Impacts of invasive Opuntia cacti on wild mammals in Kenya

In this thesis, I explored the impacts of invasive plants on animal behaviour, using the invasion of Opuntia cacti in Laikipia County, Kenya, as a specific case study. In the opening chapter, I introduced the topic of biological invasions, addressing essential background material and identifying key knowledge gaps. In the second chapter, I focused on the impacts of invasive plants on animal behaviour, an important – yet neglected – topic. I synthesised the disparate literature on invasive plants’ behavioural impacts within a novel mechanistic framework, revealing that invasive plants can cause profound behavioural changes in native animals, with ecological consequences at multiple scales. I also found that environmental context played an important role in moderating how an invader’s modes of impact translate into behavioural changes in native species, and how these behavioural changes then generate ecological impacts. Finally, I identified priority research questions relating to the behavioural impacts of invasive plants. Invasive plants’ behavioural impacts can manifest as changes to the occurrence patterns of native animals. In Chapter 3, I used simulations to explore model selection in occupancy models, which are a powerful tool for studying the patterns and drivers of occurrence. Specifically, I investigated the consequences of collider bias – a type of confounding that can arise when adding explanatory variables to a model – for model selection using the Akaike Information Criterion (AIC) and Schwarz Criterion (or Bayesian Information Criterion, BIC). I found that the effect of collider bias, and consequently the inferential and predictive accuracy of the AIC/BIC-best model, depended on whether the collider bias was present in the occupancy or detection data-generating process. My findings illustrate the importance of distinguishing between inference and prediction in ecological modelling and have more general implications for the use of information criteria in all linear modelling approaches. In Chapter 4, I applied the mechanistic framework from Chapter 2 and the modelling conclusions from Chapter 3 to the problem of understanding Opuntia’s behavioural impacts in Laikipia County. Specifically, I used camera traps to explore the effects of Opuntia on occupancy and activity for eight key mammal species. I found that the effects of Opuntia varied among mammal species and depended on the spatial scale of the Opuntia cover covariate. These findings have important implications for the conservation of endangered mammal species in the region, the future spread of Opuntia through seed dispersal, and interactions between wildlife and local communities. In Chapter 5, I addressed key knowledge gaps pertaining to Opuntia’s biotic interactions with native animals. First, I quantified the relationship between height and fruiting in O. engelmannii and O. stricta, finding that height was positively related to fruiting for both species, and that the relationship was stronger for O. engelmannii than for O. stricta. I also found that local habitat variables were related to height and/or fruiting in both Opuntia species. Second, I documented the interactions between animals and Opuntia using camera traps. In so doing, I confirmed the importance of interactions that were previously thought to be important, while also highlighting interactions which have previously received little attention in the published scientific literature

On multimodality of obnoxious faclity location models

Obnoxious single facility location models are models that have the aim to find the best location for an undesired facility. Undesired is usually expressed in relation to the so-called demand points that represent locations hindered by the facility. Because obnoxious facility location models as a rule are multimodal, the standard techniques of convex analysis used for locating desirable facilities in the plane may be trapped in local optima instead of the desired global optimum. It is assumed that having more optima coincides with being harder to solve. In this thesis the multimodality of obnoxious single facility location models is investigated in order to know which models are challenging problems in facility location problems and which are suitable for site selection. Selected for this are the obnoxious facility models that appear to be most important in literature. These are the maximin model, that maximizes the minimum distance from demand point to the obnoxious facility, the maxisum model, that maximizes the sum of distance from the demand points to the facility and the minisum model, that minimizes the sum of damage of the facility to the demand points. All models are measured with the Euclidean distances and some models also with the rectilinear distance metric. Furthermore a suitable algorithm is selected for testing multimodality. Of the tested algorithms in this thesis, Multistart is most appropriate. A small numerical experiment shows that Maximin models have on average the most optima, of which the model locating an obnoxious linesegment has the most. Maximin models have few optima and are thus not very hard to solve. From the Minisum models, the models that have the most optima are models that take wind into account. In general can be said that the generic models have less optima than the weighted versions. Models that are measured with the rectilinear norm do have more solutions than the same models measured with the Euclidean norm. This can be explained for the maximin models in the numerical example because the shape of the norm coincides with a bound of the feasible area, so not all solutions are different optima. The difference found in number of optima of the Maxisum and Minisum can not be explained by this phenomenon

Designing and Expanding Electrical Networks – Complexity and Combinatorial Algorithms

The transition from conventional to renewable power generation has a large impact on when and where electricity is generated. To deal with this change the electric transmission network needs to be adapted and expanded. Expanding the network has two benefits. Electricity can be generated at locations with high renewable energy potentials and then transmitted to the consumers via the transmission network. Without the expansion the existing transmission network may be unable to cope with the transmission needs, thus requiring power generation at locations closer to the energy demand, but at less well-suited locations. Second, renewable energy generation (e.g., from wind or solar irradiation) is typically volatile. Having strong interconnections between regions within a large geographical area allows to the smooth the generation and demand over that area. This smoothing makes them more predictable and the volatility of the generation easier to handle. In this thesis we consider problems that arise when designing and expanding electric transmission networks. As the first step we formalize them such that we have a precise mathematical problem formulation. Afterwards, we pursue two goals: first, improve the theoretical understanding of these problems by determining their computational complexity under various restrictions, and second, develop algorithms that can solve these problems. A basic formulation of the expansion planning problem models the network as a graph and potential new transmission lines as edges that may be added to the graph. We formalize this formulation as the problems Flow Expansion and Electrical Flow Expansion, which differ in the flow model (graph-theoretical vs. electrical flow). We prove that in general the decision variants of these problems are $\mathcal{NP}$-complete, even if the network structure is already very simple, e.g., a star. For certain restrictions, we give polynomial-time algorithms as well. Our results delineate the boundary between the $\mathcal{NP}$-complete cases and the cases that can be solved in polynomial time. The basic expansion planning problems mentioned above ignore that real transmission networks should still be able to operate if a small part of the transmission equipment fails. We employ a criticality measure from the literature, which measures the dynamic effects of the failure of a single transmission line on the whole transmission network. In a first step, we compare this criticality measure to the well-used $N-1$ criterion. Moreover, we formulate this criticality measure as a set of linear inequalities, which may be added to any formulation of a network design problem as a mathematical program. To exemplify this usage, we introduce the criticality criterion in two transmission network expansion planning problems, which can be formulated as mixed-integer linear programs (MILPs). We then evaluate the performance of solving the MILPs. Finally, we develop a greedy heuristic for one of the two problems, and compare its performance to solving the MILP. Microgrids play an important role in the electrification of rural areas. We formalize the design of the cable layout of a microgrid as a geometric optimization problem, which we call Microgrid Cable Layout. A key difference to the network design problems above is that there is no graph with candidate edges given. Instead, edges and new vertices may be placed anywhere in the plane. We present a hybrid genetic algorithm for Microgrid Cable Layout and evaluate it on a set of benchmark instances, which include a real microgrid in the Democratic Republic of the Congo. Finally, instead of expanding electrical networks one may place electric equipment such as FACTS (flexible AC transmission system). These influence the properties of the transmission lines such that the network can be used more efficiently. We apply a model of FACTS from the literature and study the problem whether a given network with given positions and properties of the FACTS admits an electrical flow provided that FACTS are set appropriately. We call such a flow a FACTS flow. In this thesis we prove that in general it is $\mathcal{NP}$-complete to determine whether a network admits a FACTS flow, and we present polynomial-time algorithms for two restricted cases

Exploring New Computing Paradigms for Data-Intensive Applications

L'abstract è presente nell'allegato / the abstract is in the attachmen

Local Revenue Hills: A General Equilibrium Specification with Evidence from Four U.S. Cities

We provide estimates of the impact and long-run elasticities of tax base with respect to tax rates for four large U.S. cities: Houston (property taxation), Minneapolis (property taxation), New York City (property, general sales, and income taxation), and Philadelphia (property, gross receipts, and wage taxation). Results suggest that all four of our cities are near the peaks of their longer-run revenue hills. Equilibrium effects are observed within three to four fiscal years after the initial increase in local tax rates. A significant negative impact (current period) effect of a balanced budget increase in city property tax rates on city property base is interpreted as a capitalization effect and suggests that marginal increases in city spending do not provide positive net benefits to property owners. Estimates of the effects of taxes on city employment levels for New York City and Philadelphia the two cities for which employment series are available show the local income and wage tax rates have significant negative effects on city employment levels.

Characterization and evaluation of Portuguese Opuntia spp. germplasm

The main objectives of this thesis were to characterize and evaluate Portuguese Opuntia spp. ecotypes for biomass production and the cladodes nutritional quality for fodder, and for fruit yield and quality. In addition, the genetic diversity was assessed with nuclear microsatellite (nuSSR) markers. The plant vigour and biomass production were evaluated in germplasm of O. ficus-indica by non-destructive methods, 3 years following planting. Among ecotypes, significant differences were found in the studied biomass-related parameters and several homogeneous groups were established. In the case of the cladodes nutritional profile significant, differences were found in the crude protein and the ash content, and different groups were unfolded. In general, O. ficus-indica has a low dry matter content, crude protein, and neutral detergent fiber, and high content in non-fiber carbohydrates and metabolizable energy. Fruit production was evaluated in the second and third years after plantation. Significant differences were found among O. ficus-indica ecotypes, and different groups were established. The Italian cultivars “Gialla” and “Bianca” had highest fruit yield than Portuguese ecotypes. Besides, the morphology, bioactive compounds and antioxidant properties of fruits were studied in twenty ecotypes belonging to the species O. ficus-indica, O. robusta, O. dillenii and O. elata. The fruits displayed variability in morphological and bioactive characteristics. The analysis of genetic diversity using nuSSR markers within a set of 19 ecotypes, belonging to the four previously-mentioned species, was undertaken. The hierarchical clustering analysis revealed four major groups that clearly disentangled the Opuntia spp. species. Two subclusters were found considering the O. ficus-indica ecotypes. The results revealed a low level of genetic diversity among the ecotypes of O. ficus-indica.info:eu-repo/semantics/publishedVersio

Application of digital image processing techniques to astronomical imagery 1980

Topics include: (1) polar coordinate transformations (M83); (2) multispectral ratios (M82); (3) maximum entropy restoration (M87); (4) automated computation of stellar magnitudes in nebulosity; (5) color and polarization; (6) aliasing

A review of network location theory and models

Cataloged from PDF version of article.In this study, we review the existing literature on network location problems. The study has a broad scope that includes problems featuring desirable and undesirable facilities, point facilities and extensive facilities, monopolistic and competitive markets, and single or multiple objectives. Deterministic and stochastic models as well as robust models are covered. Demand data aggregation is also discussed. More than 500 papers in this area are reviewed and critical issues, research directions, and problem extensions are emphasized.Erdoğan, Damla SelinM.S