bluuebunny/crossref_metadata_2025_split huggingface dataset:
Trade‐Off Between Data Retention and Switching Speed in Resistive Switching ReRAM Devices
Authors: Siegel Sebastian , Baeumer Christoph , Gutsche Alexander , von Witzleben Moritz , Waser Rainer , Menzel Stephan , Dittmann Regina 
Published: November 2020

AbstractMemristive switching devices are promising for future data storage and neuromorphic computing applications to overcome the scaling and power dissipation limits of classical CMOS technology. Many groups have engineered bilayer oxide structures to enhance the switching performance especially in terms of retention and device reliability. Here, introducing retention enhancement oxide layers into the memristive stack is shown to result in a reduction of the switching speed not only by changing the voltage and temperature distribution in the cell, but also by influencing the rate‐limiting‐step of the switching kinetics. In particular, it is demonstrated that by introducing a retention enhancement layer into resistive switching SrTiO3 devices, the kinetics are no longer determined by the interface exchange reaction between switching oxide and active electrode, but depend on the oxygen ion migration in the additional interface layer. Thus, the oxygen migration barrier in the additional layer determines the switching speed. This trade‐off between retention and switching speed is of general importance for rational engineering of memristive devices.
Key Roles of Trace Oxygen Treatment for High‐Performance Zn‐Doped CuI p‐Channel Transistors
Authors: Liu Ao , Zhu Huihui , Shim Kyu In , Hong Jisu , Jung Haksoon , Han Jeong Woo , Noh Yong‐Young 
Published: November 2020

AbstractThe development of transparent and high‐performance p‐type semiconductors as a counterpart of n‐type metal oxide semiconductors has attracted significant interest for the integration of complementary circuits and p–n junction devices. This study investigates the effect of trace O2 for high‐performance and solution‐processed inorganic p‐channel Zn‐doped copper iodide (CuI) thin‐film transistors (TFTs) via a combined computation–experiment approach. The absorbed O2 molecules in the CuI film can occupy iodine vacancies, acting as trap passivator. Meanwhile, the strong electronegativity of O2 enables electron capture from the CuI matrix, leading to p‐doping. Trace O2‐treated Zn‐doped CuI TFTs exhibit significantly improved electrical performance compared to untreated devices. Optimized TFTs exhibit a high field‐effect hole mobility of 4.4 cm2 V−1 s−1, high on/off current ratio of ≈107, and small hysteresis. These findings provide a clear basis for realizing reproducible and high‐performance metal‐halide (e.g., CuI and perovskite) optoelectronic devices using low‐cost solution process.
Coordination Engineering of Single‐Atom Catalysts for the Oxygen Reduction Reaction: A Review
Authors: Zhang Jincheng , Yang Hongbin , Liu Bin 
Published: November 2020

AbstractFuture renewable energy supplies and a sustainable environment rely on many important catalytic processes. Single‐atom catalysts (SACs) are attractive because of their maximum atom utilization efficiency, tunable electronic structures, and outstanding catalytic performance. Of particular note, transition‐metal SACs exhibit excellent catalytic activity and selectivity for the oxygen reduction reaction (ORR)—an important half reaction in fuel cells and metal–air batteries as well as for portable hydrogen peroxide (H2O2) production. Although considerable efforts have been made on the synthesis of SACs for ORR, the regulation of the coordination environments of SACs and thus the electronic structures still pose a big challenge. In this review, strategies for manipulating the coordination environments of SACs are classified into three categories, including regulation of the center metal atoms, manipulation of the surrounding environment connecting to the center metal atom, and modification of the geometric configuration of the support. Finally, some issues regarding the future development of SACs for ORR are raised and possible solutions are proposed.
High‐Entropy Metal Sulfide Nanoparticles Promise High‐Performance Oxygen Evolution Reaction
Authors: Cui Mingjin , Yang Chunpeng , Li Boyang , Dong Qi , Wu Meiling , Hwang Sooyeon , Xie Hua , Wang Xizheng , Wang Guofeng , Hu Liangbing 
Published: November 2020

AbstractTransition metal sulfides with a multi‐elemental nature represent a class of promising catalysts for oxygen evolution reaction (OER) owing to their good catalytic activity. However, their synthesis remains a challenge due to the thermodynamic immiscibility of the constituent multimetallic elements in a sulfide structure. Herein, for the first time the synthesis of high‐entropy metal sulfide (HEMS, i.e., (CrMnFeCoNi)Sx) solid solution nanoparticles is reported. Computational and X‐ray photoelectron spectroscopy analysis suggest that the (CrMnFeCoNi)Sx exhibits a synergistic effect among metal atoms that leads to desired electronic states to enhance OER activity. The (CrMnFeCoNi)Sx nanoparticles show one of the best activities (low overpotential 295 mV at 100 mA cm−2 in 1 m KOH solution) and good durability (only slight polarization after 10 h by chronopotentiometry) compared with their unary, binary, ternary, and quaternary sulfide counterparts. This work opens up a new synthesis paradigm for high‐entropy compound nanoparticles for highly efficient electrocatalysis applications.
Patient understanding of diagnostic ultrasound examinations in an Australian private radiology clinic
Authors: Starcevich Amy , Lombardo Paul , Schneider Michal 
Published: November 2020

AbstractPurposeTo determine patient understanding and expectations of ultrasound imaging and its safety, sources of examination information and levels of examination anxiety.Methods1070 consecutive patients presenting to a private, regional radiology practice in New South Wales, Australia between 16th May and 14th June 2019, were invited to complete a survey while waiting for their non‐interventional ultrasound examination. The survey included questions on demographic characteristics, knowledge such as examination risks and safety, ultrasound expectations such as dissemination of results, sources of examination information and levels of participant anxiety. Data were analysed using Kruskal–Wallis tests (SPSS v. 25) to determine statistical associations between participant demographic factors, knowledge, anxiety level and the main source of examination information.ResultsA total of 215/1070 (20%) patients voluntarily participated in the study. Most were female (74%, 159/215), with a median (range) age of 55 (18–92) years. Participant's median (range) score of ultrasound imaging knowledge was 3 (0–5) scored out of six and indicated uncertainty regarding the ultrasound procedure, result dissemination and ultrasound safety. Participants with previous personal experience had significantly higher levels of ultrasound imaging knowledge than those whose primary information source was their referring doctor (P = 0.0005) or the internet (P = 0.026). Significantly higher levels of ultrasound examination knowledge were also associated with lower self‐reported levels of anxiety (P = 0.002).ConclusionParticipants had incomplete ultrasound examination knowledge, including misconceptions regarding safety and result dissemination, some of which could be clarified by the sonographer at the beginning of the ultrasound examination.
Head‐to‐head comparison of clinical performance of CSF phospho‐tau T181 and T217 biomarkers for Alzheimer's disease diagnosis
Authors: Karikari Thomas K. , Emeršič Andreja , Vrillon Agathe , Lantero‐Rodriguez Juan , Ashton Nicholas J. , Kramberger Milica Gregorič , Dumurgier Julien , Hourregue Claire , Čučnik Saša , Brinkmalm Gunnar , Rot Uroš , Zetterberg Henrik , Paquet Claire , Blennow Kaj 
Published: November 2020

AbstractIntroductionPhosphorylated tau (p‐tau) in cerebrospinal fluid (CSF) is an established Alzheimer's disease (AD) biomarker. Novel immunoassays targeting N‐terminal and mid‐region p‐tau181 and p‐tau217 fragments are available, but head‐to‐head comparison in clinical settings is lacking.MethodsN‐terminal‐directed p‐tau217 (N‐p‐tau217), N‐terminal‐directed p‐tau181 (N‐p‐tau181), and standard mid‐region p‐tau181 (Mid‐p‐tau181) biomarkers in CSF were evaluated in three cohorts (n = 503) to assess diagnostic performance, concordance, and associations with amyloid beta (Aβ).ResultsCSF N‐p‐tau217 and N‐p‐tau181 had better concordance (88.2%) than either with Mid‐p‐tau181 (79.7%–82.7%). N‐p‐tau217 and N‐p‐tau181 were significantly increased in early mild cognitive impairment (MCI)‐AD (A+T–N–) without changes in Mid‐p‐tau181 until AD‐dementia. N‐p‐tau217 and N‐p‐tau181 identified Aβ pathophysiology (area under the curve [AUC] = 94.8%–97.1%) and distinguished MCI‐AD from non‐AD MCI (AUC = 82.6%–90.5%) signficantly better than Mid‐p‐tau181 (AUC = 91.2% and 70.6%, respectively). P‐tau biomarkers equally differentiated AD from non‐AD dementia (AUC = 99.1%–99.8%).DiscussionN‐p‐tau217 and N‐p‐tau181 could improve diagnostic accuracy in prodromal‐AD and clinical trial recruitment as both identify Aβ pathophysiology and differentiate early MCI‐AD better than Mid‐p‐tau181.
Impurity Control in Catalyst Design: The Role of Sodium in Promoting and Stabilizing Co and Co2C for Syngas Conversion
Authors: Asundi Arun S. , Hoffman Adam S. , Nathan Sindhu S. , Boubnov Alexey , Bare Simon R. , Bent Stacey F. 
Published: November 2020

AbstractThe design of supported heterogeneous catalysts requires a detailed understanding of the structure and chemistry of the active surface. Although the chemical components of the active phase, support material, and process feed are typically considered to be the most important factors governing catalyst structure and performance, many common commercial supports contain trace impurities, which can have profound effects on catalyst properties. In this work, we study silica‐supported cobalt‐based catalysts, which are widely used in syngas conversion to value‐added products. Supported metallic Co is a commercial Fischer‐Tropsch catalyst, whereas Co2C has shown promise for the direct conversion of syngas to higher oxygenates. This study examines the effects of Na, a commonly detected support impurity and a frequently used promoter, on the structure and reactivity of Co and Co2C. We show that trace Na impurities significantly decrease catalyst activity of supported metallic Co, and that high Na concentrations result in Co2C formation and a loss in Fischer‐Tropsch activity. However, in Co2C catalysts, Na plays an important role in stabilizing the Co2C phase, but excess Na decreases catalyst activity. We use in situ X‐ray absorption spectroscopy to study Co2C formation and decomposition in the Na‐free catalyst under carburization and reaction conditions. The work reveals the importance of carefully controlling alkali metal content, particularly at trace levels, in catalyst design.
Optimizing the Reduction Potential of Sulfonamides on Polyamidoamine Dendrimers
Authors: Ghosh Animesh , Tan Nigel C. S. , Shi Raymond R. S. , Webster Richard D. , Steele Terry W. J. 
Published: November 2020

Abstractp‐Toluenesulfonamide serves as an important functional group to protect alkyl amines. However, the electrochemical deprotection of sulfonamides requires relatively high reduction potentials (−2.4 V vs SCE) that would interfere with other functional groups. Previous investigations suggest that methods are available to decrease the reduction potential, but no systematic investigation has been conducted that evaluates the reduction potential as a function of aryl‐substitution, mediator, or multi‐arm grafting. Cyclic voltammetric studies of a library of bis‐sulfonamides bearing different aryl substituents in DMF reveals that p‐NO2 substituted bis‐sulfonamide has the lowest reduction potential. Further investigations aimed at lowering the cathodic potential with polycyclic aromatic hydrocarbon mediators display negligible or no impact. This optimized condition was successfully applied to fully p‐nitrobenzenesulfonyl protected generation‐zero and generation‐one polyamidoamine dendrimers (G0.0‐PAMAM‐Ns and G1.0‐PAMAM‐Ns, respectively), demonstrating successful amine protection and deprotection on dendrimers for the first time.
The Kinetics of Droplet Sedimentation in Liquid‐Liquid Extraction
Authors: Bol Pornprapa , Rudelstorfer Georg , Grafschafter Annika , Siebenhofer Matthäus 
Published: November 2020

AbstractLiquid‐liquid extraction is a major separation process in chemical industry. Beside appropriate design of mass transfer equipment, successful design of phase separation equipment is an important issue. Therefore, the separation of liquid‐liquid dispersions was investigated and modeled with kinetic approaches to gain information for settler design. A modified first‐order sedimentation rate model, a first‐order consecutive step rate model, and a mixed‐order rate model were applied and compared to the experimental data. The advantage of kinetic modeling of the rate of sedimentation, specifically addressing the impact of viscosity and electrolyte concentration, was successfully demonstrated.
Cesium Ion‐Mediated Microporous Carbon for CO2 Capture and Lithium‐Ion Storage
Authors: Lee Hyeon Jeong , Ko Dongah , Kim Joo‐Seong , Park Youngbin , Hwang Insu , Yavuz Cafer T. , Choi Jang Wook 
Published: November 2020

AbstractActivated carbon has been used in a wide range of applications owing to its large specific area, facile synthesis, and low cost. The synthesis of activated carbon mostly relies on potassium hydroxide (KOH)‐mediated activation which leads to the formation of micropores (<2 nm) after a washing step with acid. Here we report the preparation of activated carbon with an anomalously large surface area (3288 m2 g−1), obtained by employing an activation process mediated by cesium (Cs) ions. The high affinity of the carbon lattice for Cs ions induces immense interlayer expansion upon complexation of the intercalant Cs ion with the carbon host. Furthermore, the Cs‐activation process maintains the nitrogen content of the carbon source by enabling the activation process at low temperature. The large surface area and well‐preserved nitrogen content of Cs‐activated carbon takes advantage of its enhanced interaction with CO2 molecules (for superior CO2 capture) and lithium ions (for improved Li ion storage), respectively. The present investigation unveils a new approach toward tuning the key structural properties of activated carbon; that is, controlling the affinity of the carbon host for the intercalant ion when they engage in complex formation during the activation process.
Area‐Minimizing Currents mod 2Q: Linear Regularity Theory
Authors: De Lellis Camillo , Hirsch Jonas , Marchese Andrea , Stuvard Salvatore 
Published: November 2020

AbstractWe establish a theory of Q‐valued functions minimizing a suitable generalization of the Dirichlet integral. In a second paper the theory will be used to approximate efficiently area minimizing currents mod(p) when p = 2Q, and to establish a first general partial regularity theorem for every p in any dimension and codimension . © 2020 The Authors. Communications on Pure and Applied Mathematics published by Wiley Periodicals LLC.
Protocols for Experimental Sjögren's Syndrome
Authors: Bagavant Harini , Deshmukh Umesh S. 
Published: November 2020

AbstractSjögren's syndrome (SS) is a systemic autoimmune disease affecting multiple organ systems. Salivary and lacrimal gland involvement cause dry mouth and dry eye and are the most common clinical presentations of the disease. Patients with SS also have autoantibodies targeting multiple nuclear and cytoplasmic antigens. Innate immune activation plays a critical role in SS pathogenesis. This article describes the activation of specific innate immune pathways in mice to study SS salivary gland manifestations. Methodologies for evaluating salivary gland inflammation and salivary function are described. This article also describes protocols for in‐house assays to measure autoantibody titers in serum. © 2020 Wiley Periodicals LLCBasic Protocol 1: Acceleration of Sjögren's syndrome by activating the toll‐like receptor 3 pathwayBasic Protocol 2: Induction of Sjögren's syndrome by activating the stimulator of interferon genes pathwayAlternate Protocol: Acceleration of Sjögren's syndrome by the administration of Freund's incomplete adjuvantSupport Protocol 1: Evaluating salivary gland functionSupport Protocol 2: Evaluating salivary gland inflammationSupport Protocol 3: Measuring autoantibody titers by indirect immunofluorescence
Tacrolimus Exposure Prediction Using Machine Learning
Authors: Woillard Jean‐Baptiste , Labriffe Marc , Debord Jean , Marquet Pierre 
Published: November 2020

The aim of this work is to estimate the area‐under the blood concentration curve of tacrolimus (TAC) following b.i.d. or q.d. dosing in organ transplant patients, using Xgboost machine learning (ML) models. A total of 4,997 and 1,452 TAC interdose area under the curves (AUCs) from patients on b.i.d. and q.d. TAC, sent to our Immunosuppressant Bayesian Dose Adjustment expert system (www.pharmaco.chu‐limoges.fr/) for AUC estimation and dose recommendation based on TAC concentrations measured at least at 3 sampling times (predose, ~ 1 and 3 hours after dosing) were used to develop 4 ML models based on 2 or 3 concentrations. For each model, data splitting was performed to obtain a training set (75%) and a test set (25%). The Xgboost models in the training set with the lowest root mean square error (RMSE) in a 10‐fold cross‐validation experiment were evaluated in the test set and in 6 independent full‐pharmacokinetic (PK) datasets from renal, liver, and heart transplant patients. ML models based on two or three concentrations, differences between these concentrations, relative deviations from theoretical times of sampling, and four covariates (dose, type of transplantation, age, and time between transplantation and sampling) yielded excellent AUC estimation performance in the test datasets (relative bias < 5% and relative RMSE < 10%) and better performance than maximum a posteriori Bayesian estimation in the six independent full‐PK datasets. The Xgboost ML models described allow accurate estimation of TAC interdose AUC and can be used for routine TAC exposure estimation and dose adjustment. They will soon be implemented in a dedicated web interface.
Performance and Sustainability Tradeoffs of Oxidized Carbon Nanotubes as a Cathodic Material in Lithium‐Oxygen Batteries
Authors: Falinski Mark M. , Albalghiti Eva M. , Backhaus Andreas , Zimmerman Julie B. 
Published: November 2020

AbstractClimate change mitigation efforts will require a portfolio of solutions, including improvements to energy storage technologies in electric vehicles and renewable energy sources, such as the high‐energy‐density lithium‐oxygen battery (LOB). However, if LOB technology will contribute to addressing climate change, improvements to LOB performance must not come at the cost of disproportionate increases in global warming potential (GWP) or cumulative energy demand (CED) over their lifecycle. Here, oxygen‐functionalized multi‐walled carbon nanotube (O‐MWCNT) cathodes were produced and assessed for their initial discharge capacities and cyclability. Contrary to previous findings, the discharge capacity of O‐MWCNT cathodes increased with the ratio of carbonyl/carboxyl moieties, outperforming pristine MWCNTs. However, increased oxygen concentrations decreased LOB cyclability, while high‐temperature annealing increased both discharge capacity and cyclability. Improved performance resulting from MWCNT post‐processing came at the cost of increased GWP and CED, which in some cases was disproportionately higher than the level of improved performance. Based on the findings presented here, there is a need to simultaneously advance research in improving LOB performance while minimizing or mitigating the environmental impacts of LOB production.
In Situ Classification of Cell Types in Human Kidney Tissue Using 3D Nuclear Staining
Authors: Woloshuk Andre , Khochare Suraj , Almulhim Aljohara F. , McNutt Andrew T. , Dean Dawson , Barwinska Daria , Ferkowicz Michael J. , Eadon Michael T. , Kelly Katherine J. , Dunn Kenneth W. , Hasan Mohammad A. , El‐Achkar Tarek M. , Winfree Seth 
Published: November 2020

AbstractTo understand the physiology and pathology of disease, capturing the heterogeneity of cell types within their tissue environment is fundamental. In such an endeavor, the human kidney presents a formidable challenge because its complex organizational structure is tightly linked to key physiological functions. Advances in imaging‐based cell classification may be limited by the need to incorporate specific markers that can link classification to function. Multiplex imaging can mitigate these limitations, but requires cumulative incorporation of markers, which may lead to tissue exhaustion. Furthermore, the application of such strategies in large scale 3‐dimensional (3D) imaging is challenging. Here, we propose that 3D nuclear signatures from a DNA stain, DAPI, which could be incorporated in most experimental imaging, can be used for classifying cells in intact human kidney tissue. We developed an unsupervised approach that uses 3D tissue cytometry to generate a large training dataset of nuclei images (NephNuc), where each nucleus is associated with a cell type label. We then devised various supervised machine learning approaches for kidney cell classification and demonstrated that a deep learning approach outperforms classical machine learning or shape‐based classifiers. Specifically, a custom 3D convolutional neural network (NephNet3D) trained on nuclei image volumes achieved a balanced accuracy of 80.26%. Importantly, integrating NephNet3D classification with tissue cytometry allowed in situ visualization of cell type classifications in kidney tissue. In conclusion, we present a tissue cytometry and deep learning approach for in situ classification of cell types in human kidney tissue using only a DNA stain. This methodology is generalizable to other tissues and has potential advantages on tissue economy and non‐exhaustive classification of different cell types.
Review of registered clinical trials for the treatment of COVID‐19
Authors: Babaei Fatemeh , Mirzababaei Mohammadreza , Nassiri‐Asl Marjan , Hosseinzadeh Hossein 
Published: November 2020

AbstractCoronavirus disease 2019 (COVID‐19) is a viral disease caused by severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2). The disease was first reported in December 2019 in Wuhan, China, but now more than 200 countries have been affected and the coronavirus pandemic is still ongoing. The severity of COVID‐19 symptoms can range from mild to severe. FDA approved remdesivir as a treatment of COVID‐19 so far. Various clinical trials are underway to find an effective method to treat patients with COVID‐19. This review aimed at summarizing 219 registered clinical trials in the ClinicalTrials.gov database with possible mechanisms, and novel findings of them, and other recent publications related to COVID‐19. According to our analyses, various treatment approaches and drugs are being investigated to find an effective drug to cure COVID‐19 and among all strategies, three important mechanisms are suggested to be important against COVID‐19 including antiviral, anti‐inflammatory, and immunomodulatory properties. Our review can help future studies get on the way to finding an effective drug for COVID‐19 treatment by providing ideas for similar researches.