bluuebunny/crossref_metadata_2025_split huggingface dataset:
Charge Carrier Doping As Mechanism of Self‐Assembled Monolayers Functionalized Electrodes in Organic Field Effect Transistors
Authors: Patrikar Kalyani , Bothra Urvashi , Rao Valipe Ramgopal , Kabra Dinesh 
Published: November 2021

AbstractCoating electrodes with self‐assembled monolayer (SAM) of polar molecules is known to reduce contact resistance (RC) in organic field effect transistors (OFETs). It is shown that the behavior of SAM in OFETs can be explained by considering a mechanism of interfacial doping in organic semiconductor by electrodes due to charge transfer during interface formation. The enhancement is analyzed in performance of pentacene OFETs with Cu electrodes, by coating Cu with SAM of pentafluorobenzenethiol or perfluorodecanethiol. It is found that application of either SAM leads to an increase in work function of Cu surface. However, work function shift due to SAM does not correlate with trends inRCand OFET drain current. Further, first principle calculations reveal a notable difference in delocalization of frontal orbitals with either SAM, an indicator of the difference in ease of charge transfer across interface. Based on the mechanism of interfacial doping, a semiconductor physics model is developed for estimating interface doping and injection barrier, and for predicting the consequent device characteristics. It is believed that the model and methodology developed in this study can be utilized beyond the SAM and semiconductor system used here.
Amphiphilic Perforated Honeycomb Films for Gravimetric Liquid Separation
Authors: Chen Bihai , Wada Takehiko , Yabu Hiroshi 
Published: November 2021

AbstractThe separation of oil and water is an important technology for solving a wide range of water‐related problems such as purification of industrial wastewater. Herein, the fabrication of an extremely thin oil–water separation membrane is reported by precisely controlling the wettability of a honeycomb (HC) porous membrane. The developed membrane can easily separate water and oil by gravity and capillary force. The method of wettability control by UV–O3 treatment and the resultant change in the separated liquid are discussed. Amphiphilic perforated HC films with controlled wettability can be used in membranes that can separate different liquids according to their densities when the initial liquid added to the surface of the HC film is changed.
Visible Achromatic Metalens Design Based on Artificial Neural Network
Authors: Wang Feilou , Geng Guangzhou , Wang Xueqian , Li Junjie , Bai Yang , Li Jianqiang , Wen Yongzheng , Li Bo , Sun Jingbo , Zhou Ji 
Published: November 2021

AbstractMetasurfaces, known as ultra‐thin and planar structures, are widely used in optical components with their excellent ability to manipulate the wavefront of the light. The key function of the metasurfaces is the spatial phase modulation, originated from the meta‐atoms. Thus, to find the relation between the phase modulation and the parameters of an individual meta‐atom, including the sizes, shapes, and material's optical properties, is the most important but also time‐consuming part in the metasurface design. Here by developing a backpropagation neural network based machine learning tool, the design process of a high performance achromatic metalens can be greatly simplified and accelerated. A library of the phase modulation data from 15 753 meta‐atoms can be generated in less than 1 s by our backpropagation neural network. In the experiment, it is demonstrated that the designed metalens shows an excellent achromatic focusing and imaging ability in the visible wavelengths from 420 to 640 nm without the polarization dependence.
When Do We Need Massive Computations to Perform Detailed COVID‐19 Simulations?
Authors: Lutz Christopher B. , Giabbanelli Philippe J. 
Published: November 2021

AbstractThe COVID‐19 pandemic has infected over 250 million people worldwide and killed more than 5 million as of November 2021. Many intervention strategies are utilized (e.g., masks, social distancing, vaccinations), but officials making decisions have a limited time to act. Computer simulations can aid them by predicting future disease outcomes, but they also require significant processing power or time. It is examined whether a machine learning model can be trained on a small subset of simulation runs to inexpensively predict future disease trajectories resembling the original simulation results. Using four previously published agent‐based models (ABMs) for COVID‐19, a decision tree regression for each ABM is built and its predictions are compared to the corresponding ABM. Accurate machine learning meta‐models are generated from ABMs without strong interventions (e.g., vaccines, lockdowns) using small amounts of simulation data: the root‐mean‐square error (RMSE) with 25% of the data is close to the RMSE for the full dataset (0.15 vs 0.14 in one model; 0.07 vs 0.06 in another). However, meta‐models for ABMs employing strong interventions require much more training data (at least 60%) to achieve a similar accuracy. In conclusion, machine learning meta‐models can be used in some scenarios to assist in faster decision‐making.
Boosting Output Performance of Triboelectric Nanogenerator via Mutual Coupling Effects Enabled Photon‐Carriers and Plasmon
Authors: Chen Xin , Zhao Yanjun , Wang Fayang , Tong Daqiao , Gao Lingxiao , Li Dongxiao , Wu Liangke , Mu Xiaojing , Yang Ya 
Published: November 2021

AbstractBoosting the output performance of triboelectric nanogenerators via some unique methods is always a meaningful way to speed up their commercialization. However, the available approach to boost performance is mainly restricted to one physics effect based and the basic research of boosting performance via mutual coupling effects is little research. Herein, a new strategy is creatively proposed based on charge traps from mutual coupling effects, generated from g‐C3N4/MXene‐Au composites, to further promote the output performance of triboelectric nanogenerator. It is found that photon‐generated carriers coupling surface plasmon effect enables composites filled into tribo‐material with visible light is an excellent value in boosting performance. The charge traps from mutual coupling effects for boosting performance are analyzed theoretically and verified by experiments. The output power of boosting‐triboelectric nanogenerator (TENG) achieves a sixfold enhancement (20 mW) of normal TENG with polydimethylsiloxane (PDMS) in ambient conditions. This work provides a profound understanding of the working mechanism of mutual coupling effects boosting the performance of TENG and an effective way for promoting TENG output.
Flexible sensors based on assembled carbon nanotubes
Authors: He Sisi , Hong Yang , Liao Meng , Li Yingchun , Qiu Longbin , Peng Huisheng 
Published: November 2021

AbstractFlexible sensors have attracted significant attention as they could be directly attached to/implanted into the body or incorporated into textiles to monitor human activities and give feedbacks for healthcare. A typical fabrication method is the direct use of intrinsically flexible active materials such as carbon nanotubes (CNTs). CNTs are generally assembled into aligned structures to extend their remarkable chemical, mechanical, and electrical properties to macroscopic scale to afford high sensing performances. In this review, we present the recent advance of CNT assemblies as electrodes or functional materials for flexible sensors. The realizations of aligned CNTs are firstly investigated. A variety of flexible sensors based on the aligned CNTs are then carefully explored, with an emphasis on understanding the working mechanism for their high sensing properties. The main attention is later paid to comparing two main categories of flexible sensors with fiber and film shapes. The remaining challenges are finally highlighted to offer some insights for future study.
Objective criteria for explanations of machine learning models
Authors: Yeh Chih‐Kuan , Ravikumar Pradeep 
Published: November 2021

AbstractObjective criteria to evaluate the performance of machine learning (ML) model explanations are a critical ingredient in bringing greater rigor to the field of explainable artificial intelligence. In this article, we survey three of our proposed criteria that each target different classes of explanations. In the first, targeted at real‐valued feature importance explanations, we define a class of “infidelity” measures that capture how well the explanations match the ML models. We show that instances of such infidelity minimizing explanations correspond to many popular recently proposed explanations and, moreover, can be shown to satisfy well‐known game‐theoretic axiomatic properties. In the second, targeted to feature set explanations, we define a robustness analysis‐based criterion and show that deriving explainable feature sets based on the robustness criterion yields more qualitatively impressive explanations. Lastly, for sample explanations, we provide a decomposition‐based criterion that allows us to provide very scalable and compelling classes of sample‐based explanations.
Acid catalyzedepoxy–methylolphenolthermosets: Astructure–propertystudy
Authors: Roy Choudhury Shreya , Houston Katelyn R. , Mason Dawn C. , Dingemans Theo J. 
Published: November 2021

AbstractWe have explored the structure–property relationships of a series epoxy–methylolphenol based thermoset films. Ortho‐, meta‐, and para‐isomers of methylolphenol, that is, ortho‐methylolphenol, meta‐methylolphenol and para‐methylolphenol, respectively, were reacted with the diglycidyl ether of bisphenol A (DGEBA) in the presence of an acid catalyst (CYCAT® XK 406 N). Thermogravimetric analyses showed that irrespective of the methylolphenol structure used, all crosslinked films exhibit 5% weight loss at 343–360°C under nitrogen. The glass transition temperature (Tg) decreases in the order of ortho‐ (Tg = 117°C) > para‐(Tg = 102°C) > meta‐methylolphenol (Tg = 82°C) as measured by differential scanning calorimetry. Uniaxial tensile testing of thin films shows good stress–strain behavior, with ultimate tensile strength values of 75 MPa and 6% strain‐at‐break. Homo‐crosslinking of methylolphenol moieties can occur under the reaction conditions used but in the presence of DGEBA, the methylolphenols prefer to undergo epoxy ring‐opening reactions. This was confirmed by the uniform networks that were formed, that is, no block‐formation was observed. The results of this study confirm that simple methylolphenol hardeners can be used to prepare crosslinked epoxy‐based films with excellent thermomechanical properties.
Asymmetric Direct/Stepwise Dearomatization Reactions Involving Hypervalent Iodine Reagents
Authors: Kumar Ravi , Singh Fateh V. , Takenaga Naoko , Dohi Toshifumi 
Published: November 2021

AbstractA remarkable growth in hypervalent iodine‐mediated oxidative transformations as stoichiometric reagents as well as catalysts has been well‐documented due to their excellent properties, such as mildness, easy handling, high selectivity, environmentally friendly nature, and high stability. This review aims at highlighting the asymmetric oxidative dearomatization reactions involving hypervalent iodine compounds. The present article summarizes asymmetric intra‐ and intermolecular dearomatization reactions using chiral hypervalent iodine reagents/catalysts as well as hypervalent iodine‐mediated dearomatization reactions followed by desymmetrization.
Current Comment: The Illiberal Academic Authority. An Oxymoron?
Authors: Pető Andrea 
Published: November 2021

AbstractThe emergence of illiberal science policy also raises serious questions about the European scientific authorization process as the rapid spread of illiberal science policies, such as closing accredited study programs and research institutions, privatizing higher education, appointing university leaders based on their loyalty to the government, ignoring quality assurance, etc. demand not only a reaction but also critical analysis. The article applies the theoretical framework of the polypore state (Grzebalska, Pető) to tackle the difficulty lies in understanding the rise of illiberal science policy in Hungary, as it is a twofold case study in both polypore government control/state capture, and neoliberal marketization of higher education.
Cancer prevention, screening, and survivorship ECHO: A pilot experience with an educational telehealth program
Authors: Severance Tyler S. , Milgrom Zheng , Carson Anyé , Scanlon Caitlin M. , Chauhan O’Brien Rishika , Anderson Brent , Robertson Mary , Janota Andrea , Coven Scott L. , Mendonca Eneida A. , Duwve Joan , Vik Terry A. 
Published: November 2021

AbstractIntroductionThe American Cancer Society, Inc. (ACS) estimates that 37,940 Indiana residents were diagnosed with cancer in 2020, which remains the leading cause of death in the state. Across the cancer continuum, national goals have been established targeting recommended benchmarks for states in prevention, screening, treatment, and survivorship. Indiana consistently falls below most goals for each of these targeted categories.MethodsTo address these disparities, we implemented Project ECHO (Extension for Community Healthcare Outcomes) as a virtual telehealth educational platform targeted at local healthcare providers. ECHO programs utilize a novel tele‐mentoring approach to the education of clinicians in a hub/spoke design. Sessions occurred twice monthly from September 2019 to September 2020 and consisted of a traditional didactic lecture and a case‐based discussion led by participating providers.ResultsDuring the pilot year there were a total of 22 ECHO sessions with 140 different participants. On average, 15.5 spokes attended each session with increasing participation at the end of the year. Post‐session surveys suggested generally favorable perception with 72% of respondents finding the quality “excellent.”DiscussionGiven the increasing rate of recurrent participation toward the end of the pilot year in conjunction with the favorable survey responses following each session, it was felt that the program was overall successful and warranted continued implementation.ConclusionThe Project ECHO platform is a validated telehealth education platform that has the potential to impact cancer care at multiple points along the cancer continuum at the regional level.
Optimum cycle length models using atom search optimization and grasshopper optimization algorithms
Authors: Korkmaz Ersin , Akgüngör Ali Payıdar 
Published: November 2021

AbstractA fixed‐time traffic control system is widely used to manage the traffic flow at intersections. Cycle length has an important effect on the performance of the fixed‐time control system and the Webster model is widely used in the literature to determine the cycle length. However, when the traffic flow ratio (Y) approaches 1, the Webster model loses its effectiveness and cannot determine the cycle length when Y is above 1. In the scope of this study, it is aimed to develop models that can predict cycle length for all traffic conditions in which are Y ≤ 1 and Y ≥ 1. Two different heuristic algorithms, atom search optimization (ASO) and grasshopper optimization algorithm (GOA) were used in the development of models and the performances of these algorithms were demonstrated. The efficiency of the developed models has been demonstrated by comparing them with both Webster's model and VISTRO optimization program. Models developed in exponential, power, and quadratic forms have been able to predict cycle lengths with lower delay values by showing better performance than Webster and VISTRO. In addition, statistical results show that the ASO approach is more successful than the GOA approach.
Population‐specific responses of an insect herbivore to variation in host‐plant quality
Authors: Kuczyk Josephine , Raharivololoniaina Ange , Fischer Klaus 
Published: November 2021

AbstractAnthropogenic climate change poses a substantial challenge to many organisms, to which they need to respond to avoid fitness reductions. Investigating responses to environmental change is particularly interesting in herbivores, as they are potentially affected by indirect effects mediated via variation in host‐plant quality. We here use the herbivorous insectPieris napito investigate geographic variation in the response to variation in food quality. We performed a common garden experiment using replicated populations from Germany and Italy, and manipulated host quality by growing host plants at different temperature and water regimes. We found that feeding on plants grown at a higher temperature generally diminished the performance ofP.napi, evidenced by a prolonged development time and reduced larval growth rate, body mass, fat content, and phenoloxidase activity. Genotype by environment interactions (G × E) were present in several performance traits, indicating that Italian populations (1) respond more strongly to variation in host‐plant quality and (2) are more sensitive to poor food quality than German ones. This may reflect a cost of the rapid lifestyle found in Italian populations. Consequently, German populations may be more resilient against environmental perturbations and may perhaps even benefit from warmer temperatures, while Italian populations will likely suffer from the concomitantly reduced host‐plant quality. Our study thus exemplifies how investigating G × E may help to better understand the vulnerability of populations to climate change.
Strong trait correlation and phylogenetic signal in North American ground beetle (Carabidae) morphology
Authors: Stachewicz Jacob D. , Fountain‐Jones Nicholas M. , Koontz Austin , Woolf Hillary , Pearse William D. , Gallinat Amanda S. 
Published: November 2021

AbstractFunctional traits mediate species' responses to, and roles within, their environment and are constrained by evolutionary history. While we have a strong understanding of trait evolution for macro‐taxa such as birds and mammals, our understanding of invertebrates is comparatively limited. Here, we address this gap in North American beetles with a sample of ground beetles (Carabidae), leveraging a large‐scale collection and digitization effort by the National Ecological Observatory Network (NEON). For 154 ground beetle species, we measured seven morphological traits, which we placed into a recently developed effect–response framework that characterizes traits by how they predict species' effects on their ecosystems or responses to environmental stressors. We then used cytochrome oxidase 1 sequences from the same specimens to generate a phylogeny and tested the evolutionary tempo and mode of the traits. We found strong phylogenetic signal in, and correlations among, ground beetle morphological traits. These results indicate that, for these species, beetle body shape trait evolution is constrained, and phylogenetic inertia is a stronger driver of beetle traits than (recent) environmental responses. Strong correlations among effect and response traits suggest that future environmental drivers are likely to affect both ecological composition and functioning in these beetles.
Decreased bee emergence along an elevation gradient: Implications for climate change revealed by a transplant experiment
Authors: McCabe Lindsie M. , Aslan Clare E. , Cobb Neil S. 
Published: November 2021

AbstractBees experience differences in thermal tolerance based on their geographical range; however, there are virtually no studies that examine how overwintering temperatures may influence immature survival rates. Here, we conducted a transplant experiment along an elevation gradient to test for climate‐change effects on immature overwinter survival using movement along elevational gradient for a community of 26 cavity‐nesting bee species in the family Megachilidae along the San Francisco Peaks, Arizona elevational gradient. In each of three years, we placed nest blocks at three elevations, to be colonized by native Megachilidae. Colonized blocks were then (1) moved to lower (warmer) elevations; (2) moved to higher (cooler) elevations; or (3) left in their natal habitat (no change in temperature). Because Megachilidae occupy high elevations with colder temperatures more than any other family of bees, we predicted that emergence would decrease in nest blocks moved to lower elevations, but that we would find no differences in emergence when nest blocks were moved to higher elevations. We found three major results: (1) Bee species moved to lower (warmer) habitats exhibited a 30% decrease in emergence compared with species moved within their natal habitat. (2) Habitat generalists were more likely than habitat specialists to emerge when moved up or down in elevation regardless of their natal life zones. (3) At our highest elevation treatment, emergence increased when blocks were moved to higher elevations, indicating that at least some Megachilidae species can survive at colder temperatures. Our results suggest that direct effects of warming temperatures will have negative impacts on the overall survival of Megachilidae. Additionally, above the tree line, low availability of wood‐nesting resources is a probable limiting factor on bees moving up in elevation.
Machine learning optimization of an electronic health record audit for heart failure in primary care
Authors: Raat Willem , Smeets Miek , Henrard Severine , Aertgeerts Bert , Penders Joris , Droogne Walter , Mullens Wilfried , Janssens Stefan , Vaes Bert 
Published: November 2021

AbstractAimsThe diagnosis of heart failure (HF) is an important problem in primary care. We previously demonstrated a 74% increase in registered HF diagnoses in primary care electronic health records (EHRs) following an extended audit procedure. What remains unclear is the accuracy of registered HF pre‐audit and which EHR variables are most important in the extended audit strategy. This study aims to describe the diagnostic HF classification sequence at different stages, assess general practitioner (GP) HF misclassification, and test the predictive performance of an optimized audit.Methods and resultsThis is a secondary analysis of the OSCAR‐HF study, a prospective observational trial including 51 participating GPs. OSCAR used an extended audit based on typical HF risk factors, signs, symptoms, and medications in GPs' EHR. This resulted in a list of possible HF patients, which participating GPs had to classify as HF or non‐HF. We compared registered HF diagnoses before and after GPs' assessment. For our analysis of audit performance, we used GPs' assessment of HF as primary outcome and audit queries as dichotomous predictor variables for a gradient boosted machine (GBM) decision tree algorithm and logistic regression model. Of the 18 011 patients eligible for the audit intervention, 4678 (26.0%) were identified as possible HF patients and submitted for GPs' assessment in the audit stage. There were 310 patients with registered HF before GP assessment, of whom 146 (47.1%) were judged not to have HF by their GP (over‐registration). There were 538 patients with registered HF after GP assessment, of whom 374 (69.5%) did not have registered HF before GP assessment (under‐registration). The GBM and logistic regression model had a comparable predictive performance (area under the curve of 0.70 [95% confidence interval 0.65–0.77] and 0.69 [95% confidence interval 0.64–0.75], respectively). This was not significantly impacted by reducing the set of predictor variables to the 10 most important variables identified in the GBM model (free‐text and coded cardiomyopathy, ischaemic heart disease and atrial fibrillation, digoxin, mineralocorticoid receptor antagonists, and combinations of renin‐angiotensin system inhibitors and beta‐blockers with diuretics). This optimized query set was enough to identify 86% (n = 461/538) of GPs' self‐assessed HF population with a 33% reduction (n = 1537/4678) in screening caseload.ConclusionsDiagnostic coding of HF in primary care health records is inaccurate with a high degree of under‐registration and over‐registration. An optimized query set enabled identification of more than 80% of GPs' self‐assessed HF population.