cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
Saussurea alpina DC.
Creators: name: Info Flora
Publisher: name: Zenodo
Year: 2021
Subjects: Biodiversity
Taxonomy
Plantae
Tracheophyta
Magnoliopsida
Asterales
Asteraceae
Saussurea
Saussurea alpina

description: Saussurea alpina (L.) DC.
Echte Alpenscharte
Art ISFS: 371050 Checklist: 1041510 Asteraceae Saussurea Saussurea alpina (L.) DC. Enthält: Saussurea alpina (L.) DC. subsp. alpina Saussurea alpina subsp. depressa (Gren.) Nyman
Bestimmungsschlüssel
Zusammenfassung
Artbeschreibung (nach Lauber & al. 2018): 2-15(-30) cm hoch, dicht beblättert. Blätter lanzettlich, ganzrandig oder mit einzelnen Zähnen, meist allmählich in den Stiel verschmälert. Blütenköpfe 1,5- 2 cm lang, mit spinnwebiger Hülle, zu 3-8 in einem dichten, kopfigen Gesamtblütenstand. Alle Blüten röhrenförmig, violett. Früchte 4-5 mm lang, mit 10-12 mm langen, federigen Pappusborsten.
Status
Status IUCN: Nicht gefährdet
Ökologie
Lebensraum Lebensraumnach Delarze & al. 2015
KEINE ANGABE
Ökologische Zeigerwerte nach Landolt & al. (2010)
BodenfaktorenKlimafaktorenSalztoleranzFeuchtezahl F--Lichtzahl L--Salzzeichen--Reaktionszahl R--Temperaturzahl T--Nährstoffzahl N--Kontinentalitätszahl K--
Nomenklatur
Gültiger Name (Checklist 2017):Saussurea alpina(L.) DC.
Volksname Deutscher Name: Echte Alpenscharte Nom français: Saussurée des Alpes Nome italiano: Saussurea delle Alpi
Übereinstimmung mit anderen Referenzwerken
RelationNomReferenzwerkeNo=Saussurea alpina (L.) DC.Checklist 2017371050=Saussurea alpina (L.) DC.Flora Helvetica 20182195-2196=Saussurea alpina (L.) DC. s.l.SISF/ISFS 2371050
= Taxon stimmt mit akzeptiertem Taxon überein (Checklist 2017)  Taxon enthält (neben anderen) auch das akzeptierte Taxon (Checklist 2017)
Kommentare aus der Checklist 2017 Wegfall des Ausdrucks s.l.: Die Art wurde bisher als "sensu lato" (s.l.) gekennzeichnet. Da die früher gleichlautende "sensu stricto-Art" (s.str.) in eine Unterart umbenannt wurde, erübrigt sich die Kennzeichnung s.l. Checklist
Status Indigenat: Indigen
Liste der gefährdeten Pflanzen IUCN(nach Walter & Gillett 1997): Nein
Status Rote Liste national 2016
Status IUCN: Nicht gefährdet
Zusätzliche InformationenKriterien IUCN: --
Status Rote Liste regional 2019
Biogeografische RegionenStatusKriterien IUCNJura (JU)--Mittelland (MP)--Alpennordflanke (NA)nicht gefährdet (Least Concern)Alpensüdflanke (SA)potenziell gefährdet (Near Threatened)B2a; D2Östliche Zentralalpen (EA)nicht gefährdet (Least Concern)Westliche Zentralalpen (WA)nicht gefährdet (Least Concern)
Status nationale Priorität /Verantwortung
Keine nationale Priorität oder internationale Verantwortung
Schutzstatus
International (Berner Konvention)NeinGLVollständig geschützt(07.05.2006)
Schweiz--
description: Published as part of Info Flora, 2021,
Structural and thermodynamics properties of pure phase alkanes, monoamides and alkane/monoamide mixtures with an ab initio based force-field model
Creators: name: Failali, Abdelmounaim
name: Acher, Eléonor
name: Guillaumont, Dominique
name: Vallet, Valérie
name: Réal, Florent
Publisher: name: arXiv
Year: 2021
Subjects: subject: Chemical Physics (physics.chem-ph)
subject: FOS: Physical sciences

description: A polarizable force-field (FF) model for short- and long-alkane chains and amide derivatives was constructed based solely on accurate quantum chemical (QC) calculations. First, the FF model accuracy was accessed by performing molecular dynamics (MD) simulations to calculate liquid-phase thermodynamic and structural properties for alkanes, for which experimental data are available. Second, The FF was then used to perform molecular dynamics simulations to calculate thermodynamic, structural and excess properties of monoamide/dodecane mixtures, namely DEHiBA/dodecane and DEHBA/dodecane. Aggregation phenomena appear for both types of mixtures and monoamide pure phases. A detailed structural analysis revealed, at small monoamide mole fraction the formation of dimers, while trimerization at larger monoamide concentrations and in their pure phases. Analysis of the relative orientation of the dimers have also been performed and showed a small difference for both phases.
description: 15 pages, 11 figures
Carbon Dynamics across Contrasting Temperate Agroecosystems: Soil Organic Matter Pools, Mycorrhizae, Water Use-efficiency, Methane and Carbon Dioxide Fluxes
Creators: Kim, Keunbae
Publisher: name: University of Alberta Library
Year: 2022

Perennial grain crops have been proposed as a sustainable alternative to conventional annual grain crops, since they potentially hold multiple desirable features including increased soil C sequestration and biodiversity, mitigation of greenhouse gases (GHGs), and reduction of water loss and others. These attributes are accomplished by their no-tillage management, longer growing season, and pervasive root systems. Nonetheless, the ramifications of implementing novel perennial grain cropping systems to the atmosphere, lithosphere, and biosphere remains elusive. In this research, comprehensive comparisons were made to enhance current understanding of how annual versus perennial grain cropping differ in soil organic matter (SOM) pools, GHGs emissions, and mycorrhizae (i.e., AMF). Five contrasting cropping systems —fallow, annual-grain, biennial-grain, perennial-grain, and perennial-forage — were compared with and without N fertilizer addition. A randomized complete block design consisting of four replicates was initiated at sites located in Edmonton and Breton, Alberta, Canada. In addition to the replicate plots, two adjacent 4-ha fields, including annual vs. perennial grain crops, were set up for eddy covariance measurements at the Breton site. By doing so, it was expected that they address a limitation of the chamber measurements with respect to instantaneous and heterogeneous capture, as well as evapotranspiration (ET) comparison. As a result of SOC fractionation, perennial grain crops increased soil C concentration in both transitory and stable pools compared with annual grain compartments, although overall soil C sequestration occurred as a function of N fertilizer, cropping systems, and underlying soil texture. Moreover, substantial CH4 and CO2 uptake were observed in perennial grain cropping system compared with annual grain crops likely due to a shift to favorable GHGs sink conditions such as aeration-moisture balance, photosynthetic activity, and microbial decomposition. However, overall cumulative ET and associated ecosystem-water use efficiency were similar with between the two cropping systems. Lastly, arbuscular mycorrhizal fungi (AMF) community compositions between annual and perennial grain cropping systems exhibited no significant difference, likely due to the genetic similarity of two crops. In addition, the two contrasting study sites had different patterns of AMF alpha and beta diversity, which may be a result of differing inherent soil properties and management legacy effect across field sites. In sum, AMF communities appear to be impervious to annual vs perennial grain crops, rather their most pronounced difference are field site specific. In sum, my research has been conducted for an overall assessment of whether perennial grain crops play a multifunctional role in agroecosystems toward better sustainability.
Sample-Efficient Control with Directed Exploration in Discounted MDPs Under Linear Function Approximation
Creators: Kumaraswamy, Raksha K
Publisher: name: University of Alberta Library
Year: 2022

An important goal of online reinforcement learning algorithms is efficient data collection to learn near-optimal behaviour, that is, optimizing the exploration-exploitation trade-off to reduce the sample-complexity of learning. To improve sample-complexity of learning it is essential that the agent directs its exploratory behaviour towards either visiting unvisited parts of the environment, or reducing uncertainty it may have with respect to the visited parts. In addition to such directed exploration, sample-complexity of learning can be improved by using a representation space that is amenable to online reinforcement learning. This thesis presents several algorithms that focus on these avenues for improving the sample-complexity of online reinforcement learning, specifically in the setting of discounted MDPs under linear function approximation.

A key challenge to direct effective online exploration is the learning of reliable uncertainty estimates. We address this by deriving high-probability confidence-bounds for value uncertainty estimation. We use these derived confidence-bounds to design two algorithms that direct effective online exploration; they differ mainly in their approach to directing ex- ploration for visiting unknown regions of the environment. In the first algorithm we propose a heuristic to do so, whereas the second algorithm uses a more principled strategy based on optimistic initialization. The second algorithm is also a planning-compatible algorithm that can be parallelized, scaling sample-efficiency benefits with the compute resources afforded to the algorithm.

To improve sample-efficiency by utilizing representations that are amenable to online reinforcement learning, the thesis proposes a simple strategy for learning such representations offline. The representation learning algorithm encodes a property we call locality. Locality reduces interference in learning targets used by online reinforcement learning algorithms, consequently improving its sample-efficiency. The thesis shows that these learned representations also aid effective online exploration.

Overall, this thesis proposes algorithms for improving sample-efficiency of online reinforcement learning, motivates their utility, and evaluates their benefits empirically.
Implementation of a Binary Neural Network on a Passive Array of Magnetic Tunnel Junctions
Creators: name: Goodwill, Jonathan M.
name: Prasad, Nitin
name: Hoskins, Brian D.
name: Daniels, Matthew W.
name: Madhavan, Advait
name: Wan, Lei
name: Santos, Tiffany S.
name: Tran, Michael
name: Katine, Jordan A.
name: Braganca, Patrick M.
name: Stiles, Mark D.
name: McClelland, Jabez J.
Publisher: name: arXiv
Year: 2021
Subjects: subject: Emerging Technologies (cs.ET)
subject: Disordered Systems and Neural Networks (cond-mat.dis-nn)
subject: Materials Science (cond-mat.mtrl-sci)
subject: Machine Learning (cs.LG)
subject: Applied Physics (physics.app-ph)
subject: FOS: Computer and information sciences
subject: FOS: Physical sciences

description: The increasing scale of neural networks and their growing application space have produced demand for more energy- and memory-efficient artificial-intelligence-specific hardware. Avenues to mitigate the main issue, the von Neumann bottleneck, include in-memory and near-memory architectures, as well as algorithmic approaches. Here we leverage the low-power and the inherently binary operation of magnetic tunnel junctions (MTJs) to demonstrate neural network hardware inference based on passive arrays of MTJs. In general, transferring a trained network model to hardware for inference is confronted by degradation in performance due to device-to-device variations, write errors, parasitic resistance, and nonidealities in the substrate. To quantify the effect of these hardware realities, we benchmark 300 unique weight matrix solutions of a 2-layer perceptron to classify the Wine dataset for both classification accuracy and write fidelity. Despite device imperfections, we achieve software-equivalent accuracy of up to 95.3 % with proper tuning of network parameters in 15 x 15 MTJ arrays having a range of device sizes. The success of this tuning process shows that new metrics are needed to characterize the performance and quality of networks reproduced in mixed signal hardware.
description: 22 pages plus 8 pages supplemental material; 7 figures plus 7 supplemental figures
Reinforcement learning framework for window hardware installation
Creators: Huang, Tzu-Hao
Publisher: name: University of Alberta Library
Year: 2022

The repetitiveness and precision of manufacturing tasks has increased the need for robots in the automation of the manufacturing industry; however, the complex and varied nature of manufacturing production lines poses challenges in terms of applying the rule-based automation approach. This has contributed to the trend of employing artificial intelligence-driven robotic systems. Previous applications relied on accomplishing a single automated task with its specifically designed AI model, and thus failed to provide a scalable AI solution that could accomplish a variety of tasks. In the present case study, window hardware installation was simulated with a reinforcement learning solution using the soft actor critic algorithm to improve model learning efficiency and scalability. Agent training techniques, such as rewarding shaping and curriculum training, were introduced into the model’s learning configuration. The proposed curriculum guided reinforcement learning structure provides the training agent a gradual and effective way to comprehend assigned tasks. The proposed approach further increases the potential for artificial intelligence-driven robotic hardware installation systems to be more sensitive and flexible to environment change and target hardware variations with the implementation of training guidelines. The model’s performance is demonstrated by refined self- driven motion planning and hardware sensitive decision-making. This application indicates that a robust and scalable artificial intelligence model can be realized by thoughtful agent incentives and learning pathways, and the case study demonstrates the framework required to facilitate such a possibility.
Quantum Imaging of Magnetic Phase Transitions and Spin Fluctuations in Intrinsic Magnetic Topological Nanoflakes
Creators: name: McLaughlin, Nathan J.
name: Hu, Chaowei
name: Huang, Mengqi
name: Zhang, Shu
name: Lu, Hanyi
name: Wang, Hailong
name: Tserkovnyak, Yaroslav
name: Ni, Ni
name: Du, Chunhui Rita
Publisher: name: arXiv
Year: 2021
Subjects: subject: Materials Science (cond-mat.mtrl-sci)
subject: Mesoscale and Nanoscale Physics (cond-mat.mes-hall)
subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences

description: Topological materials featuring exotic band structures, unconventional current flow patterns, and emergent organizing principles offer attractive platforms for the development of next-generation transformative quantum electronic technologies. The family of MnBi2Te4 (Bi2Te3)n materials is naturally relevant in this context due to their nontrivial band topology, tunable magnetism, and recently discovered extraordinary quantum transport behaviors. Despite numerous pioneering studies, to date, the local magnetic properties of MnBi2Te4 (Bi2Te3)n remain an open question, hindering a comprehensive understanding of their fundamental material properties. Exploiting nitrogen-vacancy (NV) centers in diamond, we report nanoscale quantum imaging of magnetic phase transitions and spin fluctuations in exfoliated MnBi2Te4 (Bi2Te3)n flakes, revealing the underlying spin transport physics and magnetic domains at the nanoscale. Our results highlight the unique advantage of NV centers in exploring the magnetic properties of emergent quantum materials, opening new opportunities for investigating the interplay between topology and magnetism.
description: 19 pages, 6 figures
Spectral Efficient Non-orthogonal Radio Designs For Future Wireless Networks
Creators: Mohammadian, Amirhossein
Publisher: name: University of Alberta Library
Year: 2022

The fifth-generation (5G) and beyond wireless networks aim to increase the current data rates to more than 10 Gbit/s. Thus,  the spectrum crunch necessitates increasing spectral efficiency (SE).  Key non-orthogonal technologies for this goal are   (I) full-duplex wireless, (II) generalized frequency division multiplexing (GFDM), (III) cognitive radio.    Non-orthogonal subcarriers instead of orthogonal subcarriers are the basis of  GFDM.   All these technologies exploit non-orthogonal designs in exchange for a favorable tradeoff between interference and improved SE. However,   interference can also increase with radio frequency (RF) impairments. Thus, this research's primary goal is to investigate the interplay among non-orthogonal designs, SE improvement, and     RF impairments. To this end,  the SE improvement of cellular base stations (BS) with non-orthogonal signaling is investigated. Thus, a GFDM full-duplex BS transceiver with optimal filters is proposed to enhance the SE of both uplink and downlink transmissions.   Moreover, the SE enhancement of secondary links in cognitive radios is studied. It is shown that the proposed GFDM-based full-duplex secondary links significantly improve the achievable SE in the presence of RF impairments and adjacent channel interference (ACI) constraints. However, it is also shown that RF impairments may negatively impact potential SE  gains. Therefore, standard estimators and deep learning (DL) algorithms are proposed for RF impairment compensation in channel estimation and data detection for GFDM  and multiple-input multiple-output (MIMO)-GFDM full-duplex systems. This thesis demonstrates that the non-orthogonal designs enhance the SE. Moreover, the RF impairments limit the SE gain, while the proposed compensation algorithms eliminate their impacts.
A hybrid Lagrangian -- Eulerian flow solver applied to elastically mounted cylinders in tandem arrangement
Creators: name: Papadakis, George
name: Riziotis, Vasilis A.
name: Voutsinas, Spyros G.
Publisher: name: arXiv
Year: 2021
Subjects: subject: Fluid Dynamics (physics.flu-dyn)
subject: FOS: Physical sciences

description: The fluid structure interaction of cylinders in tandem arrangement is used as validation basis of a multi-domain Lagrangian-Eulerian hybrid flow solver. In this hybrid combination, separate grids of limited width are defined around every solid body, on which the Eulerian flow equations are solved using finite volume approximations. In order to interconnect the domains defined by the grids, the entire flow is described in Lagrangian coordinates and the corresponding equations are solved via particle approximations in fully coupled mode with the solutions within the Eulerian grids. The flow solver is also strongly (implicitly) coupled with the structural dynamic equations in case the cylinders are elastically supported. In the present work, the Eulerian part solves the compressible flow equations in density-velocity-pressure formulation and uses pre-conditioning at low Ma while the Lagrangian part is based on the density-dilatation-vorticity-pressure formulation. The hybrid solver is first validated in the case of an isolated rigid cylinder at $Re=100$. Then the case of a single elastically mounted cylinder at $Re=200$ is considered, followed by the case of two cylinders in tandem arrangement that are either rigid or elastically mounted. Good agreement with results produced with spectral and immersed boundary methods is found indicating the capabilities of the hybrid predictions. Also the flexibility of the method in handling complex multi-body fluid structure interaction problems is demonstrated by allowing grid-overlapping.
description: Submitted to Journal of Fluids and Stuctures
Two-dimensional quantum motion of a levitated nanosphere
Creators: name: Ranfagni, A.
name: Børkje, K.
name: Marino, F.
name: Marin, F.
Publisher: name: arXiv
Year: 2021
Subjects: subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences

description: We report on the two-dimensional (2D) dynamics of a levitated nanoparticle in an optical cavity. The motion of the nanosphere is strongly coupled to the cavity field by coherent scattering and heavily cooled in the plane orthogonal to the tweezer axis. Due to the characteristics of the 2D motion and the strong optomechanical coupling, the motional sideband asymmetry that reveals the quantum nature of the dynamics is not limited to mere scale factors between Stokes and anti-Stokes peaks, as customary in quantum optomechanics, but assumes a peculiar spectral dependence. We introduce and discuss an effective thermal occupancy that quantifies how close the system is to a minimum uncertainty state and allows us to consistently characterize the particle motion. By rotating the polarization angle of the tweezer beam we tune the system from a one-dimensional (1D) cooling regime, where we achieve a best thermal occupancy of 0.51 $\pm$ 0.05, to a regime in which the fully 2D dynamics of the particle exhibits strong non-classical properties. We achieve a strong 2D confinement with thermal occupancy of 3.4 $\pm$ 0.4 along the warmest direction and around unity in the orthogonal one. These results represents a major improvement with respect to previous experiments both considering the 1D and 2D motion, and pave the way towards the preparation of tripartite optomechanical entangled states and novel applications to directional force and displacement quantum sensing.
Barriers to and Opportunities for Indigenous Involvement in the Management of Chronic Wasting Disease in Alberta, Canada
Creators: Cunningham, Hannah
Publisher: name: University of Alberta Library
Year: 2022

The management of Chronic Wasting Disease (CWD) in Alberta is a complex issue that affects multiple stakeholders, including Indigenous communities who highly value the affected species both nutritionally and culturally. Despite the relevancy of CWD management to the livelihoods of these Indigenous communities, particularly in central Alberta where the disease is an immediate threat, the focus of much of the existing research on the social aspects of CWD, as well as the provincial monitoring program, have been recreational hunters. The purpose of this thesis is to answer three questions: how do Indigenous hunters in central Alberta feel about CWD, what are the barriers that Indigenous people in central Alberta face to participating in current CWD management, and what are the best practices that could be utilized to develop a community-based monitoring program for CWD in Alberta? This thesis uses the concepts of knowledge and power, access theory, and the perception of risk to identify why the current CWD monitoring program in Alberta does not adequately reflect the views of Indigenous communities impacted by this disease, and presents community-based monitoring as a potential solution. Through a research partnership with Samson Cree Nation in Maskwacîs, Alberta, Indigenous hunters expressed that they were concerned about CWD and that this concern has some affect on where they choose to hunt, adding to existing barriers to accessing safe traditional foods. A series of best practices for the development of a community-based monitoring program for CWD in Alberta were developed with the aims of overcoming knowledge and cultural gaps that create barriers to participating in the provincial monitoring program, managing the risks associated with CWD, and increasing community confidence in traditional foods.
The Land is Our Casebook: Revitalizing Indigenous Law in Relation with the Living World
Creators: Borrows, Lindsay
Publisher: name: University of Alberta Library
Year: 2022

This thesis addresses how we can learn about law from nature. People can learn from nature (such as plants, animals, rocks, water etc.) through careful observation. This practice is the foundation of science, and inspires the arts. “Reading” nature as a form of legal precedent  embedded in the earth is not part of the current Canadian legal system. I draw from my experience learning Tsilhqot’in law as an articled student, to show how legal stories can be embedded in the landscape and guide Tsilhqot’in understandings of how to live today. I look at academic literature from a range of disciplines to examine how various Indigenous legal traditions form law through relationships with the earth. I also consider the importance of embodied experiences and land-based learning in acquiring this form of legal knowledge. As legal professionals in Canada increasingly engage with Indigenous law, this thesis can help them understand an Indigenous theory of law that relies more on discernment and relationships, than on demands and norms.
Si modification in hypereutectic Al-Si: Combining rapid solidification and alloying
Creators: Diaz Jimenez, Daniela
Publisher: name: University of Alberta Library
Year: 2022

Four alloys were studied to observe the effects of Rapid Solidification and alloying on the morphology of a hypereutectic Al-40Si. Impulse Atomization was used to produce the samples studied. This processing technique was used to attain high undercoolings and liquid cooling

rates ranging 103-105 K/s, thus producing rapidly solidified microstructures. Chemically modified alloys include Al-40Si-1.5Ce, Al-40Si-9.2Mg, and Al-40Si-2.75Fe-2.75Mn-1.5Sc. The resulting microstructures were qualitatively analyzed by comparing the changes in primary Si morphology and distribution across different powder sizes for each alloy and across all alloys for specific powder sizes. Quantitative results include measured phase fractions of primary Si for all alloys, and halo and eutectic for Al-40Si and Al-40Si-1.5Ce.

The results presented suggest Ce and Mg additions are suitable for modifying primary Si shape and distribution in rapidly solidified Al-40Si. Both alloying approaches led to an improvement in primary Si distribution when produced at high cooling rates as compared to Al-40Si. Al-40Si-1.5Ce presents a similar primary Si morphology evolution to that seen in Al-40Si as cooling rate increases. This alloy also contains a large Al-halo vol%, which may be

conducive to improved toughness in this alloy compared to Al-40Si. Primary Si morphology in Al-40Si-9.2Mg does not respond to changes in cooling rate. However, primary Si in this alloy consistently presents a small aspect ratio, which leads to a more homogeneous primary Si distribution in this alloy than in Al-40Si (particularly at slow cooling rates).
Quantum Toroidal Comodule Algebra of Type $A_{n-1}$ and Integrals of Motion
Creators: name: Feigin, Boris
name: Jimbo, Michio
name: Mukhin, Evgeny
Publisher: name: arXiv
Year: 2021
Subjects: subject: Quantum Algebra (math.QA)
subject: Mathematical Physics (math-ph)
subject: FOS: Mathematics
subject: FOS: Physical sciences

description: We introduce an algebra $\mathcal{K}_n$ which has a structure of a left comodule over the quantum toroidal algebra of type $A_{n-1}$. Algebra $\mathcal{K}_n$ is a higher rank generalization of $\mathcal{K}_1$, which provides a uniform description of deformed $W$ algebras associated with Lie (super)algebras of types BCD. We show that $\mathcal{K}_n$ possesses a family of commutative subalgebras.
Electric field and Strain-induced Band-gap Engineering and Manipulation of the Rashba Spin Splitting in Janus van der Waals Heterostructures
Creators: name: Patel, Shubham
name: Dey, Urmimala
name: Adhikari, Narayan Prasad
name: Taraphder, A.
Publisher: name: arXiv
Year: 2021
Subjects: subject: Materials Science (cond-mat.mtrl-sci)
subject: Mesoscale and Nanoscale Physics (cond-mat.mes-hall)
subject: Strongly Correlated Electrons (cond-mat.str-el)
subject: FOS: Physical sciences

description: The compositional as well as structural asymmetries in Janus transition metal dichalcogenides (J-TMDs) and their van der Waals heterostructures (vdW HSs) induce an intrinsic Rashba spin-splitting. We investigate the variation of band-gaps and the Rashba parameter in three different Janus heterostructures having AB-stacked Mo$XY$/W$XY$ ($X$, $Y$ = S, Se, Te; $X\neq Y$) geometry with a $Y-Y$ interface, using first-principles calculations. We consider the effect of external electric field and in-plane biaxial strain in tuning the strength of the intrinsic electric field, which leads to remarkable modifications of the band-gap and the Rashba spin-splitting. In particular, it is found that the positive applied field and compressive in-plane biaxial strain can lead to a notable increase in the Rashba spin-splitting of the valence bands about the $Γ$-point. Moreover, our \textit{ab-initio} density functional theory (DFT) calculations reveal the existence of a type-II band alignment in these heterostructures, which remains robust under positive external field and biaxial strain. These suggest novel ways of engineering the electronic, optical, and spin properties of J-TMD van der Waals heterostructures holding a huge promise in spintronic and optoelectronic devices. Detailed $\mathbf{k\cdot p}$ model analyses have been performed to investigate the electronic and spin properties near the $Γ$ and K points of the Brillouin zone.
description: 17 pages, 12 figures
Exact Mobility edges and topological Anderson insulating phase in a slowly varying quasiperiodic model
Creators: name: Lu, Zhanpeng
name: Xu, Zhihao
name: Zhang, Yunbo
Publisher: name: arXiv
Year: 2022
Subjects: subject: Disordered Systems and Neural Networks (cond-mat.dis-nn)
subject: FOS: Physical sciences

description: We uncover the relationship of topology and disorder in a one-dimensional Su-Schrieffer-Heeger chain subjected to a slowly varying quasi-periodic modulation. By numerically calculating the disorder-averaged winding number and analytically studying the localization length of the zero modes, we obtain the topological phase diagram, which implies that the topological Anderson insulator (TAI) can be induced by a slowly varying quasi-periodic modulation. Moreover, unlike the localization properties in the TAI phase caused by random disorder, mobility edges can enter into the TAI region identified by the fractal dimension, the inverse participation ratio, and the spatial distributions of the wave functions, the boundaries of which coincide with our analytical results.
description: 9 pages, 8 figures
Scolymus hispanicus L.
Creators: name: Info Flora
Publisher: name: Zenodo
Year: 2021
Subjects: Biodiversity
Taxonomy
Plantae
Tracheophyta
Magnoliopsida
Asterales
Asteraceae
Scolymus
Scolymus hispanicus

description: Scolymus hispanicus L.
Art ISFS: 380700 Checklist: 1042490 Asteraceae Scolymus Scolymus hispanicus L.
ZusammenfassungKEINE ANGABE
Ökologie
Lebensraum Lebensraumnach Delarze & al. 2015
KEINE ANGABE
Ökologische Zeigerwerte nach Landolt & al. (2010)
BodenfaktorenKlimafaktorenSalztoleranzFeuchtezahl F--Lichtzahl L--Salzzeichen--Reaktionszahl R--Temperaturzahl T--Nährstoffzahl N--Kontinentalitätszahl K--
Nomenklatur
Gültiger Name (Checklist 2017):Scolymus hispanicusL.
Volksname
Deutscher Name: -- Nom français: -- Nome italiano: --
Übereinstimmung mit anderen Referenzwerken
RelationNomReferenzwerkeNo=Scolymus hispanicus L.Index synonymique 1996380700=Scolymus hispanicus L.Landolt 19773230=Scolymus hispanicus L.SISF/ISFS 2380700
= Taxon stimmt mit akzeptiertem Taxon überein (Checklist 2017)  Taxon enthält (neben anderen) auch das akzeptierte Taxon (Checklist 2017)
Status Indigenat: -
Liste der gefährdeten Pflanzen IUCN(nach Walter & Gillett 1997): Nein
description: Published as part of Info Flora, 2021,
BASS XXX: Distribution Functions of DR2 Eddington-ratios, Black Hole Masses, and X-ray Luminosities
Creators: name: Ananna, Tonima Tasnim
name: Weigel, Anna K.
name: Trakhtenbrot, Benny
name: Koss, Michael J.
name: Urry, C. Megan
name: Ricci, Claudio
name: Hickox, Ryan C.
name: Treister, Ezequiel
name: Bauer, Franz E.
name: Ueda, Yoshihiro
name: Mushotzky, Richard
name: Ricci, Federica
name: Oh, Kyuseok
name: Mejia-Restrepo, Julian E.
name: Brok, Jakob Den
name: Stern, Daniel
name: Powell, Meredith C.
name: Caglar, Turgay
name: Ichikawa, Kohei
name: Wong, O. Ivy
name: Harrison, Fiona A.
name: Schawinski, Kevin
Publisher: name: arXiv
Year: 2022
Subjects: subject: High Energy Astrophysical Phenomena (astro-ph.HE)
subject: Astrophysics of Galaxies (astro-ph.GA)
subject: FOS: Physical sciences

description: We determine the low-redshift X-ray luminosity function (XLF), active black hole mass function (BHMF), and Eddington-ratio distribution function (ERDF) for both unobscured (Type 1) and obscured (Type 2) active galactic nuclei (AGN) using the unprecedented spectroscopic completeness of the BAT AGN Spectroscopic Survey (BASS) data release 2. In addition to a straightforward 1/Vmax approach, we also compute the intrinsic distributions, accounting for sample truncation by employing a forward modeling approach to recover the observed BHMF and ERDF. As previous BHMFs and ERDFs have been robustly determined only for samples of bright, broad-line (Type 1) AGNs and/or quasars, ours is the first directly observationally constrained BHMF and ERDF of Type 2 AGN. We find that after accounting for all observational biases, the intrinsic ERDF of Type 2 AGN is significantly skewed towards lower Eddington ratios than the intrinsic ERDF of Type 1 AGN. This result supports the radiation-regulated unification scenario, in which radiation pressure dictates the geometry of the dusty obscuring structure around an AGN. Calculating the ERDFs in two separate mass bins, we verify that the derived shape is consistent, validating the assumption that the ERDF (shape) is mass independent. We report the local AGN duty cycle as a function of mass and Eddington ratio, by comparing the BASS active BHMF with the local mass function for all SMBH. We also present the log N-log S of Swift-BAT 70-month sources.
description: Accepted by APJS
Plasma Polymerized Ultra-Smooth Polypyrrole Thin Film Optical Waveguide For Integrated Optics
Creators: name: Aviraj A. Jatratkar
name: Patil, Rahul B.
name: R.K. Puri
name: Puri, Vijaya
name: Jyotiprakash B. Yadav
Publisher: name: Zenodo
Year: 2018

description: The talk presented at 29th Annual General Meeting Of Materials Research Society Of India And National Symposium On Advances In Functional And Exotic Materials.
SIENNA D3.2: Analysis of the legal and human rights requirements for Human Enhancement Technologies in and outside the EU
Creators: name: Warso, Zuzanna
name: Gaskell, Sarah
Publisher: name: Zenodo
Year: 2019
Subjects: Human enhancement
legal analysis
human rights
international law
regional laws
national laws
regulation

description: This report will help readers better understand the international, EU and selected countries’ legal developments and approaches to specific legal issues and human rights challenges related to human enhancement. The report broadly discusses the legal issues and human rights challenges of human enhancement. It analyses relevant international, EU and regional laws and human rights standards. It summarises and compares the results of the country studies on law and human enhancement. It also discusses the adequacy of existing norms and standards and gaps and presents some recommendations that will be further developed in the forthcoming SIENNA work.
Scorzonera aristata DC.
Creators: name: Info Flora
Publisher: name: Zenodo
Year: 2021
Subjects: Biodiversity
Taxonomy
Plantae
Tracheophyta
Magnoliopsida
Asterales
Asteraceae
Scorzonera
Scorzonera aristata

description: Scorzonera aristata DC.
Art ISFS: 380900 Checklist: 1042510 Asteraceae Scorzonera Scorzonera aristata DC.
Bestimmungsschlüssel
ZusammenfassungKEINE ANGABE
Ökologie
Lebensraum Lebensraumnach Delarze & al. 2015
KEINE ANGABE
Ökologische Zeigerwerte nach Landolt & al. (2010)
BodenfaktorenKlimafaktorenSalztoleranzFeuchtezahl F--Lichtzahl L--Salzzeichen--Reaktionszahl R--Temperaturzahl T--Nährstoffzahl N--Kontinentalitätszahl K--
Nomenklatur
Gültiger Name (Checklist 2017):Scorzonera aristataDC.
Volksname
Deutscher Name: -- Nom français: -- Nome italiano: --
Übereinstimmung mit anderen Referenzwerken
RelationNomReferenzwerkeNo=Scorzonera aristata DC.Checklist 2017380900=Scorzonera aristata DC.Index synonymique 1996380900=Scorzonera aristata DC.Landolt 19773249=Scorzonera aristata DC.SISF/ISFS 2380900
= Taxon stimmt mit akzeptiertem Taxon überein (Checklist 2017)  Taxon enthält (neben anderen) auch das akzeptierte Taxon (Checklist 2017)
Status Indigenat: -
Liste der gefährdeten Pflanzen IUCN(nach Walter & Gillett 1997): Nein
description: Published as part of Info Flora, 2021,
Using machine learning to parametrize postmerger signals from binary neutron stars
Creators: name: Whittaker, Tim
name: East, William E.
name: Green, Stephen R.
name: Lehner, Luis
name: Yang, Huan
Publisher: name: arXiv
Year: 2022
Subjects: subject: General Relativity and Quantum Cosmology (gr-qc)
subject: High Energy Astrophysical Phenomena (astro-ph.HE)
subject: Machine Learning (cs.LG)
subject: Machine Learning (stat.ML)
subject: FOS: Physical sciences
subject: FOS: Computer and information sciences

description: There is growing interest in the detection and characterization of gravitational waves from postmerger oscillations of binary neutron stars. These signals contain information about the nature of the remnant and the high-density and out-of-equilibrium physics of the postmerger processes, which would complement any electromagnetic signal. However, the construction of binary neutron star postmerger waveforms is much more complicated than for binary black holes: (i) there are theoretical uncertainties in the neutron-star equation of state and other aspects of the high-density physics, (ii) numerical simulations are expensive and available ones only cover a small fraction of the parameter space with limited numerical accuracy, and (iii) it is unclear how to parametrize the theoretical uncertainties and interpolate across parameter space. In this work, we describe the use of a machine-learning method called a conditional variational autoencoder (CVAE) to construct postmerger models for hyper/massive neutron star remnant signals based on numerical-relativity simulations. The CVAE provides a probabilistic model, which encodes uncertainties in the training data within a set of latent parameters. We estimate that training such a model will ultimately require $\sim 10^4$ waveforms. However, using synthetic training waveforms as a proof-of-principle, we show that the CVAE can be used as an accurate generative model and that it encodes the equation of state in a useful latent representation.
Putting Vibrio cholerae in context: the ecology and evolution of the Cholerae clade
Creators: Islam, Mohammad Tarequl
Publisher: name: University of Alberta Library
Year: 2022

Phylogenomic structuring of the Vibrio cholerae clade is an important area of study in the context of the alarming spike of human morbidities due to environmental pathogens around the world. Even after decades of research, the structuring of natural populations of V. cholerae and its sister species is poorly understood. Ecological and epidemiological importance of the clade shouts for a sound understanding of the phylogenetic relationships and environmental dynamics within the clade in their natural settings. In this thesis, my goal is to answer few broad questions on the biology of the V. cholerae clade: i) How different is the evolutionary trajectory of pathogenic lineages from environmental populations ii) To what extent environmental and biogeographic factors impact the intra-species diversity of the model species: V. cholerae iii) Is our understanding of the phylogeny and ecology of the V. cholerae clade consistent with the inclusion of the recently discovered sister species of V. cholerae from both environmental and clinical settings. To address these questions, I have employed culture-based techniques, phenotypic characterization, high throughput amplicon sequencing, whole genome sequencing, quantitative PCR (qPCR) as well as phylogenetic and taxonomic inference tools. I have found potential signatures in V. cholerae population structure in cholera endemic and non-endemic regions. I have also shown the impact of environmental factors on the intra-species diversity of V. cholerae population naturally occurring in a cholera endemic area. Furthermore, I am describing here the genetic, phylogenetic and biological traits, as well as interaction of a novel sister species with V. cholerae: V. paracholerae sp. nov. Moreover, I delineate the phylogenetic and molecular spectrum of a novel sister species of V. cholerae: V. tarriae, isolated from human and environmental samples only from cholera free locations in the USA. The studies presented herein consolidates the understanding of the natural diversity and ecology of the clade containing V. cholerae and its close relatives at species and sub-species level, which could be a significant stride in our knowledge on this group of microorganisms.
Challenges in Migrating Imperative Deep Learning Programs to Graph Execution: An Empirical Study
Creators: name: Vélez, Tatiana Castro
name: Khatchadourian, Raffi
name: Bagherzadeh, Mehdi
name: Raja, Anita
Publisher: name: arXiv
Year: 2022
Subjects: subject: Software Engineering (cs.SE)
subject: Machine Learning (cs.LG)
subject: Programming Languages (cs.PL)
subject: FOS: Computer and information sciences
subject: D.2.m

description: Efficiency is essential to support responsiveness w.r.t. ever-growing datasets, especially for Deep Learning (DL) systems. DL frameworks have traditionally embraced deferred execution-style DL code that supports symbolic, graph-based Deep Neural Network (DNN) computation. While scalable, such development tends to produce DL code that is error-prone, non-intuitive, and difficult to debug. Consequently, more natural, less error-prone imperative DL frameworks encouraging eager execution have emerged but at the expense of run-time performance. While hybrid approaches aim for the "best of both worlds," the challenges in applying them in the real world are largely unknown. We conduct a data-driven analysis of challenges -- and resultant bugs -- involved in writing reliable yet performant imperative DL code by studying 250 open-source projects, consisting of 19.7 MLOC, along with 470 and 446 manually examined code patches and bug reports, respectively. The results indicate that hybridization: (i) is prone to API misuse, (ii) can result in performance degradation -- the opposite of its intention, and (iii) has limited application due to execution mode incompatibility. We put forth several recommendations, best practices, and anti-patterns for effectively hybridizing imperative DL code, potentially benefiting DL practitioners, API designers, tool developers, and educators.
description: International Conference on Mining Software Repositories, MSR 2022. ACM/IEEE, ACM, May 2022
Non-perturbative treatment of giant atoms using chain transformations
Creators: name: Noachtar, David D.
name: Knörzer, Johannes
name: Jonsson, Robert H.
Publisher: name: arXiv
Year: 2022
Subjects: subject: Quantum Physics (quant-ph)
subject: Mesoscale and Nanoscale Physics (cond-mat.mes-hall)
subject: FOS: Physical sciences

description: Superconducting circuits coupled to acoustic waveguides have extended the range of phenomena that can be experimentally studied using tools from quantum optics. In particular giant artificial atoms permit the investigation of systems in which the electric dipole approximation breaks down and pronounced non-Markovian effects become important. While previous studies of giant atoms focused on the realm of the rotating-wave approximation, we go beyond this and perform a numerically exact analysis of giant atoms strongly coupled to their environment, in regimes where counterrotating terms cannot be neglected. To achieve this, we use a Lanczos transformation to cast the field Hamiltonian into the form of a one-dimensional chain and employ matrix-product state simulations. This approach yields access to a wide range of system-bath observables and to previously unexplored parameter regimes.
description: 8+5 pages, 8+2 figures, 1+1 tables. v3: update published version
Consumer preferences for the genomic selection for particular traits in  breeding dairy cows in Canada
Creators: Jiwon, Kim
Publisher: name: University of Alberta Library
Year: 2022

This study examines Canadian public preferences for the use of genomic selection in breeding dairy cows for four main traits– feed efficiency, methane emission reduction, enhanced disease resilience, improved cow fertility as well as the use of antibiotics. Since this research information might be helpful to guide farmers to tap into consumer preferences and make better decisions which can beneficial for both animal, environment and themselves, this study identified the characteristics of individuals who are more or less in favor of one or more traits as well as public preferences for the four main traits and the use of antibiotics. Based on the survey results, two approaches, conditional logit and latent class models which can capture respondent heterogeneity were estimated, and heterogeneity does exist across survey respondents. Given the analyses, the feed efficiency trait was preferred the most based in the conditional logit models. On the other hand, the enhanced disease resilience and feed efficiency traits are preferred the most based on the latent class model. Furthermore, as the latent class model may reflect the reality well through exploring heterogeneity, there were nine identified classes of respondents with different preferences. There are variations across classes with respect to environmental self-assessed knowledge, myths of nature, animal husbandry, and on top of gender, number of children under age 18 across the nine classes. Lastly, the predicted shares for dairy products produced with genomic selective breeding with each of the four traits was predicted. There is around 67.3~74.6% market demand for the dairy products produced with the enhanced disease resilience trait. Regarding the feed efficiency trait, the expected market demand is around 51.9~54.9%, while around 8.5~9.2% for the improved fertility trait. Also, there is about 34.7~41% market demand for the dairy products which have the methane emission reduction attribute. When it comes to the use of antibiotics, around 48.4~55.3% people like the therapeutic use of antibiotics as opposed to no antibiotics.
Fused Filament Fabrication of Metal-Ceramic High-Density Polyethylene Composites
Creators: Bhardwaj, Nancy
Publisher: name: University of Alberta Library
Year: 2022

This thesis focuses on the manufacturing of high carbide content wear-resistant parts by extrusion- based Additive Manufacturing (AM) based on the principles of Powder Metallurgy (PM). A new manufacturing technique, termed Fused Filament Fabrication of Cermets (FFFC) is presented. First, particle packing theory is applied to develop a methodology for maximizing packing density and carbide content in non-ideal binary powder mixtures. Based on this optimization, sinterable metal-ceramic polymer filaments suitable for Fused Filament Fabrication (FFF) are prepared and printed. It is shown that a traditional polymer 3D printer can be used to successfully deposit high- density polyethylene (HDPE) composite filaments containing up to 46 vol% Ni-TiC and Ni-WC fillers, to produce dense green parts for sintering. A characterization of the composite filaments and resultant printed parts is provided. An analysis of the random loose void fractions in dry fillers and the fraction of polymer in the composite after polymer is injected into the dry filler is presented. It is concluded that, the maximum void contraction (∆Θmax) is a function of the ratio of mean particles sizes (δ) in binary dry powder mixtures. As δ decreases and the particle sizes become more dissimilar, an increasing deviation from the ideal rule-of-mixtures law is observed. The critical δ is revealed to be 0.65. Furthermore, when dry filler is mixed with HDPE to form composite filaments for FFF, the particles are rearranged, and the polymer content of the filled composite is greater than the void fraction observed in dry filler packing. Fillers having lower dry void fractions, reported higher polymer contents in their composites. The important role of non- ideal particle packing in binary filler mixtures is emphasized, where the goal is to produce high carbide content cermet parts. Some remarks about process parameters that influence part quality and suggestions for future work are included.