bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effects of low‐pressure radio‐frequency cold plasma on the biochemical parameters and fatty acid profile of wheat flours
Authors: Gao Guangbiao , Wu Jianzhang , Wei Zheng , Li Xingjun 
Published: October 2022

AbstractBackground and ObjectivesCold plasma (CP) treatment is a promising way to remove mycotoxins from cereal kernels, although its effects on nutrient contents remain unclear. This study evaluates the biochemical parameters, gelatinization properties, and fatty acid profile of Chinese hard‐white wheat flour treated with low‐pressure radio‐frequency (RF) CP (13.56 MHz, 140 Pa, helium or oxygen, 120 W, 0–180 s, 70 g sample).Findings120 W oxygen and helium plasma respectively required 90 and 120 s treatment to remove 50% deoxynivalenol (DON) from hard‐white wheat flour samples with 1.22 μg/g DON. A General Linear Model–Univariate analysis shows that oxygen and helium plasma both significantly increased water absorption rate, conductivity, and contents of reducing sugars, amylose, soluble protein, and saturated fatty acids in wheat flours but decreased the contents of soluble amino acids, total, unsaturated, mono‐unsaturated and poly‐unsaturated fatty acids, and enthalpy of gelatinization, and kept gelatinization peak temperature. At the same treatment time, helium plasma induced a higher water absorption rate, conductivity, and contents of pentosan and sulfhydryl groups in wheat flours than oxygen plasma. Oxygen plasma induced more reductions in mono‐ and poly‐unsaturated fatty acids in wheat flours than helium plasma. Compared with the untreated samples, helium plasma increased the values of water SRC, NaHCO3 SRC, and sucrose SRC, but decreased the lactic acid SRC, suggesting that the flour functional polymers were modified by helium plasma treatment, but oxygen plasma kept these four SRC values and did not significantly alter the functional polymers in wheat flour.ConclusionThe treatment with low‐pressure RF CP can increase hydrophilicity, and unsaturated fatty acid oxidation in wheat flours while kept starch gelatinization, and helium plasma can modify the flour's functional polymers.Significance and NoveltyThe suitable helium CP treatment (low‐pressure RF, 120 W, and 90–120 s) is a promising way to reduce the contaminants of wheat flours and improve their functional properties.
Visualizing Structural and Chemical Transformations of an Industrial Cu/ZnO/Al2O3 Pre‐catalyst during Activation and CO2 Reduction
Authors: Huang Xing , Beck Arik , Fedorov Alexey , Frey Hannes , Zhang Bingsen , Klötzer Bernhard , van Bokhoven Jeroen A. , Copéret Christophe , Willinger Marc‐Georg 
Published: October 2022

AbstractThe typical industrial catalyst used for methanol synthesis is a multi‐component catalyst based on Cu/ZnO/Al2O3. The synergies between various phases of this catalyst play a vital role in defining the overall catalytic function and performance. To gain insights into the role and interaction between the relevant components and phases, ex situ and in situ transmission electron microscopy (TEM) was deployed to investigate the structures and phases of an industrial Cu/ZnO/Al2O3 in its precursor, activated and reaction states. High structural inhomogeneity in this material is revealed, i. e. the presence of various phases with different morphologies and compositions. It is shown how structural and compositional changes occur during hydrogen treatment and how compositional inhomogeneity in the starting material translates into differences in the local composition of the activated and working catalyst. The formation of defective metallic copper particles (stacking faults and twins) that are in an intimate contact with zinc oxide (poorly crystalline, partially reduced ZnOx and crystalline ZnO), alumina, Zn−Al oxide and carbon‐zinc‐oxygen containing phases (such as zinc formate) is observed. It is also uncovered that alumina plays a potentially important role in stabilizing cationic zinc species. This work provides atomic‐level insight into the relevant state of an industrial methanol synthesis catalyst and the associated synergistic interplay between the involved phases in reactive atmosphere.
Cationic Palladium Catalyzed Nonalternating Copolymerization of Ethylene with Carbon Monoxide: Microstructure Analysis and Computational Study†
Authors: Li Shi‐Huan , Pan Ru‐Chao , Ren Bai‐Hao , Yang Jian‐Wei , Kang Xiaohui , Liu Ye 
Published: October 2022

Comprehensive SummaryThe introduction of carbonyl group with a high density in polyethylene backbone corresponds to polyketone materials, which features excellent mechanical strength, crystallinity, photodegradability, hydrophilicity, surface and barrier properties. Due to the extremely high binding affinity of carbon monoxide (CO) and kinetic preference for its subsequent insertion, the formation of nonalternating structure with extra ethylene insertion is exceptionally challenging, however, this nonalternating strategy is of significant importance for polymer modification in term of processing and solubility. Here, we have communicated our study on cationic palladium coordinated diphosphazane monoxide (PNPO) for the nonalternating copolymerization of ethylene with CO, the systematical investigation on the amine and phosphine oxide moieties in PNPO platform in term of electronic and steric modulation has been performed. It is discovered that the installation of aliphatic structure on amine moiety favors the improvement of catalyst activity and longevity, while the amino groups on phosphine oxide moiety promotes the nonalternating copolymerization. In particular, we have computationally investigated herein the aspects of the nonalternating degree by comparing with PNPO platform and 1,3‐bis(diphenylphosphanyl)propane ligands based palladium catalysts. These mechanistic studies can help to understand the catalyst structure and polyketone property relationships and shed light on future design of high‐performance copolymerization catalysts.
Imidazolylpyrrolone‐Based Small Molecules as Anticancer Agents for Renal Cell Carcinoma
Authors: Sousa Ana , Pontes Olívia , Andrade Juliana , Baltazar Fátima , Costa Marta , Proença Fernanda 
Published: October 2022

AbstractAn in silico study focused on known cancer‐related target proteins, identified a selection of imidazo[4,5‐b]pyrrolo[3,4‐d]pyridines as potentially active. These compounds were prepared by a novel synthetic approach, designed and developed in‐house, based on the reaction of 5‐amino‐4‐cyanoformimidoyl imidazoles with N‐substituted cyanoacetamides. The substituted imidazolylpyrrolones obtained, were cyclized intramolecularly to generate the intended imidazo[4,5‐b]pyrrolo[3,4‐d]pyridines in a process catalyzed by DBU. Treating the imidazolylpyrrolones with an excess of triethyl orthoformate and heating at 80 °C in the presence of acid catalysis led to imidazopyrrolodiazepines. These compounds were screened for their anticancer potential, using the renal cell carcinoma cell line model (A498 and 786‐O cell lines). Two compounds exhibited IC50 values in the low micromolar range with a good selectivity index, when compared to non‐neoplastic kidney cell line HK2 and the reference compounds rapamycin, cediranib and sunitinib.
Evaluating COVID‐19 risk under the estimation of population mean using two attributes
Authors: Mushtaq Nadia , Saleem Iram , Amjad Mustansar Aatizaz 
Published: October 2022

AbstractThe virus of COVID‐19 has affected humans physically, mentally, and economically all over the world. Each country's development level, resources, and immunization to have coping capacity against this covid19 differ country‐wise. Thus, understanding socioeconomic vulnerability and coping capacity among countries under different health systems can be crucial. Contrasting most articles on COVID‐19, this article focuses on evaluating and estimating the COVID‐19 risk and lack of coping capacity in 190 countries. This present study suggests an exponential estimator using two auxiliary attributes. Theoretically, the mean square error expressions are derived and compared with some existing estimators. These findings were supported by using the real data of INFORM COVID‐19 risk.
An energy efficiency perceptive on MIMO‐OFDM systems using hybrid fruit fly‐based salp swarm optimization technique
Authors: Harish Kumar G. , Rao P. Trinatha 
Published: October 2022

AbstractThis paper is to plan for the development of energy‐efficient MIMO‐OFDM mobile multimedia communication systems using the intelligent meta‐heuristic approach. This model is concentrated on solving the multi‐channel optimization problem. Recent research work is focused on single‐channel optimization problems, and hence the conversion of multi‐channel optimization problems into single‐channel optimization problems is considered the challenging point in this research. In the proposed MIMO‐OFDM method for mobile multimedia communication systems, the channel‐matrix Singular Value Decomposition (SVD) method is used for implementing the sub‐channel grouping scheme, which has simplified the multichannel problem to a multi‐target single‐channel optimization problem. In this optimization problem, the transmission power‐allocation threshold is optimized for attaining the objective function of maximization of energy efficiency. A hybridized optimization algorithm named Hybrid Fruit Fly‐based Salp Swarm Optimization (HFF‐SSO) is utilized for energy optimization in the MIMO‐OFDM mobile multimedia communication system. This hybrid algorithm has reached an energy‐efficient system with a high convergence rate, which is proved by the comparison over the conventional systems.
Secure multicasting in wireless sensor networks using identity based cryptography
Authors: Sampradeepraj T , Anusuya Devi V , Raja S. P. 
Published: October 2022

SummarySecurity in wireless sensor networks (WSNs) is challenging, owing to resource, computing, and environmental constraints. Researchers have proposed several security systems for multicasting in WSNs, but none have offered foolproof security. To make high‐security multicasting a reality, the proposed I‐RLNMCDS‐ODMRP protocol uses state‐of‐the‐art techniques such as identity‐based cryptography, random linear network coding, the minimum connected dominating set, and the on‐demand multicast routing protocol. Also, this article analyzes computation and memory overhead in the proposed protocol in terms of time in seconds and bytes, respectively, and examines its security properties. In the experimental results, the proposed protocol does not take much time to compute encryption and decryption parameters. Further, it requires little memory to store multicast message information. In the future, the proposed protocol will be tested on healthcare applications for intrabody communication through wireless body area networks.
Employing machine learning based malicious signal detection for cognitive radio networks
Authors: Turkyilmaz Yasin , Senturk Arafat , Bayrakdar Muhammed Enes 
Published: October 2022

SummaryIn cognitive radio networks, the empty spectrum that is also named as spectrum hole is detected with the help of spectrum sensing techniques. Energy detection is the most utilized spectrum sensing technique owing to its low complexity. In the energy detection technique, a spectrum hole is detected with a predefined threshold. In this article, machine learning based malicious signal detection is employed for cognitive radio networks. The design of cognitive radio users and network environment is simulated with Riverbed simulation software. The received signal is controlled whether it is a malicious signal or just a secure sensing signal. The fuzzy logic based system is utilized for the security categorization of spectrum sensing signals as malicious, suspicious, and secure sensing signals. Fuzzy logic parameters are taken from the machine learning features that are chosen as the most effective 3 features among all 49 features. The security of primary users is enhanced when compared to other schemes in the literature. The results of the proposed machine learning based malicious signal detection system are validated with the results acquired from the fuzzy logic based approach. The random forest method gives the best results among all machine learning methods for the detection of signals.
Tailored Charge Transfer Kinetics in Precursors for Organic Radical Batteries: A Joint Synthetic‐Theoretical Approach**
Authors: Zens Clara , Friebe Christian , Schubert Ulrich S. , Richter Martin , Kupfer Stephan 
Published: October 2022

AbstractThe development of sustainable energy storage devices is crucial for the transformation of our energy management. In this scope, organic batteries attracted considerable attention. To overcome the shortcomings of typically applied materials from the classes of redox‐active conjugated polymers (i. e., unstable cell voltages) and soft matter‐embedded stable organic radicals (i. e., low conductivity), a novel design concept was introduced, integrating such stable radicals within a conductive polymer backbone. In the present theory‐driven design approach, redox‐active (2,2,6,6‐tetramethylpiperidin‐1‐yl)oxyls (TEMPOs) were incorporated in thiophene‐based polymer model systems, while structure‐property relationships governing the thermodynamic properties as well as the charge transfer kinetics underlying the charging and discharging processes were investigated in a systematical approach. Thereby, the impact of the substitution pattern, the length as well as the nature of the chemical linker, and the ratio of TEMPO and thiophene units was studied using state‐of‐the‐art quantum chemical and quantum dynamical simulations for a set of six molecular model systems. Finally, two promising candidates were synthesized and electrochemically characterized, paving the way to applications in the frame of novel organic radical batteries.
Epstein–Barr virus infection, B‐cell dysfunction and other risk factors converge in gut‐associated lymphoid tissue to drive the immunopathogenesis of multiple sclerosis: a hypothesis
Authors: Leffler Jonatan , Trend Stephanie , Hart Prue H , French Martyn A 
Published: October 2022

AbstractMultiple sclerosis is associated with Epstein–Barr virus (EBV) infection, B‐cell dysfunction, gut dysbiosis, and environmental and genetic risk factors, including female sex. A disease model incorporating all these factors remains elusive. Here, we hypothesise that EBV‐infected memory B cells (MBCs) migrate to gut‐associated lymphoid tissue (GALT) through EBV‐induced expression of LPAM‐1, where they are subsequently activated by gut microbes and/or their products resulting in EBV reactivation and compartmentalised anti‐EBV immune responses. These responses involve marginal zone (MZ) B cells that activate CD4+ T‐cell responses, via HLA‐DRB1, which promote downstream B‐cell differentiation towards CD11c+/T‐bet+ MBCs, as well as conventional MBCs. Intrinsic expression of low‐affinity B‐cell receptors (BCRs) by MZ B cells and CD11c+/T‐bet+ MBCs promotes polyreactive BCR/antibody responses against EBV proteins (e.g. EBNA‐1) that cross‐react with central nervous system (CNS) autoantigens (e.g. GlialCAM). EBV protein/autoantigen‐specific CD11c+/T‐bet+ MBCs migrate to the meningeal immune system and CNS, facilitated by their expression of CXCR3, and induce cytotoxic CD8+ T‐cell responses against CNS autoantigens amplified by BAFF, released from EBV‐infected MBCs. An increased abundance of circulating IgA+ MBCs, observed in MS patients, might also reflect GALT‐derived immune responses, including disease‐enhancing IgA antibody responses against EBV and gut microbiota‐specific regulatory IgA+ plasma cells. Female sex increases MZ B‐cell and CD11c+/T‐bet+ MBC activity while environmental risk factors affect gut dysbiosis. Thus, EBV infection, B‐cell dysfunction and other risk factors converge in GALT to generate aberrant B‐cell responses that drive pathogenic T‐cell responses in the CNS.
Identification of MRAP protein family as broad‐spectrum GPCR modulators
Authors: Wang Meng , Wang Xiaozhu , Jiang Bopei , Zhai Yue , Zheng Jihong , Yang Liu , Tai Xiaolu , Li Yunpeng , Fu Shaliu , Xu Jing , Lei Xiaowei , Kuang Zhe , Zhang Cong , Bai Xuanxuan , Li Mingyu , Zan Tao , Qu Shen , Li Qingfeng , Zhang Chao 
Published: October 2022

AbstractBackgroundThe melanocortin receptor accessory proteins (MRAP1 and MRAP2) are well‐known endocrine regulators for the trafficking and signalling of all five melanocortin receptors (MC1R–MC5R). The observation of MRAP2 on regulating several non‐melanocortin G protein‐coupled receptors (GPCRs) has been sporadically reported, whereas other endogenous GPCR partners of the MRAP protein family are largely unknown.MethodsHere, we performed single‐cell transcriptome analysis and drew a fine GPCR blueprint and MRAPs‐associated network of two major endocrine organs, the hypothalamus and adrenal gland at single‐cell resolution. We also integrated multiple bulk RNA‐seq profiles and single‐cell datasets of human and mouse tissues, and narrowed down a list of 48 GPCRs with strong endogenous co‐expression correlation with MRAPs.Results36 and 46 metabolic‐related GPCRs were consequently identified as novel interacting partners of MRAP1 or MRAP2, respectively. MRAPs exhibited protein–protein interactions and varying pharmacological properties on the surface translocation, constitutive activities and ligand‐stimulated downstream signalling of these GPCRs. Knockdown of MRAP2 expression by hypothalamic administration of adeno‐associated virus (AAV) packed shRNA stimulated body weight gain in mouse model. Co‐injection of corticotropinreleasing factor (CRF), the agonist of corticotropin releasing hormone receptor 1 (CRHR1), suppressed feeding behaviour in a MRAP2‐dependent manner.ConclusionsCollectively, our study has comprehensively elucidated the complex GPCR networks in two major endocrine organs and redefined the MRAP protein family as broad‐spectrum GPCR modulators. MRAP proteins not only serve as a vital endocrine pivot on the regulation of global GPCR activities in vivo that could explain the composite physiological phenotypes of the MRAP2 null murine model but also provide us with new insights of the phenotyping investigation of GPCR–MRAP functional complexes.
The effect of emotional uncertainty on attentional bias toward neutral infant faces in adults
Authors: Li Yue Lin , Cheng Gang , Wu Xiu Hong , Dai Huang Yan , Jia Yun Cheng 
Published: October 2022

AbstractRecent studies have found that adults have stronger attentional bias toward neutral infant faces than emotional (positive or negative) infant faces. This phenomenon may derive from uncertainty over neutral expressions. To test this hypothesis, we recruited 176 participants to examine the relationship between their attentional bias toward neutral infant faces (with neutral adult faces as a comparison baseline) and their level of certainty in their appraisal of emotional valence through eye‐tracking indices. The results showed that participants had a longer dwell time and higher fixation counts for infant faces than for adult faces and that a more uncertain appraisal of facial expressions positively predicted attentional bias toward neutral infant faces. Therefore, this study preliminarily demonstrates that emotional uncertainty heightens adults’ attentional bias toward infant faces with neutral expressions.
Droplets in soft materials
Authors: Wang Hong , Xiong Xinhong , Yang Li , Cui Jiaxi 
Published: October 2022

AbstractDroplets display many unique properties in soft solid matrices, leading to various fascinating phenomena. These phenomena have inspired multidisciplinary scientific designs involving both fundamental studies and application exploration in the fields of physics, mechanics, chemistry, materials, biology, and so on. These emerging researches are diverse, ranging from artificial trees to antifouling coatings, and have not been concluded from the viewpoint of their composite structures, that is, droplet‐embedded soft materials. A comprehensive understanding of these structures will favor the designs of new systems with various predictable properties. We thus review the recent progress of this topic here. This contribution starts from the basic structural characteristics of the droplet‐embedded soft materials in the introduction section, followed by the section describing the main fabrication methods to create droplets in soft materials. In the third part, we divide the reported examples into five categories based on the hydrophobicity of the droplets and the miscibility between droplets and matrices and discuss their properties. Afterward, the applications of these systems with droplets are discussed, including self‐healing, antifouling surfaces, anticounterfeiting, radiative cooling, and so on. Finally, the promising developments and facing challenges of this topic are proposed. We envision that this review can deliver a comprehensive understanding of droplets in soft matrices and promote the development of this topic.
We don't know what we're missing: Evidence of a vastly undersampled invasive plant pool
Authors: Laginhas Brittany B. , Fertakos Matthew E. , Bradley Bethany A. 
Published: October 2022

AbstractInvasive plants are a prominent threat to ecosystems and economies worldwide. Knowing the identity of invasive plants is critical for preventing their introduction and spread. Yet several lines of evidence, including spatial and taxonomic biases in reporting and the ongoing emergence of new invasives, suggest that we are missing basic information about the identity of invasive plants. Using a database of invasive plants reported in the peer‐reviewed literature between 1959 and 2020, we examined trends in the accumulation of new invasive plants over time and estimated the size of the current pool of invasive plants both continentally and globally. The number of new invasive plants continues to increase exponentially over time, showing no sign of saturation, even in the best studied regions. Moreover, a sample‐size based rarefaction‐extrapolation curve of reported taxa suggests that what is documented in the current literature (3008 taxa) only captures 64% of the likely number of invasive plants globally (4721 taxa ± 132 SE). These estimates varied continentally; less than half of invasive plant taxa have likely been identified in Oceania and Central and South Americas. Studies that included multiple invasive plants (e.g., floristic studies) were much more efficient at adding new taxa to our global understanding of what is invasive (identifying 4.2 times more new taxa than single‐taxon studies). With more potential invaders arriving every day, this analysis highlights a critical gap in our knowledge of the current invasive plant pool. Expanding invasion science to better encompass understudied geographic areas and increasing the numbers of floristic surveys would greatly improve our ability to accurately and efficiently identify what taxa are invasive. Preventing invasive plant introductions is incumbent upon knowing the identity of invasive plants. Thus, large knowledge gaps remain in invasion ecology that hinder efforts to proactively prevent and manage invasive plants.