bluuebunny/crossref_metadata_2025_split huggingface dataset:
Probing the Properties of Quasi‐Isolated ClAlPc by Using Polycrystalline h‐BN on Pt(111) as a Testbed
Authors: Guo Haojie , Izquierdo‐Cid Marta , Jiménez‐Sánchez Mariano D. , Martínez‐Galera Antonio J. , Gómez‐Rodríguez José M. 
Published: October 2021

AbstractThe structural and electronic properties of chloro‐aluminum phthalocyanine (ClAlPc) molecules on insulating hexagonal boron nitride (h‐BN) monolayers (MLs) grown on Pt(111) surfaces are studied via scanning tunneling microscopy and spectroscopy (STM/STS) along with low energy electron diffraction in ultra‐high vacuum conditions. As a reference, the structural properties of the h‐BN/Pt(111) surface are studied, where various moiré patterns associated to different orientations of the h‐BN lattice with respect to the Pt(111) surface below are characterized, for the first time, at the atomic scale. Room temperature deposition of ClAlPc molecules on h‐BN/Pt(111) gives rise to the formation of mainly bilayer molecular structures, where the ClAlPc molecules adopt an alternating Cl‐up and Cl‐down stacking configuration. Upon annealing, bilayer molecular structures become islands comprising only a single layer of molecules adsorbed in a Cl‐up configuration. In the ML regime, the possible influence of the moiré pattern superstructure and the h‐BN lattice on the molecular ordering is also studied. Finally, the electronic properties of ClAlPc on h‐BN/Pt(111) are investigated through high‐resolution STM imaging of the frontier molecular orbitals and differential conductance plots. The results point toward a weak molecule–substrate interaction.
The Tooth Fairy collection (la collection Petite souris), a sample of documented human deciduous teeth at the University of Bordeaux, France
Authors: Le Luyer Mona , Bayle Priscilla 
Published: October 2021

AbstractThe aim of this article is to describe the composition of the Tooth Fairy collection (collection Petite souris as it is known in French), a documented sample of deciduous teeth from individuals with known kinship curated at the University of Bordeaux (France). Since 2014, we have collected naturally exfoliated deciduous teeth from French children of known kinship and life histories. The life‐history records include date and place of birth, sex, birth weight, and length, weight measurements during the first 6 months of life, whether the child was born premature or full‐term, delivery conditions, and dietary information including weaning age. Data collection and exploitation was approved by the French authority Commission Nationale de l'Informatique et des Libertés. The collection, which is still expanding, is currently composed of 995 deciduous teeth belonging to 99 individuals from 42 families. The sample includes 61 female individuals and 38 male individuals, born between 1953 and 2013, the majority from France. Siblings are the most represented kinship type within the collection. The Tooth Fairy collection of deciduous teeth from individuals with known life history and kinship offers a unique window into the variation in human growth. Available for macro‐, meso‐, and microstructural analysis, the collection offers new insights into the multiple factors influencing dental growth, human variation, and diet, especially around birth and during early postnatal life. This collection is particularly relevant for studies in forensic, dental, and biological anthropology.
Development and psychometric evaluation of a Thai Diagnostic Autism Scale for the early diagnosis of Autism Spectrum Disorder
Authors: Tangviriyapaiboon Duangkamol , Sirithongthaworn Samai , Apikomonkon Hataichanok , Suyakong Chidawan , Srikummoon Pimwarat , Kawilapat Suttipong , Traisathit Patrinee 
Published: October 2021

AbstractThe Thai Diagnostic Autism Scale (TDAS) was developed for use as a diagnostic tool for the early diagnosis of Autism Spectrum Disorder (ASD) in Thai children aged 12–48 months old. TDAS consists of 23 items (13 and 17 items in the observational and interview sections, respectively) classified into seven domains (A1–A3 and B1–B4) according to the criteria in the Diagnostic and Statistical Manual of Mental Disorder, fifth edition (DSM‐5). Children with a single score in the A1–A3 domains and at least two of the B1–B4 domains were classified with ASD. The item‐objective congruence (IOC) index, confirmatory factor analysis, and Kappa coefficient were used to evaluate the content, constructs, and inter‐rater validity levels between the evaluators and concurrent validity between TDAS and physicians' diagnoses, respectively. TDAS showed good overall content validity (IOC range 0.71–1.00), suitable construct validity (root‐mean‐squared errors of approximation of 0.076 and 0.067, comparative fit indexes of 0.902 and 0.858, and Tucker‐Lewis indexes of 0.882 and 0.837 for the observation and interview sections, respectively), and excellent diagnostic agreement between TDAS and the evaluators (Kappa = 1.000) as well as between TDAS and the physicians' diagnoses (Kappa = 0.871). The sensitivity and specificity of TDAS were 100% and 82.4%, respectively. In conclusion, TDAS yielded a high level of content validity, concurrent validity, and inter‐rater reliability for the early diagnosis of ASD in Thai children. A large‐scale study using TDAS is needed to determine an appropriate cut‐off point as well as its efficacy.Lay SummaryThe Thai Diagnostic Autism Scale was developed for use as a diagnostic tool for the early diagnosis of Autism Spectrum Disorder (ASD) among Thai children. It contains 23 items in seven domains for the screening via observations and interviews. The psychometric properties of this diagnostic tool provide its reliability and suitability for the early diagnosis of ASD. A large‐scale study using it is needed to determine an appropriate cut‐off point as well as its efficacy.
The efficacy and possible mechanisms of immune checkpoint inhibitors in treating non‐small cell lung cancer patients with epidermal growth factor receptor mutation
Authors: Ma Lin , Diao Bowen , Huang Zhaoqin , Wang Bin , Yu Jinming , Meng Xiangjiao 
Published: October 2021

AbstractOver the past few years, immune checkpoint inhibitors (ICIs) have greatly improved the survival for patients with non‐small cell lung cancer (NSCLC) without driver mutations. Compared with wild‐type tumors, tumors with epidermal growth factor receptor (EGFR) mutations show more heterogeneity in the expression level of programmed cell death‐ligand 1 (PD‐L1), tumor mutational burden (TMB), and other immune microenvironment characteristics. Whether ICIs are suitable for NSCLC patients with EGFR mutations is still worth exploring. In previous studies, no significantly improved benefits were observed with immunotherapy monotherapy in NSCLC patients with EGFR mutation. Here, we summarized and analyzed data from the clinical trials of ICIs or combined therapy in NSCLC patients with EGFR mutations. We also focused on the mechanisms affecting the efficacy of ICIs in NSCLC patients with EGFR mutations, the characteristics of potential responders, and provided insights into areas worth further investigations in future studies.
Scalable Synthesis of NiFe‐LDH/Ni9S8/NF Nanosheets by Two‐Step Corrosion for Efficient Oxygen Electrocatalysis
Authors: Yao Yue , Hu Enlai , Zheng Heqi , Chen Yi , Wang Zhiyu , Cui Yuanjing , Qian Guodong 
Published: October 2021

AbstractScalable synthesis of non‐noble‐metal‐based electrocatalysts achieved by energy‐saving and cost‐effective strategies towards efficient oxygen evolution is primary significant for the practical application of water splitting, however, it is still a great challenge. In this work, a two‐step corrosion engineering is proposed to construct ultrathin NiFe‐LDH and high‐conductivity Ni9S8 composites (denoted as NiFe‐LDH/Ni9S8/NF) at room temperature. By ingeniously using the corrosion reaction between nickel foam (NF) and S2O32− under acidic condition, Ni9S8 was firstly formed on the surface of Ni foam. Then, ultrathin NiFe‐LDH nanosheets were precipitated on the Ni9S8 surface through an ultrafast Fe2+ ions‐assisted corrosion treatment. Featured with fast electron/mass transfer rates, sheet‐stacked structure, and superior hydrophilicity, NiFe‐LDH/Ni9S8/NF exhibits an enhanced oxygen evolution reaction (OER) activity with low overpotentials of 223 and 265 mV at 10 and 100 mA cm−2, respectively. Such feasible, economical, and scale‐up synthesis method might open a new avenue for the wide‐scale fabrication of materials for various electrochemical applications.
Transesterification of Refined Sunflower Oil to Biodiesel Using a CaO/ZSM‐5 Powder Catalyst
Authors: Dahdah Eliane , Estephane Jane , Moussa Chalouhi Lena , Sammoury Safa , El Khoury Bilal , Gennequin Cedric , Abi-Aad Edmond , Aouad Samer 
Published: October 2021

AbstractThe production of biodiesel from refined sunflower vegetable oil over basic CaO/ZSM‐5 catalysts was investigated. Several catalysts with various loadings of CaO on ZSM‐5 were prepared, calcined at 800 °C, and characterized by N2 adsorption‐desorption, X‐ray diffraction, Fourier transform infrared spectroscopy, and CO2‐temperature‐programmed desorption techniques. Calcined catalysts were tested in the transesterification reaction and reaction conditions were optimized by varying the catalyst‐to‐oil ratio and reaction time. The most active catalyst was the CaO/ZSM‐5 catalyst with a 35 wt % loading which gave the highest fatty acid methyl ester yield. The high catalytic activity was attributed to the active basic sites generated following CaO addition. Furthermore, the catalyst demonstrated stability against the leaching process.
Enhanced Electrochemical Performance of LiNi0.8Co0.1Mn0.1O2 with SiO2 Surface Coating Via Homogeneous Precipitation
Authors: Dou Lintao , Hu Pu , Shang Chaoqun , Wang Heng , Xiao Dongdong , Ahuja Utkarsh , Aifantis Katerina , Zhang Zhanhui , Huang Zhiliang 
Published: October 2021

AbstractNi‐rich LiNi0.8Co0.1Mn0.1O2 (NCM811) has been considered as a promising cathode material for high energy density lithium‐ion batteries. However, it experiences undesirable interfacial side‐reactions with the electrolyte, which lead to a rapid capacity decay. In this work, a homogeneous precipitation method is proposed for forming a uniform silicon dioxide (SiO2) coating on the NCM811 surface. The strong Si−O network provided a stable protective layer between the NCM811 active material and electrolyte to improve the electrochemical stability. As a result, the NCM811@SiO2 cathode showed superior cycling stability (84.9 % after 100 cycles at 0.2 C) and rate capability (142.7 mA h g−1 at 5 C) compared to the pristine NCM811 cathode (56.6 % after 100 cycles, 127.9 mA h g−1 at 5 C). Moreover, the SiO2 coating effectively suppressed voltage decay and pulverization of the NCM811 particles during long term cycling. This uniform coating technique offers a viable approach for stabilizing Ni‐rich cathode materials for high‐energy density lithium‐ion batteries.
Prediction of Bubble Sizes in Bubble Columns with Machine Learning Methods
Authors: Biessey Philip , Bayer Hakan , Theßeling Christin , Hilbrands Eske , Grünewald Marcus 
Published: October 2021

AbstractTwo Machine Learning algorithms – LASSO and Random Forest – are applied to derive regression models for the prediction of gas bubble diameters using supervised learning techniques. Experimental data obtained from wire‐mesh sensor (WMS) measurements in a deionized water/air system serve as the data base. Python libraries are used to extract features characterizing WMS measurement signals of single passing bubbles. Prediction accuracy is largely increased with the obtained regression models, compared to well‐established methods to predict bubble sizes based on WMS measurements.
Spatiotemporal map of key signaling factors during early penis development
Authors: Tarulli Gerard A. , Cripps Samuel M. , Pask Andrew J. , Renfree Marilyn B. 
Published: October 2021

AbstractThe formation of the external genitalia is a highly complex developmental process, considering it involves a wide range of cell types and results in sexually dimorphic outcomes. Development is controlled by several secreted signalling factors produced in complex spatiotemporal patterns, including the hedgehog (HH), bone morphogenic protein (BMP), fibroblast growth factor (FGF) and WNT signalling families. Many of these factors act on or are influenced by the actions of the androgen receptor (AR) that is critical to masculinisation. This complexity of expression makes it difficult to conceptualise patterns of potential importance. Mapping expression during key stages of development is needed to develop a comprehensive model of how different cell types interact in formation of external genitalia, and the global regulatory networks at play. This is particularly true in light of the sensitivity of this process to environmental disruption during key stages of development. The goal of this review is to integrate all recent studies on gene expression in early penis development to create a comprehensive spatiotemporal map. This serves as a resource to aid in visualising potentially significant interactions involved in external genital development.
Physician Perspectives on Including Pregnant Women in Covid‐19 Clinical Trials: Time for a Paradigm Change
Authors: Trahan Marie‐Julie , Cumyn Annabelle , Cheng Matthew P. , McDonald Emily G. , Lapinsky Stephen E. , Daneman Nick , Abenhaim Haim A. , Malhamé Isabelle 
Published: October 2021

AbstractExcluding pregnant people from Covid‐19 clinical trials may lead to unintended harmful consequences. For this study, an online questionnaire was sent to physicians belonging to Canadian professional medical associations in order to evaluate their perspectives on the participation of pregnant women in Covid‐19 clinical trials. The majority of respondents expressed support for including pregnant women in Covid‐19 trials (119/165; 72%), especially those investigating therapies with a prior safety record in pregnancy (139/164; 85%). The main perceived barriers to inclusion identified were unwillingness of pregnant patients to participate and of treating teams to offer participation, the burden of regulatory approval, and a general “culture of exclusion” of pregnant women from trials. We describe why some physicians may be reluctant to include pregnant individuals in trials, and we identify barriers to the appropriate participation of pregnant people in clinical research.
Supporting adaptive management with ecological forecasting: chronic wasting disease in the Jackson Elk Herd
Authors: Galloway Nathan L. , Monello Ryan J. , Brimeyer Doug , Cole Eric K. , Hobbs N. Thompson 
Published: October 2021

AbstractAdaptive management has emerged as the prevailing approach for combining environmental research and management to advance science and policy. Adaptive management, as originally formulated by Carl Walters in 1986, depends on the use of Bayesian models to provide a framework to accumulate knowledge. The emergence of ecological forecasting using the Bayesian framework has provided robust tools and supports a new approach to informing adaptive management, which can be particularly useful in developing policy for managing infectious disease in wildlife. We used the potential infection of elk populations with chronic wasting disease in the Jackson Valley of Wyoming and the National Elk Refuge as a model system to show how Bayesian forecasting can support adaptive management in anticipation of management challenges. The core of our approach resembles the sex‐ and age‐structured, discrete time models used to support management decisions on elk harvest throughout western North America. Our model differs by including stages for CWD‐infected and unaffected animals. We used data on population counts, sex and age classification, and CWD testing, as well as results from prior research, in a Bayesian statistical framework to predict model parameters and the number of animals in each age, sex, and disease stage over time. Initial forecasts suggested CWD may reach a mean prevalence in the population of 12%, but uncertainty in this forecast is large and we cannot rule out a mean forecasted prevalence as high as 20%. Using recruitment rates observed during the last two decades, the model predicted that a CWD prevalence of 7% in females would cause the population growth rate () to drop below 1, resulting in population declines even when female harvest was zero. The primary value of this ecological forecasting approach is to provide a framework to assimilate data with understanding of disease processes to enable continuous improvement in understanding the ecology of CWD and its management.
Forward modeling of Rayleigh surface waves for analytical characterization of dominant dispersion trends
Authors: Lin Shibin , Yi Ting‐Hua , Ashlock Jeramy , Gucunski Nenad 
Published: October 2021

AbstractForward modeling is of critical importance for inversion analysis of surface wave methods to obtain shear‐wave velocity (VS) profiles of soil sites. The dynamic stiffness matrix (DSM) method can provide forward modeling of Rayleigh surface waves to simulate complex wave propagation in layered soil sites. However, contamination from body waves and interference of multiple Rayleigh wave modes can reduce the accuracy of theoretical dispersion curves, especially at irregular soil sites with embedded low‐velocity or high‐velocity layers. An analytical method is developed herein to combine the techniques of the multichannel analysis of surface waves method with the DSM method to improve the accuracy of the theoretical dispersion analysis for soil sites. The proposed method implements multichannel analysis of the analytical displacement responses to capture dominant dispersion trends. Comparison of the results obtained with the new method against those from the transfer matrix method and the literature indicates that the new method can (1) effectively minimize the effects of contamination caused by body waves and interference from several Rayleigh wave modes, and (2) generate accurate dominant dispersion trends for soil sites with various stiffness profiles, especially for the high‐frequency dispersion characteristics of the profiles with embedded low‐velocity layers.
Regeneration of CO2‐rich aqueous amine‐ionic liquid blends in CO2 capture process
Authors: Perumal Muthumari , Jayaraman Dhanalakshmi 
Published: October 2021

AbstractIn this present work, solvent regeneration of CO2‐rich aqueous solvent blends containing Monoethanolamine (MEA) and Ionic liquids was studied experimentally. The ionic liquids (ILs) used are tetrabutylammonium acetate [TBA][OAC] and tetrabutylammonium bromide [TBA][Br]. The solvent mixture composition of ILs are 2, 5, 10 wt% and their respective MEA as 28, 25, 20 wt%. CO2 absorption and desorption process were performed using solvent blends. The recovery of solvent was performed for three different temperatures 358, 368 and 373 K. The findings reveal that solvent blends of MEA with [TBA][Br] exhibit higher regeneration efficiency and lower regeneration energy than MEA with [TBA][OAC] blends with a minimum composition of 2 wt% [TBA][Br]. Energy consumption for recovery of 2 wt% [TBA][Br] blend with 28 wt% MEA was found to be 65.66 KJ mole−1 of CO2 which is 41.97% less than 30 wt% MEA. Furthermore, physicochemical properties such as pH, density, viscosity, carbon loading and surface tension have been measured before and after CO2 absorption and desorption process. © 2021 Society of Chemical Industry and John Wiley & Sons, Ltd.
Effect of the water injection pressure on coal permeability based on the pore‐fracture fractal characteristics: An experimental study
Authors: Wang Kai , Guo Yangyang , Du Feng , Dong Huzi , Xu Chao 
Published: October 2021

AbstractCoal seam water injection is a commonly used method by which to improve coal seam permeability. To reveal how this method can enhance coal permeability from the perspective of the pore‐fracture structure, the permeability and porosity of raw coal samples under different water injection pressures were tested. Low‐temperature nitrogen adsorption (N2GA) and high‐pressure mercury intrusion porosimetry (MIP) were employed to characterize the changes in the pore‐fracture structures of water‐injected coal samples. Moreover, the relationship between the fractal dimension and coal permeability was studied using fractal theory. The results revealed the following. The internal pore‐fracture structures of the coal samples were rich in variety, and the pore span was large. With the increase of the water injection pressure, the volume ratios of macropores and mesopores gradually increased. Moreover, in the test interval, the fractal dimension of the water‐injected samples did not fluctuate substantially. With the increase of the water injection pressure, the integral dimension of seepage pores became positively correlated with permeability, while the fractal dimension of diffusion pores became negatively correlated with permeability. The results indicate that the increase in the water injection pressure not only increases the proportion of seepage pores, but also densifies the diffusion pores. Thus, the uniformity of diffusion pores can well reflect the permeability level of coal samples. © 2021 Society of Chemical Industry and John Wiley & Sons, Ltd.
Extended and optimized deep convolutional neural network‐based lung tumor identification in big data
Authors: Ananth Antony Dennis , Palanisamy Chenniappan 
Published: October 2021

AbstractLung tumor is a complex disease caused due to the irregular growth of lung cells. A key factor in effective treatment planning is the early detection of lung tumor. Visual similarity between benign and malignant nodules, heterogeneity and low contrast variation are the factors that make accurate cancerous lesion recognition, a very challenging task. In this paper, Optimized Deep convolutional neural network (DCNN) and Fuzzy C‐means with Equilibrium optimizer (FCM‐EO) is proposed for classification and segmentation of CT lung images. The proposed architecture is comprised of four phases such as preprocessing, feature extraction, classification and segmentation. In preprocessing, the weighted mean histogram analysis (WMHA) is utilized to enhance the quality of images and noise removal. Hybrid Dual tree‐complex wavelet transform (DT‐CWT) with Gabor filter is proposed in feature extraction to extract the features from the preprocessed images. DCNN model is designed to classify the original images into benign and malignant images. The weight of DCNN model is updated using the Enhanced black widow optimization algorithm (EBWOA). In segmentation, FCM‐EO is introduced to identify the tumor regions and remove the outliers from the malignant images. LIDC‐IDRI dataset is utilized for the experimental analysis and MATLAB is the implementation tool. The simulation analysis is performed for both the classification and segmentation processes. Accuracy, specificity, sensitivity, precision, F‐measure, FROC, DSC, MCC, and IoU are evaluated for both these processes. The experimental results showed the proposed framework is efficient for the identification of tumor from the CT lung images.