cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
title: Reorganisationspotentiale im Bauwesen durch Nutzung mobiler Informations- & Kommunikationstechnologien
Creators: name: Menzel, Karsten
name: Schach, Reiner
name: Scherer, Raimar J.
Publisher: name: Bauhaus-Universität Weimar
Year: 2003
Subjects: subject: Baubetrieb
subject: Unternehmen / Organisation
subject: Internet
subject: 620

description: Die Verfügbarkeit und die sichere Beherrschung moderner und kostengünstiger Informations- und Kommunikationstechnologien gestattet es auch kleinen unternehmerischen Einheiten im Bauwesen sich in betriebsübergreifenden Netzwerken zu organisieren und sich besser in die Wertschöpfungskette am Bau zu integrieren. In sogenannten >Virtuellen Organisationen< (VO) können diese für die Volkswirtschaft wichtigen Unternehmen ihre Wettbewerbsvorteile wie höhere Flexibilität, schnelle Reaktion auf Kundenwünsche und Marktnähe nutzen und somit ihr langfristiges Bestehen in einem liberalen Wettbewerb auf einem erweiterten EU-Markt sichern und ausbauen. Die derzeit existierenden Hindernisse im Informationsfluss zwischen Baustelle und Büro können durch den Einsatz mobiler, funkvernetzter Endgeräte, wie beispielsweise >Smart-Phones<, und einer neu zu gestaltenden Infrastruktur zum Wissensmanagement und zur kontextsensitiven Informationsdarstellung abgebaut werden. Im Rahmen dieser Veröffentlichung werden konzeptionelle Ansätze eines integrierten Informationsmanagements zur Unterstützung von VO, die im Rahmen des BMBF-Projektes >IuK-System Bau< derzeit entwickelt werden, vorgestellt.
description: Internationales Kolloquium über Anwendungen der Informatik und Mathematik in Architektur und Bauwesen : 10. bis 12.06.2003, Bauhaus-Universität Weimar, vol. 16, 2003
A Machine Learning-Based Analytic Pipeline Applied to Clinical and Serum IgG Immunoproteome Data To Predict Chlamydia trachomatis Genital Tract Ascension and Incident Infection in Women
Creators: name: Mokashi, Neha Vivek
name: Hufnagel, Katrin
name: Darville, Toni
name: Waterboer, Tim
name: Zheng, Xiaojing
name: Liu, Chuwen
name: Sun, Xuejun
name: O’Connell, Catherine M.
Publisher: name: American Society for Microbiology
Year: 2023

description:
We developed a reusable and open-source machine learning (ML) pipeline that can provide an analytical framework for rigorous biomarker discovery. We implemented the ML pipeline to determine the predictive potential of clinical and immunoproteome antibody data for outcomes associated with Chlamydia trachomatis (Ct) infection collected from 222 cis-gender females with high Ct exposure. We compared the predictive performance of 4 ML algorithms (naive Bayes, random forest, extreme gradient boosting with linear booster [xgbLinear], and k-nearest neighbors [KNN]), screened from 215 ML methods, in combination with two different feature selection strategies, Boruta and recursive feature elimination. Recursive feature elimination performed better than Boruta in this study. In prediction of Ct ascending infection, naive Bayes yielded a slightly higher median value of are under the receiver operating characteristic curve (AUROC) 0.57 (95% confidence interval [CI], 0.54 to 0.59) than other methods and provided biological interpretability. For prediction of incident infection among women uninfected at enrollment, KNN performed slightly better than other algorithms, with a median AUROC of 0.61 (95% CI, 0.49 to 0.70). In contrast, xgbLinear and random forest had higher predictive performances, with median AUROC of 0.63 (95% CI, 0.58 to 0.67) and 0.62 (95% CI, 0.58 to 0.64), respectively, for women infected at enrollment. Our findings suggest that clinical factors and serum anti-Ct protein IgGs are inadequate biomarkers for ascension or incident Ct infection. Nevertheless, our analysis highlights the utility of a pipeline that searches for biomarkers and evaluates prediction performance and interpretability. IMPORTANCE Biomarker discovery to aid early diagnosis and treatment using machine learning (ML) approaches is a rapidly developing area in host-microbe studies. However, lack of reproducibility and interpretability of ML-driven biomarker analysis hinders selection of robust biomarkers that can be applied in clinical practice. We thus developed a rigorous ML analytical framework and provide recommendations for enhancing reproducibility of biomarkers. We emphasize the importance of robustness in selection of ML methods, evaluation of performance, and interpretability of biomarkers. Our ML pipeline is reusable and open-source and can be used not only to identify host-pathogen interaction biomarkers but also in microbiome studies and ecological and environmental microbiology research.
Intertwining certain fractional derivatives
Creators: name: Patie, Pierre
name: Simon, Thomas
Publisher: name: arXiv
Year: 2010
Subjects: subject: Probability (math.PR)
subject: FOS: Mathematics
subject: 60G18, 60G51, 60J25, 26A33, 33E12

description: We obtain an intertwining relation between some Riemann-Liouville operators of order a in (1,2) connecting through a certain multiplicative identity in law the one-dimensional marginals of reflected completely asymmetric a-stable Lévy processes. An alternative approach based on recurrent extensions of positive self-similar Markov processes and exponential functionals of Lévy processes is also discussed.
title: Finite Element Approximation auf der Basis geometrischer Zellen
Creators: name: Milbradt, Peter
name: Schwöppe, Axel
Publisher: name: Bauhaus-Universität Weimar
Year: 2003
Subjects: subject: Finite-Elemente-Methode
subject: Approximation
subject: 620

description: Die Methode der Finiten Elemente ist ein numerisches Verfahren zur Interpolation vorgegebener Werte und zur numerischen Approximation von Lösungen stationärer oder instationärer partieller Differentialgleichungen bzw. Systemen partieller Differentialgleichungen. Grundlage dieser Verfahren ist die Formulierung geeigneter Finiter Elemente und Finiter Element Zerlegungen. Finite Elemente besitzen in der Regel eine geometrische Basis bestehend aus Strecken im eindimensionalen, Drei- oder Vierecken im zweidimensionalen und Tetra- oder Hexaedern im dreidimensionalen euklidischen Raum, eine Menge von Freiheitsgraden und eine Basis von Funktionen. Die geometrische Basis eines Finiten Elements wird verallgemeinert als geometrische Zelle formuliert. Diese geschlossene geometrische Formulierung führt zu einer geometrieunabhängigen Definition der Basisfunktionen eines Finiten Elements in den Zellkoordinaten der geometrischen Zelle. Finite Elemente auf der Basis geometrischer Zellen werden als Bestandteile Finiter Element Zerlegungen in Finiten Element Interpolationen und Finiten Element Approximationen verwendet. Die Finiten Element Approximationen werden am Beispiel der 2-dimensionalen Diffusionsgleichung über das Standard-Galerkin-Verfahren ermittelt.
description: Internationales Kolloquium über Anwendungen der Informatik und Mathematik in Architektur und Bauwesen : 10. bis 12.06.2003, Bauhaus-Universität Weimar, vol. 16, 2003
Acricotopus lucens
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
Acricotopus
Acricotopus lucens

description: Acricotopus lucens (Zetterstedt, 1850)
Notes
Morpho-molecular identification (GenBank ID: PQ 458072). New record for Lithuania.
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
title: Stabilisierte Finite Elemente in der Hydrodynamik
Creators: name: Milbradt, Peter
Publisher: name: Bauhaus-Universität Weimar
Year: 2003
Subjects: subject: Hydrodynamik
subject: Finite-Elemente-Methode
subject: 620

description: Hydro- und morphodynamischen Prozesse in Binnengewässern und im Küstennahbereich erzeugen hochkomplexe Phänomene. Zur Beurteilung der Entwicklung von Küstenzohnen, von Flussbetten sowie von Eingriffen des Menschen in Form von Schutzbauwerken sind geeignete numerische Modellwerkzeuge notwendig. Es wird ein holistischer Modellansatz zur Approximation gekoppelter Seegangs-, Strömungs- und Morphodynamischer Prozesse auf der Basis stabilisierter Finiter Elemente vorgestellt. Der Großteil der Modellgleichungen der Hydro- und Morphodynamik sind Transportgleichungen. Dem Transportcharakter dieser Gleichungen entsprechend wird ein stabilisiertes Finites Element Verfahren auf Dreiecken vorgestellt. Die vorgestellte Approximation entspricht einem streamline upwinding Petrov-Galerkin-Verfahrens für vektorwertige mehrdimensionale Probleme, bei dem der Fehler eines Standard-Galerkin-Verfahrens mit Hilfe eines Upwinding-Koeffizienten minimiert wird. Die Wahl des Upwinding-Koeffizienten ist übertragbar auf andere Problemklassen und basiert ausschließlich auf dem Charakter der zugrundeliegene Das Modell wurde für Seegangs- und Strömungs-Untersuchungen im Jade-Weser-Ästuar an der deutschen Nordseeküste eingesetzt.
description: Internationales Kolloquium über Anwendungen der Informatik und Mathematik in Architektur und Bauwesen : 10. bis 12.06.2003, Bauhaus-Universität Weimar, vol. 16, 2003
Risk Factors for Respiratory Viral Infections: A Spotlight on Climate Change and Air Pollution
Creators: name: Burbank, Allison J
Publisher: name: Taylor & Francis
Year: 2023

description:
Climate change has both direct and indirect effects on human health, and some populations are more vulnerable to these effects than others. Viral respiratory infections are most common illnesses in humans, with estimated 17 billion incident infections globally in 2019. Anthropogenic drivers of climate change, chiefly the emission of greenhouse gases and toxic pollutants from burning of fossil fuels, and the consequential changes in temperature, precipitation, and frequency of extreme weather events have been linked with increased susceptibility to viral respiratory infections. Air pollutants like nitrogen dioxide, particulate matter, diesel exhaust particles, and ozone have been shown to impact susceptibility and immune responses to viral infections through various mechanisms, including exaggerated or impaired innate and adaptive immune responses, disruption of the airway epithelial barrier, altered cell surface receptor expression, and impaired cytotoxic function. An estimated 90% of the world's population is exposed to air pollution, making this a topic with high relevance to human health. This review summarizes the available epidemiologic and experimental evidence for an association between climate change, air pollution, and viral respiratory infection.
A small and non-simple geometric transition
Creators: name: Rossi, Michele
Publisher: name: arXiv
Year: 2012
Subjects: subject: Algebraic Geometry (math.AG)
subject: FOS: Mathematics
subject: 14B07, 32G10, 14E15, 14J32, 14J27

description: Following notation introduced in the recent paper \cite{Rdef}, this paper is aimed to present in detail an example of a "small" geometric transition which is not a "simple" one i.e. a deformation of a conifold transition. This is realized by means of a detailed analysis of the Kuranishi space of a Namikawa cuspidal fiber product, which in particular improves the conclusion of Y.~Namikawa in Remark 2.8 and Example 1.11 of \cite{N}. The physical interest of this example is presenting a geometric transition which can't be immediately explained as a massive black hole condensation to a massless one, as described by A.~Strominger \cite{Strominger95}.
description: 22 pages. v2: final version to appear in Mathematical Physics, Analysis and Geometry. Minor changes: title, abstract, result in Remark 3 emphasized by Theorem 5, as suggested by a referee. Some typos corrected
Seismic risk assessment of mega-thrust Mw9-class subduction earthquakes and aftershocks in Victoria, British Columbia, Canada using multi-variate seismic demand models
Creators: name: Goda, Katsuichiro
name: Tesfamariam, Solomon
Publisher: name: The University of British Columbia
Year: 2015

description: This study extends current seismic demand estimation methods based on incremental dynamic analysis by characterizing dependence among different engineering demand parameters using copulas explicitly. The developed method is applied to a 4-story non-ductile reinforced concrete frame in Victoria, British Columbia, Canada. The developed multi-variate seismic demand models are integrated with a story-based damage-loss model to assess the seismic risk due to different earthquake loss generation modes (i.e. non-collapse repairs, collapse, and demolition). Results obtained from this study indicate that the effects of multi-variate seismic demand modeling on the expected seismic loss ratios are significant. The critical information is the limit state threshold for demolition. In addition, consideration of a realistic dependence structure of maximum and residual inter-story drift ratios can be important for seismic loss estimation as well as for multi-criteria seismic performance evaluation.
PeakDecoder enables machine learning-based metabolite annotation and accurate profiling in multidimensional mass spectrometry measurements
Creators: name: Gao, Yuqian
name: Baker, Erin S.
name: Poorey, Kunal
name: Tanjore, Deepti
name: Kim, Joonhoon
name: Oksen, Ethan
name: Tsalenko, Anya
name: Munoz, Nathalie
name: Deng, Shuang
name: Orton, Daniel J.
name: Magnuson, Jon K.
name: Gee, Aaron
name: Gardner, James
name: Wilton, Rosemarie
name: Fasani, Rick A.
name: Bilbao, Aivett
name: Michener, Joshua K.
name: Burnum-Johnson, Kristin E.
name: Smith, Richard D.
name: Petzold, Christopher J.
name: Pomraning, Kyle R.
name: Burnet, Meagan
name: Kim, Young-Mo
name: Apffel, Alex
name: Weitz, Karl
name: Nicora, Carrie D.
name: Dai, Ziyu
name: Gladden, John M.
Publisher: name: Springer Nature
Year: 2023

description:
Multidimensional measurements using state-of-the-art separations and mass spectrometry provide advantages in untargeted metabolomics analyses for studying biological and environmental bio-chemical processes. However, the lack of rapid analytical methods and robust algorithms for these heterogeneous data has limited its application. Here, we develop and evaluate a sensitive and high-throughput analytical and computational workflow to enable accurate metabolite profiling. Our workflow combines liquid chromatography, ion mobility spectrometry and data-independent acquisition mass spectrometry with PeakDecoder, a machine learning-based algorithm that learns to distinguish true co-elution and co-mobility from raw data and calculates metabolite identification error rates. We apply PeakDecoder for metabolite profiling of various engineered strains of Aspergillus pseudoterreus, Aspergillus niger, Pseudomonas putida and Rhodosporidium toruloides. Results, validated manually and against selected reaction monitoring and gas-chromatography platforms, show that 2683 features could be confidently annotated and quantified across 116 microbial sample runs using a library built from 64 standards.
Improved probability distribution models for seismic fragility assessment
Creators: name: Qin, Jianjun
name: Mackie, Kevin R.
name: Stojadinovic, Bozidar
Publisher: name: The University of British Columbia
Year: 2015

description: The paper presents a new formulation for the probabilistic modeling of the variables to reduce the errors between the model and the available data sets and to facilitate seismic fragility assessment. Traditionally, one probability distribution, e.g., lognormal distribution, is adopted to describe one variable throughout the domain of values. However, there are potential errors in the probability content, especially in the high tail. The consequences of such tail sensitivity are particularly detrimental in fragility assessment when the limit states under consideration result in small probabilities of failure. To address the tail sensitivity problem, the data sets of the variables are divided into two parts, i.e., bulk and high tail. Each part is considered separately for the probabilistic modeling and integrated into one continuous distribution for fragility analysis. For illustration purposes, probabilistic seismic assessment of a typical reinforced concrete bridge column is compared using the proposed framework and compared to the results based only on lognormal random variable distributions. Results show that for complementary cumulative distribution function (CCDF), the difference may reach one or more magnitudes; for limit states that exercise the tails of the random variable distributions, the difference in the fragility estimates can increase with the hazard level.
Thoracic endometriosis syndrome: a rare cause of pneumothorax in young women
Creators: name: Etxano, Jon
Publisher: name: EURORAD
Year: 2016
Subjects: subject: Lung
subject: CT
subject: MR
subject: Plain radiographic studies
subject: Diagnostic procedure
subject: Pathology

description: Clinical History Image Findings Discussion Find Diagnosis Differential Diagnosis
description: female, 29 years
description: Clinical History: A 29 year old smoker woman came to our emergency department with right thoracic pain and dyspnea. Auscultation revealed hypophonesis on right hemithorax.The patient did not present fever, cough or other symptoms. Final Diagnosis: Thoracic endometriosis with catamenial pneumothorax
Archival snapshot of: Systems Science Education & Knowledge Engineering group (2022-2024)
Creators: name: Many participants over the years
name: Young, Rob
name: Smerald, Chris
name: Mobus, George
name: Thornton, Shingai
name: Friedman, Daniel
Publisher: name: Self
Year: 2024

description: This is a downloaded version of the Coda document here https://coda.io/d/Education-Knowledge-Engineering_doO72TniKUt/Overview-Welcome_suFlqzL2#_lu-KWjiu  which was used as a collaborative workspace for Systems Science related meetings from ~September 2022 to November 2024.

Please note the informal nature of this archival snapshot of a living, multi-author, heterogenous document.
Precision Medicine-Based Machine Learning Analyses to Explore Optimal Exercise Therapies for Individuals With Knee Osteoarthritis: Random Forest-Informed Tree-Based Learning.
Creators: name: Arbeeva, Liubov
name: Nelson, Amanda E
name: Allen, Kelli D
name: Kosorok, Michael R
name: Schwartz, Todd A
name: Kim, Siyeon
name: Callahan, Leigh F
name: Golightly, Yvonne M
Publisher: name: The Journal of Rheumatology
Year: 2023

description:
OBJECTIVE: We applied a precision medicine-based machine learning approach to discover underlying patient characteristics associated with differential improvement in knee osteoarthritis symptoms following standard physical therapy (PT), internet-based exercise training (IBET), and a usual care/wait list control condition. METHODS: Participants (n = 303) were from the Physical Therapy vs Internet-Based Training for Patients with Knee Osteoarthritis trial. The primary outcome was the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) total score at 12-month follow-up. Random forest-informed tree-based learning was applied to identify patient characteristics that were critical to improving outcomes, and patients with those features were grouped. RESULTS: Age, BMI, and Brief Fear of Movement (BFOM) score, all at baseline, were identified as characteristics that effectively divided participants, creating 6 subgroups. Assigning treatments according to these models, compared to assigning a single best treatment to all patients, resulted in greater improvements of the average WOMAC at 12 months (P = 0.01). Key patterns were that IBET was the optimal treatment for patients of younger age and low BFOM, whereas PT was the optimal treatment for patients of older age, high BFOM, and BMI (kg/m2) between 26.3 and 37.2. CONCLUSION: These results suggest that easily assessed patient characteristics including age, fear of movement, and BMI could be used to guide patients toward either home-based exercise or PT, though additional studies are needed to confirm these findings. (ClinicalTrials.gov: NCT02312713).
title: Implementierung eines webbasierten Talsperren-Monitoring-Systems
Creators: name: Mittrup, Ingo
name: Smarsly, Kay
name: Hartmann, Dietrich
Publisher: name: Bauhaus-Universität Weimar
Year: 2003
Subjects: subject: Talsperre
subject: Bauwerksüberwachung
subject: Internet
subject: 620

description: Die Bauwerksüberwachung gewinnt aus sicherheitstechnischen sowie aus wirtschaftlichen Gründen zunehmend an Bedeutung. Nicht nur die Bauwerkssicherheit kann durch leistungsfähige Monitoring-Systeme angemessen beurteilt, auch die Nutzungsdauer bestehender Bauwerke kann durch die gewonnenen Informationen deutlich verlängert werden. Das vorliegende Papier beschreibt die Entwicklung eines webbasierten Talsperren-Monitoring-Systems, das die automatisierte Erfassung von Daten vor Ort sowie die computergestützte Aufbereitung und Analyse der gesammelten Messdaten ermöglicht. Das Monitoring-System ist durch seinen modularen Aufbau nicht auf die Talsperren-Überwachung beschränkt, sondern kann ohne großen Aufwand an andere Überwachungsaufgaben angepasst werden. Das System besteht aus drei wesentlichen Modulen: (i) einer erweiterbaren Klassenbibliothek, die die Steuerung der im Bauwerk installierten Messelektronik ermöglicht, (ii) einem webbasierten Datenerfassungsmodul, das neben der automatischen Datenerfassung eine Fernsteuerung der Messelektronik erlaubt und Funktionen zur Verwaltung der Überwachungsaufgaben bereitstellt, sowie (iii) einem webbasierten Visualisierungs- und Auswertungsmodul zur Aufbereitung und Analyse der gesammelten Daten. Alle an der Überwachung beteiligten Mitarbeiter können mit einem üblichen Web-Browser über das Internet auf das entwickelte System zugreifen; ein Zugriff mittels Mobiltelefon ist alternativ möglich. Das implementierte Talsperren-Monitoring-System begleitet die beteiligten Fachleute von der Erfassung der Daten vor Ort bis hin zur Aufbereitung und Analyse der Messdaten an zentraler Stelle: Die Mitarbeiter werden durch einen einfachen Zugriff auf die installierte Messelektronik, automatisierte Messungen und umfangreiche Analysefunktionalitäten bei ihren spezifischen Aufgaben unterstützt. Der bisherige manuelle Arbeitsaufwand für Datenerfassung, -transfer und Analyse wird somit deutlich reduziert.
description: Internationales Kolloquium über Anwendungen der Informatik und Mathematik in Architektur und Bauwesen : 10. bis 12.06.2003, Bauhaus-Universität Weimar, vol. 16, 2003
A variational approach to the Brown-Ravenhall operator for the relativistic one-electron atoms
Creators: name: Zelati, Vittorio Coti
name: Nolasco, Margherita
Publisher: name: arXiv
Year: 2014
Subjects: subject: Analysis of PDEs (math.AP)
subject: Mathematical Physics (math-ph)
subject: FOS: Mathematics
subject: FOS: Physical sciences
subject: 35Q75

description: We use the Foldy--Wouthuysen (unitary) transformation to give an alternative characterization of the eigenvalues and eigenfunctions for the Brown-Ravenhall operator (the projected Dirac operator) in the case of a one-electron atom. In particular we transform the eigenvalues problem into an elliptic problem in the 4-dim half space $\mathbb{R}^4_{+}$ with Neumann boundary condition.
Intimate partner violence and suicide mortality: a cross-sectional study using machine learning and natural language processing of suicide data from 43 states
Creators: name: Moracco, Kathryn Elizabeth
name: Kafka, Julie M
name: Reyes, Luz McNaughton
name: Trangenstein, Pamela J
name: Pence, Brian W
name: Fliss, Mike Dolan
Publisher: name: BMJ
Year: 2023

description:
INTRODUCTION: Intimate partner violence (IPV) is associated with suicidal ideation, yet it remains unclear how often IPV precipitates suicide mortality. To overcome limitations with national data, we applied novel methods to: (1) document the prevalence of IPV-related suicide in the USA and (2) identify correlates for IPV-related suicide. METHODS: Using National Violent Death Reporting System data (NVDRS, 2015-2019, n=1 30 550), we recorded IPV circumstances (yes/no) by leveraging prior textual reviews of death narratives and applying a validated natural language processing tool. We could not systematically differentiate IPV perpetration versus victimisation given limited details in NVDRS. Logistic regression compared IPV-related suicides with referent group suicides (no evidence of IPV), stratified by sex. RESULTS: 7.1% of suicides were IPV related (n=9210), most were isolated suicide events (82.8%, n=7625; ie, not homicide suicide). There were higher odds of IPV circumstances when the decedent had civil legal problems (aOR for men: 3.6 (3.3 to 3.9), aOR for women: 2.6 (2.2 to 3.2)), criminal legal problems (aOR men: 2.3 (2.2 to 2.5), aOR for women: 1.7 (1.4 to 2.1)), or used a firearm (aOR men: 1.9 (1.8 to 2.0), aOR for women: 1.9 (1.7 to 2.1)). There were lower odds of IPV circumstances when the decedent had a current mental health problem (aOR men: 0.7 (0.7 to 0.8), aOR for women: 0.7 (0.6 to 0.8)). CONCLUSIONS: IPV circumstances contribute to a notable proportion of suicides. IPV-related suicides are distinct from other suicide deaths. Targeted suicide screening and intervention in IPV settings may be beneficial for prevention.
Cauchy Problem of the non-self-adjoint Gauss-Laguerre semigroups and uniform bounds of generalized Laguerre polynomials
Creators: name: Patie, Pierre
name: Savov, Mladen
Publisher: name: arXiv
Year: 2015
Subjects: subject: Probability (math.PR)
subject: Functional Analysis (math.FA)
subject: Spectral Theory (math.SP)
subject: FOS: Mathematics
subject: 47A70 47D07 47G20 47B38 46E30

description: We propose a new approach to construct the eigenvalue expansion in a weighted Hilbert space of the solution to the Cauchy problem associated to Gauss-Laguerre invariant Markov semigroups that we introduce. Their generators turn out to be natural non-self-adjoint and non-local generalizations of the Laguerre differential operator. Our methods rely on intertwining relations that we establish between these semigroups and the classical Laguerre semigroup and combine with techniques based on non-harmonic analysis. As a by-product we also provide regularity properties for the semigroups as well as for their heat kernels. The biorthogonal sequences that appear in their eigenvalue expansion can be expressed in terms of sequences of polynomials, and they generalize the Laguerre polynomials. By means of a delicate saddle point method, we derive uniform asymptotic bounds that allow us to get an upper bound for their norms in weighted Hilbert spaces. We believe that this work opens a way to construct spectral expansions for more general non-self-adjoint Markov semigroups.
description: 33 pages
Transcendental equations satisfied by the individual zeros of Riemann $ζ$, Dirichlet and modular $L$-functions
Creators: name: França, Guilherme
name: LeClair, André
Publisher: name: arXiv
Year: 2015
Subjects: subject: Number Theory (math.NT)
subject: High Energy Physics - Theory (hep-th)
subject: Mathematical Physics (math-ph)
subject: FOS: Mathematics
subject: FOS: Physical sciences
subject: 11M26

description: We consider the non-trivial zeros of the Riemann $ζ$-function and two classes of $L$-functions; Dirichlet $L$-functions and those based on level one modular forms. We show that there are an infinite number of zeros on the critical line in one-to-one correspondence with the zeros of the cosine function, and thus enumerated by an integer $n$. From this it follows that the ordinate of the $n$-th zero satisfies a transcendental equation that depends only on $n$. Under weak assumptions, we show that the number of solutions of this equation already saturates the counting formula on the entire critical strip. We compute numerical solutions of these transcendental equations and also its asymptotic limit of large ordinate. The starting point is an explicit formula, yielding an approximate solution for the ordinates of the zeros in terms of the Lambert $W$-function. Our approach is a novel and simple method, that takes into account $\arg L$, to numerically compute non-trivial zeros of $L$-functions. The method is surprisingly accurate, fast and easy to implement. Employing these numerical solutions, in particular for the $ζ$-function, we verify that the leading order asymptotic expansion is accurate enough to numerically support Montgomery's and Odlyzko's pair correlation conjectures, and also to reconstruct the prime number counting function. Furthermore, the numerical solutions of the exact transcendental equation can determine the ordinates of the zeros to any desired accuracy. We also study in detail Dirichlet $L$-functions and the $L$-function for the modular form based on the Ramanujan $τ$-function, which is closely related to the bosonic string partition function.
description: Matches the version to appear in Communications in Number Theory and Physics, based on arXiv:1407.4358 [math.NT], arXiv:1309.7019 [math.NT], and arXiv:1307.8395 [math.NT]
Estimation of a Machine Learning-Based Decision Rule to Reduce Hypoglycemia Among Older Adults With Type 1 Diabetes: A Post Hoc Analysis of Continuous Glucose Monitoring in the WISDM Study.
Creators: name: Young, Laura A
name: Kahkoska, Anna R
name: Pratley, Richard E
name: Shah, Kushal S
name: Kosorok, Michael R
name: Miller, Kellee M
name: Rickels, Michael
name: Weinstock, Ruth S
Publisher: name: SAGE Publications
Year: 2023

description:
BACKGROUND: The Wireless Innovation for Seniors with Diabetes Mellitus (WISDM) study demonstrated continuous glucose monitoring (CGM) reduced hypoglycemia over 6 months among older adults with type 1 diabetes (T1D) compared with blood glucose monitoring (BGM). We explored heterogeneous treatment effects of CGM on hypoglycemia by formulating a data-driven decision rule that selects an intervention (ie, CGM vs BGM) to minimize percentage of time <70 mg/dL for each individual WISDM participant. METHOD: The precision medicine analyses used data from participants with complete data (n = 194 older adults, including those who received CGM [n = 100] and BGM [n = 94] in the trial). Policy tree and decision list algorithms were fit with 14 baseline demographic, clinical, and laboratory measures. The primary outcome was CGM-measured percentage of time spent in hypoglycemic range (<70 mg/dL), and the decision rule assigned participants to a subgroup reflecting the treatment estimated to minimize this outcome across all follow-up visits. RESULTS: The optimal decision rule was found to be a decision list with 3 steps. The first step moved WISDM participants with baseline time-below range >1.35% and no detectable C-peptide levels to the CGM subgroup (n = 139), and the second step moved WISDM participants with a baseline time-below range of >6.45% to the CGM subgroup (n = 18). The remaining participants (n = 37) were left in the BGM subgroup. Compared with the BGM subgroup (n = 37; 19%), the group for whom CGM minimized hypoglycemia (n = 157; 81%) had more baseline hypoglycemia, a lower proportion of detectable C-peptide, higher glycemic variability, longer disease duration, and higher proportion of insulin pump use. CONCLUSIONS: The decision rule underscores the benefits of CGM for older adults to reduce hypoglycemia. Diagnostic CGM and laboratory markers may inform decision-making surrounding therapeutic CGM and identify older adults for whom CGM may be a critical intervention to reduce hypoglycemia.
Singularities and stable homotopy groups of spheres I
Creators: name: Nagy, Csaba
name: Szűcs, András
name: Terpai, Tamás
Publisher: name: arXiv
Year: 2015
Subjects: subject: Geometric Topology (math.GT)
subject: FOS: Mathematics
subject: 57R45, 57R90, 55P42

description: We establish an interesting connection between Morin singularities and stable homotopy groups of spheres. We apply this connection to computations of cobordism groups of certain singular maps. The differentials of the spectral sequence computing these cobordism groups are given by the composition multiplication in the stable homotopy groups of spheres.
description: 39 pages, 1 figure, revised again for Journal of Singularities
Relating process and outcome metrics for meaningful and interpretable cannulation skill assessment: A machine learning paradigm
Creators: name: Petersen, Lydia
name: Singapogu, Ravikiran
name: Roy-Chaudhury, Prabir
name: Liu, Zhanhe
name: Zhang, Ziyang
name: Bible, Joe
Publisher: name: Elsevier
Year: 2023

description:
BACKGROUND AND OBJECTIVES: The quality of healthcare delivery depends directly on the skills of clinicians. For patients on hemodialysis, medical errors or injuries caused during cannulation can lead to adverse outcomes, including potential death. To promote objective skill assessment and effective training, we present a machine learning approach, which utilizes a highly-sensorized cannulation simulator and a set of objective process and outcome metrics. METHODS: In this study, 52 clinicians were recruited to perform a set of pre-defined cannulation tasks on the simulator. Based on data collected by sensors during their task performance, the feature space was then constructed based on force, motion, and infrared sensor data. Following this, three machine learning models- support vector machine (SVM), support vector regression (SVR), and elastic net (EN)- were constructed to relate the feature space to objective outcome metrics. Our models utilize classification based on the conventional skill classification labels as well as a new method that represents skill on a continuum. RESULTS: With less than 5% of trials misplaced by two classes, the SVM model was effective in predicting skill based on the feature space. In addition, the SVR model effectively places both skill and outcome on a fine-grained continuum (versus discrete divisions) that is representative of reality. As importantly, the elastic net model enabled the identification of a set of process metrics that highly impact outcomes of the cannulation task, including smoothness of motion, needle angles, and pinch forces. CONCLUSIONS: The proposed cannulation simulator, paired with machine learning assessment, demonstrates definite advantages over current cannulation training practices. The methods presented here can be adopted to drastically increase the effectiveness of skill assessment and training, thereby potentially improving clinical outcomes of hemodialysis treatment.
Singularities and stable homotopy groups of spheres II
Creators: name: Szűcs, A.
name: Terpai, T.
Publisher: name: arXiv
Year: 2015
Subjects: subject: Geometric Topology (math.GT)
subject: K-Theory and Homology (math.KT)
subject: FOS: Mathematics
subject: 57R45, 57R90, 55P42, 55T25

description: We establish a connection between Morin singularities and stable homotopy groups of spheres. This connection allows us to describe how the images of singularity strata behave around the image of a more complicated stratum.
description: 31 pages, submitted to Journal of Singularities
title: Application of the "fictious crack model" to meshless crack growth simulations
Creators: name: Most, Thomas
name: Bucher, Christian
Publisher: name: Bauhaus-Universität Weimar
Year: 2003
Subjects: subject: Bruchmechanik
subject: Rissbildung
subject: Modellierung
subject: 620

description: In this paper a meshless component is presented, which internally uses the common meshless interpolation technique >Moving Least Squares<. In contrast to usual meshless integration schemes like the cell quadrature and the nodal integration in this study integration zones with triangular geometry spanned by three nodes are used for 2D analysis. The boundary of the structure is defined by boundary nodes, which are similar to finite element nodes. By using the neighborhood relations of the integration zones an efficient search algorithm to detected the nodes in the influence of the integration points was developed. The components are directly coupled with finite elements by using a penalty method. An widely accepted model to describe the fracture behavior of concrete is the >Fictitious Crack Model< which is applied in this study, which differentiates between micro cracks and macro cracks, with and without force transmission over the crack surface, respectively. In this study the crack surface is discretized by node pairs in form of a polygon, which is part of the boundary. To apply the >Fictitious Crack Model< finite interface elements are included between the crack surface nodes. The determination of the maximum principal strain at the crack tip is done by introducing an influence area around the singularity. On a practical example it is shown that the included elements improve the model by the transmission of the surface forces during monotonic loading and by the representation of the contact forces of closed cracks during reverse loading.
description: Internationales Kolloquium über Anwendungen der Informatik und Mathematik in Architektur und Bauwesen : 10. bis 12.06.2003, Bauhaus-Universität Weimar, vol. 16, 2003
Fibration and classification of smooth projective toric varieties of low Picard number
Creators: name: Rossi, Michele
name: Terracini, Lea
Publisher: name: arXiv
Year: 2015
Subjects: subject: Algebraic Geometry (math.AG)
subject: FOS: Mathematics

description: In this paper we show that a smooth toric variety $X$ of Picard number $r\leq 3$ always admits a nef primitive collection supported on a hyperplane admitting non-trivial intersection with the cone $\Nef(X)$ of numerically effective divisors and cutting a facet of the pseudo-effective cone $\Eff(X)$, that is $\Nef(X)\cap\partial\overline{\Eff}(X)\neq\{0\}$. In particular this means that $X$ admits non-trivial and non-big numerically effective divisors. Geometrically this guarantees the existence of a fiber type contraction morphism over a smooth toric variety of dimension and Picard number lower than those of $X$, so giving rise to a classification of smooth and complete toric varieties with $r\leq 3$. Moreover we revise and improve results of Oda-Miyake by exhibiting an extension of the above result to projective, toric, varieties of dimension $n=3$ and Picard number $r=4$, allowing us to classifying all these threefolds. We then improve results of Fujino-Sato, by presenting sharp (counter)examples of smooth, projective, toric varieties of any dimension $n\geq4$ and Picard number $r=4$ whose non-trivial nef divisors are big, that is $\Nef(X)\cap\partial\overline{\Eff}(X)=\{0\}$. Producing those examples represents an important goal of computational techniques in definitely setting an open geometric problem. In particular, for $n=4$, the given example turns out to be a weak Fano toric fourfold of Picard number 4.
description: 26 pages; 7 figures. Final version for pubblication in International Journal of Mathematics. Minor changes following referee's suggestions: in particular the proof of Lemma 3.2 has been rewritten to making it clearer
Levee reliability analysis considering different failure mechanisms : a case study (Gueishan Levee) in southern Taiwan
Creators: name: Huang, Wen-Chao
name: Yu, Hong-Wen
Publisher: name: The University of British Columbia
Year: 2015

description: Because Taiwan is located in a subtropical area, it is unavoidable to encounter severe disasters induced by typhoons during the summer season. On August 8, 2009, Typhoon Morakot invaded Southern Taiwan and many levees and revetments in southern Taiwan were damaged during this event. In this study, the uncertainty of the parameters was considered in stability analyses of one of the failed levees, the Gueishan Levee, under different flood return periods to examine the effect of the extreme weather conditions. Analysis results have shown that the slope sliding safety factor coefficient of variation (C.O.V.) is more influenced by the change of water level difference and less influenced by the change of flood return period. As the water level difference (WLD) coefficient increases, the safety factor is more concentrated and exhibit less uncertainty. The C.O.V. of sliding and overturning of retaining structure are both influenced by the variations of flood return periods and the WLD coefficient. As the flood return period increases, the two failure mechanisms associated with retaining structure exhibit less uncertainty under a long flood return period. On the other hand, as the WLD coefficient increases, the response of the two failure mechanisms related to retaining structure exhibit more uncertainty. It is therefore recommended to consider the water heights and possible scouring depths from hydrologic analysis of floods, and empirical equations in the levee stability analysis. If a specific levee is more important (more lives and properties are expected to be influenced), possible failure mechanisms may need to be considered under the effect of extreme weather condition, and thus the design can be reexamined and redesigned as a countermeasure to face the extreme weather conditions in the future.
Chaetocladius (Chaetocladius) piger
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
Chaetocladius
Chaetocladius piger

description: Chaetocladius (Chaetocladius) piger (Goetghebuer, 1913)
Notes
Morpho identification. New record for Lithuania.
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
Bernstein-gamma functions and exponential functionals of Levy Processes
Creators: name: Patie, Pierre
name: Savov, Mladen
Publisher: name: arXiv
Year: 2016
Subjects: subject: Probability (math.PR)
subject: FOS: Mathematics

description: We study the equation $M_Ψ(z+1)=\frac{-z}{Ψ(-z)}M_Ψ(z), M_Ψ(1)=1$ defined on a subset of the imaginary line and where $Ψ$ is a negative definite functions. Using the Wiener-Hopf method we solve this equation in a two terms product which consists of functions that extend the classical gamma function. These functions are in a bijection with Bernstein functions and for this reason we call them Bernstein-gamma functions. Via a couple of computable parameters we characterize of these functions as meromorphic functions on a complex strip. We also establish explicit and universal Stirling type asymptotic in terms of the constituting Bernstein function. The decay of $|M_Ψ(z)|$ along imaginary lines is computed. Important quantities for theoretical and applied studies are rendered accessible. As an application we investigate the exponential functionals of Levy Processes whose Mellin transform satisfies the recurrent equation above. Although these variables have been intensively studied, our new perspective, based on a combination of probabilistic and complex analytical techniques, enables us to derive comprehensive and substantial properties and strengthen several results on the law of these random variables. These include smoothness, regularity and analytical properties, large and small asymptotic behaviour, including asymptotic expansions, bounds, and Mellin-Barnes representations for the density and its successive derivatives. We also study the weak convergence of exponential functionals on a finite time horizon when the latter expands to infinity. As a result of new factorizations of the law of the exponential functional we deliver important intertwining relation between members of the class of positive self-similar semigroups. The derivation of our results relies on a mixture of complex-analytical and probabilistic techniques.
Injectivity theorem for pseudo-effective line bundles and its applications
Creators: name: Fujino, Osamu
name: Matsumura, Shin-ichi
Publisher: name: arXiv
Year: 2016
Subjects: subject: Complex Variables (math.CV)
subject: Algebraic Geometry (math.AG)
subject: Differential Geometry (math.DG)
subject: FOS: Mathematics
subject: 32L10 (Primary), 32Q15 (Secondary)

description: We formulate and establish a generalization of Kollár's injectivity theorem for adjoint bundles twisted by suitable multiplier ideal sheaves. As applications, we generalize Kollár's torsion-freeness, Kollár's vanishing theorem, and a generic vanishing theorem for pseudo-effective line bundles. Our approach is not Hodge theoretic but analytic, which enables us to treat singular Hermitian metrics with nonalgebraic singularities. For the proof of the main injectivity theorem, we use $L^{2}$-harmonic forms on noncompact Kähler manifolds. For applications, we prove a Bertini-type theorem on the restriction of multiplier ideal sheaves to general members of free linear systems.
description: 34 pages, v3: minor revisions, completely revised version
Estimating Risk of Locoregional Failure and Overall Survival in Anal Cancer Following Chemoradiation: A Machine Learning Approach
Creators: name: Goffredo, Paolo
name: Chen, Kevin A
name: Hu, David
name: Gomez, Shawn M
name: Joisa, Chinmaya U
name: Guillem, Jose G
name: Kapadia, Muneera R
Publisher: name: Elsevier
Year: 2023

description:
BACKGROUND: Optimal treatment of anal squamous cell carcinoma (ASCC) is definitive chemoradiation. Patients with persistent or recurrent disease require abdominoperineal resection (APR). Current models for predicting need for APR and overall survival are limited by low accuracy or small datasets. This study sought to use machine learning (ML) to develop more accurate models for locoregional failure and overall survival for ASCC. METHODS: This study used the National Cancer Database from 2004-2018, divided into training, validation, and test sets. We included patients with stage I-III ASCC who underwent chemoradiation. Our primary outcomes were need for APR and 3-year overall survival. Random forest (RF), gradient boosting (XGB), and neural network (NN) ML-based models were developed and compared with logistic regression (LR). Accuracy was assessed using area under the receiver operating characteristic curve (AUROC). RESULTS: APR was required in 5.3% (1,015/18,978) of patients. XGB performed best with AUROC of 0.813, compared with 0.691 for LR. Tumor size, lymphovascular invasion, and tumor grade showed the strongest influence on model predictions. Mortality was 23.6% (7,988/33,834). AUROC for XGB and LR were similar at 0.766 and 0.748, respectively. For this model, age, radiation dose, sex, and insurance status were the most influential variables. CONCLUSIONS: We developed and internally validated machine learning-based models for predicting outcomes in ASCC and showed higher accuracy versus LR for locoregional failure, but not overall survival. After external validation, these models may assist clinicians with identifying patients with ASCC at high risk of treatment failure.