bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sensitivity and identification quantification by a relative latent model complexity perturbation in Bayesian meta‐analysis
Authors: Roos Małgorzata , Hunanyan Sona , Bakka Haakon , Rue Håvard 
Published: August 2021

AbstractIn recent years, Bayesian meta‐analysis expressed by a normal–normal hierarchical model (NNHM) has been widely used for combining evidence from multiple studies. Data provided for the NNHM are frequently based on a small number of studies and on uncertain within‐study standard deviation values. Despite the widespread use of Bayesian NNHM, it has always been unclear to what extent the posterior inference is impacted by the heterogeneity prior (sensitivity ) and by the uncertainty in the within‐study standard deviation values (identification ). Thus, to answer this question, we developed a unified method to simultaneously quantify both sensitivity and identification (‐) for all model parameters in a Bayesian NNHM, based on derivatives of the Bhattacharyya coefficient with respect to relative latent model complexity (RLMC) perturbations. Three case studies exemplify the applicability of the method proposed: historical data for a conventional therapy, data from which one large study is first included and then excluded, and two subgroup meta‐analyses specified by their randomization status. We analyzed six scenarios, crossing three RLMC targets with two heterogeneity priors (half‐normal, half‐Cauchy). The results show that ‐ explicitly reveals which parameters are affected by the heterogeneity prior and by the uncertainty in the within‐study standard deviation values. In addition, we compare the impact of both heterogeneity priors and quantify how ‐ values are affected by omitting one large study and by the randomization status. Finally, the range of applicability of ‐ is extended to Bayesian NtHM. A dedicated R package facilitates automatic ‐ quantification in applied Bayesian meta‐analyses.
Effect of wheat quality traits and glutenin composition on tortilla quality from the USDA Southern Regional Performance Nursery
Authors: Zhang Pingping , Tilley Michael , Bai Guihua , Harmer Sarah , Duke Sara , Seabourn Bradford W. , Zhang Guorong 
Published: August 2021

AbstractThe popularity of wheat flour tortillas is spreading throughout the world and has become one of the highest‐selling bread products. The USDA Southern Regional Performance Nursery (SRPN) serves as the largest wheat‐growing region in the USA, but the tortilla quality of germplasm in SRPN has remained unknown. This study investigated the kernel and flour quality traits, dough rheological properties, and tortilla quality parameters, and glutenin composition of 131 wheat lines from 1995 to 2007 in SRPN. The high molecular weight glutenin subunits (HMW‐GS) composition and wheat–rye 1RS translocation status of these wheat lines were also detected. A wide variation of wheat and tortilla quality traits was observed among these wheat lines. Association analysis showed that increased protein content and gluten strength significantly decreased the tortilla diameter and improved the tortilla shelf life in terms of 2‐D extensibility parameters (P < .001). The group of wheat lines with acceptable tortilla quality (both diameter >165 mm and day 16 flexibility score >3.0) had medium protein content and dough strength. Compared to wheat lines with 5 + 10 and non‐1RS translocation, those with 2 + 12 and 1RS translocation generally showed lower dough strength and shelf life, and higher tortilla diameter and specific volume (P < 0.01). TAM 302, HBG0358, CO99W192, and CO99534 showed premium tortilla quality with a diameter ≥180 mm and a day 16 flexibility score ≥4.00, which could be used as parents in tortilla wheat breeding program.
Heterogeneous Cobalt‐Catalyzed C−C Bond Cleavage in Alcohols to Carbonyl Compounds
Authors: Teng Jia‐nan , Zhu Rui , Li Xinglong , Fu Yao 
Published: August 2021

AbstractCobalt oxide hydrate (Co(OH)x) supported on metal oxides were prepared. The oxidative cleavage of C(OH)−C bond in alcohol was catalyzed by Co(OH)x/metal oxides using molecular oxygen as the oxidant, and the corresponding product was obtained with high selectivity. The composition and characteristics of the catalysts were analyzed by X‐ray diffraction (XRD), high resolution transmission electron microscopy (HRTEM), high‐angle ring dark‐field scanning TEM (HAADF‐STEM), N2 physico‐adsorption characterization, inductively coupled plasma optical emission spectrometry (ICP‐OES), Fourier transform infrared spectrum (FTIR), X‐ray photoelectron spectroscopy (XPS) and NH3‐temperature‐programmed desorption (NH3‐TPD). Additionally, a reasonable reaction mechanism was proposed based on the characterization results and a series of controlled experiments. Notably, this heterogeneous catalytic system did not require any additives and had good recycling performance.
The Synthesis of Porous Na3V2(PO4)3 for Sodium‐Ion Storage
Authors: Xiong Hailong , Qi Chunyu , Lv Shiquan , Zhang Ling , Qiao Zhen‐An 
Published: August 2021

AbstractNa3V2(PO4)3 (NVP) has been regarded as a potential cathode material for sodium‐ion batteries (SIBs) due to its excellent structural stability and rapid Na+ conductivity. However, its electrochemical performances are restricted by the large bulk structure and poor electronic conductivity. The construction of porous NVP materials is a powerful method to improve the electrochemical properties. This concept aims to provide an overview of recent progress of porous NVP materials for SIBs. Herein, the synthetic strategies and formation mechanisms of porous NVP materials as well as the relationship between the porous structures and electrochemical performances of NVP materials are reviewed. Furthermore, the challenges and prospects for the preparation of porous NVP materials in this field are outlined.
Suppression of liquid slugs and phase separation through pipeline bends
Authors: Igbokwe Loveday C. , Naterer Greg F. , Zendehboudi Sohrab , Pedersen Simon , Jespersen Stefan 
Published: August 2021

AbstractThis study examines the suppression of liquid slugs in the transport and separation of multiphase flows in pipelines. Two well‐known slug control approaches are evaluated in this paper. The methods are employed to control and stabilize an undesired and unstable flow regime, optimize flow production, reduce operating costs, and in general, improve overall safety requirements of oil and gas pipelines. Unlike designs with an additional flowline to separate gas upstream, this study shows that active topside choking can suppress slugs and stabilize the system flowrates and pressures without the requirement of separation upstream of the topside valve. Careful choking is required to minimize production losses that can result from excess back pressure. A riser‐based, gas‐lift method reduces system instability and increases production. This study also reveals that negligible improvement in stability is achieved when large volumes of gas are injected. The system shifts into an annular flow regime when the injection is further increased. A large separator may be required to accommodate high gas volumes. This study shows that gas‐lift not coordinated with choking is not effective for slug mitigation through pipeline bends. This paper also presents and discusses new non‐dimensional correlations, including slug control inputs in the pipelines such as choke openings, based on new experimental data.
The effects of luminance contrast and color combination on icon cognitive performance
Authors: Ming Chengye , Wu Zhengxin , Gu Haoran , Chen Chunpeng , Zhang Ying 
Published: August 2021

AbstractThis study explored and identified the effects of luminance contrast and color combinations on icon cognitive performance. A total of 50 participants took part in the experiment. As designed, icon cognitive performance was measured as a function of the following independent variables: 4 levels of luminance contrast, 16 target/background color combinations. Experiment A showed that a luminance contrast of 18:1 provide participants with the highest cognitive performance. Yellow on black, yellow on blue, and white on blue were the three most legible color combinations. To explore the individual effects of luminance contrast and color combination on cognitive performance, in experiment B, the material was decolored. Comparing the reaction time data of experiment A with experiment B, it was found that both luminance contrast and color combination can significantly affect cognitive performance. Under the same luminance contrast, yellow on black, yellow on blue, and white on blue significantly improve the search speed, while green on red, yellow on purple, green on blue, and turquoise on blue significantly slow down the search speed. In experiment C, event related potential technology was used to verify the results of behavioral experiment B. It was found that under 18:1 high luminance contrast visual stimulation, the activation of prefrontal and occipital regions was stronger, and the peak and average amplitude of P100 curve were significantly higher than the other three luminance contrasts. To explain why some color combinations shorten reaction time, in experiment D, peak latency of P100 at visual‐cortex area (O1, O2, OZ) showed significantly faster response time with fast search speed color combinations than with slow search speed color combinations. These results provide some guidance for human–software interface design.
The Impact of 5‐Hydroxymethylfurfural (HMF)‐Metal Interactions on the Electrochemical Reduction Pathways of HMF on Various Metal Electrodes
Authors: Lee Dong Ki , Kubota Stephen R. , Janes Aurora N. , Bender Michael T. , Woo Jongin , Schmidt J. R. , Choi Kyoung‐Shin 
Published: August 2021

Abstract5‐Hydroxymethylfurfural (HMF), which can be derived from lignocellulosic biomass, is an important platform molecule that can be used to produce valuable biofuels and polymeric materials. Electrochemical reduction of HMF is of great interest as it uses water as the hydrogen source and achieves desired reduction reactions at room temperature and ambient pressure. Hydrogenation and hydrogenolysis are two important reactions for reductive HMF conversion. Therefore, elucidating key characteristics of electrocatalysts that govern the selectivity for hydrogenation and hydrogenolysis is critical in rationally developing efficient and selective electrocatalysts. In this study, combined experimental and computational investigations are used to demonstrate how the adsorption energy of HMF on metal surfaces and the resulting changes in the intramolecular bond lengths of adsorbed HMF directly impact the reduction pathways of HMF. These results make it possible to rationally understand a general trend in the behaviors observed when using various metal electrodes for HMF reduction.
Pyrimidine‐Functionalized Covalent Organic Framework and its Cobalt Complex as an Efficient Electrocatalyst for Oxygen Evolution Reaction
Authors: Zhao Yuxiang , Yang Yingjie , Xia Tian , Tian Hao , Li Yongpeng , Sui Zhuyin , Yuan Ning , Tian Xinlong , Chen Qi 
Published: August 2021

AbstractA pyrimidine‐modified covalent organic framework (COF‐Pyr) was designed to be synthesized via the Povarov reaction. The nitrogen atom on the pyrimidine showed excellent coordination ability to metal ions. Their stable metal composite material (Co@COF‐Pyr) exhibited remarkable performance for electrocatalytic oxygen evolution reaction (OER) in 1.0 m KOH aqueous solution. The overpotential was 450 mV at 10 mA cm−2. The Co@COF‐Pyr with large specific surface area (392 m2 g−1) and regular crystal structure provided free passage for H2O to move and make them fully contact with the uniformly dispersed cobalt ions on the surface. Thus, the turnover frequency of Co@COF‐Pyr was 0.1 s−1 at the overpotential of 370 mV, which was higher than most reported OER catalysts. This work provided a new way to design and prepare nitrogen‐containing heterocyclic functionalized COFs. They can be combined with metal ions to expand the application of COFs in the field of electrocatalysis.
A novel pinwheel fractal multiband antenna design using particle swarm optimization for wireless applications
Authors: Manikandan Palanivel , Sivakumar Pothiraj 
Published: August 2021

SummaryA novel multiband pinwheel fractal antenna with monopole configuration is proposed. The pinwheel fractal antenna has been fabricated on a commercially available FR4 substrate with a thickness of 1.6 mm. This paper proposes a novel pinwheel antenna with a 50% reduction in the dimension of width with a reduced level of return loss. The proposed antenna has multiband characteristics covering the bands of GSM (900 MHz), DCS (1710 GHz), PCS (1900 MHz), UMTS (1920 MHz), and WLAN (2.4–5.9 GHz) applications. The projected antenna resonates at multiple frequencies with acceptable antenna gain and directivity. The proposed antenna design is optimized by particle swarm optimization (PSO) algorithm. The parametric studies and the design rule for the proposed fractal have been reported. The prototypes of the proposed multiband antenna have been demonstrated. The measured and simulated results ensure the multi‐resonance characteristics and authorize the projected design method and gratify the necessities of handheld wireless communication systems. The performance analysis proves that the proposed novel pinwheel antenna provides reduced return loss.
Design and fabrication of compact triangular multiband microstrip patch antenna for C‐ and X‐band applications
Authors: Chinnagurusamy Balamurugan , Perumalsamy Marichamy , Thankamony Sarasam Arun Samuel 
Published: August 2021

SummaryModern portable communication devices require a compact antenna with superior performance and lower weight and size. The design and development of such a compact size antenna are a significant challenge for researchers. This proposed work compact slot‐based triangular patch antenna to work at the multiple resonance frequencies from 5 to 10 GHz using FR4 substrate is presented. The proposed antenna is simulated using High‐Frequency Structural Simulator (HFSS 2020R1). Simulated and fabricated antenna test results show that the proposed antenna can be suitably employed for the portable wireless transceivers in C and X bands. It has been inferred from the fabricated and measured results that the proposed slot‐based triangular patch antenna achieves the peak gain of 8 dBi and has excellent impedance matching properties such that return loss S11 is less than −10 dB and VSWR value is significantly closer to 1 at all the resonance frequencies.
An LSTM‐based cell association scheme for proactive bandwidth management in 5G fog radio access networks
Authors: Manzoor Sanaullah , Mian Adnan Noor , Mazhar Suleman 
Published: August 2021

SummaryCellular networks are evolving into dynamic, dense, and heterogeneous networks to meet the unprecedented traffic demands which introduced new challenges for cell resource management. To address this, various cell association schemes have been proposed. However, the current schemes ignore users' mobility information, and as a result, their cell admission and bandwidth allocation policy are reactive. In order to enable proactive bandwidth management in emerging 5G fog access radio networks (FRANs), we proposed a novel mobility‐aware cell association scheme (MACA) that exploits user's mobility and downlink rate demand information to associate it with the maximum rate offering cell. In MACA, the mobility prediction model consists of long‐short‐term memory (LSTM)‐based neural network that considers joint information of unique cell identification numbers with the corresponding sojourn times and predicts the user's most probable next cell. Later, the underlying future cell assignment is formulated as a convex problem and solved using the Lagrangian dual decomposition method and compared the proposed framework performance with Semi‐Markov, deep neural network (DNN), and MaxRSRP‐based cell association approaches in terms of the next cell prediction accuracy, the impact of downlink rate allocation, and user satisfaction percentage. MACA scheme is trained using two publicly available pedestrian datasets. Simulation results show that the proposed scheme performs significantly better than the other schemes and yields the average next cell prediction accuracy of 93.42%, 1.63 times higher downlink rates, and 56.8%users satisfied with the allocated bandwidth.
Atypical cells in fine needle aspiration biopsies of pancreas: Causes, work‐up, and recommendations for management
Authors: HooKim Kim , Reid Michelle D. 
Published: August 2021

AbstractEndoscopic ultrasound‐guided fine needle aspiration (EUS‐FNA) is a sensitive and specific method for diagnosing cancer in solid pancreatic masses. However, some cases receive indeterminate atypical diagnoses, which creates management dilemmas. In the 2014 Papanicolaou Society of Cytopathology (PSC) standardized guidelines for pancreatobiliary cytology, specimens in the “Atypical” category show a spectrum of architectural and/or cellular changes beyond normal or reactive, but, quantitatively or qualitatively, insufficient for classification as neoplastic (benign/other), suspicious or positive for malignancy. Implementation of the PSC system decreased atypical diagnoses, particularly for cystic lesions, and redistributed many cases into benign and neoplastic categories. Because no set cytologic criteria exist for the “Atypical” category there is wide variability in its use, and its frequency ranges from 0%–16% (mean 6%). It consists of a heterogeneous mix of cases that occur because of preanalytic, lesion‐specific (low cellularity, necrosis, cystic, reactive and premalignant changes), to pathologist‐dependent factors (experience, expertise, training and institutional case volume). Outcomes of atypical diagnoses in solid pancreatic masses range from benign to premalignant and malignant and include reactive atypia in pancreatitis, well differentiated adenocarcinoma, and non‐ductal malignancies. The associated risk of malignancy (ROM) ranges from 28%–100%, with an overall intermediate ROM in large‐scale studies. Cytopathologists and institutions should monitor and keep their personal and/or laboratory's atypical rates low by judiciously using rapid onsite evaluation, ancillary studies, consensus or expert review, as well as correlation with clinical and radiologic findings. Early repeat EUS‐FNA is indicated for unresolved cases.
Predicting range shifts of Davidia involucrata Ball. under future climate change
Authors: Long Teng , Tang Junfeng , Pilfold Nicholas W. , Zhao Xuzhe , Dong Tingfa 
Published: August 2021

AbstractUnderstanding and predicting how species will respond to climate change is crucial for biodiversity conservation. Here, we assessed future climate change impacts on the distribution of a rare and endangered plant species, Davidia involucrate in China, using the most recent global circulation models developed in the sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC6). We assessed the potential range shifts in this species by using an ensemble of species distribution models (SDMs). The ensemble SDMs exhibited high predictive ability and suggested that the temperature annual range, annual mean temperature, and precipitation of the driest month are the most influential predictors in shaping distribution patterns of this species. The projections of the ensemble SDMs also suggested that D. involucrate is very vulnerable to future climate change, with at least one‐third of its suitable range expected to be lost in all future climate change scenarios and will shift to the northward of high‐latitude regions. Similarly, at least one‐fifth of the overlap area of the current nature reserve networks and projected suitable habitat is also expected to be lost. These findings suggest that it is of great importance to ensure that adaptive conservation management strategies are in place to mitigate the impacts of climate change on D. involucrate.
Reactivities of quercetin and metallo‐quercetin with superoxide anion radical and molecular oxygen
Authors: Lewis Tyra , Wallace William , Peterson Finlay Dingman , Rafferty Steven , Martic Sanela 
Published: August 2021

AbstractThis work describes the differential quenching of molecular oxygen and superoxide anion radical (O2˙–) by (metallo)‐quercetin (QCR) complexes. The in situ complexes were more reactive with molecular oxygen than preformed complexes. By adjusting the potential range, it was determined that Cu2+ complexes exhibited similar superoxide anion radical (O2˙–) quenching ability as free QCR. The Fe3+ complexes were less reactive than free QCR or Cu2+ complexes. The data indicate that metal ions significantly modulated reactivity of QCR with O2˙– or molecular oxygen, and may regulate antioxidant activity and reactive oxygen species levels in a complex biological setting.
Developing an attack detection framework for wireless sensor network‐based healthcare applications using hybrid convolutional neural network
Authors: Subasini C. A. , Karuppiah S. P. , Sheeba Adlin , Padmakala S. 
Published: August 2021

AbstractAttack detection is the major issue in healthcare‐based wireless sensor networks (H‐WSNs). Due to their low processing speed, very low storage space, poor attack detection rate, longer deployment time, poor communication range, and reduced energy, H‐WSNs are subjected to difficult implementation and have their own limitations. To tackle these issues, we have presented a hybrid deep learning model using convolutional neural network and long short term memory (HDMCL) for attack detection in H‐WSN. This research is divided into three steps: preprocessing, dimensionality reduction, and classification (attack detection). At first, the raw input data (patient's health data) is preprocessed using the one‐hot encoding method. Next, the modified Huber independent component analysis based squirrel search algorithm (MHICA‐SSA) effectively reduces the data dimensionality in which the MHICA‐SSA is the amalgamation of both modified Huber independent component analysis and squirrel search algorithm. The novel algorithm designed overcomes the complexities associated with existing techniques such as the curse of dimensionality problem, improves the parameter interpretation, minimizes the time and storage space, minimizes space complexity, and enhances the attack detection accuracy of the convolutional neural network‐based long short‐term memory (CNN‐LSTM). After that, the deep learning CNN‐LSTM model is utilized for normal, black hole, and gray hole attack detection. The NS2.34 network simulator implements the proposed work thereby the proposed work efficiency is validated using different performance measures such as packet delivery ratio, false alarm rate, network lifetime, energy consumption, throughput, attack detection time, and rate. The proposed work performance is evaluated using different existing methods such as fish swarm optimization based particle swarm optimization, intelligent opportunistic routing algorithm, Jensen‐Shannon divergence‐based independent component analysis, and radio frequency identification based WSN. The throughput of the proposed work is increased up to 3.2 times and the network lifetime is increased up to 4 times when compared to the existing techniques.