cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
Parameter Study and Calibration of SPH–DEM Coupling Simulations for Fluid–Granular Solid Systems
Creators: name: Tran, Hai Nam
Publisher: name: University of Wollongong
Year: 2025
Subjects: classificationCode: 4017
subject: Mechanical engineering
subject: FOS: Mechanical engineering
classificationCode: 401706
subject: Numerical modelling and mechanical characterisation
classificationCode: 400406
subject: Powder and particle technology

description: The presence of fluid–granular solid flows can be found in a wide range of industrial applications such as pneumatic conveying, wet ball milling, and slurry transport. The majority of such fluid–granular solid flows are too intricate to be sufficiently modelled by fundamental theories. As a result, there has been a research effort conducted on using computer-aided engineering (CAE) tools to model industrial systems that handle fluid–granular solid flows. Apart from using conventional methods, some researchers have explored the coupling between smoothed particle hydrodynamics (SPH) and discrete element method (DEM) to model specific fluid–granular solid flows with free surfaces, complex geometries, mobile interfaces, large deformations, and fast dynamics. However, even though many feasibility studies have been conducted on SPH–DEM simulations, there is still a general lack of standardised methodologies to conduct parameter study and calibration of this newer simulation tool.With this motivation, this thesis aims to develop a dedicated model parameter study and calibration framework for new SPH–DEM coupling models using bench-scale experiments. The developed framework is utilised to construct an SPH–DEM model to simulate the mixture between water and irregularly shaped cohesionless dark peach pebbles. In this framework, length scale refinement strategies are investigated to see if they can help a standard SPH implementation make accurate predictions of 3D free-surface fluid flows. Experimental test rigs are designed to accommodate for both a dry mode granular solid sample and a submerged mode fluid–granular solid mixture on the same system. Using the experimental data as the validation reference, a manual calibration process followed by a comprehensive calibration process are performed to obtain an understanding of how SPH length scales and DEM contact parameters affect the SPH–DEM simulation model.While the research indicates a considerable challenge in using length scale refinement strategies to achieve simulation convergence only with a standard SPH implementation, it also illustrates that SPH length scale sizes, along with the DEM contact parameter values, have a substantial impact on the SPH–DEM results. The conducted manual and comprehensive calibration studies demonstrate the potential of a dedicated calibration framework to develop a fully calibrated SPH–DEM model. These studies also emphasise the need to treat dry mode DEM calibration and submerged mode SPH–DEM calibration independently.
Quantum walks: Schur functions meet symmetry protected topological phases
Creators: name: Cedzich, C.
name: Geib, T.
name: Grünbaum, F. A.
name: Velázquez, L.
name: Werner, A. H.
name: Werner, R. F.
Publisher: name: arXiv
Year: 2019
Subjects: subject: Mathematical Physics (math-ph)
subject: Classical Analysis and ODEs (math.CA)
subject: Complex Variables (math.CV)
subject: Functional Analysis (math.FA)
subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences
subject: FOS: Mathematics

description: This paper uncovers and exploits a link between a central object in harmonic analysis, the so-called Schur functions, and the very hot topic of symmetry protected topological phases of quantum matter. This connection is found in the setting of quantum walks, i.e. quantum analogs of classical random walks. We prove that topological indices classifying symmetry protected topological phases of quantum walks are encoded by matrix Schur functions built out of the walk. This main result of the paper reduces the calculation of these topological indices to a linear algebra problem: calculating symmetry indices of finite-dimensional unitaries obtained by evaluating such matrix Schur functions at the symmetry protected points $\pm1$. The Schur representation fully covers the complete set of symmetry indices for 1D quantum walks with a group of symmetries realizing any of the symmetry types of the tenfold way. The main advantage of the Schur approach is its validity in the absence of translation invariance, which allows us to go beyond standard Fourier methods, leading to the complete classification of non-translation invariant phases for typical examples.
description: 33 pages, 1 figure
Tight Approximation Bounds for Maximum Multi-Coverage
Creators: name: Barman, Siddharth
name: Fawzi, Omar
name: Ghoshal, Suprovat
name: Gürpınar, Emirhan
Publisher: name: arXiv
Year: 2019
Subjects: subject: Data Structures and Algorithms (cs.DS)
subject: FOS: Computer and information sciences

description: In the classic maximum coverage problem, we are given subsets $T_1, \dots, T_m$ of a universe $[n]$ along with an integer $k$ and the objective is to find a subset $S \subseteq [m]$ of size $k$ that maximizes $C(S) := |\cup_{i \in S} T_i|$. It is well-known that the greedy algorithm for this problem achieves an approximation ratio of $(1-e^{-1})$ and there is a matching inapproximability result. We note that in the maximum coverage problem if an element $e \in [n]$ is covered by several sets, it is still counted only once. By contrast, if we change the problem and count each element $e$ as many times as it is covered, then we obtain a linear objective function, $C^{(\infty)}(S) = \sum_{i \in S} |T_i|$, which can be easily maximized under a cardinality constraint. We study the maximum $\ell$-multi-coverage problem which naturally interpolates between these two extremes. In this problem, an element can be counted up to $\ell$ times but no more; hence, we consider maximizing the function $C^{(\ell)}(S) = \sum_{e \in [n]} \min\{\ell, |\{i \in S : e \in T_i\}| \}$, subject to the constraint $|S| \leq k$. Note that the case of $\ell = 1$ corresponds to the standard maximum coverage setting and $\ell = \infty$ gives us a linear objective. We develop an efficient approximation algorithm that achieves an approximation ratio of $1 - \frac{\ell^{\ell}e^{-\ell}}{\ell!}$ for the $\ell$-multi-coverage problem. In particular, when $\ell = 2$, this factor is $1-2e^{-2} \approx 0.73$ and as $\ell$ grows the approximation ratio behaves as $1 - \frac{1}{\sqrt{2π\ell}}$. We also prove that this approximation ratio is tight, i.e., establish a matching hardness-of-approximation result, under the Unique Games Conjecture.
description: 27 pages
Self-similar Cauchy problems and generalized Mittag-Leffler functions
Creators: name: Patie, P.
name: Srapionyan, A.
Publisher: name: arXiv
Year: 2019
Subjects: subject: Probability (math.PR)
subject: Analysis of PDEs (math.AP)
subject: FOS: Mathematics

description: By observing that the fractional Caputo derivative can be expressed in terms of a multiplicative convolution operator, we introduce and study a class of such operators which also have the same self-similarity property as the Caputo derivative. We proceed by identifying a subclass which is in bijection with the set of Bernstein functions and we provide several representations of their eigenfunctions, expressed in terms of the corresponding Bernstein function, that generalize the Mittag-Leffler function. Each eigenfunction turns out to be the Laplace transform of the right-inverse of a non-decreasing self-similar Markov process associated via the so-called Lamperti mapping to this Bernstein function. Resorting to spectral theoretical arguments, we investigate the generalized Cauchy problems, defined with these self-similar multiplicative convolution operators. In particular, we provide both a stochastic representation, expressed in terms of these inverse processes and an explicit representation, given in terms of the generalized Mittag-Leffler functions, of the solution of these self-similar Cauchy problems.
title: Untersuchungen zum zeitabhängigen Tragverhalten von Verbundquerschnitten mit Hilfe der Laplace-Transformation
Creators: name: Raue, Erich
name: Heidolf, Thorsten
Publisher: name: Bauhaus-Universität Weimar
Year: 2003
Subjects: subject: Bauteil
subject: Verbundbauweise
subject: Tragverhalten
subject: Zeitabhängigkeit
subject: Laplace-Transformation
subject: 620

description: Im Stahlbeton- und Spannbetonbau kommen in zunehmendem Maße Verbundkonstruktionen aus Betonfertigteilen und Ortbetonergänzungen zum Einsatz. Die Fertigteile werden je nach Spannweite, Belastung und speziellen Anforderungen mit schlaffer oder vorgespannter Be-wehrung ausgeführt. Aufgrund der im Allgemeinen unterschiedlichen Betone der einzelnen Querschnittsanteile sowie bedingt durch den zeitlichen Versatz in der Herstellung der Fertig-teile und der Ortbetonergänzungen ergeben sich Unterschiede im Langzeitverhalten, die bei der Bemessung und Nachweisführung zu berücksichtigen sind. Das Kriechen und Schwinden der Betone als Folge des zeitabhängigen Materialverhaltens und die Spezifik des Verbund-querschnitts können für die Gebrauchstauglichkeit relevant sein, insbesondere wenn die Fer-tigteile vorgespannt sind. Eine hinreichend wirklichkeitsnahe Beschreibung des Langzeitverhaltens von Beton gestattet die Theorie des elastisch-kriechenden Körpers, wobei sich im Allgemeinen keine geschlosse-ne Lösung für bewehrte Betonverbundquerschnitte angeben lässt. Eine Alternative hierzu ergibt sich, wenn für die einzelnen Kriechintervalle ein vereinfachter Ansatz für den Verlauf der Kriechfunktion entsprechend der Theorie des Alterns getroffen wird. Dabei werden die im Zeitintervall (tj-1,tj) umgelagerten Schnittgrößen als neue Belastung der einzelnen Querschnittsanteile im Zeitintervall (tj,tj+1) mit der Kriech-funktion f(tj+1,tj) berücksichtigt. Bei hinreichend kleinen Zeitschritten können die Nachteile der getroffenen Vereinfachung vernachlässigt werden.
description: Internationales Kolloquium über Anwendungen der Informatik und Mathematik in Architektur und Bauwesen : 10. bis 12.06.2003, Bauhaus-Universität Weimar, vol. 16, 2003
Symptoms, Viral Loads, and Rebound Among COVID-19 Outpatients Treated With Nirmatrelvir/Ritonavir Compared With Propensity Score–Matched Untreated Individuals
Creators: name: Goodman, Sara
name: Govindaranjan, Prasanthi
name: Petrie, Joshua G
name: Pryor, Kathleen
name: Haehnel, Quenla
name: Lutrick, Karen
name: Asturias, Edwin
name: Rolfes, Melissa A R
name: Battan-Wraith, Steph
name: Yang, Amy
name: Merrill, Lori
name: Schmitz, Jonathan
name: Talbot, H Keipp
name: Biddle, Jessica E
name: Smith-Jeffcoat, Sarah E
name: Salvatore, Phillip P
name: Sarnquist, Clea C
name: Vargas, Celibell Y
name: McLaren, Son H
name: Belongia, Edward A
name: Stockwell, Melissa S
name: Bowman, Natalie M
name: Ellingson, Katherine D
name: McLean, Huong Q
name: Kirking, Hannah L
name: Johnson, Sheroi
name: Olivo, Vanessa
name: Sano, Ellen
name: Ledezma, Karla
name: Maldonado, Yvonne
name: Bullock, Ayla
name: Mellis, Alexandra M
name: Morrissey, Kerry Grace
name: Zhu, Yuwei
name: Hart, Kimberly
name: Grijalva, Carlos G
name: Rao, Suchitra
Publisher: name: Oxford University Press (OUP)
Year: 2023

description:
BACKGROUND: Nirmatrelvir/ritonavir (N/R) reduces severe outcomes from coronavirus disease 2019 (COVID-19); however, rebound after treatment has been reported. We compared symptom and viral dynamics in individuals with COVID-19 who completed N/R treatment and similar untreated individuals. METHODS: We identified symptomatic participants who tested severe acute respiratory syndrome coronavirus 2-positive and were N/R eligible from a COVID-19 household transmission study. Index cases from ambulatory settings and their households contacts were enrolled. We collected daily symptoms, medication use, and respiratory specimens for quantitative polymerase chain reaction for 10 days during March 2022-May 2023. Participants who completed N/R treatment (treated) were propensity score matched to untreated participants. We compared symptom rebound, viral load (VL) rebound, average daily symptoms, and average daily VL by treatment status measured after N/R treatment completion or 7 days after symptom onset if untreated. RESULTS: Treated (n = 130) and untreated participants (n = 241) had similar baseline characteristics. After treatment completion, treated participants had greater occurrence of symptom rebound (32% vs 20%; P = .009) and VL rebound (27% vs 7%; P < .001). Average daily symptoms were lower among treated participants without symptom rebound (1.0 vs 1.6; P < .01) but not statistically lower with symptom rebound (3.0 vs 3.4; P = .5). Treated participants had lower average daily VLs without VL rebound (0.9 vs 2.6; P < .01) but not statistically lower with VL rebound (4.8 vs 5.1; P = .7). CONCLUSIONS: Individuals who completed N/R treatment experienced fewer symptoms and lower VL but rebound occured more often compared with untreated individuals. Providers should prescribe N/R, when indicated, and communicate rebound risk to patients.
Seeding with Costly Network Information
Creators: name: Eckles, Dean
name: Esfandiari, Hossein
name: Mossel, Elchanan
name: Rahimian, M. Amin
Publisher: name: arXiv
Year: 2019
Subjects: subject: Social and Information Networks (cs.SI)
subject: Computational Complexity (cs.CC)
subject: Probability (math.PR)
subject: Physics and Society (physics.soc-ph)
subject: FOS: Computer and information sciences
subject: FOS: Mathematics
subject: FOS: Physical sciences

description: We study the task of selecting $k$ nodes, in a social network of size $n$, to seed a diffusion with maximum expected spread size, under the independent cascade model with cascade probability $p$. Most of the previous work on this problem (known as influence maximization) focuses on efficient algorithms to approximate the optimal seed set with provable guarantees given knowledge of the entire network; however, obtaining full knowledge of the network is often very costly in practice. Here we develop algorithms and guarantees for approximating the optimal seed set while bounding how much network information is collected. First, we study the achievable guarantees using a sublinear influence sample size. We provide an almost tight approximation algorithm with an additive $εn$ loss and show that the squared dependence of sample size on $k$ is asymptotically optimal when $ε$ is small. We then propose a probing algorithm that queries edges from the graph and use them to find a seed set with the same almost tight approximation guarantee. We also provide a matching (up to logarithmic factors) lower-bound on the required number of edges. This algorithm is implementable in field surveys or in crawling online networks. Our probing takes $p$ as an input which may not be known in advance, and we show how to down-sample the probed edges to match the best estimate of $p$ if they are collected with a higher probability. Finally, we test our algorithms on an empirical network to quantify the tradeoff between the cost of obtaining more refined network information and the benefit of the added information for guiding improved seeding strategies.
title: Optimization of street lane usage
Creators: name: Rudnicki, Andrzej
name: Wainaina, Simon
name: Hempel, Lorenz
Publisher: name: Bauhaus-Universität Weimar
Year: 2003
Subjects: subject: Öffentlicher Personennahverkehr
subject: Busspur
subject: Transportproblem
subject: 620

description: This paper contributes to discussion on introduction of exclusive lane for public transport. Analyses of results have been presented on effectiveness of usage of a 4 - lane and a 6 - lane street with and without an exclusive lane for buses. Two basic sub-models have been applied: - the binary logit model for modal split estimation; it takes into consideration the relation of travel time performed by private cars to public transport, - the polynomial model for predicting link impedance; the real travel time is affected by relation of traffic volume to the design capacity The parameters of both sub-models have been calibrated for the Polish conditions. The relationships are determined between number of person trips and traffic volume of buses/private cars, market share of public transport in motorised trips, average travel time lost in trips, average operation cost. An iterative technique addresses a feedback between the modal split and traffic volumes. Numerical calculations by use of EXCEL and MATLAB were carried out. Typical values of corridor length, occupancy rate of passenger car, design capacity of the bus, access and egress time to and from the parking/bus-stop in urban areas were applied. On the basis of the estimated results, the marginal parameter values: number of people carried at which separated lane for buses is most effective , traffic volume for private cars, traffic volume for buses and share of public transport in trips have been got by consideration of the average travel time lost and operational cost as criteria: Then introduction of street lanes with and without exclusive lane for buses in relation to number of person trips can be optimized.
description: Internationales Kolloquium über Anwendungen der Informatik und Mathematik in Architektur und Bauwesen : 10. bis 12.06.2003, Bauhaus-Universität Weimar, vol. 16, 2003
Performance of Statistical and Machine Learning Risk Prediction Models for Surveillance Benefits and Failures in Breast Cancer Survivors.
Creators: name: Sprague, Brian L
name: Henderson, Louise M
name: Su, Yu-Ru
name: Kerlikowske, Karla
name: Lee, Janie M
name: Wernli, Karen J
name: Buist, Diana S M
name: Hubbard, Rebecca A
name: Miglioretti, Diana L
name: Lowry, Kathryn P
name: Tosteson, Anna
name: Ichikawa, Laura
name: Bowles, Erin J Aiello
Publisher: name: American Association for Cancer Research (AACR)
Year: 2023

description:
BACKGROUND: Machine learning (ML) approaches facilitate risk prediction model development using high-dimensional predictors and higher-order interactions at the cost of model interpretability and transparency. We compared the relative predictive performance of statistical and ML models to guide modeling strategy selection for surveillance mammography outcomes in women with a personal history of breast cancer (PHBC). METHODS: We cross-validated seven risk prediction models for two surveillance outcomes, failure (breast cancer within 12 months of a negative surveillance mammogram) and benefit (surveillance-detected breast cancer). We included 9,447 mammograms (495 failures, 1,414 benefits, and 7,538 nonevents) from years 1996 to 2017 using a 1:4 matched case-control samples of women with PHBC in the Breast Cancer Surveillance Consortium. We assessed model performance of conventional regression, regularized regressions (LASSO and elastic-net), and ML methods (random forests and gradient boosting machines) by evaluating their calibration and, among well-calibrated models, comparing the area under the receiver operating characteristic curve (AUC) and 95% confidence intervals (CI). RESULTS: LASSO and elastic-net consistently provided well-calibrated predicted risks for surveillance failure and benefit. The AUCs of LASSO and elastic-net were both 0.63 (95% CI, 0.60-0.66) for surveillance failure and 0.66 (95% CI, 0.64-0.68) for surveillance benefit, the highest among well-calibrated models. CONCLUSIONS: For predicting breast cancer surveillance mammography outcomes, regularized regression outperformed other modeling approaches and balanced the trade-off between model flexibility and interpretability. IMPACT: Regularized regression may be preferred for developing risk prediction models in other contexts with rare outcomes, similar training sample sizes, and low-dimensional features.
On the existence of minimal models for log canonical pairs
Creators: name: Lazić, Vladimir
name: Tsakanikas, Nikolaos
Publisher: name: arXiv
Year: 2019
Subjects: subject: Algebraic Geometry (math.AG)
subject: FOS: Mathematics
subject: 14E30

description: We show that minimal models of log canonical pairs exist, assuming the existence of minimal models of smooth varieties.
description: v3: minor changes; title changed; to appear in Publ. Res. Inst. Math. Sci
A performance impact of Andrew's Sine threshold for a robust regularized SRR based on ML framework
Creators: name: Vorapoj Patanavijit
Publisher: name: Rangsit University
Year: 2016
Subjects: SRR (Super-Resolution Reconstruction), DIR (Digital Image Reconstruction), DIP (Digital Image Processing), ML (Maximum Likelihood) Estimation, DSP (Digital Signal Processing)

description: Rangsit Journal of Arts and Sciences, 6, 1
The effect of under-reporting of non-fatal involvements in snow avalanches on vulnerability
Creators: name: Jamieson, Bruce
name: Jones, Alan S. T.
Publisher: name: The University of British Columbia
Year: 2015

description: For a person caught in a snow avalanche of specified magnitude, vulnerability is probability death. In North America and most alpine countries, most fatalities due to snow avalanches occur during recreation and are thus a voluntary risk. The previously reported vulnerability of recreationists to snow avalanches is typically in the range of 0.1 to 0.25, which is also applied to workers travelling on skis and snowmobiles in uncontrolled areas (backcountry). This is the base rate (prior probability) for many studies of survival factors such as use of specific rescue devices, burial depth, etc. Most studies of people caught in avalanches assume that all non-fatal involvements are reported. However, in a recent Canadian study, Jamieson and Jones (2012) argued that only 5 to 10% of persons caught but not killed by an avalanche during recreation are reported. This results in potential overestimation of vulnerability by a factor of about 10 or greater. Such uncertainty in the base rate can undermine statistical studies of survival factors. We review the assumed reporting rates from international studies and their calculated vulnerability rates from snow avalanches in uncontrolled terrain. We conducted a survey of those who had been caught in an avalanche, which indicated that 11% of non-fatal involvements are reported in Canada. We discuss both positive and negative biases in our survey results. Based on Canadian data, we conclude that the vulnerability for persons travelling on skis or snowmobilers and caught in a potentially fatal avalanche is approximately 0.03. This revised base rate may prove useful in studies of rescue devices, burial depths, public avalanche education programs, and policies concerning risk management and resource allocation.
title: Numerische Simulation auf Basis des IFC-Bauwerksmodells
Creators: name: Romberg, Richard
name: Treeck, Christioph van
name: Niggl, Andreas
Publisher: name: Bauhaus-Universität Weimar
Year: 2003
Subjects: subject: Bauwerk
subject: Dreidimensionales Modell
subject: Datenaustausch
subject: 620

description: Dieser Beitrag zeigt einen Ansatz, verschiedene numerische Simulationsaufgaben auf ein gemeinsames und durchgängig dreidimensionales Geometriemodell zu gründen. Hinsichtlich der physikalischen Modelle reicht die Bandbreite der hier vorgestellten Anwendungen von einer ganzheitlichen Betrachtung der Gebäudestruktur in der Strukturmechanik über die raumbezogene, hochauflösende Modellierung konvektiver Raumluftströmungen bis hin zur Simulation des thermischen Verhaltens eines ganzen Gebäudes. Das jeweils zugrunde liegende numerische Verfahren setzt dabei auf einem stets gleichen Zwischenmodell der realen Geometrie der Struktur auf, ohne dabei vereinfachende dimensionsreduzierte Modelle anzuwenden. Nachfolgende Werkzeuge werden derzeit im Rahmen mehrerer Forschungsprojekte an dieses Geometriemodell angeschlossen: Die p-Version der FEM für die Strukturanalyse, ein sog. Mehrzonenmodell für die thermische Gebäudesimulation sowie ein auf dem sog. hybriden thermischen Gitter-Boltzmann-Verfahren (hTLBE) basierender Strömungssimulationscode. Der Import geometrischer wie semantischer Daten eines Bauwerks in das Simulations-Framework erfolgt nach dem Produktmodell der Industry Foundation Classes (IFC), das sich als Quasi-Standard für den Datenaustausch im Bauwesen etabliert hat. Das IFC-Schema dient dabei nicht als Modell zur internen Speicherung von Daten, sondern wird hier als Schnittstelle zur Anbindung unterschiedlicher Programme wie CAD-Anwendungen für Architekten oder anderen Modellierungstools verwendet. Die Implementierung dieser Schnittstelle erfolgt unter Verwendung einer sog. Toolbox, die das Objektschema der IFC auf ein Klassenmodell einer objektorientierten Programmiersprache abbildet und Werkzeuge für den effizienten Objektzugriff zur Verfügung stellt. Damit werden Grenzen zwischen spezialisierten Softwarepaketen, die maßgeschneidert auf spezielle Erfordernisse ausgerichtet sind, aufgebrochen und der Datenaustausch über die Anwendungsgrenzen hinaus unterstützt. Dies ist eine Konsequenz aus einer dem Wunsch nach vernetzt-kooperativen Planung von Bauwerken....
description: Internationales Kolloquium über Anwendungen der Informatik und Mathematik in Architektur und Bauwesen : 10. bis 12.06.2003, Bauhaus-Universität Weimar, vol. 16, 2003
On non-local ergodic Jacobi semigroups: spectral theory, convergence-to-equilibrium and contractivity
Creators: name: Cheridito, Patrick
name: Patie, Pierre
name: Srapionyan, Anna
name: Vaidyanathan, Aditya
Publisher: name: arXiv
Year: 2019
Subjects: subject: Probability (math.PR)
subject: Analysis of PDEs (math.AP)
subject: Spectral Theory (math.SP)
subject: FOS: Mathematics

description: In this paper, we introduce and study non-local Jacobi operators, which generalize the classical (local) Jacobi operators. We show that these operators extend to generators of ergodic Markov semigroups with unique invariant probability measures and study their spectral and convergence properties. In particular, we derive a series expansion of the semigroup in terms of explicitly defined polynomials, which generalize the classical Jacobi orthogonal polynomials. In addition, we give a complete characterization of the spectrum of the non-self-adjoint generator and semigroup. We show that the variance decay of the semigroup is hypocoercive with explicit constants, which provides a natural generalization of the spectral gap estimate. After a random warm-up time, the semigroup also decays exponentially in entropy and is both hypercontractive and ultracontractive. Our proofs hinge on the development of commutation identities, known as intertwining relations, between local and non-local Jacobi operators and semigroups, with the local objects serving as reference points for transferring properties from the local to the non-local case.
title: Vernetzte Bauprozesssteuerung auf der Basis bauteilspezifischer Prozessmuster für geotechnische Konstruktionselemente
Creators: name: Rüppel, Uwe
name: Meißner, Udo F.
name: Greb, Steffen
Publisher: name: Bauhaus-Universität Weimar
Year: 2003
Subjects: subject: Geotechnik
subject: CAD
subject: Prozessmodell
subject: Rechnernetz
subject: 620

description: Der Beitrag basiert auf den Ansätzen und Ergebnissen des Forschungsprojekts >Prozessorientierte Vernetzung von Ingenieurplanungen am Beispiel der Geotechnik<, des DFG-Schwerpunktprogramms 1103 >Vernetzt-kooperative Planungsprozesse im Konstruktiven Ingenieurbau<. Ziel ist die Entwicklung einer netzwerkbasierten Kooperationsplattform zur Unterstützung von Ingenieurplanungen. Methodische Grundlagen hierfür stellen die Petri-Netze mit individuellen Marken in Verbindung mit einer semantischen Informationsbewertung dar. Der Beitrag zeigt an einem Beispiel die grundlegenden Möglichkeiten der Petri-Netze auf und stellt die Steuerung der Planungsprozesse aufgrund von Metainformationen dar. Darüber hinaus wird der Ansatz verfolgt, auf der Basis bauteilorientierter Prozessmuster für geotechnische Konstruktionselemente den veränderlichen Prozessablauf zu erfassen. Abschließend wird ein Weg zur Implementierung gezeigt.
description: Internationales Kolloquium über Anwendungen der Informatik und Mathematik in Architektur und Bauwesen : 10. bis 12.06.2003, Bauhaus-Universität Weimar, vol. 16, 2003
Ursodeoxycholic acid is associated with a reduction in SARS‐CoV‐2 infection and reduced severity of COVID‐19 in patients with cirrhosis
Creators: name: Brevini, Teresa
name: Chin, Allison M.
name: Kaplan, David E.
name: Sampaziotis, Fotios
name: Webb, Gwilym
name: Dahman, Bassam
name: Mahmud, Nadim
name: Chao, Hann‐Hsiang
name: Bastaich, Dustin
name: Taddei, Tamar H.
name: Serper, Marina
name: Deng, Yangyang
name: Ferreira, Raphaella D.
name: John, Binu V.
name: Moon, Andrew
Publisher: name: Wiley
Year: 2023

description:
BACKGROUND AND AIMS: Studies have demonstrated that reducing farnesoid X receptor activity with ursodeoxycholic acid (UDCA) downregulates angiotensin-converting enzyme in human lung, intestinal and cholangiocytes organoids in vitro, in human lungs and livers perfused ex situ, reducing internalization of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) into the host cell. This offers a potential novel target against coronavirus disease 2019 (COVID-19). The objective of our study was to compare the association between UDCA exposure and SARS-CoV-2 infection, as well as varying severities of COVID-19, in a large national cohort of participants with cirrhosis. METHODS: In this retrospective cohort study among participants with cirrhosis in the Veterans Outcomes and Costs Associated with Liver cohort, we compared participants with exposure to UDCA, with a propensity score (PS) matched group of participants without UDCA exposure, matched for clinical characteristics, and vaccination status. The outcomes included SARS-CoV-2 infection, symptomatic, at least moderate, severe, or critical COVID-19, and COVID-19-related death. RESULTS: We compared 1607 participants with cirrhosis who were on UDCA, with 1607 PS-matched controls. On multivariable logistic regression, UDCA exposure was associated with reduced odds of developing SARS-CoV-2 infection (adjusted odds ratio [aOR] 0.54, 95% confidence interval [CI] 0.41-0.71, p < 0.0001). Among patients who developed COVID-19, UDCA use was associated with reduced disease severity, including symptomatic COVID-19 (aOR 0.54, 95% CI 0.39-0.73, p < 0.0001), at least moderate COVID-19 (aOR 0.51, 95% CI 0.32-0.81, p = 0.005), and severe or critical COVID-19 (aOR 0.48, 95% CI 0.25-0.94, p = 0.03). CONCLUSIONS: In participants with cirrhosis, UDCA exposure was associated with both a decrease in SARS-CoV-2 infection, and reduction in symptomatic, at least moderate, and severe/critical COVID-19.
Motivational Profile as a Predictor of Physical Activity Among US Adults During the Early Months of the COVID-19 Pandemic: A Daily Diary Study.
Creators: name: Nuss, Kayla
name: Li, Kaigang
name: Moore, Kristen N
name: Do, Bridgette
name: Courtney, Jimikaye B
name: Graham, Dan J
name: Dunton, Genevieve F
name: Wang, Shirlene D
Publisher: name: Human Kinetics
Year: 2023

description:
This study used a daily diary approach to examine associations between day-level physical activity (PA) behavior, PA-specific motivational profile, and days since the COVID-19 national emergency declaration during the early months (April-June 2020) of the pandemic. A total of 468 US adults (Mage = 34.8 y, 79% female) participated in a 28-day smartphone-based daily diary study assessing PA. A baseline survey assessed PA and motivation for PA using the Behavioral Regulation in Exercise Questionnaire. Multilevel linear regression models examined the main effects and interactions of motivational profile and time (days since the US March 13, 2020, COVID-19 national emergency declaration) on daily PA minutes. Latent profile analysis identified 4 distinct motivational profiles for PA among this sample: profile 1: high amotivation (n = 100, 21%); profile 2: low controlled motivation (n = 55, 12%); profile 3: high external regulation (n = 47, 10%); and profile 4: moderate autonomous motivation (n = 266, 57%). After controlling for baseline PA, there were significant interactions between profile and time on daily PA (-0.21, P < .01). Profile 2 showed greater decreases in daily PA minutes over time than profile 1 (b = -0.29, P < .01). Profiles 3 and 4 did not indicate significant decreases in PA compared with profile 1 (b = 0.14, P = .31 and b = -0.16, P = .05, respectively). Contrary to previous research, individuals with lower controlled or moderate autonomous motivation demonstrated the largest decreases in PA over time, whereas individuals with higher amotivation or external regulation demonstrated smaller decreases over time. These findings suggest that external motivation may have provided short-term protection against declines in PA observed during early months of the COVID-19 pandemic.
Epoicocladius ephemerae
Creators: name: Stasiukynas, Laurynas
name: Laurindo da Silva, Fabio
name: Havelka, Jekaterina
name: Podėnas, Sigitas
name: Lekoveckaitė, Aistė
Publisher: name: Zenodo
Year: 2024
Subjects: Biodiversity
Taxonomy
Animalia
Arthropoda
Insecta
Diptera
Chironomidae
Epoicocladius
Epoicocladius ephemerae

description: Epoicocladius ephemerae (Kieffer, 1924)
Notes
Morpho identification. First record for Lithuania (Virbickas and Pliūraitė 2002).
description: Published as part of Stasiukynas, Laurynas, Laurindo da Silva, Fabio, Havelka, Jekaterina, Podėnas, Sigitas & Lekoveckaitė, Aistė, 2024, Chironomidae (Diptera) of the Šventoji and Žeimena sub-basins in Lithuania, pp. e 130218 in Biodiversity Data Journal 12 on page e130218, DOI: 10.3897/BDJ.12.e130218
Predicting Tropical Cyclone‐Induced Sea Surface Temperature Responses Using Machine Learning
Creators: name: Gu, Xiaowei
name: Tang, Danling
name: Sui, Yi
name: Cui, Hongxing
name: Liu, Hongbin
name: Mei, Wei
Publisher: name: American Geophysical Union (AGU)
Year: 2023

description:
This study proposes to construct a model using random forest method, an efficient machine learning‐based method, to predict the spatial structure and temporal evolution of the sea surface temperature (SST) cooling induced by northwest Pacific tropical cyclones (TCs), a process of the so‐called wind pump. The predictors in use include 12 predictors related to TC characteristics and pre‐storm ocean conditions. The model is shown to skillfully predict the spatiotemporal evolutions of the cold wake generated by TCs of different intensity groups, and capture the cross‐case variance in the observed SST response. Another model is further built based on the same method to assess the relative importance of the 12 predictors in determining the magnitude of the maximum cooling. Computations of feature scores of those predictors show that TC intensity, translation speed and size, and pre‐storm mixed layer depth and SST dominate, depending on the area where the cooling is considered. Plain Language Summary While many studies have been devoted to understanding the processes and mechanisms underlying the sea surface temperature (SST) cooling induced by tropical cyclones (TCs), few studies have attempted to predict the spatial and temporal evolution of the sea surface temperature (SST) cooling triggered by TCs. In this study, we proposed to achieve this goal by building a model using an efficient and robust machine learning‐based method. The constructed model uses 12 predictors associated with TC characteristics (e.g., intensity, and translation speed) and pre‐storm ocean states (e.g., mixed layer depth). The model performs well in producing the TC‐induced spatial structure and temporal evolution of the cold wake and can capture most of the variance in the observed SST response. We quantified the relative importance of the 12 predictors, and found that TC intensity, translation speed and size, and pre‐storm mixed layer depth and SST dominate in deciding the magnitude of the SST response. The results and proposed method have important implications for predicting the response of ocean primary production to the TC wind pump effects. Key Points A machine learning‐based model is built to predict the spatiotemporal evolution of the tropical cyclone‐induced sea surface temperature response The model well predicts the spatial structure and temporal evolution of the observed response and captures the observed cross‐case variance Feature scores are computed to assess the relative importance of the predictors in determining the magnitude of the SST response
Spectral projections correlation structure for short-to-long range dependent processes
Creators: name: Patie, Pierre
name: Srapionyan, Anna
Publisher: name: arXiv
Year: 2019
Subjects: subject: Probability (math.PR)
subject: Statistics Theory (math.ST)
subject: FOS: Mathematics

description: Let $\mathbf{X}=(\mathbf{X}_t)_{t \geq 0}$ be a stochastic process issued from $x \in \mathbb R$ that admits a marginal stationary measure $ν$, i.e. $ν\mathbf{P}_t f = νf$ for all $t \geq 0$, where $\mathbf{P}_t f(x)= \mathbb{E}_x[f(\mathbf{X}_t)]$. In this paper, we introduce the (resp. biorthogonal) spectral projections correlation functions which are expressed in terms of projections into the eigenspaces of $\mathbf{P}_t$ (resp. and of its adjoint in the weighted Hilbert space $L^2(ν)$). We obtain closed-form expressions involving eigenvalues, the condition number and/or the angle between the projections in the following different situations: when $\mathbf{X}=X$ with $X=(X_t)_{t \geq 0}$ is a Markov process, $\mathbf{X}$ is the subordination of $X$ in the sense of Bochner, and $\mathbf X$ is a non-Markovian process which is obtained by time-changing $X$ with an inverse of a subordinator. It turns out that these spectral projections correlation functions have different expressions with respect to these classes of processes which enables to identify substantial and deep properties about their dynamics. This interesting fact can be used to design original statistical tests to make inferences, for example, about the path properties of the process (presence of jumps), distance from symmetry (self-adjoint or non-self-adjoint) and short-to-long-range dependence. To reveal the usefulness of our results, we apply them to a class of non-self-adjoint Markov semigroups studied in Patie and Savov [28], and then time-change by subordinators and their inverses.
A Novel Approach to Quantum Gravity in the Presence of Matter without the Problem of Time
Creators: name: Pavšič, Matej
Publisher: name: arXiv
Year: 2019
Subjects: subject: General Physics (physics.gen-ph)
subject: FOS: Physical sciences

description: An approach to the quantization of gravity in the presence matter is examined which starts from the classical Einstein-Hilbert action and matter approximated by "point" particles minimally coupled to the metric. Upon quantization, the Hamilton constraint assumes the form of the Schrödinger equation: it contains the usual Wheeler-DeWitt term and the term with the time derivative of the wave function. In addition, the wave function also satisfies the Klein-Gordon equation, which arises as the quantum counterpart of the constraint among particles' momenta. Comparison of the novel approach with the usual one in which matter is represented by scalar fields is performed, and shown that those approaches do not exclude, but complement each other. In final discussion it is pointed out that the classical matter could consist of superparticles or spinning particles, described by the commuting and anticommuting Grassmann coordinates, in which case spinor fields would occur after quantization.
description: 30 pages; Published version (improved text, references added)
Discovery of a First-in-Class Small-Molecule Ligand for WDR91 Using DNA-Encoded Chemical Library Selection Followed by Machine Learning
Creators: name: Seitova, Alma
name: Cuozzo, John W.
name: Brown, Peter J.
name: Feng, Jianwen A.
name: Ghiabi, Pegah
name: Hutchinson, Ashley
name: Dong, Aiping
name: Li, Yanjun
name: Ackloo, Suzanne
name: Keefe, Anthony D.
name: Santhakumar, Vijayaratnam
name: Ahmad, Shabbir
name: Zhang, Ying
name: von Rechenberg, Moritz
name: Li, Yen-Yen
name: Halabelian, Levon
name: Zeng, Hong
name: Bolotokova, Albina
name: Clark, Matthew A.
name: Guié, Marie-Aude
name: Cerruti, Thomas
name: Loppnau, Peter
name: Centrella, Paolo A.
name: Xu, Jin
name: Guilinger, John P.
Publisher: name: American Chemical Society (ACS)
Year: 2023

description:
WD40 repeat-containing protein 91 (WDR91) regulates early-to-late endosome conversion and plays vital roles in endosome fusion, recycling, and transport. WDR91 was recently identified as a potential host factor for viral infection. We employed DNA-encoded chemical library (DEL) selection against the WDR domain of WDR91, followed by machine learning to predict ligands from the synthetically accessible Enamine REAL database. Screening of predicted compounds identified a WDR91 selective compound 1, with a KD of 6 ± 2 μM by surface plasmon resonance. The co-crystal structure confirmed the binding of 1 to the WDR91 side pocket, in proximity to cysteine 487, which led to the discovery of covalent analogues 18 and 19. The covalent adduct formation for 18 and 19 was confirmed by intact mass liquid chromatography-mass spectrometry. The discovery of 1, 18, and 19, accompanying structure-activity relationship, and the co-crystal structures provide valuable insights for designing potent and selective chemical tools against WDR91 to evaluate its therapeutic potential.
Anderson localization for electric quantum walks and skew-shift CMV matrices
Creators: name: Cedzich, C.
name: Werner, A. H.
Publisher: name: arXiv
Year: 2019
Subjects: subject: Mathematical Physics (math-ph)
subject: Dynamical Systems (math.DS)
subject: Spectral Theory (math.SP)
subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences
subject: FOS: Mathematics

description: We consider the spectral and dynamical properties of one-dimensional quantum walks placed into homogenous electric fields according to a discrete version of the minimal coupling principle. We show that for all irrational fields the absolutely continuous spectrum of these systems is empty, and prove Anderson localization for almost all (irrational) fields. This result closes a gap which was left open in the original study of electric quantum walks: a spectral and dynamical characterization of these systems for typical fields. Additionally, we derive an analytic and explicit expression for the Lyapunov exponent of this model. Making use of a connection between quantum walks and CMV matrices our result implies Anderson localization for CMV matrices with a particular choice of skew-shift Verblunsky coefficients as well as for quasi-periodic unitary band matrices.
description: 18 pages, 2 figures
A fully parametric non-stationary spectral-based stochastic ground motion model
Creators: name: Vlachos, Christos
name: Deodatis, George
name: Papakonstantinou, Konstantinos G.
Publisher: name: The University of British Columbia
Year: 2015

description: A novel strong ground motion stochastic model is formulated in association with physically interpretable parameters that are capable of efficiently characterizing the complex evolutionary nature of the phenomenon. A multi-modal, analytical, fully non-stationary spectral version of the Kanai-Tajimi model is introduced achieving a realistic description of the evolutionary spectral energy distribution of the seismic ground motions. The functional forms describing the temporal evolution of the model parameters can effectively model complex highly non-stationary power spectral characteristics. The analysis space, where the analytical forms describing the evolution of the model parameters are established, is the energy domain instead of the typical use of the time domain. The Spectral Representation Method facilitates the simulation of sample model realizations.
Supplementary document for Unsupervised Fourier-inspired neural network for real-time and high-fidelity computer-generated holography - 6210703.pdf
Creators: name: Dong, Zhenxing
name: Xu, Chao
name: Ling, Yuye
name: Li, Yan
name: Su, Yikai
Publisher: name: Optica Publishing Group
Year: 2025
Subjects: Uncategorized

description: Supplement 1
Development of an interpretable machine learning-based intelligent system of exercise prescription for cardio-oncology preventive care: A study protocol
Creators: name: Tao, Xiaoyu
name: Chen, Weiming
name: Gao, Tianyu
name: Xu, Yuming
name: Jing, Fengshi
name: Ren, Hao
name: Liang, Deyi
name: He, Shan
name: Chen, Kecheng
name: Xu, Zhongzhi
name: Dong, Heling
name: Zhu, Yuxin
name: Wang, Yufan
name: Cheng, Weibin
Publisher: name: Frontiers
Year: 2023

description:
Background: Cardiovascular disease (CVD) and cancer are the first and second causes of death in over 130 countries across the world. They are also among the top three causes in almost 180 countries worldwide. Cardiovascular complications are often noticed in cancer patients, with nearly 20% exhibiting cardiovascular comorbidities. Physical exercise may be helpful for cancer survivors and people living with cancer (PLWC), as it prevents relapses, CVD, and cardiotoxicity. Therefore, it is beneficial to recommend exercise as part of cardio-oncology preventive care. Objective: With the progress of deep learning algorithms and the improvement of big data processing techniques, artificial intelligence (AI) has gradually become popular in the fields of medicine and healthcare. In the context of the shortage of medical resources in China, it is of great significance to adopt AI and machine learning methods for prescription recommendations. This study aims to develop an interpretable machine learning-based intelligent system of exercise prescription for cardio-oncology preventive care, and this paper presents the study protocol. Methods: This will be a retrospective machine learning modeling cohort study with interventional methods (i.e., exercise prescription). We will recruit PLWC participants at baseline (from 1 January 2025 to 31 December 2026) and follow up over several years (from 1 January 2027 to 31 December 2028). Specifically, participants will be eligible if they are (1) PLWC in Stage I or cancer survivors from Stage I; (2) aged between 18 and 55 years; (3) interested in physical exercise for rehabilitation; (4) willing to wear smart sensors/watches; (5) assessed by doctors as suitable for exercise interventions. At baseline, clinical exercise physiologist certificated by the joint training program (from 1 January 2023 to 31 December 2024) of American College of Sports Medicine and Chinese Association of Sports Medicine will recommend exercise prescription to each participant. During the follow-up, effective exercise prescription will be determined by assessing the CVD status of the participants. Expected outcomes: This study aims to develop not only an interpretable machine learning model to recommend exercise prescription but also an intelligent system of exercise prescription for precision cardio-oncology preventive care. Ethics: This study is approved by Human Experimental Ethics Inspection of Guangzhou Sport University. Clinical trial registration: http://www.chictr.org.cn, identifier ChiCTR2300077887.