bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fully Light‐Controlled Memory and Neuromorphic Computation in Layered Black Phosphorus
Authors: Ahmed Taimur , Tahir Muhammad , Low Mei Xian , Ren Yanyun , Tawfik Sherif Abdulkader , Mayes Edwin L. H. , Kuriakose Sruthi , Nawaz Shahid , Spencer Michelle J. S. , Chen Hua , Bhaskaran Madhu , Sriram Sharath , Walia Sumeet 
Published: November 2020

AbstractImprinting vision as memory is a core attribute of human cognitive learning. Fundamental to artificial intelligence systems are bioinspired neuromorphic vision components for the visible and invisible segments of the electromagnetic spectrum. Realization of a single imaging unit with a combination of in‐built memory and signal processing capability is imperative to deploy efficient brain‐like vision systems. However, the lack of a platform that can be fully controlled by light without the need to apply alternating polarity electric signals has hampered this technological advance. Here, a neuromorphic imaging element based on a fully light‐modulated 2D semiconductor in a simple reconfigurable phototransistor structure is presented. This standalone device exhibits inherent characteristics that enable neuromorphic image pre‐processing and recognition. Fundamentally, the unique photoresponse induced by oxidation‐related defects in 2D black phosphorus (BP) is exploited to achieve visual memory, wavelength‐selective multibit programming, and erasing functions, which allow in‐pixel image pre‐processing. Furthermore, all‐optically driven neuromorphic computation is demonstrated by machine learning to classify numbers and recognize images with an accuracy of over 90%. The devices provide a promising approach toward neurorobotics, human–machine interaction technologies, and scalable bionic systems with visual data storage/buffering and processing.
How Can Interfacial Phenomena in Nature Inspire Smaller Robots
Authors: Feldmann David , Das Rakesh , Pinchasik Bat‐El 
Published: November 2020

AbstractIn nature, surfaces are evolutionarily designed to allow adaptation of species to their environments. Insects make extensive use of interfacial phenomena because of their small size and thus, large surface‐area‐to‐volume ratio. This enables them to walk on different terrains, dive, swim, and adhere to surfaces in air and underwater. Moreover, they toggle between different interfaces, move in confined spaces, and overcome a wide range of obstacles. This progress report summarizes emerging directions in the field of bioinspired robotics with an emphasis on micro and nanoscale dynamic interactions. It is envisioned that interfacial phenomena will allow to miniaturize robots and increase the complexity of their operation. The key to success is the combination of functional surfaces, structural design and multiple modes of locomotion. For this to be realized, however, new paradigms are needed in terms of materials, fabrication, energy consumption, and actuation. This report discusses the development of small robots inspired by water striders, the bell spider, the leaf and ladybird beetles, backswimmers and cockroaches, among many others. It also discusses small soft robots inspired by roundworms, larvae, and parasites. From a broader perspective, fabrication of many small robots will enable to study collective effects and self‐assembly, group behavior and swarming.
Tunable Optical Properties of 2D Materials and Their Applications
Authors: Ma Qijie , Ren Guanghui , Xu Kai , Ou Jian Zhen 
Published: November 2020

AbstractRecent efforts have been heavily devoted to the development of next‐generation optoelectronic devices based on 2D materials, due to their unique optical properties that are distinctly different from those of bulk counterparts. Given that the feature of flexible tunability is highly desired, various approaches have been demonstrated to efficiently modulate the optical properties, eventually enabling peculiar functionalities or realizing high‐performance nanoscale devices. Here, this review focuses on recent advances in tuning the optical properties of 2D materials by external stimuli including electric field, mechanical strain, magnetic field, acoustic wave, and thermal heating. Also, such tunability leads to many emerging applications in the fields of electronics, optics, sensors, and energy harvesting, which are summarized and critically discussed in the paper.
Covalent Organic Frameworks in Catalytic Organic Synthesis
Authors: Cheng Hai‐Yang , Wang Tao 
Published: November 2020

AbstractCovalent organic frameworks (COFs), which are built upon dynamic covalent chemistry (DCC) with various organic building blocks, possess predesignable, highly ordered and crystalline porous structures. These features endow COFs with great potential in the development of function‐tailored materials, particularly in catalytic organic synthesis. Start from selective oxidation reactions early introduced by Ferdi, Thomas and their co‐workers, and then Wang and co‐workers performed Suzuki‐Miyaura reaction through integrating palladium into COFs, increasing numbers of works were established to explore their potentials in the 4.5catalysis of organic reactions. As heterogeneous organic catalysts, COFs bring benefits and solve problems, but also create new obstacles. Hence, we would like to establish a comprehensive system to review some pioneering works in this area. This will help us get a better view so that we can discuss the key and challenging issues we are currently confronted with.magnified image
Recent Advances in the Synthesis of Heterocyclics via Cascade Cyclization of Propargylic Alcohols
Authors: Song Xian‐Rong , Yang Ruchun , Xiao Qiang 
Published: November 2020

AbstractHeterocyclic compounds are important organic compounds and have emerged as key scaffolds in numerous drugs, natural products, vitamins, biologically and pharmaceutically active compounds. Over the past few decades, the development of versatile methodologies employing propargylic alcohols as synthons for the construction of heterocyclic skeletons has attracted great attention from synthetic chemists. In this review, recent developments in the cascade cyclization of propargylic alcohols with diverse nucleophiles to construct heterocyclic compounds are summarized. According to the types of nucleophiles, these reactions can be divided into four categories: 1) Reactions involving C‐nucleophiles to capture allenyl carbocation; 2) Reactions involving O, S‐nucleophiles to capture allenyl carbocation; 3) Reactions involving N, P‐nucleophiles to capture allenyl carbocation; 4) Reactions involving halo‐nucleophiles to capture allenyl carbocation.magnified image
Photocatalytic Oxygen Evolution from Water Splitting
Authors: Lin Sen , Huang Hongwei , Ma Tianyi , Zhang Yihe 
Published: November 2020

AbstractPhotocatalytic water splitting has attracted a lot of attention in recent years, and O2 evolution is the decisive step owing to the complex four‐electrons reaction process. Though many studies have been conducted, it is necessary to systematically summarize and introduce the research on photocatalytic O2 evolution, and thus a systematic review is needed. First, the corresponding principles about O2 evolution and some urgently encountered issues based on the fundamentals of photocatalytic water splitting are introduced. Then, several types of classical water oxidation photocatalysts, including TiO2, BiVO4, WO3, α‐Fe2O3, and some newly developed ones, such as Sillén–Aurivillius perovskites, porphyrins, metal–organic frameworks, etc., are highlighted in detail, in terms of their crystal structures, synthetic approaches, and morphologies. Third, diverse strategies for O2 evolution activity improvement via enhancing photoabsorption and charge separation are presented, including the cocatalysts loading, heterojunction construction, doping and vacancy formation, and other strategies. Finally, the key challenges and future prospects with regard to photocatalytic O2 evolution are proposed. The purpose of this review is to provide a timely summary and guideline for the future research works for O2 evolution.
Revealing the Similarities of α,β‐Unsaturated Iminiums and Acylazoliums in Organocatalysis
Authors: Ghosh Arghya , Biju Akkattu T. 
Published: November 2020

AbstractThe secondary amine‐catalyzed reactions proceeding via α,β‐unsaturated iminiums and the N‐heterocyclic carbene (NHC)‐catalyzed transformations taking place via α,β‐unsaturated acylazoliums are the two widely used electrophilic intermediates in organocatalysis. Over the last two decades, these two intermediates are extensively utilized for the enantioselective construction of valuable molecules. Both intermediates are generated by the covalent binding of catalysts to the substrates leading to LUMO activation of α,β‐unsaturated carbonyls. A variety of soft nucleophiles are known to add to the α,β‐unsaturated iminiums and acylazoliums in a conjugate fashion, and in many cases, striking similarity in reactivity has been observed. Having said this, there are few cases where these intermediates exhibit difference in reactivity. This Minireview is aimed at highlighting the resemblances in reactivity between α,β‐unsaturated iminiums and acylazoliums thereby shedding light on the unnoticed parallels of the two intermediates in organocatalysis.
Atypical Inter‐Network Deactivation Associated With the Posterior Default‐Mode Network in Autism Spectrum Disorder
Authors: Kotila Aija , Järvelä Matti , Korhonen Vesa , Loukusa Soile , Hurtig Tuula , Ebeling Hanna , Kiviniemi Vesa , Raatikainen Ville 
Published: November 2020

Previous studies have suggested that atypical deactivation of functional brain networks contributes to the complex cognitive and behavioral profile associated with autism spectrum disorder (ASD). However, these studies have not considered the temporal dynamics of deactivation mechanisms between the networks. In this study, we examined (a) mutual deactivation and (b) mutual activation‐deactivation (i.e., anticorrelated) time‐lag patterns between resting‐state networks (RSNs) in young adults with ASD (n = 20) and controls (n = 20) by applying the recently defined dynamic lag analysis (DLA) method, which measures time‐lag variations peak‐by‐peak between the networks. In order to achieve temporally accurate lag patterns, the brain imaging data was acquired with a fast functional magnetic resonance imaging (fMRI) sequence (TR = 100 ms). Group‐level independent component analysis was used to identify 16 RSNs for the DLA. We found altered mutual deactivation timings in ASD in (a) three of the deactivated and (b) two of the transiently anticorrelated (activated‐deactivated) RSN pairs, which survived the strict threshold for significance of surrogate data. Of the significant RSN pairs, 80% included the posterior default‐mode network (DMN). We propose that temporally altered deactivation mechanisms, including timings and directionality, between the posterior DMN and RSNs mediating processing of socially relevant information may contribute to the ASD phenotype.Lay SummaryTo understand autistic traits on a neural level, we examined temporal fluctuations in information flow between brain regions in young adults with autism spectrum disorder (ASD) and controls. We used a fast neuroimaging procedure to investigate deactivation mechanisms between brain regions. We found that timings and directionality of communication between certain brain regions were temporally altered in ASD, suggesting atypical deactivation mechanisms associated with the posterior default‐mode network.
Scaffold‐free biofabrication of adipocyte structures with magnetic levitation
Authors: Sarigil Oyku , Anil‐Inevi Muge , Firatligil‐Yildirir Burcu , Unal Yagmur Ceren , Yalcin‐Ozuysal Ozden , Mese Gulistan , Tekin H. Cumhur , Ozcivici Engin 
Published: November 2020

AbstractTissue engineering research aims to repair the form and/or function of impaired tissues. Tissue engineering studies mostly rely on scaffold‐based techniques. However, these techniques have certain challenges, such as the selection of proper scaffold material, including mechanical properties, sterilization, and fabrication processes. As an alternative, we propose a novel scaffold‐free adipose tissue biofabrication technique based on magnetic levitation. In this study, a label‐free magnetic levitation technique was used to form three‐dimensional (3D) scaffold‐free adipocyte structures with various fabrication strategies in a microcapillary‐based setup. Adipogenic‐differentiated 7F2 cells and growth D1 ORL UVA stem cells were used as model cells. The morphological properties of the 3D structures of single and cocultured cells were analyzed. The developed procedure leads to the formation of different patterns of single and cocultured adipocytes without a scaffold. Our results indicated that adipocytes formed loose structures while growth cells were tightly packed during 3D culture in the magnetic levitation platform. This system has potential for ex vivo modeling of adipose tissue for drug testing and transplantation applications for cell therapy in soft tissue damage. Also, it will be possible to extend this technique to other cell and tissue types.
Carbon management accounting and financial performance: Evidence from the European Union emission trading system
Authors: Naranjo Tuesta Yenny , Crespo Soler Cristina , Ripoll Feliu Vicente 
Published: November 2020

AbstractCompanies are responding to the effects of climate change by reducing CO2emissions as a way of managing stakeholder interests and complying with legal and regulatory requirements. In Europe, the emissions trading system is consolidated as a limiting market and control scheme to support business climate change management through a collaborative relationship between government and industry. This work focuses on the economic accounting field, analysing carbon management accounting and its impact on financial performance in scenarios attached to that trading system. The methodological approach used is quantitative, empirically testing the hypotheses through a multiple regression analysis with a sample of 350 European companies. The results attest to the importance of carbon management accounting (CMA) control and its effects on financial performance. Compared with European emission trading, the results failed to display significant differences in the relationship studied between those that make up this type of market and those that do not.
Deactivation of Industrial Pd/Al2O3 Catalysts by Ethanol: A Spectroscopic Study
Authors: Carosso Michele , Vottero Eleonora , Morandi Sara , Manzoli Maela , Ferri Davide , Fovanna Thibault , Pellegrini Riccardo , Piovano Andrea , Groppo Elena 
Published: November 2020

AbstractThe chemical processes involved in the decomposition of ethanol over two industrial Pd/Al2O3 catalysts characterized by different Pd dispersions, particles morphology and reducibility of the active metal phase was thoroughly investigated in gas‐phase and in liquid‐phase by transmission FT‐IR and ATR‐IR spectroscopies, respectively. In both cases, two main products were detected, arising from two competitive paths: acetates from ethanol oxidation and carbonyls from acetaldehyde decarbonylation. The regularity of the Pd particles greatly affects the relative proportion of the two products, while the initial Pd oxidation state influences the kinetics of the two processes. Ethanol oxidation to acetates is the kinetically favored reaction path both in gas‐phase and in liquid‐phase. In contrast, the presence of a solvent dampens the decarbonylation process to very low levels, because the solvent competes with ethanol in occupying the available surface sites. Since adsorbed carbonyls are considered as surface poisons of industrial Pd/Al2O3 catalysts in processes involving aliphatic as well as aromatic alcohols, the rationalization of the experimental variables affecting alcohols decomposition can help in establishing working protocols and in designing preparation procedures that minimize the unwanted poisoning effects.
(o‐Phenylenediamino)borylstannanes: Efficient Reagents for Borylation of Various Alkyl Radical Precursors
Authors: Suzuki Kensuke , Nishimoto Yoshihiro , Yasuda Makoto 
Published: November 2020

Abstract(o‐Phenylenediamino)borylstannanes were newly synthesized to achieve radical boryl substitutions of a variety of alkyl radical precursors. Dehalogenative, deaminative, decharcogenative, and decarboxylative borylations proceeded in the presence of a radical initiator to give the corresponding organic boron compounds. Radical clock experiments and computational studies have provided insights into the mechanism of the homolytic substitution (SH2) of the borylstannanes with alkyl radical intermediates. DFT calculation disclosed that the phenylenediamino structure lowered the LUMO level including the vacant p‐orbital on the boron atom to enhance the reactivity to alkyl radicals in SH2. Moreover, C(sp3)‐H borylation of THF was accomplished using the triplet state of xanthone.
Lung cancer screening eligibility and use with low‐dose computed tomography: Results from the 2018 Behavioral Risk Factor Surveillance System cross‐sectional survey
Authors: Narayan Anand K. , Gupta Yasha , Little Brent P. , Shepard Joanne O. , Flores Efren J. 
Published: November 2020

BackgroundIn randomized controlled trials, lung cancer screening with low‐dose chest computed tomography (LCS) has been reported to reduce lung cancer mortality. Although initial studies suggested that only approximately 5% of eligible patients have undergone LCS, recent studies have indicated that use of LCS may be increasing nationwide. The objective of the current study was to estimate recent LCS use using cross‐sectional survey data from the 2018 Behavioral Risk Factor Surveillance System (BRFSS) survey.MethodsThe BRFSS is a nationally representative, cross‐sectional telephone survey of adults in the United States (response rate of approximately 50%). The 2018 BRFSS survey included questions regarding LCS eligibility and use in 8 states. The primary outcome was the percentage of participants (aged 55‐79 years with a smoking history of >30 pack‐years) who reported undergoing LCS. Logistic regression analyses evaluated the association between LCS use and sociodemographic characteristics, adjusted for potential confounders and accounting for complex survey design elements.ResultsA total of 26,910 participants were included, 9.9% of whom were eligible for LCS (95% CI, 8.8%‐10.6%). Of the eligible patients, 19.2% reported undergoing LCS (95% CI, 14.0%‐24.4%). Approximately 16.4% of current smokers were eligible for LCS (95% CI, 14.2%‐18.6%). In our multiple variable analyses of eligible patients, age, sex, marital status, current smoking status, and race were not found to be associated with statistically significant differences in reported LCS (P > .05). Retired patients, patients with personal physicians, and patients who did not complete a high school education were more likely to report receiving LCS (P < .05).ConclusionsCompared with previously published studies, the results of the current study suggested that LCS use is increasing. However, LCS use remains low (19%) among eligible participants.
Nanorods Based on Mesoporous Silica Containing Iron Oxide Nanoparticles as Catalytic Nanomotors: Study of Motion Dynamics
Authors: Mestre Rafael , Cadefau Núria , Hortelão Ana C. , Grzelak Jan , Gich Martí , Roig Anna , Sánchez Samuel 
Published: November 2020

AbstractSelf‐propelled particles and, in particular, those based on mesoporous silica, have raised considerable interest due to their potential applications in the environmental and biomedical fields thanks to their biocompatibility, tunable surface chemistry and large porosity. Although spherical particles have been widely used to fabricate nano‐ and micromotors, not much attention has been paid to other geometries, such as nanorods. Here, we report the fabrication of self‐propelled mesoporous silica nanorods (MSNRs) that move by the catalytic decomposition of hydrogen peroxide by a sputtered Pt layer, Fe2O3 nanoparticles grown within the mesopores, or the synergistic combination of both. We show that motion can occur in two distinct sub‐populations characterized by two different motion dynamics, namely enhanced diffusion or directional propulsion, especially when both catalysts are used. These results open up the possibility of using MSNRs as chassis for the fabrication of self‐propelled particles for the environmental or biomedical fields.
Stock movement prediction with sentiment analysis based on deep learning networks
Authors: Shi Yong , Zheng Yuanchun , Guo Kun , Ren Xinyue 
Published: November 2020

AbstractWith the development of Internet and big data, it is more convenient for investors to share opinions or have a discuss with others via the web, which creates massive unstructured data. These data reflect investors' emotions and their investment intentions, and it will further affect the movement of the stock market. Although researchers have been attempted to use sentiment information to predict the market, the sentiment features used are driven by outdated emotion extraction systems. In this article, we proposed a new sentiment analysis system with deep neural networks for stock comments and applied estimated sentiment information to the stock movement forecasting. The empirical results showed that our deep sentiment classification method achieved a 9% improvement over the logistic regression algorithm, and provided an accurate sentiment extractor for the next predicting step. In addition our new hybrid features that mix stock trading data and sentiment information achieved 1.25% improvement among 150 Chinese stocks in the testing dataset. For American stocks, the sentiment information would reduced the predicting results. We found that emotion features extracted from comments are indeed effective for stocks with a higher price to book value and a lower beta risk value in China.
Artificial Neural Networks for Noise Removal in Data‐Sparse Charged Particle Imaging Experiments
Authors: Sparling Chris , Ruget Alice , Kotsina Nikoleta , Leach Jonathan , Townsend Dave 
Published: November 2020

AbstractWe present the first demonstration of artificial neural networks (ANNs) for the removal of Poissonian noise in charged particle imaging measurements with very low overall counts. The approach is successfully applied to both simulated and real experimental image data relating to the detection of photoions/photoelectrons in unimolecular photochemical dynamics studies. Specific examples consider the multiphoton ionization of pyrrole and (S)‐camphor. Our results reveal an extremely high level of performance, with the ANNs transforming images that are unusable for any form of quantitative analysis into statistically reliable data with an impressive similarity to benchmark references. Given the widespread use of charged particle imaging methods within the chemical dynamics community, we anticipate that the use of ANNs has significant potential impact – particularly, for example, when working in the limit of very low absorption/photoionization cross‐sections, or when attempting to reliably extract subtle image features originating from phenomena such as photofragment vector correlations or photoelectron circular dichroism.