bluuebunny/crossref_metadata_2025_split huggingface dataset:
Benchmarking the Electrochemical CO2 Reduction on Polycrystalline Copper Foils: The Importance of Microstructure Versus Applied Potential
Authors: Asperti Simone , Hendrikx Ruud , Gonzalez‐Garcia Yaiza , Kortlever Ruud 
Published: July 2022

AbstractCopper is one of the most promising catalysts for the CO2 reduction reaction (CO2RR) due to its unique capability of producing multicarbon products in appreciable quantities. Most of the CO2RR research efforts have been directed towards the development of new electrocatalysts to either increase product selectivities or decrease overpotentials. In contrast, only a few studies have systematically tested or benchmarked CO2RR performances of electrocatalysts. In this paper, for the first time, the performances of five different polycrystalline copper foils purchased from different suppliers are benchmarked for their CO2RR performance. Their differences are characterized in terms of microstructural features and the effect that these microstructural properties have on the electrocatalytic behavior during potentiostatic CO2RR experiments are evaluated. It is shown that the potential applied is the dominant factor controlling CO2RR selectivities, leading to the conclusion that microstructural properties of polycrystalline copper electrodes have a negligible effect on the outcome of CO2RR experiments.
Efficient Cleavage of Lignin Model Compounds into Phenols and Aldehydes over NiOOH Catalyst
Authors: Mei Xuelei , Liu Huizhen , Wu Haihong , Wu Wei , Zheng Bingxiao , Zhang Kaili , Xu Caiyun , Xu Jiao , He Mingyuan , Han Buxing 
Published: July 2022

AbstractThe highly‐efficient utilization of lignin and its derivatives is of great importance. Phenylacetaldehyde, as an important industrial raw material, is rarely reported to be directly obtained from biomass sources via thermal catalytic transformation. In this work, we found that NiOOH catalyst could efficiently catalyze the cleavage of β‐O‐4 lignin model compound to phenylacetaldehyde and phenol in water without need of any exogenous hydrogen. The catalytic mechanism study indicates that NiOOH could catalyze the elimination of Cα−OH to form an enol ether intermediate, which is then hydrated to phenylacetaldehyde and phenol.
Effect of Nanoparticle Size on Plasmonic Heat‐Driven Organic Transformation
Authors: Kashyap Radha Krishna , Parammal Muhammed Jibin , Pillai Pramod P. 
Published: July 2022

AbstractPlasmonic nanomaterials have the potential to convert light to heat energy in an efficient and localized fashion. Here, we report the use of plasmonic heat from gold nanoparticles (AuNPs) in performing an important chemical transformation of pyrone to pyridinone in water. The yield obtained using plasmonic heat (∼75%) is comparable to that obtained from normal heating at ∼90 °C. Further, this photothermally driven organic reaction is used as a tool to study the effect of NP size on the practical utilization of the plasmonic heat dissipated. AuNPs in the size regime of 10–24 nm are found to be most efficient in driving the pyrone to pyridinone conversion, which is attributed to the dependence of absorption cross‐section and heat capacity on the NP size. The results obtained are validated using conventional plasmonically driven solar‐vapor generation experiments. Our study proves the suitability of a thermally driven organic reaction for qualitatively comparing the effect of various NP parameters on the chemical effectiveness of the plasmonic heat, which can be crucial in our efforts to understand the role of thermalization process in different plasmonically powered processes.
Substation instrumentation target detection based on multi‐scale feature fusion
Authors: Feng Qiaosheng , Huang Li , Sun Ying , Tong Xiliang , Liu Xin , Xie Yuanmin , Li Jun , Fan Hanwen , Chen Baojia 
Published: July 2022

SUMMARYWith the promotion of smart grid construction work, the use of high‐precision and high‐efficiency substation inspection robot has become the development trend of substation inspection. A multi‐scale feature fusion meter target detection algorithm is proposed to address the problems of low efficiency and susceptibility to surrounding environmental factors by the traditional manual meter reading method. Kinecct is used to acquire color images of substation meters with different backgrounds, light intensities, and angles to build a substation meter dataset. Based on the complementarity and correlation of multi‐scale features, an SSD target detection model with multi‐scale feature fusion is established, and the performance of the algorithm is tested on the constructed dataset, and comparative experiments are conducted to verify the effectiveness of the algorithm for target detection accuracy improvement.
Effective Photosensitization in Excited‐State Equilibrium: Brilliant Luminescence of TbIII Coordination Polymers Through Ancillary Ligand Modifications
Authors: Kitagawa Yuichi , Moriake Ryoma , Akama Tomoko , Saito Koki , Aikawa Kota , Shoji Sunao , Fushimi Koji , Kobayashi Masato , Taketsugu Tetsuya , Hasegawa Yasuchika 
Published: July 2022

AbstractMolecular photosensitizers provide efficient light‐absorbing abilities for photo‐functional materials. Herein, effective photosensitization in excited‐state equilibrium is demonstrated using five TbIII coordination polymers. The coordination polymers are composed of TbIII ions (emission center), hexafluoroacetylacetonato (photosensitizer ligands), and phosphine oxide‐based bridges (ancillary ligands). The two types of ligand combinations induces a rigid coordination structure via intermolecular interactions, resulting in high thermal stability (with decomposition temperatures above 300 °C). Excited‐triplet‐state lifetimes of photosensitizer ligands (τ=120–1320 μs) are strongly dependent on the structure of the ancillary ligands. The photosensitizer with a long excited‐triplet‐state lifetime (τ≥1120 μs) controls the excited state equilibrium between the photosensitizer and TbIII, allowing the construction of TbIII coordination polymer with high TbIII emission quantum yield (≥70 %).
High step‐up active switched coupled inductor DC‐DC converter with voltage multiplier
Authors: Andrade António Manuel Santos Spencer , Faistel Tiago Miguel Klein , Toebe Ademir , Guisso Ronaldo António , da Silva Mauricio Mendes 
Published: July 2022

AbstractHigh step‐up DC‐DC converters are commonly used in new energy applications such as DC microgrid, photovoltaic cell, and fuel cell. Thus, this article introduces a new nonisolated high step‐up DC‐DC converter based on active switched coupled inductor with a voltage multiplier cell. The proposed converter presents low current and voltage stress across the switches owing of the dual active switches structure. Besides that, by the voltage multiplier cell (one diode and one capacitor), the voltage gain of proposed converter is increased. In addition, it can be highlighted that the proposed converter has low component count, simplicity of operation in continuous and discontinuous conduction mode, and energy stored in the leakage inductor that is recycled in the capacitor of voltage multiplier cell. This article discussed the principle of operation, the ideal and nonideal voltage gain, external characteristic, voltage and current stress, design guidelines, and performance comparison with previous high step‐up converters. Finally, a prototype circuit with input power 300 W, input voltage 30 V, and output voltage 400 V was built in the laboratory to verify the theoretical evaluation, and the maximum achieved efficiency was 95.35% at nominal power 300 W.
Reconfigurable multivalued memristor FPGA model for digital recognition
Authors: Zhang Zhang , Xu Ao , Ren Hong Tao , Liu Gang , Cheng Xin 
Published: July 2022

AbstractCompared with the traditional memristor, it's more significant to research the multivalued memristor in improving the stability and reliability of memristive neural networks. Developing some multivalued memristor emulators is highly attractive since the fabrication and integration of the memristor are not mature at present. This work presents a behavioral‐level model of a general multivalued memristor FPGA that exhibits continuous or discrete behavior, similar to electrochemical metallization memories. The proposed solution has been successfully synthesized and verified on a Xilinx ZYNQ‐7000 FPGA XQ7Z020 with less than 1% hardware utilization. Additionally, to test the synaptic function of the memristor model in artificial neural networks, this paper constructs a quantized artificial neural network based on eight‐valued memristors in FPGA. In the training of the neural network, the pixel values of the images and the network weights are quantized and then mapped to the input voltage and conductance respectively of the memristor during the forward propagation. The experimental results show that the memristive network circuit achieves 92.8% recognition accuracy for 10,000 MNIST images.
Prediction of depth of invasion and lymph node metastasis in superficial pharyngeal cancer by magnifying endoscopy using the Japan Esophageal Society classification
Authors: Yamaguchi Hayato , Kawai Takashi , Fukuzawa Masakatsu , Nemoto Daiki , Kagawa Yasuyuki , Kono Shin , Naito Sakiko , Sato Hiroki , Nagata Naoyoshi , Sugimoto Mitsushige , Tsukahara Kiyoaki , Itoi Takao 
Published: July 2022

AbstractBackgroundsThe pharynx has no muscularis mucosae, so it is unclear whether diagnostic techniques used for the esophagus can be applied to the pharynx. This study investigated the usefulness of magnifying endoscopy with narrowband imaging using the Japan Esophageal Society (JES) classification for predicting the depth of invasion and lymph node metastasis (LNM) in pharyngeal cancer.MethodsA total of 123 superficial pharyngeal carcinoma lesions that had been observed preoperatively with magnifying endoscopy with narrowband imaging between January 2014 and June 2021 were analyzed. Predictors of subepithelial invasion (SEP) and LNM were sought based on endoscopic findings, including microvascular morphology, using the JES classification.ResultsThe lesions were divided into carcinoma in situ (n = 41) and SEP (n = 82). Multivariate analysis identified B2–B3 vessels (odds ratio [OR] 6.54, 95% confidence interval [CI] 1.74–24.61, p = 0.005) and a middle/large avascular area (OR 4.15, 95% CI 1.18–14.62, p = 0.027) as independent predictors of SEP. Significant predictors of LNM were protruding type, B2–B3 vessels, middle/large avascular area, SEP, venous invasion, lymphatic invasion, and tumor thickness > 1000 μm. Median tumor thickness increased significantly in the order of B1 < B2 < B3 vessels (B1, 305 μm; B2, 1045 μm; B3, 4043 μm; p < 0.001). The LNM rates for B1, B2, and B3 vessels were 1.6% (1/63), 4.8% (2/42), and 55.6% (10/18), respectively (p < 0.001).ConclusionsMagnifying endoscopy with narrowband imaging using the JES classification could predict the depth of invasion in superficial pharyngeal carcinoma. The JES classification may contribute to the prediction of LNM, suggesting that it could serve as an alternative to tumor thickness.
The development of the gut microbiome and temperament during infancy and early childhood: A systematic review
Authors: Alving‐Jessep Emma , Botchway Edith , Wood Amanda G. , Hilton Anthony C. , Blissett Jacqueline M. 
Published: July 2022

AbstractTemperament in early childhood is a good predictor of later personality, behavior, and risk of psychopathology. Variation in temperament can be explained by environmental and biological factors. One biological mechanism of interest is the gut microbiome (GM), which has been associated with mental and physical health. This review synthesized existing literature evaluating the relationship between GM composition and diversity, and temperament in early life. Web of Science, PsycInfo, PubMed, and Scopus were searched, and data were extracted according to PRISMA guidelines. In total, 1562 studies were identified, of which six remained following application of exclusion/inclusion criteria. The findings suggest that there is an association between higher alpha diversity and temperament: greater Surgency/Extraversion and High‐Intensity Pleasure in males, and lower Effortful Control in females. Unique community structures (beta diversity) were found for Surgency/Extraversion in males and Fear in females. An emerging pattern of positive temperament traits being associated with GM communities biased toward short‐chain fatty acid production from a metabolism based on dietary fiber and complex carbohydrates was observed and is worthy of further investigation. To gain deeper understanding of the relationship, future research should investigate further the functional aspects of the microbiome and the influence of diet.
Rhizosphere soil bacterial communities and nitrogen cycling affected by deciduous and evergreen tree species
Authors: Liu Jiantong , Wang Xinyu , Liu Lin , Wu Xuefeng , Xia Zhichao , Guo Qingxue 
Published: July 2022

AbstractDeciduous and evergreen trees differ in their responses to drought and nitrogen (N) demand. Whether or not these functional types affect the role of the bacterial community in the N cycle during drought remains uncertain. Two deciduous tree species (Alnus cremastogyne, an N2‐fixing species, and Liquidambar formosana) and two evergreen trees (Cunninghamia lanceolata and Pinus massoniana) were used to assess factors in controlling rhizosphere soil bacterial community and N cycling functions. Photosynthetic rates and biomass production of plants, 16S rRNA sequencing and N‐cycling‐related genes of rhizosphere soil were measured. The relative abundance of the phyla Actinobacteria and Firmicutes was higher, and that of Proteobacteria, Acidobacteria, and Gemmatimondaetes was lower in rhizosphere soil of deciduous trees than that of evergreen. Beta‐diversity of bacterial community also significantly differed between the two types of trees. Deciduous trees showed significantly higher net photosynthetic rates and biomass production than evergreen species both at well water condition and short‐term drought. Root biomass was the most important factor in driving soil bacterial community and N‐cycling functions than total biomass and aboveground biomass. Furthermore, 44 bacteria genera with a decreasing response and 46 taxa showed an increased response along the root biomass gradient. Regarding N‐cycle‐related functional genes, copy numbers of ammonia‐oxidizing bacteria (AOB) and autotrophic ammonia‐oxidizing archaea (AOA), N2 fixation gene (nifH), and denitrification genes (nirK, nirS) were significantly higher in the soil of deciduous trees than in that of the evergreen. Structural equation models explained 50.2%, 47.6%, 48.6%, 49.4%, and 37.3% of the variability in copy numbers of nifH, AOB, AOA, nirK, and nirS, respectively, and revealed that root biomass had significant positive effects on copy numbers of all N‐cycle functional genes. In conclusion, root biomass played key roles in affecting bacterial community structure and soil N cycling. Our findings have important implications for our understanding of plants control over bacterial community and N‐cycling function in artificial forest ecosystems.
The Spatiotemporal Weighted Efficient Drought Index—A new generalized procedure of regional drought indicator
Authors: Ali Farman , Riaz Saba , Ali Zulfiqar , Qamar Sadia , Li Bing‐Zhao , Khan Muhammad Asif 
Published: July 2022

AbstractDrought is a multifaceted climate phenomenon. Due to recent climate warming, the risk of drought has increased. Regional drought management requires accurate regional drought characterization to prepare early warning drought mitigation policies. Therefore, a more flexible and efficient procedure is necessary for characterizing drought at a regional level. This study provides a new spatiotemporal weighting scheme for integrating precipitation data from various meteorological stations located in a specific region. Consequently, this article presents a new generalized regional drought indicator—The Spatiotemporal Weighted Efficient Drought Index (STWEDI). The methodology of STWEDI consists of two stages: (1) The first stage combines the meteorological data of various stations located in a certain region under the proposed weighting scheme, and (2) the second stage standardizes the cumulative distribution function (CDF) of mixture probability models. In application, this research estimated the time series data of STWEDI of seven regions containing a varying number of meteorological stations. To assess the performance of STWEDI, we compared the time series data of STWEDI with the most commonly used Standardized Precipitation Index (SPI) using the Pearson correlation. Results show that STWEDI is strongly correlated with individual SPIs in all the clusters and scales. Moreover, we found that STWEDI is strongly associated with SPI at all time scales. These statistical measures show that STWEDI is the more effective drought indicator for regional drought monitoring.
Effect of β‐blocker on patients with moderate functional mitral regurgitation undergoing surgical aortic valve replacement
Authors: Tiemuerniyazi Xieraili , Nan Yifeng , Song Yangwu , Yang Ziang , Zhao Wei , Xu Fei , Feng Wei 
Published: July 2022

AbstractAimsThe optimal treatment for severe aortic valve disease complicated with moderate function mitral regurgitation (FMR) remains controversial. Although isolated surgical aortic valve replacement (SAVR) is reasonable, previous studies also show that moderate FMR might deteriorate after surgical treatment and result in poorer prognosis. Because the left ventricular remodelling plays a critical role in the development of FMR, these patients might potentially benefit from the administration of β‐blocker (BB). Unfortunately, relevant clinical evidence is lacking. This study aimed to investigate the impact of post‐operative administration of BB on the outcomes of moderate FMR patients undergoing isolated SAVR.MethodsIn this single‐centre cohort study, patients who underwent isolated SAVR and complicated with pre‐operative moderate FMR during 2010 and 2019 at our centre were retrospectively recruited. Patients were divided into two groups according to postoperative administration of BB (BB group vs. control group). The cumulative survival rates were calculated using the Kaplan–Meier method and tested by the log‐rank test, followed by inverse probability treatment weighting (IPTW) analysis to further control the between‐group imbalances. The primary outcome was the major adverse cardiovascular and cerebrovascular events (MACCE), a composite endpoint of all‐cause death, repeat heart valve surgery, non‐fatal myocardial infarction, stroke, and hospitalization for heart failure.ResultsA total of 165 patients were enrolled, 57 (34.6%) of whom were female, and the mean age was 59.2 ± 12.2 years. Eighty (48.5%) patients received post‐operative BB therapy. The median follow‐up time was 18.4 months. The administration of BB was not associated with lower risk of MACCE [hazard ratio (HR): 0.68, 95% confidence interval (CI): 0.29–1.62, P = 0.388] or all‐cause death (HR: 1.03, 95% CI: 0.30–0.56, P = 0.967). In the IPTW dataset, the total number of patients were 326.89, and the outcomes regarding the risk of MACCE (HR: 0.79, 95% CI: 0.31–1.97, P = 0.607) and all‐cause death (HR: 1.33, 95% CI:0.35–5.05, P = 0.674) were in line with the unmatched analysis. The follow‐up echocardiographic results were available for 72.2% of the overall cohort, and the use of BB was observed to be associated with higher improvement rate of follow‐up FMR according to the IPTW analysis (92.2% vs. 98.3%, P = 0.033).ConclusionsThe administration of BB after SAVR was not associated with lower risk of MACCE for patients of severe aortic valve disease complicated with moderate FMR, but was potentially beneficial for improving FMR.
Detection of dish waste degree based on image processing and convolutional neural networks
Authors: Pu Jing , Zhu Shiping , Miao Yujie , Huang Hua 
Published: July 2022

AbstractMany restaurants have a certain amount of food waste. The monitoring of food waste will help restaurants to eliminate some dishes with outrageous waste and reduce waste from the source. In view of this, this research proposed a method to detect waste of dishes through image processing and deep learning technology. According to the remaining quantity of the dishes, the collected dish images were preliminarily divided into six levels, which were used as sample labels, and then the image of the uneaten dishes and the image of the dishes after eating were stacked as the input of the network. Trained in the InceptionV3, Xception, and ResNet18 network models, we find that compared with the single image data as the input, the effect of stacking the two images data as the input was better. The accuracy of sample label recognition increased by 6.97%, 5.81%, and 4.1% respectively. Further analysis discovered that the sample that predicted wrong on the test set data, its true label, and the predicted wrong label were adjacent. Therefore, with the help of the probability vector output by the trained network model, the definition method of the level of dish waste degree and its corresponding accuracy metric standard was further given. Finally, the recognition accuracy of the best network structure InceptionV3 on the test set data can reach 98.47%.
The probability‐based granular field of vegetated soils
Authors: Zhang Jun , Li Yong , Liu Daochuan , Jiang Ning , Yang Taiqiang , Guo Xiaojun , Yao Yingjie 
Published: July 2022

AbstractSoils in vegetation‐covered areas are of high variability in space and time, and the variability is crucial for hydro‐geophysical processes at small and large scales. Conventionally, the spatial heterogeneity at large scale is visualized as a regional division map of soil properties by extrapolating sample measurements. No formalized method is available for assigning parameters for soils at the resolution of a small grid cell. This study formulates a method of establishing parameter space for vegetated soil by a single index (μ) derived from the unified grain size distribution (GSD). The index μ varies in space as a random variable and defines soil as a granular field. The μ‐division represents the concentration of fine grains in response to root–soil interactions. Coupling μ‐division with moisture distribution suggests that the gradient of μ plays a potential role in rooted soil hydraulics. It is further found that μ satisfies the Weibull distribution, which makes it possible to establish the μ‐field for a soil space at large scale using the random dataset of μ. A case study is conducted in two vegetated slopes based on high‐resolution digital elevation models (DEM) derived from unmanned aerial vehicle survey to create the field and illustrate its implications in morphology and hydrology. It is expected that the μ‐field may derive parameter fields of various soil properties as functions of the GSD parameters and thus equip DEM with a complete dataset of soil. The paradigm proposed in the study fills the gap of establishing high‐resolution data space for soil at large scale for dynamics of surface processes.