Alien Registration- Lindestad, Gunda (Bar Harbor, Hancock County)

https://digitalmaine.com/alien_docs/17171/thumbnail.jp

Predicting Bitcoin Returns Using Artificial Neural Networks - An Application of Large Datasets to Convolutional Neural Networks and Long Short-Term Memory Based Artificial Neural Networks in Finance.

Time series forecasting is one of the foremost challenges studied in finance. In this thesis various Convolutional Neural Network and Long Short Term Memory Artificial Neural Network models are used to predict Bitcoin returns. Previous literature has explored using data from Sentiment analysis of Social Media, and Blockchain information in isolation. This thesis seeks to combine the predictive power of earlier smaller models into a larger model that better utilizes a broader category of features in time series prediction. The resulting models are able to predict Bitcoin returns well, beating out simpler methods that do not utilize Artificial Neural Networks

Climate-induced phenology shifts linked to range expansions in species with multiple reproductive cycles per year

Advances in phenology (the annual timing of species’ life-cycles) in response to climate change are generally viewed as bioindicators of climate change, but have not been considered as predictors of range expansions. Here, we show that phenology advances combine with the number of reproductive cycles per year (voltinism) to shape abundance and distribution trends in 130 species of British Lepidoptera, in response to ~0.5 °C spring-temperature warming between 1995 and 2014. Early adult emergence in warm years resulted in increased within- and between-year population growth for species with multiple reproductive cycles per year (n = 39 multivoltine species). By contrast, early emergence had neutral or negative consequences for species with a single annual reproductive cycle (n = 91 univoltine species), depending on habitat specialisation. We conclude that phenology advances facilitate polewards range expansions in species exhibiting plasticity for both phenology and voltinism, but may inhibit expansion by less flexible species

Geographic variation in life cycles : Local adaptation and ecological genetics in a temperate butterfly

Conditions in nature change with the seasons, necessitating seasonal adaptations that synchronize the life cycles of organisms with their surroundings. Such regulatory adaptations must vary between populations to track local variation in climate and seasonality; this local adaptation is facilitated by locally specific seasonal cues, but may be hampered by gene flow and genetic history.       For populations of temperate insects, two central features of adaptation to local climate are voltinism, the yearly number of generations; and diapause, the state of arrested development and suppressed metabolism in which most temperate insects spend winter. Delaying diapause allows for an additional generation to be produced within the same year, but this is only adaptive if the season is sufficiently long to safely accommodate such a life cycle. Hence, selection to express a locally adaptive voltinism should drive divergence between populations in diapause regulation and associated life history traits. In this thesis, I investigate variation in voltinism and life cycle regulation in a set of populations of the butterfly Pararge aegeria.       Population-level variation in seasonal plasticity was tested in two sets of experiments. The first (Paper I) focused on photoperiodic plasticity during the growing season, and revealed considerable differences between populations in diapause induction and developmental reaction norms. Mechanistic modeling based on the laboratory results indicated that differences in voltinism are actively maintained by these genetic differences. Next, I tested the idea that shorter diapause may help populations achieve higher voltinism through earlier emergence in the spring (Paper II). This idea was not supported; instead, populations differed in a manner that suggests that diapause duration is selected upon by the need to avoid premature development under warm autumn conditions.       The genetic background of seasonal adaptation in these populations was also explored. Phylogeographic structures inferred from genome-wide data put the results of the laboratory experiments into a historic context, and were used as the basis for a scan for genetic loci showing signs of differential selection (Paper III). The scan revealed novel variation in two circadian genes that have been shown to be linked to diapause control in P. aegeria, including a large deletion in the gene timeless. Finally, a test of two previously described circadian mutations (Paper IV) showed that, while these mutations may affect photoperiodic plasticity on a between-population level, they seemingly have no effect within a single population located at intermediate latitudes. Closer inspection revealed novel, locally unique mutations in the same genes, possibly compensating for the effect of diapause-delaying variants in a setting where an attempted second generation is not adaptive.       I have shown that voltinism variation in P. aegeria is enabled by population differences in seasonal plasticity, with population differences playing a greater role during some parts of the year than others. These results present voltinism as a complex trait resulting from plasticity acting at different levels of geographic specificity. Although much of the genetic variation enabling the observed local adaptation remains uncharacterized, the considerably variable circadian genes seen in these populations provide an intriguing target for future investigation.At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 2: Accepted. Paper 3: Manuscript. Paper 4: Manuscript.</p

Alien Registration- Lindestad, Gunda (Bar Harbor, Hancock County)

https://digitalmaine.com/alien_docs/17171/thumbnail.jp