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Phylogenetic Analysis of Pelecaniformes (Aves) Based on Osteological Data: Implications for Waterbird Phylogeny and Fossil Calibration Studies
Background: Debate regarding the monophyly and relationships of the avian order Pelecaniformes represents a classic example of discord between morphological and molecular estimates of phylogeny. This lack of consensus hampers interpretation of the group's fossil record, which has major implications for understanding patterns of character evolution (e.g., the evolution of wing-propelled diving) and temporal diversification (e.g., the origins of modern families). Relationships of the Pelecaniformes were inferred through parsimony analyses of an osteological dataset encompassing 59 taxa and 464 characters. The relationships of the Plotopteridae, an extinct family of wing-propelled divers, and several other fossil pelecaniforms (Limnofregata, Prophaethon, Lithoptila, ?Borvocarbo stoeffelensis) were also assessed. The antiquity of these taxa and their purported status as stem members of extant families makes them valuable for studies of higher-level avian diversification.Methodology/Principal Findings: Pelecaniform monophyly is not recovered, with Phaethontidae recovered as distantly related to all other pelecaniforms, which are supported as a monophyletic Steganopodes. Some anatomical partitions of the dataset possess different phylogenetic signals, and partitioned analyses reveal that these discrepancies are localized outside of Steganopodes, and primarily due to a few labile taxa. The Plotopteridae are recovered as the sister taxon to Phalacrocoracoidea, and the relationships of other fossil pelecaniforms representing key calibration points are well supported, including Limnofregata (sister taxon to Fregatidae), Prophaethon and Lithoptila (successive sister taxa to Phaethontidae), and ?Borvocarbo stoeffelensis (sister taxon to Phalacrocoracidae). These relationships are invariant when âbackboneâ constraints based on recent avian phylogenies are imposed.Conclusions/Significance: Relationships of extant pelecaniforms inferred from morphology are more congruent with molecular phylogenies than previously assumed, though notable conflicts remain. The phylogenetic position of the Plotopteridae implies that wing-propelled diving evolved independently in plotopterids and penguins, representing a remarkable case of convergent evolution. Despite robust support for the placement of fossil taxa representing key calibration points, the successive outgroup relationships of several âstem fossil + crown familyâ clades are variable and poorly supported across recent studies of avian phylogeny. Thus, the impact these fossils have on inferred patterns of temporal diversification depends heavily on the resolution of deep nodes in avian phylogeny.</p
Winonan
This issue of the Winonan was published on February 8, 2023.https://openriver.winona.edu/thewinonan2020s/1024/thumbnail.jp
A Benchmark Comparison of Visual Place Recognition Techniques for Resource-Constrained Embedded Platforms
Autonomous navigation has become a widely researched area of expertise over the past few years, gaining a massive following due to its necessity in creating a fully autonomous robotic system. Autonomous navigation is an exceedingly difficult task to accomplish in and of itself. Successful navigation relies heavily on the ability to self-localise oneself within a given environment. Without this awareness of oneâs
own location, it is impossible to successfully navigate in an autonomous manner. Since its inception Simultaneous Localization and Mapping (SLAM) has become one of the most widely researched areas of autonomous navigation. SLAM focuses on self-localization within a mapped or un-mapped environment, and constructing or updating the map of oneâs surroundings. Visual Place Recognition (VPR) is an essential part of any SLAM system. VPR relies on visual cues to determine oneâs location within a mapped environment.
This thesis presents two main topics within the field of VPR. First, this thesis presents a benchmark analysis of several popular embedded platforms when performing VPR. The presented benchmark analyses six different VPR techniques
across three different datasets, and investigates accuracy, CPU usage, memory usage, processing time and power consumption. The benchmark demonstrated a clear relationship between platform architecture and the metrics measured, with platforms of the same architecture achieving comparable accuracy and algorithm efficiency.
Additionally, the Raspberry Pi platform was noted as a standout in terms of algorithm efficiency and power consumption.
Secondly, this thesis proposes an evaluation framework intended to provide information about a VPR techniqueâs useability within a real-time application. The approach
makes use of the incoming frame rate of an image stream and the VPR frame rate, the rate at which the technique can perform VPR, to determine how efficient VPR techniques would be in a real-time environment. This evaluation framework determined that CoHOG would be the most effective algorithm to be deployed in a real-time environment as it had the best ratio between computation time and accuracy
Numerical investigation of shock-induced bubble collapse dynamics and fluidâsolid interactions during shock-wave lithotripsy
© 2023 Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND licence. https://creativecommons.org/licenses/by-nc-nd/4.0/In this paper we investigate the bubble collapse dynamics under shock-induced loading near soft and rigid bio-materials, during shock wave lithotripsy. A novel numerical framework was developed, that employs a Diffuse Interface Method (DIM) accounting for the interaction across fluidâsolid-gas interfaces. For the resolution of the extended variety of length scales, due to the dynamic and fine interfacial structures, an Adaptive Mesh Refinement (AMR) framework for unstructured grids was incorporated. This multi-material multi-scale approach aims to reduce the numerical diffusion and preserve sharp interfaces. The presented numerical framework is validated for cases of bubble dynamics, under high and low ambient pressure ratios, shock-induced collapses, and wave transmission problems across a fluidâsolid interface, against theoretical and numerical results. Three different configurations of shock-induced collapse applications near a kidney stone and soft tissue have been simulated for different stand-off distances and bubble attachment configurations. The obtained results reveal the detailed collapse dynamics, jet formation, solid deformation, rebound, primary and secondary shock wave emissions, and secondary collapse that govern the near-solid collapse and penetration mechanisms. Significant correlations of the problem configuration to the overall collapse mechanisms were found, stemming from the contact angle/attachment of the bubble and from the properties of solid material. In general, bubbles with their center closer to the kidney stone surface produce more violent collapses. For the soft tissue, the bubble movement prior to the collapse is of great importance as new structures can emerge which can trap the liquid jet into induced crevices. Finally, the tissue penetration is examined for these cases and a novel tension-driven tissue injury mechanism is elucidated, emanating from the complex interaction of the bubble/tissue interaction during the secondary collapse phase of an entrapped bubble in an induced crevice with the liquid jet.Peer reviewe
Canada\u27s Evergreen Playground: A History of Snow in Vancouver
The City of Vancouver is not as snowy as the rest of Canada; rain, not snow, is its defining weather feature. But snow is a common seasonal occurrence, having fallen there nearly every winter since the 1850s. This dissertation places snow at the centre of the City of Vancouverâs history. It demonstrates how cultural and natural factors influenced human experiences and relationships with snow on the coast between the 1850s and 2000s. Following Vancouverâs incorporation, commercial and civic boosters constructed â and settlers adopted â what I call an evergreen mentality. Snow was reconceptualized as a rare and infrequent phenomenon. The evergreen mentality was not completely false, but it was not entirely true, either. This mindset has framed human relationships with snow in Vancouver ever since. While this idea was consistent, how coastal residents experienced snow evolved in response to societal developments (such as the rise of the automobile and the adoption of new snow-clearing technologies) and regional climate change.
I show that the history of snow in Vancouver cannot be fully understood without incorporating the southern Coast Mountains. Snow was a connecting force between the coastal metropolis and mountainous hinterland. Settlers drew snowmelt to the urban environment for its energy potential and life-sustaining properties; snow drew settlers to the mountains for recreation and economic opportunities. Mountain snow became a valuable resource for coastal residents throughout the twentieth century. Human relationships with snow in the mountains were shaped, as they were in the city, by seasonal expectations, societal circumstances, and shifting climate conditions.
In charting a history of snow in Vancouver and the southern Coast Mountains, this dissertation clears a new path in Canadian environmental historiography by bringing snow to the historiographical forefront. It does so in an urban space not known for snow, broadening the existing geography of snow historiography. In uncovering snowâs impact on year-round activities, this work also expands the fieldâs temporal boundaries. Through this work, one sees how snow helped to make Canadaâs Evergreen Playground
Design of decorative 3D models: from geodesic ornaments to tangible assemblies
L'obiettivo di questa tesi Ăš sviluppare strumenti utili per creare opere d'arte decorative digitali in 3D. Uno dei processi decorativi piĂč comunemente usati prevede la creazione di pattern decorativi, al fine di abbellire gli oggetti. Questi pattern possono essere dipinti sull'oggetto di base o realizzati con l'applicazione di piccoli elementi decorativi. Tuttavia, la loro realizzazione nei media digitali non Ăš banale. Da un lato, gli utenti esperti possono eseguire manualmente la pittura delle texture o scolpire ogni decorazione, ma questo processo puĂČ richiedere ore per produrre un singolo pezzo e deve essere ripetuto da zero per ogni modello da decorare. D'altra parte, gli approcci automatici allo stato dell'arte si basano sull'approssimazione di questi processi con texturing basato su esempi o texturing procedurale, o con sistemi di riproiezione 3D. Tuttavia, questi approcci possono introdurre importanti limiti nei modelli utilizzabili e nella qualitĂ dei risultati. Il nostro lavoro sfrutta invece i recenti progressi e miglioramenti delle prestazioni nel campo dell'elaborazione geometrica per creare modelli decorativi direttamente sulle superfici. Presentiamo una pipeline per i pattern 2D e una per quelli 3D, e dimostriamo come ognuna di esse possa ricreare una vasta gamma di risultati con minime modifiche dei parametri. Inoltre, studiamo la possibilitĂ di creare modelli decorativi tangibili. I pattern 3D generati possono essere stampati in 3D e applicati a oggetti realmente esistenti precedentemente scansionati. Discutiamo anche la creazione di modelli con mattoncini da costruzione, e la possibilitĂ di mescolare mattoncini standard e mattoncini custom stampati in 3D. CiĂČ consente una rappresentazione precisa indipendentemente da quanto la voxelizzazione sia approssimativa. I principali contributi di questa tesi sono l'implementazione di due diverse pipeline decorative, un approccio euristico alla costruzione con mattoncini e un dataset per testare quest'ultimo.The aim of this thesis is to develop effective tools to create digital decorative 3D artworks. Real-world art often involves the use of decorative patterns to enrich objects. These patterns can be painted on the base or might be realized with the application of small decorative elements. However, their creation in digital media is not trivial. On the one hand, users can manually perform texture paint or sculpt each decoration, in a process that can take hours to produce a single piece and needs to be repeated from the ground up for every model that needs to be decorated. On the other hand, automatic approaches in state of the art rely on approximating these processes with procedural or by-example texturing or with 3D reprojection. However, these approaches can introduce significant limitations in the models that can be used and in the quality of the results. Instead, our work exploits the recent advances and performance improvements in the geometry processing field to create decorative patterns directly on surfaces. We present a pipeline for 2D and one for 3D patterns and demonstrate how each of them can recreate a variety of results with minimal tweaking of the parameters. Furthermore, we investigate the possibility of creating decorative tangible models. The 3D patterns we generate can be 3D printed and applied to previously scanned real-world objects. We also discuss the creation of models with standard building bricks and the possibility of mixing standard and custom 3D-printed bricks. This allows for a precise representation regardless of the coarseness of the voxelization. The main contributions of this thesis are the implementation of two different decorative pipelines, a heuristic approach to brick construction, and a dataset to test the latter
Annual Climate Report 2023
According to the Climate Act, the Government submits the Annual Climate Report to Parliament every year. The Report examines the trends in emissions and sinks, sufficiency of the planned measures to achieve the emission reduction targets, need for further measures, and implementation of the targets and measures of the Medium-term Climate Plan and Climate Plan for the Land Use Sector. The sufficiency and implementation of measures in the National Adaption Plan are also discussed.
Total emissions without the land use sector decreased in 2022 compared to 2021. Emissions from the emissions trading sector decreased clearly from the previous year. Emissions from the effort-sharing sector decreased as well, and they were within Finlandâs annual emission allocations in 2021 and 2022.
The land use sector was a small net sink in 2022. The fact that the sector turned from a source of net emissions in 2021 to a net sink is due the smaller felling volume in 2022. Net emissions, i.e. emissions and sinks from all sectors combined (including the land use sector), decreased in 2022 compared to the previous year.
The pace of emission reductions is in line with the emission reduction target for 2030 set in the Climate Act. If no further measures are taken in the land use sector, Finland is not likely to achieve the EU commitments under the LULUCF Regulation without buying emission credits from other Member States. Achieving the national climate neutrality target requires further measures in the land use sector and other sectors
Beam scanning by liquid-crystal biasing in a modified SIW structure
A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium
Synthetic Aperture Radar (SAR) Meets Deep Learning
This reprint focuses on the application of the combination of synthetic aperture radars and depth learning technology. It aims to further promote the development of SAR image intelligent interpretation technology. A synthetic aperture radar (SAR) is an important active microwave imaging sensor, whose all-day and all-weather working capacity give it an important place in the remote sensing community. Since the United States launched the first SAR satellite, SAR has received much attention in the remote sensing community, e.g., in geological exploration, topographic mapping, disaster forecast, and traffic monitoring. It is valuable and meaningful, therefore, to study SAR-based remote sensing applications. In recent years, deep learning represented by convolution neural networks has promoted significant progress in the computer vision community, e.g., in face recognition, the driverless field and Internet of things (IoT). Deep learning can enable computational models with multiple processing layers to learn data representations with multiple-level abstractions. This can greatly improve the performance of various applications. This reprint provides a platform for researchers to handle the above significant challenges and present their innovative and cutting-edge research results when applying deep learning to SAR in various manuscript types, e.g., articles, letters, reviews and technical reports
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