bluuebunny/crossref_metadata_2025_split huggingface dataset:
Leveraging legacy system data to examine generational propensity to volunteer
Authors: Kirby Joseph 
Published: January 2022

AbstractNonprofit organizations face increased competition in their volunteer recruitment efforts. Rapidly changing generational demographics within the US and an expanding base of digital marketing sources challenge the effective management of this critical process. Furthermore, many nonprofits lack the data and/or technical skills necessary to organize, analyze, and evaluate their volunteer recruiting processes. This study leverages legacy system data from two Midwest Big Brother Big Sister locations and finds that compared with Millennials, Boomers (2.08/1.63 times) and Gen‐Xers (1.53/1.20 times) are significantly more likely to volunteer. Regression models revealed the significant influence of marketing sources by generation, providing insight for segmented marketing strategies. Findings also suggest an increased focus on marketing to Millennials results in overall lower volunteer rates. This article profiles an approach using basic dimensional data analysis and more advanced data analytics and serves as a guide for nonprofits to follow to develop insight into their volunteer recruitment efforts.
Impact of winding parameters on the fiber bandwidth in the cylindrical area of a hydrogen pressure vessel for generating a digital twin
Authors: Hopmann Christian , Magura Nadine , Müller Robert , Schneider Daniel , Fischer Kai 
Published: January 2022

AbstractThe wet winding process is an established manufacturing technology for the production of rotationally symmetrical components made of fiber‐reinforced plastic (FRP), such as type‐IV hydrogen pressure vessels. In this process, the FRP laminate is produced by continuously depositing an impregnated fiber band on the winding core in a winding pattern adapted to the component stress. Despite a long history of the process, there are shortcomings in the understanding of the process, without which further optimization in terms of cost and material efficiency will reach its limits in the future. Currently, the fiber band is assumed to have a constant rectangular cross‐section in most simulations, which neglects manufacturing influences such as fiber spreading. The investigations carried out aim to extend the process understanding by a realistic description of the fiber bandwidth when deposited on the winding core. The investigations show that the fiber spreading, as well as the absolute fiber bandwidth, depend on the resin loading and the fiber band tension, independent of the winding pattern in the cylindrical area of a pressure vessel shaped winding core. In addition, the fiber bandwidth changes by 15%–20% during circumferential winding, depending on the machine movement.
An introduction to the full random effects model
Authors: Yngman Gunnar , Bjugård Nyberg Henrik , Nyberg Joakim , Jonsson E. Niclas , Karlsson Mats O. 
Published: January 2022

AbstractThe full random‐effects model (FREM) is a method for determining covariate effects in mixed‐effects models. Covariates are modeled as random variables, described by mean and variance. The method captures the covariate effects in estimated covariances between individual parameters and covariates. This approach is robust against issues that may cause reduced performance in methods based on estimating fixed effects (e.g., correlated covariates where the effects cannot be simultaneously identified in fixed‐effects methods). FREM covariate parameterization and transformation of covariate data records can be used to alter the covariate‐parameter relation. Four relations (linear, log‐linear, exponential, and power) were implemented and shown to provide estimates equivalent to their fixed‐effects counterparts. Comparisons between FREM and mathematically equivalent full fixed‐effects models (FFEMs) were performed in original and simulated data, in the presence and absence of non‐normally distributed and highly correlated covariates. These comparisons show that both FREM and FFEM perform well in the examined cases, with a slightly better estimation accuracy of parameter interindividual variability (IIV) in FREM. In addition, FREM offers the unique advantage of letting a single estimation simultaneously provide covariate effect coefficient estimates and IIV estimates for any subset of the examined covariates, including the effect of each covariate in isolation. Such subsets can be used to apply the model across data sources with different sets of available covariates, or to communicate covariate effects in a way that is not conditional on other covariates.
Extended prescribed performance control with input quantization for nonlinear systems
Authors: Gao Shigen , Xu Chaoan , Zheng Yue , Dong Hairong , Hu Xiaoming 
Published: January 2022

AbstractFor a class of MIMO nonlinear systems, comprised of interconnected subsystems in Brunovsky canonical form, with uncertain yet locally Lipschitz nonlinearities among subsystems and quantized inputs, the target is to form a closed‐loop system that exhibits extended prescribed performance on states tracking (accuracy determined by maximum overshoot, minimum convergence rate, maximum steady‐state error, and control gains), yet still a low‐complexity control structure, without requiring any identification, approximation, and filtering techniques, regardless of uncertainties. In this article, a static, decentralized, continuous, yet computationally inexpensive controller is designed, without requiring parameters of quantizers. Inheriting the merit of pioneering prescribed performance control (PPC) methodology, it is required that the reference signal isfunction only, while, an essential difference and new feature is that, the pioneering PPC guarantees that state tracking errors are constrained by boundary functions (also known as prescribed performance functions, PPFs) only, while, the proposed extend PPC scheme achieves that state tracking errors are constrained by boundary functions and control gains simultaneously, in other words, without “tighter” PPFs, state tracking errors can still be adjusted to arbitrarily small by choosing proper control gains. Finally, comparative simulation results are given to verify the theoretical findings.
Rivers—mouths—tides—memories: A creative, inter‐deep‐mapping of two river/tidal places. Love of place, memory and affect; movements, patterns, marks, and practices of care
Authors:   The River Severn Estuary UK,   Bahía Adair, Sonora, Mexico, Jones Owain , Green Heather 
Published: January 2022

AbstractThis article sets out the authors' attachments to, and memories of, two tidal river/channel landscapes and how these are being folded into collaborative work, which brings these places to attention through art practice and shared reflection. The rivers/channels in question are given voice in the introduction and ideas of the ecologies of mouths and river mouths, particularly those tidal, are explored in the following sections. Aspects of polyvocality and deep mapping are employed to reveal the unique characteristics of these places—particularly their tidal patterns and rhythms and our concerns for them. An art project,Tidal Timespace, lies at the heart of this article with the role of memories, shared memories, and our relationships to place as key themes. The descriptive accounts of the authors' respective place memories are set in the margins of the article in two columns. We conclude with considerations of expanded notions of ecology, and we add that loss of place, the passing of time, and wider senses of ecocide and extinction run like shadows through this narrative.
Dual‐Functional Photocatalysis for Cooperative Hydrogen Evolution and Benzylamine Oxidation Coupling over Sandwiched‐Like Pd@TiO2@ZnIn2S4 Nanobox
Authors: She Ping , Qin Jun‐sheng , Sheng Jiyao , Qi Yuanyuan , Rui Hongbang , Zhang Wei , Ge Xin , Lu Geyu , Song Xiaowei , Rao Heng 
Published: January 2022

AbstractPhotocatalytic hydrogen evolution (PHE) over semiconductor photocatalysts is usually constrained by the limited light‐harvesting and separation of photogenerated electron–hole pairs. Most of the reported systems focusing on PHE are facilitated by consuming the photoinduced holes with organic sacrificial electron donors (SEDs). The introduction of the SEDs not only causes the environmental problem, but also increases the cost of the reaction. Herein, a dual‐functional photocatalyst is developed with the morphology of sandwiched‐like hollowed Pd@TiO2@ZnIn2S4 nanobox, which is synthesized by choosing microporous zeolites with sub‐nanometer‐sized Pd nanoparticles (Pd NPs) embedded as the sacrificial templates. The ternary Pd@TiO2@ZnIn2S4 photocatalyst exhibits a superior PHE rate (5.35 mmol g−1 h−1) and benzylamine oxidation conversion rate (>99%) simultaneously without adding any other SEDs. The PHE performance is superior to the reported composites of TiO2 and ZnIn2S4, which is attributed to the elevated light capture ability induced by the hollow structure, and the enhanced charge separation efficiency facilitated by the ultrasmall sized Pd NPs. The unique design presented here holds great potential for other highly efficient cooperative dual‐functional photocatalytic reactions.
The Galapagos Chip Platform for High‐Throughput Screening of Cell Adhesive Chemical Micropatterns
Authors: Tuvshindorj Urandelger , Trouillet Vanessa , Vasilevich Aliaksei , Koch Britta , Vermeulen Steven , Carlier Aurélie , Alexander Morgan R. , Giselbrecht Stefan , Truckenmüller Roman , de Boer Jan 
Published: January 2022

AbstractIn vivo cells reside in a complex extracellular matrix (ECM) that presents spatially distributed biochemical and ‑physical cues at the nano‐ to micrometer scales. Chemical micropatterning is successfully used to generate adhesive islands to control where and how cells attach and restore cues of the ECM in vitro. Although chemical micropatterning has become a powerful tool to study cell–material interactions, only a fraction of the possible micropattern designs was covered so far, leaving many other possible designs still unexplored. Here, a high‐throughput screening platform called “Galapagos chip” is developed. It contains a library of 2176 distinct subcellular chemical patterns created using mathematical algorithms and a straightforward UV‐induced two‐step surface modification. This approach enables the immobilization of ligands in geometrically defined regions onto cell culture substrates. To validate the system, binary RGD/polyethylene glycol patterns are prepared on which human mesenchymal stem cells are cultured, and the authors observe how different patterns affect cell and organelle morphology. As proof of concept, the cells are stained for the mechanosensitive YAP protein, and, using a machine‐learning algorithm, it is demonstrated that cell shape and YAP nuclear translocation correlate. It is concluded that the Galapagos chip is a versatile platform to screen geometrical aspects of cell–ECM interaction.
Formalizing model transformation patterns
Authors: Rouhi Alireza , Kolahdouz Rahimi Shekoufeh , Lano Kevin 
Published: January 2022

AbstractModel transformation has become an established field, and it is important to improve the quality of specifications written in transformation languages. Different transformation patterns have been introduced in the model‐driven engineering (MDE) community to improve the quality of transformation specifications. However, due to the different definitions of pattern concepts by different authors, it is difficult for practitioners to understand how to apply patterns in practice. Therefore, there is a need to unify transformation pattern concepts by presenting a generic metamodel and formalizing patterns in terms of this metamodel, to define the meaning of pattern application. In this research a general metamodel for definition of different design patterns in model transformation is provided. The metamodel presents clear description of common aspects of transformation patterns, which facilitates the application of patterns on model transformations by validating the application against the underlying formalism. Additionally, a unified and precise terminology for the application and verification of model transformation patterns by using a formal model of model transformation patterns in the Z notation is presented. To show the applicability of the proposed formalism, four well‐known model transformation patterns are specified.
Shear performance of the interfaces for precast concrete shear wall components by novel preparation method
Authors: Zhu Zhangfeng , Guo Zhengxing , Lu Hepeng 
Published: January 2022

AbstractFor emulating cast‐in‐place (CIP) precast concrete (PC) shear wall structures in China, the adjacent PC shear wall components are joined by vertical post‐cast concrete. Shear behavior of concrete‐to‐concrete interfaces is critical for structural integrity. A novel preparation method, as cast using bubble film (BF) form, is proposed. Shear performance experiments are conducted to obtain the shear capacity and deformation characteristic of the specimens by the preparation methods of hydro‐demolition (HD), as‐cast by patterned steel plate (PSP) form and BF. Concrete strength and shear reinforcement are also considered. By comparison with reference CIP specimens, HD specimens performs best, followed by BF specimens, and the worst are PSP specimens. The collected shear loads for HD and BF specimens are larger than calculated results under diagonal shear failure, assuring structural integrity. Concrete strength and shear reinforcements have effective influence on interface shear capacity. Shear reinforcements with small diameter and small spacing are recommended.
How do high school students' genetics progression networks change due to genetics instruction and how do they stabilize years after instruction?
Authors: Todd Amber , Romine William , Sadeghi Reza , Cook Whitt Kate , Banerjee Tanvi 
Published: January 2022

AbstractLearning progressions (LPs) serve as frameworks for understanding the level of complexity of students' ideas within a domain. Multifaceted LPs contain multiple interrelated constructs where increased knowledge in one construct may increase knowledge of a separate construct. While it is challenging to identify and test these contingencies between constructs, our research group has used Bayesian structure learning methods to determine how mental models of genetics change with instruction. In this study, we follow a cohort of high school students for 3 years, measuring their genetics knowledge prior to instruction in 10th grade, immediately after genetics instruction in 10th grade, and at the end of 12th grade. We investigated how their idea networks change as a result of instruction and how they stabilize 2 years after instruction ended. We found students move from a phenotypic to a more molecular/mechanistic understanding of genetics immediately after instruction; students idea networks 2 years after instruction stabilized grounded within molecular explanations of diversity of life and how genetic diversity drives evolution. This study provides a robust mechanism for researchers to test connections between constructs in multifaceted LPs, illustrated by a genetics framework unable to be detected by previous methods.
Electrical Properties of Fresh Human Blood at 10 kHz–100 MHz
Authors: Takamatsu Reo , Higuchi Kenichi , Suzuki Tatsunori , Muramatsu Dairoku 
Published: January 2022

Understanding the electrical properties of blood is essential for medical applications based on bioelectromagnetic responses. However, reference values in the commonly used database were taken from measurements of ovine blood at frequencies higher than 1 MHz and treated with anticoagulants. In this study, the parallel‐plate method was used to measure the relative permittivity and conductivity of untreated fresh human blood in the frequency range of 10 kHz–100 MHz. The results showed a significant difference in the conductivity compared with the previous reference data. The variation in conductivity due to coagulation was concluded to be sufficiently small when compared with other factors. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.
Introduction to Topologies of Digital Work
Authors: Will-Zocholl Mascha , Roth-Ebner Caroline 
Published: January 2022

AbstractAt the turn of the millennium, a “spatial turn” appeared, first in cultural studies and then increasingly in the social sciences. From today's perspective, it can be said that the reinvention of space as a category of analysis has led to a renewed focus on spatial issues. On this basis, we pursue spatial constellations, references and structures using the concept of “topologies”. This volume aims at broadening the basis of topological research, taking into account the current developments of the digital transformation, theoretical considerations and empirical evidence.
Quaternionic Kähler Metrics Associated to Special Kähler Manifolds with Mutually Local Variations of BPS Structures
Authors: Cortés Vicente , Tulli Iván 
Published: January 2022

AbstractWe construct a quaternionic Kähler manifold from a conical special Kähler manifold with a certain type of mutually local variation of BPS structures. We give global and local explicit formulas for the quaternionic Kähler metric and specify under which conditions it is positive-definite. Locally, the metric is a deformation of the 1-loop corrected Ferrara–Sabharwal metric obtained via the supergravity c-map. The type of quaternionic Kähler metrics we obtain is related to work in the physics literature by S. Alexandrov and S. Banerjee, where they discuss the hypermultiplet moduli space metric of type IIA string theory, with mutually local D-instanton corrections.
Effectiveness of a Constructed Wetland with Carbon Filtration in Reducing Pesticides Associated with Agricultural Runoff
Authors: McCalla Laura B. , Phillips Bryn M. , Anderson Brian S. , Voorhees Jennifer P. , Siegler Katie , Faulkenberry Katherine R. , Goodman Maurice C. , Deng Xin , Tjeerdema Ron S. 
Published: January 2022

AbstractThe Salinas Valley in Monterey County, California, USA, is a highly productive agricultural region. Irrigation runoff containing pesticides at concentrations toxic to aquatic organisms poses a threat to aquatic ecosystems within local watersheds. This study monitored the effectiveness of a constructed wetland treatment system with a granulated activated carbon (GAC) filter installation at reducing pesticide concentrations and associated toxicity toCeriodaphnia dubia,Hyalella azteca, andChironomus dilutus. The wetland was supplied with water pumped from an impaired agricultural and urban drainage. Across five monitoring trials, the integrated system’s average pesticide concentration reduction was 52%. The wetland channel and GAC filtration components individually provided significant treatment, and within each, pesticide solubility had a significant effect on changes in pesticide concentrations. The integrated treatment system also reduced nitrate by 61%, phosphate by 73%, and turbidity by 90%. Input water was significantly toxic toC. dubiaandH. aztecain the first trial. Toxicity toC. dubiapersisted throughout the system, whereas toxicity toH. aztecawas removed by the channel, but there was residual toxicity post-GAC. The final trial had significant input toxicity toH. aztecaandC. dilutus. The channel reduced toxicity toH. aztecaand removed toxicity toC. dilutus. GAC filtration reducedH. aztecatoxicity to an insignificant level. There was no input toxicity in the other three trials. The results demonstrate that a wetland treatment system coupled with GAC filtration can reduce pesticide concentrations, nutrients, suspended particles, and aquatic toxicity associated with agricultural runoff.
Decoding the dynamics of poleward shifting climate zones using aqua-planet model simulations
Authors: Yang Hu , Lu Jian , Wang Qiang , Shi Xiaoxu , Lohmann Gerrit 
Published: January 2022

AbstractGrowing evidence indicates that the atmospheric and oceanic circulation experiences a systematic poleward shift in a warming climate. However, the complexity of the climate system, including the coupling between the ocean and the atmosphere, natural climate variability and land-sea distribution, tends to obfuscate the causal mechanism underlying the circulation shift. Here, using an idealised coupled aqua-planet model, we explore the mechanism of the shifting circulation, by isolating the contributing factors from the direct CO$$_2$$

2

forcing, the indirect ocean surface warming, and the wind-stress feedback from the ocean dynamics. We find that, in contrast to the direct CO$$_2$$

2

forcing, ocean surface warming, in particular an enhanced subtropical ocean warming, plays an important role in driving the circulation shift. This enhanced subtropical ocean warming emerges from the background Ekman convergence of surface anomalous heat in the absence of the ocean dynamical change. It expands the tropical warm water zone, causes a poleward shift of the mid-latitude temperature gradient, hence forces a corresponding shift in the atmospheric circulation and the associated wind pattern. The shift in wind, in turn drives a shift in the ocean circulation. Our simulations, despite being idealised, capture the main features of the observed climate changes, for example, the enhanced subtropical ocean warming, poleward shift of the patterns of near-surface wind, sea level pressure, storm tracks, precipitation and large-scale ocean circulation, implying that increase in greenhouse gas concentrations not only raises the temperature, but can also systematically shift the climate zones poleward.
Inverted bell-curve-based ensemble of deep learning models for detection of COVID-19 from chest X-rays
Authors: Paul Ashis , Basu Arpan , Mahmud Mufti , Kaiser M. Shamim , Sarkar Ram 
Published: January 2022

AbstractNovel Coronavirus 2019 disease or COVID-19 is a viral disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The use of chest X-rays (CXRs) has become an important practice to assist in the diagnosis of COVID-19 as they can be used to detect the abnormalities developed in the infected patients’ lungs. With the fast spread of the disease, many researchers across the world are striving to use several deep learning-based systems to identify the COVID-19 from such CXR images. To this end, we propose an inverted bell-curve-based ensemble of deep learning models for the detection of COVID-19 from CXR images. We first use a selection of models pretrained on ImageNet dataset and use the concept of transfer learning to retrain them with CXR datasets. Then the trained models are combined with the proposed inverted bell curve weighted ensemble method, where the output of each classifier is assigned a weight, and the final prediction is done by performing a weighted average of those outputs. We evaluate the proposed method on two publicly available datasets: the COVID-19 Radiography Database and the IEEE COVID Chest X-ray Dataset. The accuracy, F1 score and the AUC ROC achieved by the proposed method are 99.66%, 99.75% and 99.99%, respectively, in the first dataset, and, 99.84%, 99.81% and 99.99%, respectively, in the other dataset. Experimental results ensure that the use of transfer learning-based models and their combination using the proposed ensemble method result in improved predictions of COVID-19 in CXRs.