bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ultrathin Anion Conductors Based Memristor
Authors: Xiong Xuya , Xiong Feng , Tian He , Wang Zegao , Wang Yuqing , Tao Rui , Klausen Lasse Hyldgaard , Dong Mingdong 
Published: November 2021

AbstractThe accumulation and motion of metal ions in the ferroelectric oxide and layered dichalcogenides play a critical role in the development of nonvolatile, adaptive memories for applications in neuromorphic computing. To further simplify and control this fundamental process in electronic devices, anion conductors based memristor is first developed by using layered double hydroxide (LDH) as the active materials, where the intercalated ions in subatomic interlayer have superior ion conductivity exhibiting memristive effect. The results show that LDH memristors exhibit abnormal resistive switching behavior with ON/OFF ratio up to 105 at room temperature with the set/reset voltage distribution of 0.3 V. Further studying reveals that the LDH memristior shows stable abnormal unipolar characteristics, following the space‐charge‐limited current transport theory. In situ conductive atomic force microscopy measurements visualize the formation of conductive channels under external bias and significantly reveal the linear correlation between set voltage and the thickness of LDH with the slope of 0.13 V per molecular layer. The results indicate ions may play the key role in realizing set and reset process. The newly reported resistive switching behavior of LDH may shed lights on the development of more intercalated 2D materials based memristor.
Crystal Facet Engineering Induced Active Tin Dioxide Nanocatalysts for Highly Stable Lithium–Sulfur Batteries
Authors: Jiang Bo , Qiu Yue , Tian Da , Zhang Yu , Song Xueqin , Zhao Chenghao , Wang Maoxu , Sun Xun , Huang Huihuang , Zhao Chenyang , Zhou Hao , Chen Aosai , Fan Lishuang , Zhang Naiqing 
Published: November 2021

AbstractControlling exposed crystal facets through crystal facet engineering is an efficient strategy for enhancing the catalytic activity of nanocrystalline catalysts. Herein, the active tin dioxide nano–octahedra enclosed by {332} crystal facets (SnO2 {332}) are synthesized on reduced graphene oxide and demonstrate powerful chemisorption and catalytic ability, accelerating the redox kinetics of sulfur species in lithium–sulfur chemistry. Attributed to abundant unsaturated–coordinated Sn sites on {332} crystal planes, SnO2 {332} has outstanding adsorption and catalytic properties. The material not only adsorbs and converts polysulfides efficiently, but also prominently lowers the decomposition energy barrier of Li2S. The batteries with these high active electrocatalysts exhibit excellent cycling stability with a low capacity attenuation of 0.021% every cycle during 2000 cycles at 2 C. Even with a sulfur loading of 8.12 mg cm−2, the batteries can still cycle stably and maintain a prominent areal capacity of 6.93 mAh cm−2 over 100 cycles. This research confirms that crystal facet engineering is a promising strategy to optimize the performance of catalysts, deepens the understanding of surface structure‐oriented electrocatalysis in Li–S chemistry, while aiding the rational design of advanced sulfur electrodes.
Remembering for the right reasons: Explanations reduce catastrophic forgetting
Authors: Ebrahimi Sayna , Petryk Suzanne , Gokul Akash , Gan William , Gonzalez Joseph E. , Rohrbach Marcus , Darrell Trevor 
Published: November 2021

AbstractThe goal of continual learning (CL) is to learn a sequence of tasks without suffering from the phenomenon of catastrophic forgetting. Previous work has shown that leveraging memory in the form of a replay buffer can reduce performance degradation on prior tasks. We hypothesize that forgetting can be further reduced when the model is encouraged to remember the evidence for previously made decisions. As a first step towards exploring this hypothesis, we propose a simple novel training paradigm, called Remembering for the Right Reasons (RRR), that additionally stores visual model explanations for each example in the buffer and ensures the model has “the right reasons” for its predictions by encouraging its explanations to remain consistent with those used to make decisions at training time. Without this constraint, there is a drift in explanations and increase in forgetting as conventional continual learning algorithms learn new tasks. We demonstrate how RRR can be easily added to any memory or regularization‐based approach and results in reduced forgetting, and more importantly, improved model explanations. We have evaluated our approach in the standard and few‐shot settings and observed a consistent improvement across various CL approaches using different architectures and techniques to generate model explanations and demonstrated our approach showing a promising connection between explainability and continual learning. Our code is available at https://github.com/SaynaEbrahimi/Remembering-for-the-Right-Reasons.
Measuring and characterizing generalization in deep reinforcement learning
Authors: Witty Sam , Lee Jun K. , Tosch Emma , Atrey Akanksha , Clary Kaleigh , Littman Michael L. , Jensen David 
Published: November 2021

AbstractDeep reinforcement learning (RL) methods have achieved remarkable performance on challenging control tasks. Observations of the resulting behavior give the impression that the agent has constructed a generalized representation that supports insightful action decisions. We re‐examine what is meant by generalization in RL, and propose several definitions based on an agent's performance in on‐policy, off‐policy, and unreachable states. We propose a set of practical methods for evaluating agents with these definitions of generalization. We demonstrate these techniques on a common benchmark task for deep RL, and we show that the learned networks make poor decisions for states that differ only slightly from on‐policy states, even though those states are not selected adversarially. We focus our analyses on the deep Q‐networks (DQNs) that kicked off the modern era of deep RL. Taken together, these results call into question the extent to which DQNs learn generalized representations, and suggest that more experimentation and analysis is necessary before claims of representation learning can be supported.
Improving users' mental model with attention‐directed counterfactual edits
Authors: Alipour Kamran , Ray Arijit , Lin Xiao , Cogswell Michael , Schulze Jurgen P. , Yao Yi , Burachas Giedrius T. 
Published: November 2021

AbstractIn the domain of visual question answering (VQA), studies have shown improvement in users' mental model of the VQA system when they are exposed to examples of how these systems answer certain image‐question (IQ) pairs. In this work, we show that showing controlled counterfactual IQ examples are more effective at improving the mental model of users as compared to simply showing random examples. We compare a generative approach and a retrieval‐based approach to show counterfactual examples. We use recent advances in generative adversarial networks to generate counterfactual images by deleting and inpainting certain regions of interest in the image. We then expose users to changes in the VQA system's answer on those altered images. To select the region of interest for inpainting, we experiment with using both human‐annotated attention maps and a fully automatic method that uses the VQA system's attention values. Finally, we test the user's mental model by asking them to predict the model's performance on a test counterfactual image. We note an overall improvement in users' accuracy to predict answer change when shown counterfactual explanations. While realistic retrieved counterfactuals obviously are the most effective at improving the mental model, we show that a generative approach can also be equally effective.
Oral manifestations of Ehlers‐Danlos syndromes
Authors: Lepperdinger Ulrike , Zschocke Johannes , Kapferer‐Seebacher Ines 
Published: November 2021

AbstractEhlers‐Danlos syndromes (EDS) are a group of inherited connective tissue disorders. Patients with EDS exhibit distinct pathologies of the teeth and the oral cavity. Here, we summarize the current knowledge in the various EDS types, in particular regarding severe changes in oral health‐related quality of life, the differential emergence of periodontitis, characteristic yet highly cumbersome dental manifestations, apparent anomalies of oral soft tissues, and relevant issues related to dental implantology. Resolution of remaining open questions will primarily rely on the standardization of diagnostic criteria. Clinical centers that specialize on this rare pathology need to apply congruent approaches for exact characterization of clinical features in conjunction with genetic validation that should be reached without exception in all patients and relevant family members.
Neurodevelopmental atypisms in the context of joint hypermobility, hypermobility spectrum disorders, andEhlers–Danlossyndromes
Authors: Baeza‐Velasco Carolina 
Published: November 2021

AbstractJoint hypermobility (JHM), defined as an increased range of joint motion, is a frequent somatic trait in the general population but also the hallmark of many of the hereditary disorders of connective tissue. Ehlers–Danlos syndromes (EDS) belong to this group of diseases and are characterized by tissue fragility, skin abnormalities, and JHM. Between JHM and EDS, there are the so‐called hypermobility spectrum disorders (HSD), which is an umbrella term referring to people with symptomatic JHM who do not fulfill criteria for a syndromic connective tissue disorder such as EDS. Among the variety of clinical correlates of JHM/HSD/EDS, neurodevelopmental atypisms are common although often not screened for and identified in the clinical setting. This article reviews the pertinent literature concerning neurodevelopmental conditions for which there is some evidence of an association with JHM/HSD/EDS. These include hyperactivity and attention deficit, learning, communication, and motor problems including tic disorders such as Tourette syndrome and autism spectrum disorders. Underlying mechanism hypotheses for such interconnections are also reviewed. The coexistence of connective tissue‐altered conditions and neurodevelopmental atypisms increases disability in patients from an early age. Thus, increased awareness among clinicians and researchers is necessary to promote assessment, diagnosis, and develop management strategies to meet the specific needs of those affected.
Assessing bidirectional associations between cognitive impairment and late age‐related macular degeneration in the Age‐Related Eye Disease Study 2
Authors: Le Jimmy T. , Agrón Elvira , Keenan Tiarnan D. L. , Clemons Traci E. , Brenowitz Willa D. , Yaffe Kristine , Chew Emily Y. ,   for the AREDS2 Research Group
Published: November 2021

AbstractIntroductionWe aimed to investigate bidirectional associations between cognitive impairment and late age‐related macular degeneration (AMD).MethodsParticipants in the Age‐Related Eye Disease Study 2 (AREDS2) received annual eye examinations and cognitive function testing (e.g., Modified Telephone Interview for Cognitive Status [TICS‐M]). We examined bidirectional associations between cognitive impairment (e.g., a TICS‐M score < 30) and late AMD at 5 and 10 years.ResultsFive thousand one hundred eighty‐nine eyes (3157 participants; mean age 72.7 years) were analyzed and followed for a median of 10.4 years. Eyes of participants with cognitive impairment at baseline were more likely to progress to late AMD at 5 years (hazard ratio [HR], 1.24; 95% confidence interval [CI], 1.08–1.43) and 10 years (HR, 1.20; 95% CI, 1.05–1.37) than eyes of participants without cognitive impairment. Worse baseline AMD severity was not associated with developing cognitive impairment.DiscussionCognitive impairment is associated with late AMD progression in AREDS2. Our finding highlights the importance of eyecare for people with cognitive impairment.
Personalized nutrition for dementia prevention
Authors: Samieri Cécilia , Yassine Hussein N. , Melo van Lent Debora , Lefèvre‐Arbogast Sophie , van de Rest Ondine , Bowman Gene L. , Scarmeas Nikolaos 
Published: November 2021

AbstractThe role of nutrition has been investigated for decades under the assumption of one‐size‐fits‐all. Yet there is heterogeneity in metabolic and neurobiological responses to diet. Thus a more personalized approach may better fit biological reality and have increased efficacy to prevent dementia. Personalized nutrition builds on the food exposome, defined as the history of diet‐related exposures over the lifetime, and on its interactions with the genome and other biological characteristics (eg, metabolism, the microbiome) to shape health. We review current advances of personalized nutrition in dementia research. We discuss key questions, success milestones, and future roadmap from observational epidemiology to clinical studies through basic science. A personalized nutrition approach based on the best prescription for the most appropriate target population in the most relevant time‐window has the potential to strengthen dementia‐prevention efforts.
Preparation of Pickering‐polyHIPEs from surface modified pumice stabilized high internal phase emulsions as supporting materials for lauric acid impregnation
Authors: Mert Hatice Hande , Eslek Ali , Mert Mehmet Selçuk , Mert Emine Hilal 
Published: November 2021

AbstractPreparation of Pickering‐high internal phase emulsions (HIPEs) of methyl methacrylate (MMA) and divinylbenzene (DVB) by using natural abundant pumice zeolite was performed. Pumice was surface modified with cethyl trimethyl ammonium bromide (CTAB) to increase its compatibility with the emulsion phases. By using a combination of CTAB‐modified pumice (CtP) and low amount of non‐ionic emulsifier mixture Pickering‐HIPEs were obtained. The influence of the amount of surface modified pumice and emulsifier mixture on the emulsion stability was observed. The morphological, thermal, and mechanical properties of the obtained polyMMA‐based Pickering‐polyHIPEs were investigated by altering the amount of CtP loading. Moreover, the Pickering‐polyHIPE monolith exhibiting an open‐porous network was used as supporting matrix for lauric acid (LA). The thermal characterization of the resulting LA impregnated Pickering‐polyHIPE composite revealed that the impregnation rate of LA is 42.08%. The latter formed Pickering‐polyHIPE composite showed a good performance in latent heat storage due to the 111.2 J/g of normalized enthalpy of LA within the Pickering‐polyHIPE composite.
Construction of novel regenerated cellulose based foam derived from waste cigarette filters as effective oil adsorbent
Authors: Zhang Qingling , Cheng Youliang , Fang Changqing , Shi Jiayu 
Published: November 2021

AbstractThe reuse of waste cigarette filters is helpful to save resources and protect environment, and cellulose based functional materials can be applied in wastewater treatment due to the high porosity. Therefore, a novel kind of cellulose foams were fabricated by using waste cigarette filters and polyvinyl alcohol via a lyophilization technology and hydrophobicity modification in this work. As‐prepared foams possessed an ultra‐low density and high specific surface area (up to 40 m2 g−1). After the hydrophobicity modification, the cellulose foam exhibited a water contact angle of 91.9° and 126.2° on external surface and cross section, which showed a superior oil adsorption capacity of 14 g g−1. These developed cellulose foams have a low cost, good hydrophobicity and high adsorption capacity for oil as a promising absorbent, realizing the conversion of waste into high‐value products successfully.
Evaluating commercially available wireless cardiovascular monitors for measuring and transmitting real‐time physiological responses in children with autism
Authors: Nuske Heather J. , Goodwin Matthew S. , Kushleyeva Yelena , Forsyth Daniel , Pennington Jeffrey W. , Masino Aaron J. , Finkel Emma , Bhattacharya Anushua , Tan Jessica , Tai Hungtzu , Atkinson‐Diaz Zabryna , Bonafide Christopher P. , Herrington John D. 
Published: November 2021

AbstractCommercially available wearable biosensors have the potential to enhance psychophysiology research and digital health technologies for autism by enabling stress or arousal monitoring in naturalistic settings. However, such monitors may not be comfortable for children with autism due to sensory sensitivities. To determine the feasibility of wearable technology in children with autism age 8–12 years, we first selected six consumer‐grade wireless cardiovascular monitors and tested them during rest and movement conditions in 23 typically developing adults. Subsequently, the best performing monitors (based on data quality robustness statistics), Polar and Mio Fuse, were evaluated in 32 children with autism and 23 typically developing children during a 2‐h session, including rest and mild stress‐inducing tasks. Cardiovascular data were recorded simultaneously across monitors using custom software. We administered the Comfort Rating Scales to children. Although the Polar monitor was less comfortable for children with autism than typically developing children, absolute scores demonstrated that, on average, all children found each monitor comfortable. For most children, data from the Mio Fuse (96%–100%) and Polar (83%–96%) passed quality thresholds of data robustness. Moreover, in the stress relative to rest condition, heart rate increased for the Polar,F(1,53) = 135.70,p < 0.001,ηp2 = 0.78, and Mio Fuse,F(1,53) = 71.98,p < 0.001,ηp2 = 0.61, respectively, and heart rate variability decreased for the Polar,F(1,53) = 13.41,p = 0.001,ηp2 = 0.26, and Mio Fuse,F(1,53) = 8.89,p = 0.005,ηp2 = 0.16, respectively. This feasibility study suggests that select consumer‐grade wearable cardiovascular monitors can be used with children with autism and may be a promising means for tracking physiological stress or arousal responses in community settings.Lay SummaryCommercially available heart rate trackers have the potential to advance stress research with individuals with autism. Due to sensory sensitivities common in autism, their comfort wearing such trackers is vital to gathering robust and valid data. After assessing six trackers with typically developing adults, we tested the best trackers (based on data quality) in typically developing children and children with autism and found that two of them met criteria for comfort, robustness, and validity.
Designing a circular business strategy: 7 years of evolution at a large washing machine manufacturer
Authors: van Loon Patricia , Van Wassenhove Luk N. , Mihelic Ales 
Published: November 2021

AbstractThis paper discusses the development of circular business models for a large white goods manufacturer. A 7‐year journey in designing, discussing, adapting, and finally finding a potentially profitable circular offer is summarized, and the barriers that had to be overcome in this process are highlighted. The shift from selling washing machines to repeated leases with remanufacturing steps in‐between turned out to be very challenging. Despite the numerous claims in the consulting world that both manufacturers and consumers can benefit from the transition to a circular economy, it took multiple iterations to find a business model with the potential of being economically attractive to both the company and the client. The transformation process of shifting to a circular business model tends to be highly underestimated by companies and involves many issues beyond product design such as customer relationships, return logistics, remanufacturing operations, and service contracts. Researchers will need to work with companies to address the transition issues and to increase the relevance of circular economy research.
Experimental and Computational Analysis of the Solution and Solid‐State Conformations of Hexadepsipeptides from Beauveria felina
Authors: Du Feng‐Yu , Mándi Attila , Li Xiao‐Ming , Meng Ling‐Hong , Kurtán Tibor , Wang Bin‐Gui 
Published: November 2021

Comprehensive SummaryChemical investigation of Beauveria felina, a marine‐derived entomopathogenic fungus, obtained two new destruxin hexadepsipeptides (1 and 2) containing an L‐Ala5 residue instead of the usual N‐Me‐L‐Ala5. Interestingly, the presence of the L‐Ala5 residue enabled two slowly‐exchanging solution conformers with cis/trans (ILE3)‐(N‐Me‐Val4) amide bond for 1 and 2 with 1.5 : 1 and 1 : 1 cis/trans ratios, respectively, while only the conformer with cis amide bond was found in the solid‐state. The solution and solid‐state conformers were studied by NMR, X‐ray diffraction and solution and solid‐state ECD measurements, as well as by TDDFT‐ECD calculations. Structural (conformational) parameter‐activity correlations suggested that the extended destruxin geometry with the preferred cis (ILE3)‐(N‐Me‐Val4) bond probably resulted in improved bioactivity and reduced toxicity for the destruxin class. This was the first report on the interconversion phenomenon of cis/trans amide bonds of destruxin class, which could give insights in the development of bioactive destruxin agents with lower toxicity.
A Two‐Dimensional Semiconductive Metal‐Organic Framework for Highly Efficient Microwave Absorption
Authors: Miao Peng , Zhang Tao , Wang Teng , Chen Juan , Gao Tong , Wang You , Kong Jie , Chen Kai‐Jie 
Published: November 2021

Comprehensive SummaryAdvanced microwave absorbing materials (MAMs) are urgently required to eliminate and attenuate microwaves to address the ubiquitous microwave radiations and interference. In this contribution, we report the microwave absorption application of a two‐dimensional (2D) semiconductive metal‐organic framework (MOF), i.e., CuHT (HT = 4‐hydroxythiophenol), without any pyrolysis at high temperature. Owing to the suitable electrical conductivity (2.69 × 10–4 S·cm–1), CuHT renders remarkable microwave absorption performance, with the minimum reflection loss (RLmin) of –50.9 dB and the effective absorption bandwidth of 4.2 GHz (7.7—10.9 GHz) at a thickness of 1.74 mm. Based on DFT calculation, microwave attenuation is mainly originated from resistance loss due to the conducting planes of honeycomb‐like Cu2S layers. Thanks to the facile kilogram‐scale synthesis, CuHT holds great potential for future microwave absorption applications.
Using smooth metamers to estimate color appearance metrics for diverse color‐normal observers
Authors: Smet Kevin A. G. , Webster Michael A. , Whitehead Lorne A. 
Published: November 2021

AbstractColor‐normal subjects sometimes disagree about metameric matches involving highly structured spectral power distributions (SPDs), because their cone fundamentals differ slightly, but non‐negligibly. This has significant implications for the design of light sources and displays, so it should be estimated. We propose a broadly applicable estimation method based on a simple adaptive “front‐end” interface that can be used with any selected standard color appearance model. The interface accepts, as input, any set of color‐matching functions for the individual subject (eg, these could be that person's cone response functions) and also the associated tristimulus values for the test stimulus and also for the reference stimulus (ie, reference white). The interface converts these data into tristimulus values of the form used by the selected color appearance model (which could, eg, be X, Y, Z), while also carrying out the needed transform, which is based on an estimate of the subject's likely previous long‐term adaptations to their unique cone fundamentals. The selected standard color appearance model then provides color appearance data that are an estimate of the color appearance of the test stimulus, for that individual subject. This information has the advantage of being interpretable within that model's well‐known color space. The adaptive front end is based on the fact that, for any selected input SPD and the subject's unique color matching functions, there can be many different SPDs that are metameric for that individual. Since observer‐to‐observer color perception differences are minimized for spectrally smooth SPDs, smooth metamers predict color appearances reasonably accurately.