bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mechanical, rheological, and crystallinity properties of polylactic acid/polyethylene glycol‐polydimethylsiloxane copolymer blends by melt blending
Authors: Shi Wenying , Chen Zhize 
Published: November 2022

AbstractPolylactic acid (PLA) is high in strength and modulus, but its applications are limited partly due to its inherent brittleness. It is difficult to keep the toughness and transparency of modified PLA without damaging its tensile strength and crystallinity. To improve the properties of PLA, polyethylene glycol‐polydimethylsiloxane copolymer (PEG‐PDMS) was incorporated to PLA via melt blending. By incorporating only 5 wt% of PEG‐PDMS into PLA matrix, the elongation at break of the blends increased from 6% to 58% and the tensile strength was found to be 48.8 MPa. Differential scanning calorimetry demonstrated that the crystallinity of PLA/5%PEG‐PDMS blends reached 33.5%. At the same time, the energy storage modulus (G) and complex viscosity (η*) of the blends had been improved. UV–vis test showed the light transmittance of the PLA/5%PEG‐PDMS blends was slightly decreased. The toughened materials are sufficient to cope with the challenges brought by complex environments, achieving an efficient toughening effect.
Altered global modular organization of intrinsic functional connectivity in autism arises from atypical node‐level processing
Authors: Sigar Priyanka , Uddin Lucina Q. , Roy Dipanjan 
Published: November 2022

AbstractAutism spectrum disorder (ASD) is a neurodevelopmental condition characterized by restricted interests and repetitive behaviors as well as social‐communication deficits. These traits are associated with atypicality of functional brain networks. Modular organization in the brain plays a crucial role in network stability and adaptability for neurodevelopment. Previous neuroimaging research demonstrates discrepancies in studies of functional brain modular organization in ASD. These discrepancies result from the examination of mixed age groups. Furthermore, recent findings suggest that while much attention has been given to deriving atlases and measuring the connections between nodes, within node information may also be crucial in determining altered modular organization in ASD compared with typical development (TD). However, altered modular organization originating from systematic nodal changes are yet to be explored in younger children with ASD. Here, we used graph‐theoretical measures to fill this knowledge gap. To this end, we utilized multicenter resting‐state fMRI data collected from 5 to 10‐year‐old children—34 ASD and 40 TD obtained from the Autism Brain Image Data Exchange (ABIDE) I and II. We demonstrate that alterations in topological roles and modular cohesiveness are the two key properties of brain regions anchored in default mode, sensorimotor, and salience networks, and primarily relate to social and sensory deficits in children with ASD. These results demonstrate that atypical global network organization in children with ASD arises from nodal role changes, and contribute to the growing body of literature suggesting that there is interesting information within nodes providing critical markers of functional brain networks in autistic children.
The effects of a self‐management treatment package on daily step count in university students with depressive symptoms
Authors: Munno Reghann K. , Thomson Kendra M. , Zonneveld Kimberley L. M. 
Published: November 2022

AbstractResearch demonstrates that exercise can decrease depressive symptoms, yet it is infrequently prescribed as an intervention. Self‐management techniques offer an effective and cost‐efficient approach to increase engagement in physical activity. The purpose of this study was to evaluate the efficacy of goal setting, self‐monitoring, and feedback for increasing daily step count in university students (N = 4) reporting depressive symptoms. The treatment was efficacious for increasing steps for three participants with varying levels of consistency. All participants showed a decrease in some depression symptoms on the University Student Depression Inventory. Expert ratings on the Clinical Global Impression Scale indicated improvement in global functioning for three participants. Additional research is needed to determine the efficacy of this intervention package for increasing daily steps and the relation to depression symptoms.
How does green digitalization affect environmental innovation? The moderating role of institutional forces
Authors: Guo Qiaozhe , Geng Chengxuan , Yao Nengzhi(Chris) 
Published: November 2022

AbstractEnvironmental innovation is essential to achieving environmental and economic sustainability. This study aims to explain whether and under what conditions green digitalization may foster firm environmental innovation. Using a database of Chinese listed firms matched with provincial‐level digitalization information from 2012 to 2018, we find that green digitalization significantly increases environmental innovation, and this effect can be achieved through enhancing R&D investment. In addition, the positive effect of green digitalization on environmental innovation is moderated by formal and informal institutional forces. We establish government support (in the form of financial investment in building digital infrastructure), government intervention, and cyberculture as the theoretically important moderators. Our findings contribute to digitalization research, institutional theory, and the literature on environmental innovation and provide important practical implications for managers and policymakers seeking to improve environmental sustainability through digital transformation.
Tweaking the Optoelectronic Properties of S‐Doped Polycyclic Aromatic Hydrocarbons by Chemical Oxidation
Authors: Matuszewska Oliwia , Battisti Tommaso , Ferreira Ruben R. , Biot Nicolas , Demitri Nicola , Mézière Cécile , Allain Magali , Sallé Marc , Mañas‐Valero Samuel , Coronado Eugenio , Fresta Elisa , Costa Rubén D. , Bonifazi Davide 
Published: November 2022

AbstractPeri‐thiaxanthenothiaxanthene, an S‐doped analog ofperi‐xanthenoxanthene, is used as a polycyclic aromatic hydrocarbon (PAH) scaffold to tune the molecular semiconductor properties by editing the oxidation state of the S‐atoms. Chemical oxidation of peri‐thiaxanthenothiaxanthene with H2O2led to the relevant sulfoxide and sulfone congeners, whereas electrooxidation gave access to sulfonium‐type derivatives forming crystalline mixed valence (MV) complexes. These complexes depicted peculiar molecular and solid‐state arrangements with face‐to‐face π–π stacking organization. Photophysical studies showed a widening of the optical bandgap upon progressive oxidation of the S‐atoms, with the bis‐sulfone derivative displaying the largest value (E00=2.99 eV). While peri‐thiaxanthenothiaxanthene showed reversible oxidation properties, the sulfoxide and sulfone derivatives mainly showed reductive events, corroborating theirn‐type properties. Electric measurements of single crystals of the MV complexes exhibited a semiconducting behavior with a remarkably high conductivity at room temperature (10−1–10−2 S cm−1and 10−2–10−3 S cm−1for the O and S derivatives, respectively), one of the highest reported so far. Finally, the electroluminescence properties of the complexes were tested in light‐emitting electrochemical cells (LECs), obtaining the first S‐doped mid‐emitting PAH‐based LECs.
Data‐driven variational multiscale reduced order modeling of vaginal tissue inflation
Authors: Snyder William , McGuire Jeffrey A. , Mou Changhong , Dillard David A. , Iliescu Traian , De Vita Raffaella 
Published: November 2022

AbstractThe vagina undergoes large finite deformations and has complex geometry and microstructure, resulting in material and geometric nonlinearities, complicated boundary conditions, and nonhomogeneities within finite element (FE) simulations. These nonlinearities pose a significant challenge for numerical solvers, increasing the computational time by several orders of magnitude. Simplifying assumptions can reduce the computational time significantly, but this usually comes at the expense of simulation accuracy. This study proposed the use of reduced order modeling (ROM) techniques to capture experimentally measured displacement fields of rat vaginal tissue during inflation testing in order to attain both the accuracy of higher‐fidelity models and the speed of simpler simulations. The proper orthogonal decomposition (POD) method was used to extract the significant information from FE simulations generated by varying the luminal pressure and the parameters that introduce the anisotropy in the selected constitutive model. A new data‐driven (DD) variational multiscale (VMS) ROM framework was extended to obtain the displacement fields of rat vaginal tissue under pressure. For comparison purposes, we also investigated the classical Galerkin ROM (G‐ROM). In our numerical study, both the G‐ROM and the DD‐VMS‐ROM decreased the FE computational cost by orders of magnitude without a significant decrease in numerical accuracy. Furthermore, the DD‐VMS‐ROM improved the G‐ROM accuracy at a modest computational overhead. Our numerical investigation showed that ROM has the potential to provide efficient and accurate computational tools to describe vaginal deformations, with the ultimate goal of improving maternal health.
Taylor political monarch butterfly optimization driven deep learning model for acute lymphoblastic leukemia detection and severity classification using blood smear images
Authors: Mercy Bai Gnana Prakasam , Perumal Venkadesh 
Published: November 2022

SummaryAn image processing and classification become an exciting research region for indicative probe because of the expansion of digital microscopic imaging. Acute lymphoblastic leukemia (ALL) is caused owing to broken in bone marrow, which is general among the people around the biosphere. A leukemia generally affects blood creating organs and hence, easily spread to other tissues by blood. The hematologists afflict more to differentiate leukemia existence in body of patients based on blood smears. Hence, in this article, Taylor political monarch butterfly optimization‐enabled deep residual neural network (Taylor PMBO‐enabled DRN) is devised for ALL classification. Segmentation is the process of separating the images into small pixels. A deep joint segmentation model effectively enhances the detection accuracy and it has better segmentation capability. For a better classification procedure, the important features, such as statistical, texture, and grid features, are extracted. For ALL detection and classification processes, a deep residual neural network (DRN) classifier is trained by the Taylor PMBO. The devised Taylor PMBO‐based DRN model obtained better performance than other method by testing accuracy, sensitivity, specificity, F1‐score, and precision of 0.9656, 0.9666, 0.9709, 0.9280, and 0.9321.
Unraveling phenotypic diversity in Cynodon spp. germplasm for forage accumulation and nutritive value in the transition zone
Authors: de Souza Cleber H. L. , Fernandes Filho Claudio C. , Canny Raquel S. , Sharma Normal , Saha Malay , Wallau Marcelo O. , Anderson William , Baxter Lisa , Harris‐Shultz Karen , Rios Esteban F. 
Published: November 2022

AbstractCharacterizing phenotypic variation in germplasm collections is crucial for plant breeding. Cynodon spp. accessions maintained at the USDA National Plant Germplasm System (NPGS), and the core forage collection were screened in a replicated trial under two nitrogen rates (0 and 150 kg ha−1 per harvest) in Ardmore, OK. The goals for this study were to: (a) estimate genetic parameters for forage accumulation (FA) and nutritive value (NV), (b) estimate genotype × harvest (rgh) and genotype × environment (rge) interaction for all traits, (c) quantify FA and NV for commercial cultivars and selected accessions. The experiment was setup as a row‐column design with two replicates and augmented representation of controls: Tifton 85, Wrangler, Midland, and Cheyenne. The trial was harvested five times (twice in 2016 and three times in 2017) and data were analyzed using linear mixed models. Genetic parameters revealed the presence of significant phenotypic variation for FA and NV. Low genotype × harvest and genotype × environment interactions indicated genotypic stability and potential for selecting improved accessions for FA and NV. Several plant introductions (PIs) were identified for their improved FA and NV. The application of N increased FA and CP concentration in all harvests but did not significantly impact phenotypic variation in other NV traits. Phenotypic data will be deposited in the Germplasm Resource Information Network (GRIN)‐Global database.
Design and analysis of Hermite function‐based artificial neural network controller for performance enhancement of photovoltaic‐integrated grid system
Authors: Rai Kanchan Bala , Kumar Narendra , Singh Alka 
Published: November 2022

AbstractThis article proposes a Hermite function‐based artificial neural network (HeANN) controller for shunt compensation in photovoltaic (PV) interfaced grid system. Various power quality (PQ) issues such as load change, poor power factor, reactive power demand and current harmonics are experienced by
distribution system. The proposed HeANN algorithm is utilized to improve the PQ issues of the distribution system. Shunt active power filter (SAPF) is operated in current control mode and injects the compensating current at the point of common coupling (PCC). The inverter is connected with the green energy resource, that is, PV at its direct current terminals and contributes its power to fulfil the load active power demand. The parameters of HeANN are trained in real time. A prototype hardware of SAPF is developed using sensor circuits and space 1104. The simulation results are validated by experimental results. The comparative analysis of the results establishes the superiority of the proposed control technique to other control techniques such as synchronous reference frame, second order generalized integrator and back propagation neural network in terms of convergence, computational burden and total harmonic distortion of grid current.
Single‐cell and spatial transcriptomics reveal the fibrosis‐related immune landscape of biliary atresia
Authors: Ye Chunjing , Zhu Jiajie , Wang Junfeng , Chen Deqian , Meng Lingdu , Zhan Yong , Yang Ran , He Shiwei , Li Zifeng , Dai Shuyang , Li Yi , Sun Song , Shen Zhen , Huang Yanlei , Dong Rui , Chen Gong , Zheng Shan 
Published: November 2022

AbstractBackgroundBiliary atresia (BA) is a devastating inflammatory and fibrosing cholangiopathy of neonates with unknown aetiology. We aim to investigate the relationship between these two main characteristics.MethodsSingle‐cell RNA sequencing and spatial transcriptomics were performed on liver samples from a cohort of 14 objects (BA: n = 6; control: n = 8). We conducted data integration and cell‐type annotation based on gene expression profiling. Furthermore, we identified fibrosis‐related immune cells according to their spatial locations, GO and KEGG analysis. Finally, SPOTlight and CIBERSORTx were used to deconvolute ST data and microarray data of the GSE46960 cohorts, respectively.ResultsImmune subpopulations inhabiting the ‘fibrotic niche’ (areas of scarring), comprising ‘intermediate’ CD14++CD16+ monocytes, scar‐associated macrophages, natural killer T cells, transitional B cells and FCN3+ neutrophils were identified. GO and KEGG analyses showed that pathways including ‘positive regulation of smooth muscle cell/fibroblast proliferation’ and ‘positive regulation of/response to VEGFR/VEGF/EGFR/FGF’ were enriched in these cell types. Interactions analysis showed that communication among ‘FGF_FGFR’, ‘RPS19‐C5AR1’, ‘CD74_COPA/MIF/APP’ and ‘TNFRSF1A/B_GRN’ was extensive. Finally, the results of deconvolution for ST data and microarray data validated that the proportions of certain identified fibrosis‐related cell types we identified were increased in BA.DiscussionFibrosis is an important feature of BA, in which the immune system plays an important role. Our work reveals the subpopulations of immune cells enriched in the fibrotic niche of BA liver, as well as key related pathways and molecules; some are highlighted for the first time in liver fibrosis. These newly identified interactions might partly explain why the rate of liver fibrosis occurs much faster in BA than in other liver diseases.ConclusionOur study revealed the molecular, cellular and spatial immune microenvironment of the fibrotic niche of BA.
Determination and quantification of sedimentary processes in salt marshes using end‐member modelling of grain‐size data
Authors: Lenz Nina , Lindhorst Sebastian , Arz Helge W. 
Published: November 2022

AbstractEnd‐member modelling of bulk grain‐size distributions allows the unravelling of natural and anthropogenic depositional processes in salt marshes and quantification of their respective contribution to marsh accretion. The sedimentology of two marshes is presented: (1) a sheltered back‐barrier marsh; and (2) an exposed, reinstated foreland marsh. Sedimentological data are supplemented by an age model based on lead‐210 decay and caesium‐137, as well as geochemical data. End‐member modelling of grain‐size data shows that marsh growth in back‐barrier settings is primarily controlled by the settling of fines from suspension during marsh inundation. In addition, nearby active dunes deliver aeolian sediment (up to 77% of the total sediment accretion), potentially enhancing the capability of salt marshes to adapt to sea‐level rise. Growth of exposed marshes, by contrast, primarily results from high‐energy inundation and is attributed to two sediment‐transport processes. On the seaward edge of the marsh, sedimentation is dominated by coarser‐grained traction load, whereas further inland, settling of fine‐grained suspension load prevails. In addition, a third, coarse‐grained sediment sub‐population is interpreted to derive from anthropogenic land‐reclamation measures, that is material from drainage channels relocated onto the marsh surface. This process contributed up to 34% to the total marsh accretion and terminated synchronously with the end of land reclamation measures. Data suggest that natural sediment supply to marshes alone is sufficient to outpace contemporary sea‐level rise in the study area. This underlines the resilience potential of salt marshes in times of rising sea levels. The comparison of grain‐size sub‐populations with observed climate variability implies that even managed marshes allow for the extraction of environmental signals if natural and anthropogenic sedimentary processes are determined and their relative contribution to bulk sediment composition is quantified. Data series based solely on bulk sediments, however, seem to be of limited use because it is difficult to exclude bias of natural signals by anthropogenic measures.
Anti‐swelling polyethyleneimine‐modified MXene nanofiltration membranes for efficient and selective molecular separation
Authors: Xing Chao , Zhang Yuting , Huang Rong , Li Suhong , He Jing , Fu Rong , Lai Chao , Liu Changyu , Shen Lingdi , Zhang Shanqing 
Published: November 2022

AbstractTwo‐dimensional (2D) MXene‐based nanofiltration membranes could sustainably and rapidly produce clean water. However, the challenges related to the severe swelling of the MXene membranes in water should be overcome before the practical application. In this work, the negatively charged MXene‐based membrane is modified by positively charged polyethyleneimine (PEI) with various PEI:MXene ratios. The PEI‐MXene is deposited on a polyacrylonitrile (PAN) substrate as a top membrane to prepare an anti‐swelling composite PEI‐MXene/PAN membranes with outstanding mechanical strength and stability. Interestingly, when the interlayer spacing of the top Mxene layers are tuned between ca. 14.15 and ca. 14.52 Å, the resultant PEI‐MXene/PAN membranes exhibit the excellent ability of size sieving. For instance, PEI‐MXene(1:1)/PAN membrane presents high flux performance to Acid Blue 90 (AB90), Congo Red (CR), and Direct Red 80 (DR80) (i.e., 563.9, 882.6, and 633.6 L m−2 h−1, respectively) at 0.2 MPa, and remarkable rejection rates, that is, 99.3%, 99.82%, and 99.9%, respectively. Besides, the PEI‐MXene(0.5:1)/PAN possesses the highest flux of 1528.1 L m−2 h−1 and outstanding rejection rate of 99.9% to dye of AB8GX. Moreover, the proposed strategy can be extended to the modification of other 2D material nanofiltration membranes.image
Monitoring of the hydraulic units operation of the Sayano‐Shushenskaya hydroelectric power plant using remote seismic observations
Authors: Gromyko Pavel Vladimirovich , Fedin Konstantin Vladimirovich , Seleznev Victor Sergeevich , Kolesnikov Yury Ivanovich , Ngomayezwe Luckymore 
Published: November 2022

AbstractAfter a major accident in August 2009 at the Sayano‐Shushenskaya Hydroelectric Power Plant (SS HPP), all 10 hydroelectric units (HU) with a total capacity of 6400 MW failed. After investigating the causes of the accident and the reconstruction of the hydroelectric power plant, there was to develop a methodology for monitoring the operation of the newly commissioned HU. For inspection, a method was developed based on monitoring the natural frequencies of the dam structures and forced vibrations caused by the operation of the equipment. The article presents the main results of this study. Within the framework of the proposed approach, monitoring was carried out at various observation points of the dam structures and the turbine hall, as well as on a network of remote seismic stations. Based on the data recorded since 2009, an assessment of the parameters of dynamic impacts arising from the operation of hydraulic units of various types in different load modes on the elements of the HPP structure was carried out, and cause‐and‐effect relationships between changes in the operating modes of equipment and recorded vibrations in dam structures were investigated. An estimate of the general level of vibrations during the operation of various types of hydraulic units is given. As a result, the operating modes of hydraulic units are determined, in which there is a multiple increase in the amplitude of natural vibrations of the dam, an assessment of the operational characteristics of hydraulic units is given, taking into account the impact of seasonal conditions and changes in the water level in the reservoir.
A benchmark shaking table test on the seismic responses of an extra‐large LNG storage tank
Authors: Zhang Ding‐Yuan , Wu Jian‐Ying , Zhou Hao , Gong Mo‐Song 
Published: November 2022

AbstractIn recent years, many large‐scale liquefied natural gas (LNG) storage tanks have been built all over the world. Due to their high constructional cost and important functions to the public, the academic and engineering communities are very concerned with the operational safety of these important infrastructures once subjected to potentially disastrous actions, that is, earthquakes, typhoons, tsunamis, and so forth. This work presented a benchmark test in evaluating the aseismic performance of extra‐large prestressed reinforced concrete (RC) LNG storage tanks. A 1:14 scaled model of the prototype LNG tank was designed and constructed for shaking table tests. Two recorded and two artificial earthquake ground motions with peak ground acceleration (PGA) up to 1.2g were selected successively as seismic inputs to the tank. The acceleration, displacement, shear force, and strain responses of the model structure were presented, analyzed, and discussed in detail. It was found that due to the differences in the frequency spectra, the seismic excitations have distinct influences on the responses of the tank model. In particular, the wall‐roof junction was detected as the weakest part of the outer tank, and the filling water had non‐negligible effects on the overall seismic responses of the tank. Verified finite element simulations were also presented as supplements to the experimental study. Some suggestions were made with the aim to improve the designs of LNG storage tanks.