cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
Advancing Cardiovascular Risk Assessment with Artificial Intelligence: Opportunities and Implications in North Carolina.
Creators: name: Conners, Katherine M
name: Syed, Faisal F
name: Avery, Christy L
Publisher: name: North Carolina Institute of Medicine
Year: 2024

description: Cardiovascular disease mortality is increasing in North Carolina with persistent inequality by race, income, and location. Artificial intelligence (AI) can repurpose the widely available electrocardiogram (ECG) for enhanced assessment of cardiac dysfunction. By identifying accelerated cardiac aging from the ECG, AI offers novel insights into risk assessment and prevention.
Projecting contributions of marine protected areas to rebuild fish stocks under climate change
Creators: name: Cheung, William W. L.
name: Palacios-Abrantes, Juliano
name: Roberts, Sarah M.
Publisher: name: Springer Nature
Year: 2024

description: No-take marine protected areas (No-take MPAs) are considered as a major tool for conserving marine biodiversity and ecosystem services. No-take MPAs can also contribute to climate adaptation for exploited fish stocks. Meanwhile, many fish stocks in the world are overfished and management institutions are developing plans to rebuild them. Understanding the potential effects of no-take MPAs on fish stocks under climate change can help develop strategies for climate-resilient stock rebuilding. Here, using a linked climate-fish-fishing model, we undertake simulation experiments to examine the effects of no-take MPAs on biomass and potential catches of 231 exploited fish and invertebrate species in eight marine ecoregions in the Northeast Atlantic under climate change. The simulations include different levels of fishing, no-take MPAs coverage, atmospheric global warming levels, and account for the expected displacement of fishing to the area around the no-take MPAs. Average individual stock biomass is projected to decrease by 5–15% per degree Celsius atmospheric warming. Having 30% of the distribution of over-exploited fish stocks under no-take MPAs together with conservation-focused fisheries management of these stocks are projected to offset the negative impacts on their biomass under 2.6–2.9 °C global warming. Meanwhile, potential catches increase when a portion of the over-exploited fish stocks is protected from fishing as higher biomass in the no-take MPAs spills-over to the surrounding areas. Our findings highlight that no-take MPAs, combined with reducing fishing intensity, can help rebuild over-exploited fish biomass and benefit their dependent fisheries in the Northeast Atlantic under projected climate change in the 21st century.
Brane Cosmology in an Arbitrary Number of Dimensions
Creators: name: Chatillon, N.
name: Macesanu, C.
name: Trodden, M.
Publisher: name: arXiv
Year: 2006
Subjects: subject: General Relativity and Quantum Cosmology (gr-qc)
subject: Astrophysics (astro-ph)
subject: High Energy Physics - Theory (hep-th)
subject: FOS: Physical sciences

description: We derive the effective cosmological equations for a non-$\mathbb{Z}_2$ symmetric codimension one brane embedded in an arbitrary D-dimensional bulk spacetime, generalizing the $D=5,6$ cases much studied previously. As a particular case, this may be considered as a regularized codimension (D-4) brane avoiding the problem of curvature divergence on the brane. We apply our results to the case of spherical symmetry around the brane and to partly compactified AdS-Schwarzschild bulks.
description: 23 pages
Evaluating machine learning-enabled and multimodal data-driven exercise prescriptions for mental health: a randomized controlled trial protocol
Creators: name: Xiang, Mingqiang
name: Lu, Sanmei
name: Xiao, Yanning
name: Xie, Yewei
name: Tan, Miaoqing
name: Jing, Fengshi
name: Ren, Hao
Publisher: name: Frontiers
Year: 2024

description: Background: Mental illnesses represent a significant global health challenge, affecting millions with far-reaching social and economic impacts. Traditional exercise prescriptions for mental health often adopt a one-size-fits-all approach, which overlooks individual variations in mental and physical health. Recent advancements in artificial intelligence (AI) offer an opportunity to tailor these interventions more effectively.
Objective: This study aims to develop and evaluate a multimodal data-driven AI system for personalized exercise prescriptions, targeting individuals with mental illnesses. By leveraging AI, the study seeks to overcome the limitations of conventional exercise regimens and improve adherence and mental health outcomes.
Methods: The study is conducted in two phases. Initially, 1,000 participants will be recruited for AI model training and testing, with 800 forming the training set, augmented by 9,200 simulated samples generated by ChatGPT, and 200 as the testing set. Data annotation will be performed by experienced physicians from the Department of Mental Health at Guangdong Second Provincial General Hospital. Subsequently, a randomized controlled trial (RCT) with 40 participants will be conducted to compare the AI-driven exercise prescriptions against standard care. Assessments will be scheduled at 6, 12, and 18 months to evaluate cognitive, physical, and psychological outcomes.
Expected outcomes: The AI-driven system is expected to demonstrate greater effectiveness in improving mental health outcomes compared to standard exercise prescriptions. Personalized exercise regimens, informed by comprehensive data analysis, are anticipated to enhance participant adherence and overall mental well-being. These outcomes could signify a paradigm shift in exercise prescription for mental health, paving the way for more personalized and effective treatment modalities.
Registration and ethical approval: This is approved by Human Experimental Ethics Inspection of Guangzhou Sport University, and the registration is under review by ChiCTR.
Figure S1 from Where the wild things were: intrinsic and extrinsic extinction predictors in the world's most depleted mammal fauna
Creators: name: Turvey, Samuel T.
name: Duncan, Clare
name: Upham, Nathan S.
name: Harrison, Xavier
name: Dávalos, Liliana M.
Publisher: name: The Royal Society
Year: 2021
Subjects: subject: Ecology
subject: FOS: Biological sciences
subject: 40308 Palaeontology (incl. Palynology)
subject: FOS: Earth and related environmental sciences

description: Correlation coefficients among island variables
Measurement and Analysis of In Vivo Microwave Dielectric Properties Collected From Normal, Benign, and Malignant Rat Breast Tissues: Classification Using Supervised Machine Learning Algorithms
Creators: name: Aydinalp, Cemanur
name: Onemli, Emre
name: Ozsobaci, Nural Pastaci
name: Yilmaz, Tuba
Publisher: name: Institute of Electrical and Electronics Engineers (IEEE)
Year: 2024

description: This work presents large-scale measurements of in vivo rat breast tissue dielectric properties (DPs) from 0.5 to 6 GHz and classifies the collected data using supervised machine learning (ML) algorithms. The main goals of this work are, first, to report in vivo animal tissue DPs for microwave medical device development and, second, to demonstrate that microwave devices can be utilized for diagnostics. To this end, we separated 18 Sprague-Dawley female rats into control and experimental groups. The experimental group was subjected to chemically induced breast cancer, and the DPs of normal tissues (NTs) and tumor tissues from the control and experimental groups were measured using the open-ended coaxial probe (OECP) technique. DPs of rat breast tissues are presented with Cole-Cole parameters. The OECP method is preferred since it can collect broadband measurements without sample preparation. Due to these advantages, the method was previously envisioned as a diagnostic tool to aid in biopsy procedures. However, high measurement error prevented the specialized device’s development and, consequently, the clinical deployment of OECP. We demonstrate that high error rates can be mitigated with the application of ML algorithms. Among seven different ML algorithms, the support vector machines (SVMs) algorithm classifies rat malignant tissues, benign tissues, and NTs with a median accuracy (ACC) of 94.4%, Matthews correlation coefficient (MCC) of 91.9%, recall of 94.4%, precision of 94.9%, and $F1$ score of 94.4%.
Protoplanetary Disk Turbulence Driven by the Streaming Instability: Non-Linear Saturation and Particle Concentration
Creators: name: Johansen, Anders
name: Youdin, Andrew
Publisher: name: arXiv
Year: 2007
Subjects: subject: Astrophysics (astro-ph)
subject: FOS: Physical sciences

description: We present simulations of the non-linear evolution of streaming instabilities in protoplanetary disks. The two components of the disk, gas treated with grid hydrodynamics and solids treated as superparticles, are mutually coupled by drag forces. We find that the initially laminar equilibrium flow spontaneously develops into turbulence in our unstratified local model. Marginally coupled solids (that couple to the gas on a Keplerian time-scale) trigger an upward cascade to large particle clumps with peak overdensities above 100. The clumps evolve dynamically by losing material downstream to the radial drift flow while receiving recycled material from upstream. Smaller, more tightly coupled solids produce weaker turbulence with more transient overdensities on smaller length scales. The net inward radial drift is decreased for marginally coupled particles, whereas the tightly coupled particles migrate faster in the saturated turbulent state. The turbulent diffusion of solid particles, measured by their random walk, depends strongly on their stopping time and on the solids-to-gas ratio of the background state, but diffusion is generally modest, particularly for tightly coupled solids. Angular momentum transport is too weak and of the wrong sign to influence stellar accretion. Self-gravity and collisions will be needed to determine the relevance of particle overdensities for planetesimal formation.
description: Accepted for publication in ApJ (17 pages). Movies of the simulations can be downloaded at http://www.mpia.de/~johansen/research_en.php
A patient with follicular mucinosis was successfully treated by indomethacin and minocyline hydrochloride
Creators: name: Pi Ti Palungwachira, Pranee Palungwachira
Publisher: name: Faculty of Medicine,Srinakharinwirot University
Year: 2000
Subjects: follicular mucinosis, minocycline hydrochloride, indomethacin

description: 1, 6, Journal of Medicine and Health Sciences
Artificial intelligence innovations in neurosurgical oncology: a narrative review
Creators: name: Sexton, Daniel P.
name: Abumoussa, Andrew
name: Chambless, Lola B.
name: Pease, Matthew
name: Baker, Clayton R.
Publisher: name: Springer Nature
Year: 2024

description: Purpose Artificial Intelligence (AI) has become increasingly integrated clinically within neurosurgical oncology. This report reviews the cutting-edge technologies impacting tumor treatment and outcomes. Methods A rigorous literature search was performed with the aid of a research librarian to identify key articles referencing AI and related topics (machine learning (ML), computer vision (CV), augmented reality (AR), virtual reality (VR), etc.) for neurosurgical care of brain or spinal tumors. Results Treatment of central nervous system (CNS) tumors is being improved through advances across AI—such as AL, CV, and AR/VR. AI aided diagnostic and prognostication tools can influence pre-operative patient experience, while automated tumor segmentation and total resection predictions aid surgical planning. Novel intra-operative tools can rapidly provide histopathologic tumor classification to streamline treatment strategies. Post-operative video analysis, paired with rich surgical simulations, can enhance training feedback and regimens. Conclusion While limited generalizability, bias, and patient data security are current concerns, the advent of federated learning, along with growing data consortiums, provides an avenue for increasingly safe, powerful, and effective AI platforms in the future.
Hunting for Planetary Nebulae toward the Galactic Center
Creators: name: Hong, Jihye
name: Simpson, Janet P.
name: An, Deokkeun
name: Cotera, Angela S.
name: Ramírez, Solange V.
Publisher: name: arXiv
Year: 2021
Subjects: subject: Astrophysics of Galaxies (astro-ph.GA)
subject: Solar and Stellar Astrophysics (astro-ph.SR)
subject: FOS: Physical sciences

description: We present near-infrared (IR) spectra of two planetary nebula (PN) candidates in close lines of sight toward the Galactic center (GC) using the Gemini Near-Infrared Spectrograph (GNIRS) at Gemini North. High-resolution images from radio continuum and narrow-band IR observations reveal ringlike or barrel-shaped morphologies of these objects, and their mid-IR spectra from the Spitzer Space Telescope exhibit rich emission lines from highly-excited species such as [S IV], [Ne III], [Ne V], and [O IV]. We also derive elemental abundances using the Cloudy synthetic models, and find an excess amount of the $s$-process element Krypton in both targets, which supports their nature as PN. We estimate foreground extinction toward each object using near-IR hydrogen recombination lines, and find significant visual extinctions ($A_V > 20$). The distances inferred from the size versus surface brightness relation of other PNe are $9.0\pm1.6$ kpc and $7.6\pm1.6$ kpc for SSTGC 580183 and SSTGC 588220, respectively. These observed properties along with abundance patterns and their close proximity to Sgr A$^*$ (projected distances $<20$ pc) make it highly probable that these objects are the first confirmed PN objects in the nuclear stellar disk. The apparent scarcity of such objects resembles the extremely low rate of PN formation in old stellar systems, but is in line with the current rate of the sustained star formation activity in the Central Molecular Zone.
description: 20 pages, 9 figures, accepted for publication in the Astronomical Journal
Graph-based Deep Learning for Communication Networks: A Survey
Creators: name: Jiang, Weiwei
Publisher: name: arXiv
Year: 2021
Subjects: subject: Networking and Internet Architecture (cs.NI)
subject: Machine Learning (cs.LG)
subject: FOS: Computer and information sciences

description: Communication networks are important infrastructures in contemporary society. There are still many challenges that are not fully solved and new solutions are proposed continuously in this active research area. In recent years, to model the network topology, graph-based deep learning has achieved the state-of-the-art performance in a series of problems in communication networks. In this survey, we review the rapidly growing body of research using different graph-based deep learning models, e.g. graph convolutional and graph attention networks, in various problems from different types of communication networks, e.g. wireless networks, wired networks, and software defined networks. We also present a well-organized list of the problem and solution for each study and identify future research directions. To the best of our knowledge, this paper is the first survey that focuses on the application of graph-based deep learning methods in communication networks involving both wired and wireless scenarios. To track the follow-up research, a public GitHub repository is created, where the relevant papers will be updated continuously.
description: Accepted by Elsevier Computer Communications. Github link: https://github.com/jwwthu/GNN-Communication-Networks
Falsifying Models of New Physics Via WW Scattering
Creators: name: Distler, Jacques
name: Grinstein, Benjamin
name: Porto, Rafael A.
name: Rothstein, Ira Z.
Publisher: name: arXiv
Year: 2006
Subjects: subject: High Energy Physics - Phenomenology (hep-ph)
subject: High Energy Physics - Theory (hep-th)
subject: FOS: Physical sciences

description: We show that the coefficients of operators in the electroweak chiral Lagrangian can be bounded if the underlying theory obeys the usual assumptions of Lorentz invariance, analyticity, unitarity and crossing to arbitrarily short distances. Violations of these bounds can be explained by either the existence of new physics below the naive cut-off of the the effective theory, or by the breakdown of one of these assumptions in the short distance theory. As a corollary, if no light resonances are found, then a measured violation of the bound would falsify generic models of string theory.
description: 4 pages, 2 figures, LaTeX2e (revtex4); argument completely revisited, stronger and more pertinent bounds given
The AI Institute for Engaged Learning
Creators: name: Rowe, Jonathan
name: Roschelle, Jeremy
name: Biswas, Gautam
name: Hmelo‐Silver, Cindy
name: Bansal, Mohit
name: Lester, James
Publisher: name: Wiley
Year: 2024

description: The EngageAI Institute focuses on AI‐driven narrative‐centered learning environments that create engaging story‐based problem‐solving experiences to support collaborative learning. The institute's research has three complementary strands. First, the institute creates narrative‐centered learning environments that generate interactive story‐based problem scenarios to elicit rich communication, encourage coordination, and spark collaborative creativity. Second, the institute creates virtual embodied conversational agent technologies with multiple modalities for communication (speech, facial expression, gesture, gaze, and posture) to support student learning. Embodied conversational agents are driven by advances in natural language understanding, natural language generation, and computer vision. Third, the institute is creating an innovative multimodal learning analytics framework that analyzes parallel streams of multimodal data derived from students’ conversations, gaze, facial expressions, gesture, and posture as they interact with each other, with teachers, and with embodied conversational agents. Woven throughout the institute's activities is a strong focus on ethics, with an emphasis on creating AI‐augmented learning that is deeply informed by considerations of fairness, accountability, transparency, trust, and privacy. The institute emphasizes broad participation and diverse perspectives to ensure that advances in AI‐augmented learning address inequities in STEM. The institute brings together a multistate network of universities, diverse K‐12 school systems, science museums, and nonprofit partners. Key to all of these endeavors is an emphasis on diversity, equity, and inclusion.
An Accurate P$^{3}$M Algorithm for Gravitational Lensing Studies in Simulations
Creators: name: Xu, Kun
name: Jing, Yipeng
Publisher: name: arXiv
Year: 2021
Subjects: subject: Cosmology and Nongalactic Astrophysics (astro-ph.CO)
subject: Instrumentation and Methods for Astrophysics (astro-ph.IM)
subject: FOS: Physical sciences

description: We present a two-dimensional (2D) Particle-Particle-Particle-Mesh (P$^3$M) algorithm with an optimized Green function and adaptive softening length for gravitational lensing studies in N-Body simulations. The analytical form of the optimized Green function $\hat{G}(\rm{k})$ is given. The softening schemes ($S$) are studied for both the PM and the PP calculations in order for accurate force calculation and suppression of the particle discreteness effect. Our method is two orders of magnitude more accurate than the simple PM algorithm with the {\it poor man's} Green function ($\propto1/k^2$) at a scale of a few mesh cells or smaller. The force anisotropy is also much smaller than the conventional PM calculation. We can achieve a force accuracy better than 0.1 percent at all scales with our algorithm, which makes it an ideal (accurate and fast) algorithm for {\textit{micro}} lensing studies . When we apply the algorithm to computing {\textit{weak}} and {\textit{strong}} lensing quantities in N-Body simulations, the errors are dominated by the Poisson noise caused by particle discreteness. The Poisson noise can be suppressed by smoothing out the particle distribution, which can be achieved by simply choosing an adaptive softening length in the PP calculation. We have presented a criterion to set the adaptive softening length. Our algorithm is also applicable to cosmological simulations. We provide a \textsc{python} implementation \texttt{P3Mlens} for this algorithm.
description: 11 pages, 6 figures, accepted for publication on ApJ
Text S1 + Table S3 from Where the wild things were: intrinsic and extrinsic extinction predictors in the world's most depleted mammal fauna
Creators: name: Turvey, Samuel T.
name: Duncan, Clare
name: Upham, Nathan S.
name: Harrison, Xavier
name: Dávalos, Liliana M.
Publisher: name: The Royal Society
Year: 2021
Subjects: subject: Ecology
subject: FOS: Biological sciences
subject: 40308 Palaeontology (incl. Palynology)
subject: FOS: Earth and related environmental sciences

description: Supplementary methods and results
NeRFactor: Neural Factorization of Shape and Reflectance Under an Unknown Illumination
Creators: name: Zhang, Xiuming
name: Srinivasan, Pratul P.
name: Deng, Boyang
name: Debevec, Paul
name: Freeman, William T.
name: Barron, Jonathan T.
Publisher: name: arXiv
Year: 2021
Subjects: subject: Computer Vision and Pattern Recognition (cs.CV)
subject: Graphics (cs.GR)
subject: FOS: Computer and information sciences

description: We address the problem of recovering the shape and spatially-varying reflectance of an object from multi-view images (and their camera poses) of an object illuminated by one unknown lighting condition. This enables the rendering of novel views of the object under arbitrary environment lighting and editing of the object's material properties. The key to our approach, which we call Neural Radiance Factorization (NeRFactor), is to distill the volumetric geometry of a Neural Radiance Field (NeRF) [Mildenhall et al. 2020] representation of the object into a surface representation and then jointly refine the geometry while solving for the spatially-varying reflectance and environment lighting. Specifically, NeRFactor recovers 3D neural fields of surface normals, light visibility, albedo, and Bidirectional Reflectance Distribution Functions (BRDFs) without any supervision, using only a re-rendering loss, simple smoothness priors, and a data-driven BRDF prior learned from real-world BRDF measurements. By explicitly modeling light visibility, NeRFactor is able to separate shadows from albedo and synthesize realistic soft or hard shadows under arbitrary lighting conditions. NeRFactor is able to recover convincing 3D models for free-viewpoint relighting in this challenging and underconstrained capture setup for both synthetic and real scenes. Qualitative and quantitative experiments show that NeRFactor outperforms classic and deep learning-based state of the art across various tasks. Our videos, code, and data are available at people.csail.mit.edu/xiuming/projects/nerfactor/.
description: Camera-ready version for SIGGRAPH Asia 2021. Project Page: https://people.csail.mit.edu/xiuming/projects/nerfactor/
Quasiparticle band structure of infinite hydrogen fluoride and hydrogen chloride chains
Creators: name: Buth, Christian
Publisher: name: arXiv
Year: 2006
Subjects: subject: Other Condensed Matter (cond-mat.other)
subject: Materials Science (cond-mat.mtrl-sci)
subject: FOS: Physical sciences

description: We study the quasiparticle band structure of isolated, infinite HF and HCl bent (zigzag) chains and examine the effect of the crystal field on the energy levels of the constituent monomers. The chains are one of the simplest but realistic models of the corresponding three-dimensional crystalline solids. To describe the isolated monomers and the chains, we set out from the Hartree-Fock approximation, harnessing the advanced Green's function methods "local molecular orbital algebraic diagrammatic construction" (ADC) scheme and "local crystal orbital ADC" (CO-ADC) in a strict second order approximation, ADC(2,2) and CO-ADC(2,2), respectively, to account for electron correlations. The configuration space of the periodic correlation calculations is found to converge rapidly only requiring nearest-neighbor contributions to be regarded. Although electron correlations cause a pronounced shift of the quasiparticle band structure of the chains with respect to the Hartree-Fock result, the bandwidth essentially remains unaltered in contrast to, e.g., covalently bound compounds.
description: 11 pages, 6 figures, 6 tables, RevTeX4, corrected typoes
Archival exhibitions: purposes and principles
Creators: name: Gordon, Heather Marie
Publisher: name: University of British Columbia
Year: 2009

description: Most information on exhibitions found in the museum and library literature is of little use to the archivist faced with preparing an exhibition of archival material. A body of literature exists dealing with the allotment of institutional resources to the exhibition function and with the physical care of archival material on exhibition. However, little has been written about the principles governing an archival exhibition's inspiration and development, principles that need to be identified before addressing the methods and practice of mounting an exhibition. This thesis is a response to that need. Exploratory, rather than descriptive or explanatory, its purpose is to identify the principles governing the creation of archival exhibitions, not the practicalities or mechanics of mounting them. Primary sources for this study are exhibition catalogues and brochures solicited from various Canadian archival institutions as well as the letters from members of the Canadian archival community that accompanied the catalogues and brochures. The thesis first establishes that the creation of archival exhibitions is subject to fundamental archival theory. Then, it addresses the ideal motivations or purposes behind thematic, celebratory, institutional, and functional exhibitions and demonstrates that they are linked to the mandate of the archival institution and the nature of the targeted audience. The thesis concludes that archival exhibitions have a responsibility to promote the archival institution and its holdings and to educate people regarding archival functions and services, and that institutional and functional exhibitions are, by definition, best designed to accomplish these objectives.
Harmonizing heterogeneous transcriptomics datasets for machine learning-based analysis to identify spaceflown murine liver-specific changes
Creators: name: Elgart, Robin
name: Eley, Greg
name: Kothiyal, Prachi
name: Eslami, Parastou
name: Hoadley, Katherine A.
name: Ilangovan, Hari
Publisher: name: Springer Nature
Year: 2024

description: NASA has employed high-throughput molecular assays to identify sub-cellular changes impacting human physiology during spaceflight. Machine learning (ML) methods hold the promise to improve our ability to identify important signals within highly dimensional molecular data. However, the inherent limitation of study subject numbers within a spaceflight mission minimizes the utility of ML approaches. To overcome the sample power limitations, data from multiple spaceflight missions must be aggregated while appropriately addressing intra- and inter-study variabilities. Here we describe an approach to log transform, scale and normalize data from six heterogeneous, mouse liver-derived transcriptomics datasets (ntotal = 137) which enabled ML-methods to classify spaceflown vs. ground control animals (AUC ≥ 0.87) while mitigating the variability from mission-of-origin. Concordance was found between liver-specific biological processes identified from harmonized ML-based analysis and study-by-study classical omics analysis. This work demonstrates the feasibility of applying ML methods on integrated, heterogeneous datasets of small sample size.
Deciphering Deconfinement in Correlations of Conserved Charges
Creators: name: Majumder, A.
Publisher: name: arXiv
Year: 2006
Subjects: subject: Nuclear Theory (nucl-th)
subject: FOS: Physical sciences

description: Diagonal and off-diagonal flavor and conserved charge susceptibilities reveal the prevalent degrees of freedom of heated strongly interacting matter. Results obtained from lattice simulations are compared with various model estimates in an effort to weed down various possible pictures of a quark gluon plasma. We argue that the vanishing of the off-diagonal quark flavor susceptibilities and its derivatives with respect to chemical potential, at temperatures above 1.5Tc, can only be understood in a picture of a gas or liquid composed of quasi-particles which carry the same quantum numbers as quarks and antiquarks. A potential new observable, blind to neutral and non-strange particles, is introduced and related via isospin symmetry to the ratio of susceptibilities of baryonic strangeness to strangeness generated in the excited matter created at RHIC.
description: 5 pages, 3 figures, LATEX, To appear in the proceedings of the International Conference on Strangeness in Quark Matter, Los Angeles, CA, Mar 26-31, 2006
Formation of a quasicrystalline Pb monolayer on the ten-fold surface of the decagonal Al-Ni-Co quasicrystal
Creators: name: Smerdon, J. A.
name: Leung, L.
name: Parle, J. K.
name: Jenks, C. J.
name: McGrath, R.
name: Fournee, V.
name: Ledieu, J.
Publisher: name: arXiv
Year: 2008
Subjects: subject: Other Condensed Matter (cond-mat.other)
subject: FOS: Physical sciences

description: Lead has been deposited on the ten-fold surface of decagonal Al72Ni11Co17 to form an epitaxial quasicrystalline single-element monolayer. The overlayer grows through nucleation of nanometer-sized irregular islands and the coverage saturates at 1 ML. The overlayer is well-ordered quasiperiodically as evidenced by LEED and Fourier transforms of STM images. Annealing the film to 600 K improves the structural quality, but causes the evaporation of some material such that the film develops pores. Electronic structure measurements using X-ray photoemission spectroscopy indicate that the chemical interaction of the Pb atoms with the substrate is weak.
description: 12 pages, 5 figures
Opportunities in Quantum Reservoir Computing and Extreme Learning Machines
Creators: name: Mujal, Pere
name: Martínez-Peña, Rodrigo
name: Nokkala, Johannes
name: García-Beni, Jorge
name: Giorgi, Gian Luca
name: Soriano, Miguel C.
name: Zambrini, Roberta
Publisher: name: arXiv
Year: 2021
Subjects: subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences

description: Quantum reservoir computing (QRC) and quantum extreme learning machines (QELM) are two emerging approaches that have demonstrated their potential both in classical and quantum machine learning tasks. They exploit the quantumness of physical systems combined with an easy training strategy, achieving an excellent performance. The increasing interest in these unconventional computing approaches is fueled by the availability of diverse quantum platforms suitable for implementation and the theoretical progresses in the study of complex quantum systems. In this review article, recent proposals and first experiments displaying a broad range of possibilities are reviewed when quantum inputs, quantum physical substrates and quantum tasks are considered. The main focus is the performance of these approaches, on the advantages with respect to classical counterparts and opportunities.
The Pauluskerk: an unorthodox church in Rotterdam
Creators: name: Van Der Hoeven, Frank
Publisher: name: VostokSibAcademCenter
Year: 2014
Subjects: ?hurch; Pauluskerk; Rotterdam; CalypSO; Alsop; station development; Rotterdam Central Station; Visser; Perron Nul; homelessness; drug use

description: The tale of the rebuilding of the Pauluskerk (St. Paul’s Church) in the Dutch city of Rotterdam is a multilayered story that blurs the lines between architecture, societal issues, policymaking and urban redevelopment. The original Pauluskerk was built in the late 1950s in a city centre that was still recovering from the damage it suffered during the Second World War. The church may never have received the attention it has were it not for Reverend Visser, who developed the church into a refuge for the outcasts of Dutch society: asylum seekers, homeless people and drug addicts. Visser’s activism eventually evolved into the Perron Nul (Platform Zero) initiative, through which he organized support for the addicted and indigent on a scale not seen before in the city. The close proximity of the Pauluskerk to Rotterdam Central Station and the controversy surrounding its mission brought it slowly but steadily onto a collision course with the renewal and redevelopment of the station area, which would eventually lead to the demolition of the original Pauluskerk in 2007 and the construction of a new church building as part of the CalypSO project, designed by British architect William Alsop. This article brings these story lines together to showcase the complex process involved in an inner-city urban development founded in the well-established practice of local democracy, where consensus-seeking is the norm, even when this crosses societal borders.
description: Project Baikal, No 41 (2014): temples XXI
The 'Beograd na vodi' masterplan. Belgrade’s latest identity make over
Creators: name: Van Der Hoeven, Frank
name: Ivkovic, Milena
Publisher: name: VostokSibAcademCenter
Year: 2014
Subjects: identity; Belgrade; Beograd na vodi; urban development; romanticism; Byzantine Revival; Beogradska Moderna; Socialist city; Neonationalism; waterfront

description: Foreign investment by the United Arab Emirates in the 'Beograd na vodi' master plan sets the stage for the largest urban development in the Serbian capital since the planning of Novi Beograd. While the government embraces the plan as an instrument to spur economic growth in Serbia, critics are more cautious and warn for cliche corporate development.
description: Project Baikal, No 42 (2014): identity
Comment on "The phase diagram of the multi-matrix model with ABAB-interaction from functional renormalization"
Creators: name: Perez-Sanchez, Carlos I.
Publisher: name: arXiv
Year: 2021
Subjects: subject: High Energy Physics - Theory (hep-th)
subject: Combinatorics (math.CO)
subject: FOS: Physical sciences
subject: FOS: Mathematics
subject: 81-XX (Primary) 05Cxx (Secondary)

description: Recently, [JHEP 20 131 (2020)] obtained (a similar, scaled version of) the ($a,b$)-phase diagram derived from the Kazakov--Zinn-Justin solution of the Hermitian two-matrix model with interactions \[\mathrm{Tr\,}\Big\{\frac{a}{4} (A^4+B^4)+\frac{b}{2} ABAB\Big\}\,,\] starting from Functional Renormalization. We comment on something unexpected: the phase diagram of [JHEP 20 131 (2020)] is based on a $β_b$-function that does not have the one-loop structure of the Wetterich-Morris Equation. This raises the question of how to reproduce the phase diagram from a set of $β$-functions that is, in its totality, consistent with Functional Renormalization. A non-minimalist, yet simple truncation that could lead to the phase diagram is provided. Additionally, we identify the ensemble for which the result of op. cit. would be entirely correct.
description: 10 pages, several ribbon graphs v3: a user's guide to ribbon graphs added. Conform with the published JHEP-version (v2: minor correction)
Predicting Intimate Partner Violence Perpetration Among Young Adults Experiencing Homelessness in Seven U.S. Cities Using Interpretable Machine Learning.
Creators: name: Um, Mee Young
name: Ferguson, Kristin M
name: Maria, Diane M Santa
name: Manikonda, Lydia
name: Narendorf, Sarah C
name: Eapen, Doncy J
name: Petering, Robin
name: Barman-Adhikari, Anamika
name: Hsu, Hsun-Ta
Publisher: name: SAGE Publications
Year: 2024

description: Young adults experiencing homelessness (YAEH) are at higher risk for intimate partner violence (IPV) victimization than their housed peers. This is often due to their increased vulnerability to abuse and victimization before and during homelessness, which can result in a cycle of violence in which YAEH also perpetrates IPV. Identifying and addressing factors contributing to IPV perpetration at an early stage can reduce the risk of IPV. Yet to date, research examining YAEH's IPV perpetration is scarce and has largely employed conventional statistical approaches that are limited in modeling this complex phenomenon. To address these gaps, this study used an interpretable machine learning approach to answer the research question: What are the most salient predictors of IPV perpetration among a large sample of YAEH in seven U.S. cities? Participants (N = 1,426) on average were 21 years old (SD = 2.09) and were largely cisgender males (59%) and racially/ethnically diverse (81% were from historically excluded racial/ethnic groups; i.e., African American, Latino/a, American Indian, Asian or Pacific Islander, and mixed race/ethnicity). Over one-quarter (26%) reported IPV victimization, and 20% reported IPV perpetration while homeless. Experiencing IPV victimization while homeless was the most important factor in predicting IPV perpetration. An additional 11 predictors (e.g., faced frequent discrimination) were positively associated with IPV perpetration, whereas 8 predictors (e.g., reported higher scores of mindfulness) were negatively associated. These findings underscore the importance of developing and implementing effective interventions with YAEH that can prevent IPV, particularly those that recognize the positive association between victimization and perpetration experiences.
Competing Interactions, the Renormalization Group and the Isotropic-Nematic Phase Transition
Creators: name: Barci, Daniel G.
name: Stariolo, Daniel A.
Publisher: name: arXiv
Year: 2006
Subjects: subject: Soft Condensed Matter (cond-mat.soft)
subject: Statistical Mechanics (cond-mat.stat-mech)
subject: FOS: Physical sciences

description: We discuss 2D systems with Ising symmetry and competing interactions at different scales. In the framework of the Renormalization Group, we study the effect of relevant quartic interactions. In addition to the usual constant interaction term, we analyze the effect of quadrupole interactions in the self consistent Hartree approximation. We show that in the case of repulsive quadrupole interaction, there is a first order phase transition to a stripe phase in agreement with the well known Brazovskii result. However, in the case of attractive quadrupole interactions there is an isotropic-nematic second order transition with higher critical temperature.
description: 4 pages, no figures, version to be published in Physical Review Letters. Some scaling dimensions corrected, conclusions are the same
SEOVER: Sentence-level Emotion Orientation Vector based Conversation Emotion Recognition Model
Creators: name: Li, Zaijing
name: Tang, Fengxiao
name: Sun, Tieyu
name: Zhu, Yusen
name: Zhao, Ming
Publisher: name: arXiv
Year: 2021
Subjects: subject: Computation and Language (cs.CL)
subject: Artificial Intelligence (cs.AI)
subject: FOS: Computer and information sciences

description: For the task of conversation emotion recognition, recent works focus on speaker relationship modeling but ignore the role of utterance's emotional tendency.In this paper, we propose a new expression paradigm of sentence-level emotion orientation vector to model the potential correlation of emotions between sentence vectors. Based on it, we design an emotion recognition model, which extracts the sentence-level emotion orientation vectors from the language model and jointly learns from the dialogue sentiment analysis model and extracted sentence-level emotion orientation vectors to identify the speaker's emotional orientation during the conversation. We conduct experiments on two benchmark datasets and compare them with the five baseline models.The experimental results show that our model has better performance on all data sets.
description: 8 pages,accepted by ICONIP 2021
A machine learning approach to predict mortality due to immune-mediated thrombotic thrombocytopenic purpura
Creators: name: Woods, Ryan
name: Upreti, Harsh Vardhan
name: Zheng, X. Long
name: Raval, Jay S.
name: Kasthuri, Raj S.
name: Cataland, Spero R.
name: Johnson, Andrew D.
name: Chaturvedi, Shruti
name: Kocher, Nicole K.
name: Gangaraju, Radhika
name: Abou-Ismail, Mouhamed Yazan
name: Presson, Angela P.
name: Kreuziger, Lisa Baumann
name: Akwaa, Frank
name: Masias, Camila
name: Evans, Michael D.
name: Mazepa, Marshall
name: Zhang, Chong
name: Farland, Andrew M.
name: Clover, Todd
name: Metjian, Ara
name: Gibson, Briana
name: Liles, Darla K.
name: Davis, Elizabeth
name: Sridharan, Meera
name: Go, Ronald S.
name: McCrae, Keith R.
name: de Ridder, Gustaaf
name: Park, Yara A.
name: Thrombotic Microangiopathy Consortium
name: Lim, Ming Y.
name: Antun, Ana G.
Publisher: name: Elsevier
Year: 2024

description: Background: Mortality due to immune-mediated thrombotic thrombocytopenic purpura (iTTP) remains significant. Predicting mortality risk may potentially help individualize treatment. The French Thrombotic Microangiopathy (TMA) Reference Score has not been externally validated in the United States. Recent advances in machine learning technology can help analyze large numbers of variables with complex interactions for the development of prediction models.
Objectives: To validate the French TMA Reference Score in the United States Thrombotic Microangiopathy (USTMA) iTTP database and subsequently develop a novel mortality prediction tool, the USTMA TTP Mortality Index.
Methods: We analyzed variables available at the time of initial presentation, including demographics, symptoms, and laboratory findings. We developed our model using gradient boosting machine, a machine learning ensemble method based on classification trees, implemented in the R package gbm.
Results: In our cohort (n = 419), the French score predicted mortality with an area under the receiver operating characteristic curve of 0.63 (95% CI: 0.50-0.77), sensitivity of 0.35, and specificity of 0.84. Our gradient boosting machine model selected 8 variables to predict acute mortality with a cross-validated area under the receiver operating characteristic curve of 0.77 (95% CI: 0.71-0.82). The 2 cutoffs corresponded to sensitivities of 0.64 and 0.50 and specificities of 0.76 and 0.87, respectively.
Conclusion: The USTMA Mortality Index was acceptable for predicting mortality due to acute iTTP in the USTMA registry, but not sensitive enough to rule out death. Identifying patients at high risk of iTTP-related mortality may help individualize care and ultimately improve iTTP survival outcomes. Further studies are needed to provide external validation. Our model is one of many recent examples where machine learning models may show promise in clinical prediction tools in healthcare.
Fluctuations, correlations and finite volume effects in heavy ion collision
Creators: name: Turko, Ludwik
Publisher: name: arXiv
Year: 2007
Subjects: subject: High Energy Physics - Theory (hep-th)
subject: Statistical Mechanics (cond-mat.stat-mech)
subject: Nuclear Theory (nucl-th)
subject: FOS: Physical sciences

description: Finite volume corrections to higher moments are important observable quantities. They make possible to differentiate between different statistical ensembles even in the thermodynamic limit. It is shown that this property is a universal one. The classical grand canonical distribution is compared to the canonical distribution in the rigorous procedure of approaching the thermodynamic limit.
description: 5 pages. To appear in Int. J. Mod. Phys E, QM2006/Shanghai proceedings - poster session
Additional file 1 of Change lifestyle modification plan/transtheoretical model in non-alcoholic simple fatty liver disease: a pilot randomized study
Creators: name: Li, Lijuan
name: Hou, Kun
name: Yuan, Mengya
name: Zhang, Yan
name: Zhang, Yang
Publisher: name: figshare
Year: 2022
Subjects: subject: Medicine
subject: Biotechnology
subject: Chemical Sciences not elsewhere classified
subject: Immunology
subject: FOS: Clinical medicine
subject: Biological Sciences not elsewhere classified
subject: Cancer
subject: Science Policy

description: Supplementary Material 1. Supplementary Table 1. Transtheoretical Model and stages of change-oriented lifestyle intervention strategies and measures for simple fatty liver disease patients. Supplementary Table 2. Comparison of healthy behavior levels of the 2 groups (controls vs. transtheoretical model and stages of change) before and after intervention.
Pronominal anaphoric reference in the narratives of 3-year-old children
Creators: name: Gomme, Norma Jean
Publisher: name: University of British Columbia
Year: 2009

description: The general purpose of the present study was to investigate the way in which 3-year-old children use pronouns to refer to characters in a narrative. A form/function approach was taken, exploring not only the forms used to refer to story protagonists, but also the functions those forms served to create coherence in the narrative as a whole. The study had three specific goals. The first of these was to compare the results of this study with those of Bamberg (1987), specifically to determine whether the 3-year-old English-speaking children in this study were using the same reference strategy as the 3-year-old German-speaking children in Bamberg’s study (the thematic advancement strategy). The second goal was to compare the children’s referential use of pronouns at times when they were unfamiliar and familiar with the story. The third goal was to compare the results of this study with those of Karmiloff-Smith (1981) in an attempt to resolve differences between her study and Bamberg’s regarding the age at which children move from deictic to referential use of pronouns, and the exact nature of the thematic advancement strategy. Ten English-speaking children between the ages of 3;2.3 and 3;9.12 participated in this study. Each child told two stories, first when they were unfamiliar with the book ( T₁), and again after reading the book with their caregiver(s) over the course of a week ( T₂). Results showed that these children as a group demonstrated the developing ability to create textual coherence through pronominal reference in a manner consistent with Bamberg’s thematic advancement strategy. Closer analysis of individual stories pointed to the presence of several substrategies, and showed developmental variation in the children’s abilities to use pronouns referentially. No significant difference was found in the children’s referential use of pronouns between T₁ and T₂, although other developmental measures showed improvement with story familiarity. Further, the results did not provide evidence for purely deictic use of pronouns, or the inability to create any level of textual coherence as found by Karmiloff-Smith for English-speaking 4-year-olds. Results also disputed Karmiloff-Smith’s proposal that the thematic subject strategy involves exclusive preference for clause-initial position to be reserved for reference to the protagonist. It is proposed here that differences between the studies can be attributed to variation in experimental design.