EMCI vs. AD (95%), LMCI vs. AD (84.3%), CN vs. LMCI (77.5%), and CN vs. AD (96.5%). By applying the model to the Genome-wide Association Study, along with the sparse Partial Least Squares regression method, we successfully detected risk genes such as the APOE, TOMM40, RVRL2 and APOC1 along with the new finding of rs917100. Moreover, the research aimed to investigate the relationship of different biomarkers; especially the imaging biomarkers to better understand the precise biologic changes that characterize Alzheimer’s disease. The unique and independent contribution of APOE4 allele status (E4+\E4-), amyloid (Aβ) load status (Amy+\Amy-) and combined APOE4 and Aβ status on regional cortical thickness (CTh) and cognition were evaluated via a series of two-way ANCOVAs with post-hoc Tukey HSD tests. Results showed that decreased CTh is independently associated with Amy+ status in many brain regions, but with E4+ status in very restricted number of brain regions. Among CN and EMCI participants, E4+ status is associated with increased CTh, in medial and inferior temporal regions. Diverging association patterns of global and regional Aβ load with cortical volume were found in the entorhinal, temporal pole and parahippocampal regions, which were positively associated with regional Aβ load, but with a negative correlation for global Aβ load in MCI stages. In addition, strong positive correlations were shown between baseline regional CTh and the difference of CTh in each region between the CN and AD, even after adjusting for the regional Aβ and APOE genotype (E4+: r = 0.521 and E4-: r = 0.694).