Rediscovery of Cicindela scabrosa floridana Cartwright (Coleoptera: Cicindelidae) and its elevation to species level

First discovered in 1934 and described as a variety of Cicindela abdominalis Fabricius (Coleoptera: Cicindelidae), the form floridana, to our knowledge, has not been recollected until we discovered it in 2007, south of the presumed type locality. From our examination of the type specimen, eight paratypes and 40 specimens from the new locality and additional study, we reinterpreted its status to be a full species. This interpretation is based on distinctive and consistent differences from the closely related Cicindelidia scabrosa (Schaupp). These differences include morphology (maculation, color and elytral microsculpture), distribution, habitat, and seasonality. We present here a more detailed description of this species within the genus Cicindelidia Rivalier, following Rivalier and Wiesner becoming Cicindelidia floridana (Cartwright) new combination

Agroforestry and ritual at the ancient Maya center of Lamanai

Paleoethnobotanical data retrieved from caches of Late Classic to Early Postclassic origin at the ancient Maya site of Lamanai, Belize, revealed carbonized maize kernels, cob fragments, common beans, coyol endocarps, and an abundance of wood charcoal, from both conifer and hardwood tree species. Pinus caribaea (Caribbean pine) was the most ubiquitous species in the Late and Terminal Classic sample set and the weight of Lamanai pine wood charcoal was more than the combined weight of all known archaeobotanical collections from nearby contemporaneous sites. Pollen data from northwestern Belize showed that the pine pollen signature declined during the Late Classic period, a trajectory in keeping with intensive exploitation of the nearby pine savannas as suggested by the contents of Lamanai caches examined in this study. Although Lamanai flourished far into the Postclassic period, pine charcoal use—based on present evidence—declined in Early Postclassic ritual contexts. Concomitantly, an increase in the local pine pollen rain indicated that pine timber stocks rebounded during the Postclassic period. The observed intensive use of pine at Late Classic Lamanai combined with a concurrent decline in the regional pine pollen signature is consistent with a hypothesis of over-exploitation of pine during the Late to Terminal Classic period

Chloride Ingress Determination in Offshore Concrete Structures Using µ-XRF

Formålet med denne masteroppgaven var å se nærmere på µ-XRF som målemetode for kloridinntrenging i offshore betongkonstruksjoner. For å evaluere bruk av µ-XRF til dette formålet, ble den sammenlignet med to andre analysemetoder: ICP-MS og potensiometrisk titrering. µ-XRF ble så benyttet for å evaluere kloridinntrengingen i to offshore betongkonstuksjoner. 15 betongkjerner ble sendt fra vår industripartner, Equinor. Disse ble hentet fra to ulike offshore betongkonstruksjoner, «Structure A» og «Structure C», begge med over 30 års operasjonstid. Selve oljeriggen hviler på betongskaft som går ned til havbunnen. Fra «Structure A» ble tre kjerner tatt fra utsiden av sjøvannsskaftet over havnivå, samt fire kjerner fra innsiden av utstyrsskaftet. For «Structure C» ble alle de åtte kjernene hentet fra innsiden av utstyrsskaftet. Alle de syv kjernene fra «Structure A» ble analysert ved bruk av alle tre metodene, mens kjernene fra «Structure C» kun ble analysert ved bruk av µ-XRF. Målemetodene ble sammenlignet ved at kloridinnholdet i de syv betongkjernene fra «Structure A» ble bestemt. Kjernene ble saget i to, hvor den ene halvdelen ble brukt til µ-XRF mens den andre ble brukt til ICP-MS og titrering. Kloridinnholdet ble så bestemt ved bruk av de respektive analysemetodene og det ble laget kloridprofiler som var grunnlaget for sammenligningen. Nøyaktigheten, sammen med andre aspekter som kompleksitet, effektivitet og allsidighet, ble så vurdert. Resultatene indikerte at µ-XRF hadde betraktelig lavere nøyaktighet enn de andre metodene for bestemmelse av kloridinnhold. Kloridinntrengningsdybden målt med µ-XRF derimot, vurdert mot et kritisk kloridnivå, Clcrit = 0.07% Cl/betong [g/g], viste seg å kunne bestemmes med en usikkerhet på under ±2 mm for samtlige betongkjerner. Det ble på bakgrunn av dette, konkludert med at nøyaktigheten av kloridinntrengningsdybden var tilstrekkelig ved bruk av µ-XRF. I tillegg, viste den seg å være svært konkurransedyktig på flere av de andre vurderte aspektene. Til slutt ble kloridinntrengningsdybden i samtlige betongkjerner bestemt med bruk av µ-XRF. Vurdert mot et kritisk kloridnivå, Clcrit = 0.07% Cl/betong [g/g], varierte dybden mellom 3 mm og 29 mm i «Structure A» og mellom 0 mm og 34 mm i «Structure C». I «Structure A» finner vi den største inntrengningsdybden i skvalpesonen på utsiden av utstyrsskaftet, mens i «Structure C» finner vi den største inntrengningsdybden på innsiden av utstyrsskaftet, i et område regelmessig eksponert for sjøvann. Siden den tilsiktede betongoverdekningen er 60±10 mm i begge konstruksjonene, er det ingen mistanke om kloridindusert armeringskorrosjon i de undersøkte områdene. Den 270 mm lange betongkjernen som ble hentet fra innsiden av «Structure C» på 201 meters dyp, viste ingen synlige tegn på massetransport fra utsiden av den 1.2 m tykke veggen. Det ble derfor konkludert med at det hydrauliske trykket ikke er en dominerende transportmekanisme i en så tett betong, selv ved et slikt dyp.The purpose of this Master Thesis was to look deeper into chloride ingress determination for offshore concrete structures using µ-XRF. An evaluation of the use of µ-XRF for this purpose was performed through a comparison with two other methods of analysis: potentiometric titration and ICP-MS. µ-XRF was then used to evaluate the chloride ingress in two offshore concrete structures. A total of 15 concrete cores were received from our industrial partner, Equinor. The cores were collected from two different offshore concrete structures, Structure A and Structure C, both with over 30 years of operation. The oil rigs rest on top of concrete shafts which continue all the way down to the seabed. In Structure A, three cores were collected from the outside of the unsubmerged part of the seawater shaft, and four cores from the inside of the utility shaft. For Structure C all eight cores were collected from the inside of the utility shaft, at elevations ranging between 13 m above to 201 m below sea level. All seven cores from Structure A were analysed using all three methods for the following comparison, while the eight cores obtained from Structure C were analysed solely using µ-XRF. The comparison was performed by determining chloride content in the seven concrete cores from Structure A. The cores were sawn in two, where one half was used in the µ-XRF and the other was profile ground and used for both potentiometric titration and ICP-MS. The chloride content obtained from all three methods was used to generate chloride profiles which were used for comparison. Accuracy, in addition to other aspects such as complexity, efficiency, and versatility of the different methods, were considered. The µ-XRF was found to be significantly less accurate for chloride concentration determination than the other methods of analysis. However, the µ-XRF was able to determine the depth at which the chloride concentration had reached below Clcrit = 0.07% Cl/concrete [g/g], with an uncertainty of less than ±2 mm for all concrete cores. Based on this, the accuracy regarding chloride ingress depth measurements with µ-XRF was considered adequate. In addition, µ-XRF surpassed the other methods on several of the other comparison aspects. Finally, the chloride ingress depth in all of the concrete cores was determined using µ-XRF. Using a critical chloride content of Clcrit = 0.07% Cl/concrete [g/g], we found the chloride ingress in Structure A to range from 3 mm to 29 mm. While for Structure C the range was 0 mm to 34 mm. For Structure A the deepest ingress is found in a core collected from the splash zone on the seawater shaft. While for Structure C the deepest ingress was found in a core collected from the inside of the utility shaft, in an area regularly exposed to seawater. As the cover depth of both structures is 60±10 mm, there is no reason to suspect chloride-induced reinforcement corrosion in the investigated areas. The 270 mm long concrete core collected from the inside of Structure C, at a depth of 201 m below sea level, showed no detectable signs of mass transport coming from the outside of the 1.2 m thick wall. This led to a conclusion that the hydraulic pressure is not a dominating transport mechanism for such a dense concrete, even at this depth

Tilrettelegging for minoritetsspråklege elevar si språkutvikling: ein studie av småtrinnslærarars erfaringar

Master i grunnskolelærerutdanning 1-7. Norsk 4 - 202

Rediscovery of \u3ci\u3eCicindela scabrosa floridana\u3c/i\u3e Cartwright (Coleoptera: Cicindelidae) and its elevation to species level

First discovered in 1934 and described as a variety of Cicindela abdominalis Fabricius (Coleoptera: Cicindelidae), the form floridana, to our knowledge, has not been recollected until we discovered it in 2007, south of the presumed type locality. From our examination of the type specimen, eight paratypes and 40 specimens from the new locality and additional study, we reinterpreted its status to be a full species. This interpretation is based on distinctive and consistent differences from the closely related Cicindelidia scabrosa (Schaupp). These differences include morphology (maculation, color and elytral microsculpture), distribution, habitat, and seasonality. We present here a more detailed description of this species within the genus Cicindelidia Rivalier, following Rivalier and Wiesner becoming Cicindelidia floridana (Cartwright) new combination

Rediscovery of \u3ci\u3eCicindela scabrosa floridana\u3c/i\u3e Cartwright (Coleoptera: Cicindelidae) and its elevation to species level

First discovered in 1934 and described as a variety of Cicindela abdominalis Fabricius (Coleoptera: Cicindelidae), the form floridana, to our knowledge, has not been recollected until we discovered it in 2007, south of the presumed type locality. From our examination of the type specimen, eight paratypes and 40 specimens from the new locality and additional study, we reinterpreted its status to be a full species. This interpretation is based on distinctive and consistent differences from the closely related Cicindelidia scabrosa (Schaupp). These differences include morphology (maculation, color and elytral microsculpture), distribution, habitat, and seasonality. We present here a more detailed description of this species within the genus Cicindelidia Rivalier, following Rivalier and Wiesner becoming Cicindelidia floridana (Cartwright) new combination

Prediksjon av strømpriser i Trondheim ved bruk av maskinlæring og statistisk modellering

Formålet med denne oppgaven er å bruke modeller for sekvensiell data til å utføre prediksjoner av norske strømpriser. Ved å ta en grundig undersøkelse av det nordiske energimarkedet får vi et innblikk i relevante faktorer som er med på å påvirke de norske strømprisene. Datasettet som benyttes er bestående av forklaringsvariabler som anses som relevante for fluktuasjonene i kraftmarkedet. Det innebærer meteorologiske faktorer, energiutveksling og makroøkonomiske forhold. Den avhengige variabelen, som representerer fenomenet vi ønsker å prognostisere, er gjennomsnittlig daglig spotpris for prisområdet NO3 - Trøndelag de siste seks årene. For å predikere strømprisen i Trøndelag har vi utviklet tre modeller som følger en statistikk tilnærming, samt to modeller ved hjelp av kunstige nevrale nettverk. Den statistiske tilnærmingen består av tre ulike ARIMA modeller, der vi gradvis har inkludert eksogene variabler og sesongmessige svingninger i modelleringen. De kunstige nevrale nettverkene er basert på LSTM nettverk, der antall dager inkludert i predikeringen skiller de to ulike versjonene. Våre undersøkelser har vist at ingen av modellene presenterer nøyaktige og tilfredsstillende prediksjoner, da samtlige modeller viser begrenset evne til å fange opp de sentrale nyansene i datasettet. Dette påvirkes trolig av lav korrelasjon med forklaringsvariabler vi har identifisert, samt store svingninger i prisene de siste årene. Den fullverdige SARMAX er av høyest kvalitet blant de statistiske modellene. Blant maskinlæringsmodellene er det LSTM modellen som kun inkluderer data fra foregående dag som presterer best. Gjennom en visuell analyse av resultatene, observerer vi at dyplæringsmodellen i større fanger opp variasjonen i svingningene. På den andre siden presterer de statistiske modellene bedre basert på bruk av vurderingsverktøy.The purpose of this thesis is to utilize models for sequential data to forecast Norwegian electricity prices. Through a comprehensive examination of the nordic power market, we got an insight of relevant factors which influence the Norwegian electricity prices. The dataset used consists of explanatory variables deemed relevant for the fluctuations in the power market. That implies meteorological factors, energy exchange and macroeconomic conditions. The dependent variable, which represents the phenomenon we aim to forecast, is the average daily spot price for the price area NO3 - Trøndelag for the last six years. We have developed three models with a statistical approach, as well as two models by artificial neural network. The statistical approach consists of three ARIMA models, where we have gradually included exogenous variables and seasonality in the modeling. The artificial neural networks are built as LSTM networks, where the amount of days included in the predictions distinguish the different versions from each other. Our examinations have shown that neither of the models presents accurate and satisfactory predictions, as all models demonstrate limited capability to capture central nuances in the dataset. This is probably due to low correlation with the influence factors we have identified, as well as large fluctuations in price the last couple years. The SARMAX is of the highest quality among the statistical models. The LSTM model which only includes data from the previous day performs the best amid the machine learning models. Through a visual analysis of the results, we observe that the deep learning model more efficiently captures the variation in the fluctuations. Nevertheless, the statistical models perform better based on use of assessment tools

Pilot’s Evaluation of the Usefulness of Full Mission IFR Simulator Flights for General Aviation Pilot Training

Professional pilots, including flight instructors, who had participated in multiple session line-oriented flight training (LOFT) Instrument Flight Rules (IFR) simulator flights differing in task difficulty evaluated the value of such flights for the training of general aviation pilots. These flights, which employed a relatively low cost simulator (Frasca 141), were judged to be quite useful for instrument student flight training, for instrument rated pilots with moderate instrument experience, and for experienced pilots. The aspects of flight that were seen as receiving the greatest benefit from the flight scenarios were practicing responses to problem situations, attitude instrument flying, practicing instrument approaches under varying weather conditions, and navigation and communications for student pilots. In contrast, the simulator was not seen as useful for Visual Flight Rules (VFR) recurrent training