bluuebunny/crossref_metadata_2025_split huggingface dataset:
Chinese child unsociability, maternal maladaptive parenting, and peer exclusion among preschoolers: A cross‐lagged model
Authors: Xiao Bowen , Weng Wanjuan , Wang Longfei , Li Yan 
Published: November 2022

AbstractPrevious research has consistently found that unsociability is linked to adjustment difficulties in Chinese children. However, far less attention has been paid to how parents and peers react when confronted with unsociable children. In this study, we explored the longitudinal linkages among Chinese preschoolers' unsociability, maladaptive parenting, and peer exclusion. Participants were mothers and teachers of N = 391 (Mage = 4.4 years, SD = 0.91 years; 54.5% boys) preschoolers attending eight kindergartens in Shanghai, People's Republic of China, followed over 8 months. Multi‐source assessments were employed. Mothers rated children's unsociability and their maladaptive (physical hostility, verbal hostility, punishment) parenting practices, and teachers rated children's peer exclusion at each time point. Our results indicated that child unsociability contributed to later increases in both maladaptive parenting and peer exclusion. However, maladaptive parenting and peer exclusion could not predict later increases in unsociability. Results are discussed in terms of the implications of unsociability among Chinese children.
Are declining auction prices a result of bidder behavior or auctioneer strategy? Evidence from cattle auctions
Authors: Dorfman Jeffrey H. , Li Wenying , Zhang Jingfang 
Published: November 2022

AbstractWe test the ability of three previously advanced mechanisms to generate the declining price anomaly frequently observed in sequential auctions by employing a Bayesian hierarchical model framework to simulate heterogeneous bidders in sequential cattle auctions. One hypothesis is that declining prices are due to convergence in the buyers' bidding functions as bidders learn from each other. The second posits that as bidders fulfill their demand by winning earlier lots, the decrease in aggregate demand causes prices to fall. The third is the auction designer's strategic arrangement of lots. Results show the most plausible mechanism to be a strategic ordering of the lots.
Pressure‐assisted decomposition of tricresyl phosphate on amorphous FeO using hybrid quantum‐classical simulations
Authors: Hayashi Sota , Uemura Naoki , Uranagase Masayuki , Ogata Shuji 
Published: November 2022

AbstractThe moving components of combustion engines are operated under harsh conditions of high pressures and temperatures. Extreme‐pressure anti‐wear additives, such as tricresyl phosphate (TCP), are mixed with base oil to prevent wear through the formation of a lubricant film on the substrate. We studied the effect of liquid pressure on the decomposition pathway of TCP in base oil molecules (2,5‐dimethylhexane) using hybrid quantum‐classical simulations with density functional theory for electrons. At a temperature of 300 K, we found that: (i) bond‐breaking barrier energies of both the OC and PO bonds of TCP decrease monotonically as the liquid pressure increases; (ii) the bond‐breaking barrier energy of PO is lower than that of OC at pressures of 0 and 2.0 GPa, but is higher at a pressure of 5.0 GPa; and (iii) the applied pressure significantly lowers the bond‐breaking barrier energies of both OC and PO when the PO bond of TCP is directed upward from the substrate. These findings are explained by the inhomogeneous distribution of base oil molecules around TCP and the steric repulsion of the PO bond of TCP. These results indicate that the internal structures of the lubricant films are pressure‐dependent.
A density fitting scheme for the fast evaluation of molecular electrostatic potential
Authors: Zhang Yingfeng , Zhao Jian 
Published: November 2022

AbstractMolecular electrostatic potential (MEP) is a significant and crucial physical quantity that can be applied to a large number of scenarios, such as the prediction of nucleophilic or electrophilic attacks, fitting atomic charges, σ‐hole, and so forth. The computational cost for the MEP has anO(N2) scaling with the increase of atoms, which is intractable and laborious for macromolecules. Herein, a density fitting molecular electrostatic potential (DF‐MEP) is used to reduce the computational costs for the macromolecular MEP. It is found that the accuracy of DF‐MEP is almost identical to the conventional molecular electrostatic potential (Conv‐MEP), while the computational costs can be reduced to anO(N) scaling, for example, the computational time of 699,200 grids for the Trp‐cage molecule (304 atoms) only takes 16.6 s at the B3LYP‐D3(BJ)/def2‐SVP level of theory with 16 CPU cores compared with 3060.2 s for the Conv‐MEP method.
Optical imaging technology realizes early tumor diagnosis by detecting angiogenesis
Authors: Lu Guanhua , Han Ziyu , Hu Min 
Published: November 2022

AbstractThe occurrence and development of blood vessels play a key role in different stages of tumor growth, while current imaging techniques are difficult to detect early tumor angiogenesis because of their low sensitivity. Therefore, this article introduces high‐sensitivity optical imaging technology to achieve early tumor diagnosis by detecting tumor angiogenesis. Liver and pancreatic tumor models in nude mice were respectively established to represent tumors with a rich or poor blood supply. The two optical imaging methods, in vivo confocal fluorescence imaging and photoacoustic imaging, were used to detect tumor angiogenesis at different stages. Finally, the changes in blood vessels were verified by immunostaining. Both autoluminescence imaging and pathological staining confirmed that these two tumor models were successfully established. In vivo confocal fluorescence imaging found that the early tumor blood vessel structure had obvious characteristics: disorder, tortuous deformation, thin diameter, which were significantly different from the normal tissues. Photoacoustic imaging could effectively identify blood vessels inside early tumors, which were small and disordered and might be used as one of the predictors of early tumor development. CD31 immunostaining was used to evaluate the vascular status of tumors at different stages and under different blood supply conditions. The vascular structures observed under the microscope in the two tumor models were consistent with the results observed by optical imaging methods. The optical imaging methods could monitor the characteristics of angiogenesis in the rich or poor blood supply tumors, especially the early diagnosis of tumors.
Copper induces nitrification by ammonia‐oxidizing bacteria and archaea in pastoral soils
Authors: Matse Dumsane Themba , Jeyakumar Paramsothy , Bishop Peter , Anderson Christopher W. N. 
Published: November 2022

AbstractCopper (Cu) is the main co‐factor in the functioning of the ammonia monooxygenase (AMO) enzyme, which is responsible for the first step of ammonia oxidation. We report a greenhouse‐based pot experiment that examines the response of ammonia‐oxidizing bacteria and archaea (AOB and AOA) to different bioavailable Cu concentrations in three pastoral soils (Recent, Pallic, and Pumice soils) planted with ryegrass (Lolium perenne L.). Five treatments were used: control (no urine and Cu), urine only at 300 mg N kg−1 soil (Cu0), urine + 1 mg Cu kg−1 soil (Cu1), urine + 10 mg Cu kg−1 soil (Cu10), and urine + 100 mg Cu kg−1 soil (Cu100). Pots were destructively sampled at Day 0, 1, 7, 15, and 25 after urine application. The AOB/AOA amoA gene abundance was analyzed by real‐time quantitative polymerase chain reaction at Days 1 and 15. The AOB amoA gene abundance increased 10.0‐ and 22.6‐fold in the Recent soil and 2.1‐ and 2.5‐fold in the Pallic soil for the Cu10 compared with Cu0 on Days 1 and 15, respectively. In contrast, the Cu100 was associated with a reduction in AOB amoA gene abundance in the Recent and Pallic soils but not in the Pumice soil. This may be due to the influence of soil cation exchange capacity differences on the bioavailable Cu. Bioavailable Cu in the Recent and Pallic soils influenced nitrification and AOB amoA gene abundance, as evidenced by the strong positive correlation between bioavailable Cu, nitrification, and AOB amoA. However, bioavailable Cu did not influence the nitrification and AOA amoA gene abundance increase.
A nomogram for predicting overall survival of patients with sinonasal melanoma: A population‐based study
Authors: Yang Jingyi , Song Xiaole , Lai Yuting , Liu Quan , Sun Xicai , Wang Dehui , Yu Hongmeng 
Published: November 2022

AbstractObjectiveSinonasal melanoma (SMM) is a rare but aggressive malignancy with 5‐year overall survival (OS) rates below 40% in published studies. However, the clinicopathological predictors of the prognosis of SMM remain undefined. We aimed to establish a model to predict the survival outcomes of SMM.MethodsWe searched the Surveillance, Epidemiology, and End Results (SEER) database for patients diagnosed with SMM between 1975 and 2016. Data on patient demographics, treatment modalities, and survival outcomes were retrieved. Risk factors for OS were evaluated by survival and Cox regression analyses. We also developed and validated a nomogram for OS, and compared its performance with that of conventional staging systems.ResultsOverall, 305 SMM patients were included in this population‐based study. Multivariate Cox regression showed that primary site, American Joint Committee on Cancer stage, radiotherapy, and surgery were significant risk factors for survival. A nomogram was established using the regression model. The C‐indices, areas under the receiver operating characteristic curves, calibration plots, and decision curve analysis demonstrated reliable performance of the nomogram.ConclusionThe nomogram predicting survival outcomes of SMM patients based on clinical information showed good discriminative ability and prognostic accuracy compared with conventional stage classifications. Our nomogram could be used to predict the survival probabilities for SMM patients at different timepoints.Level of Evidence2b.
Organocatalyzed Ring‐Opening Polymerization of (S)‐3‐Benzylmorpholine‐2,5‐Dione
Authors: Göppert Natalie E. , Dirauf Michael , Liebing Phil , Weber Christine , Schubert Ulrich S. 
Published: November 2022

AbstractA 3‐benzylmorpholine‐2,5‐dione monomer is synthesized from the natural amino acid l‐phenylalanine and characterized by means of nuclear magnetic resonance and infrared spectroscopy, electrospray ionization mass spectrometry, and elemental analysis. Subsequent to preliminary polymerization studies, a well‐defined poly(ester amide) homopolymer is synthesized via ring‐opening polymerization using a binary catalyst system comprising 1,8‐diazabicyclo[5.4.0]undec‐7‐ene (DBU) and a 1‐(3,5‐bis(trifluoromethyl)phenyl)‐3‐cyclohexylthiourea (TU) cocatalyst with a feed ratio of M/I/DBU/TU = 100/1/1/10. Kinetic studies reveal high controllability of the dispersities and molar masses up to conversions of almost 80%. Analysis by mass spectrometry hints toward excellent end‐group fidelity at these conditions. In consequence, utilization of hydroxyl‐functionalized poly(ethylene glycol) and poly(2‐ethyl‐2‐oxazoline) as macroinitiators results in amphiphilic block copolymers. Bulk miscibility of the building blocks is indicated by differential scanning calorimetry investigations. As more and more promising new drugs are based on hydrophobic molecules featuring aromatic moieties, the novel polyesteramides seem highly promising materials to be used as potential drug delivery vehicles.
Emissive Substoichiometric Covalent Organic Frameworks for Water Sensing and Harvesting
Authors: Maiti Sayan , Sharma Jatan K. , Ling Jianheng , Tietje‐Mckinney Dylan , Heaney Matthew P. , Runčevski Tomče , Addicoat Matthew A. , D'Souza Francis , Milner Phillip J. , Das Anindita 
Published: November 2022

AbstractEmissive covalent organic frameworks (COFs) have recently emerged as next‐generation porous materials with attractive properties such as tunable topology, porosity, and inherent photoluminescence. Among the different types of COFs, substoichiometric frameworks (so‐called Type III COFs) are especially attractive due to the possibility of not only generating unusual topology and complex pore architectures but also facilitating the introduction of well‐defined functional groups at precise locations for desired functions. Herein, the first example of a highly emissive (PLQY 6.8%) substoichiometric 2D‐COF (COF‐SMU‐1) featuring free uncondensed aldehyde groups is reported. In particular, COF‐SMU‐1 features a dual‐pore architecture with an overall bex net topology, tunable emission in various organic solvents, and distinct colorimetric changes in the presence of water. To gain further insights into its photoluminescence properties, the charge transfer, excimer emission, and excited state exciton dynamics of COF‐SMU‐1 are investigated using femtosecond transient absorption spectroscopy in different organic solvents. Additionally, highly enhanced atmospheric water‐harvesting properties of COF‐SMU‐1 are revealed using FT‐IR and water sorption studies.The findings will not only lead to in‐depth understanding of structure–property relationships in emissive COFs but also open new opportunities for designing COFs for potential applications in solid‐state lighting and water harvesting.
Entropy‐based lamarckian quantum‐behaved particle swarm optimization for flexible ligand docking
Authors: You Qi , Li Chao , Sun Jun , Palade Vasile , Pan Feng 
Published: November 2022

AbstractAutoDock is a widely used software for flexible ligand docking problems since it is open source and easy to be implemented. In this paper, a novel hybrid algorithm is proposed and applied in the docking environment of AutoDock version 4.2.6 in order to enhance the accuracy and the efficiency for dockings with flexible ligands. This search algorithm, called entropy‐based Lamarckian quantum‐behaved particle swarm optimization (ELQPSO), is a combination of the QPSO with an entropy‐based update strategy and the Solis and Wet local search (SWLS) method. By using the PDBbind core set v.2016, the ELQPSO is compared with the Lamarckian genetic algorithm (LGA), Lamarckian particle swarm optimization (LPSO) and Lamarckian QPSO (LQPSO). The experimental results reveal that the corresponding docking program of ELQPSO, named as EQDOCK in this paper, has a competitive performance in dealing with the protein‐ligand docking problems. Moreover, for the test cases with different number of torsions, the EQDOCK outperforms the other three docking programs in finding docking conformations with small root mean squared deviation (RMSD) values in most cases. In particular, it has an advantage of solving highly flexible ligand docking problems over the others.
Deep learning‐based motion compensation for four‐dimensional cone‐beam computed tomography (4D‐CBCT) reconstruction
Authors: Zhang Zhehao , Liu Jiaming , Yang Deshan , Kamilov Ulugbek S. , Hugo Geoffrey D. 
Published: November 2022

AbstractBackgroundMotion‐compensated (MoCo) reconstruction shows great promise in improving four‐dimensional cone‐beam computed tomography (4D‐CBCT) image quality. MoCo reconstruction for a 4D‐CBCT could be more accurate using motion information at the CBCT imaging time than that obtained from previous 4D‐CT scans. However, such data‐driven approaches are hampered by the quality of initial 4D‐CBCT images used for motion modeling.PurposeThis study aims to develop a deep‐learning method to generate high‐quality motion models for MoCo reconstruction to improve the quality of final 4D‐CBCT images.MethodsA 3D artifact‐reduction convolutional neural network (CNN) was proposed to improve conventional phase‐correlated Feldkamp–Davis–Kress (PCF) reconstructions by reducing undersampling‐induced streaking artifacts while maintaining motion information. The CNN‐generated artifact‐mitigated 4D‐CBCT images (CNN enhanced) were then used to build a motion model which was used by MoCo reconstruction (CNN+MoCo). The proposed procedure was evaluated using in‐vivo patient datasets, an extended cardiac‐torso (XCAT) phantom, and the public SPARE challenge datasets. The quality of reconstructed images for XCAT phantom and SPARE datasets was quantitatively assessed using root‐mean‐square‐error (RMSE) and normalized cross‐correlation (NCC).ResultsThe trained CNN effectively reduced the streaking artifacts of PCF CBCT images for all datasets. More detailed structures can be recovered using the proposed CNN+MoCo reconstruction procedure. XCAT phantom experiments showed that the accuracy of estimated motion model using CNN enhanced images was greatly improved over PCF. CNN+MoCo showed lower RMSE and higher NCC compared to PCF, CNN enhanced and conventional MoCo. For the SPARE datasets, the average (± standard deviation) RMSE in mm−1 for body region of PCF, CNN enhanced, conventional MoCo and CNN+MoCo were 0.0040 ± 0.0009, 0.0029 ± 0.0002, 0.0024 ± 0.0003 and 0.0021 ± 0.0003. Corresponding NCC were 0.84 ± 0.05, 0.91 ± 0.05, 0.91 ± 0.05 and 0.93 ± 0.04.ConclusionsCNN‐based artifact reduction can substantially reduce the artifacts in the initial 4D‐CBCT images. The improved images could be used to enhance the motion modeling and ultimately improve the quality of the final 4D‐CBCT images reconstructed using MoCo.
Technical note: A method to evaluate the effect of scanning beam delivery error on 3D dose and its utilization on carbon ion radiotherapy for prostate cancer
Authors: Zhao Jun , Wu Xianwei , Xing Ying , Li Yongqiang , Chen Zhi 
Published: November 2022

AbstractPurposeTo establish a method for evaluating the effect of scanning ion beam delivery error on three‐dimensional (3D) dose reconstructed on patients’ CT based on log file.Materials and MethodsThis study used the MATLAB program to reconstruct the 3D dose on the patient's CT based on the log file (Doselog) for treatment delivery accuracy check. In addition, differences between the parameters in the log file and the treatment plan, such as the spot position, spot size, and particle number, were analyzed, as well as their effects on the dose distribution. The accuracy of the dose reconstruction algorithm was verified by comparing dose from TPS (DoseTPS) and the dose recalculated based on the treatment plan (Doserec). Twenty treatment plans of ten prostate cancer patients received carbon ion therapy, and their corresponding 160 log files were selected for analysis and treatment delivery accuracy check. The regions with dose higher than 10% of the maximum dose were selected and 2 mm/2% criteria were used for global gamma analysis. Multiple linear regression was used to evaluate the relation between dose deviation and delivery errors.ResultsFor the algorithm accuracy verification, the mean relative dose difference is 1.02% ± 0.12%. For prostate cancer patients treated in our facility using carbon ion radiotherapy, the average passing rate of the gamma analysis between the Doselog and the DoseTPS was 95.3%. The dose deviation caused by the difference in the spot position and the number of particles was smaller than that caused by the spot size deviation.ConclusionThis study established a 3D dose verification method based on log files to evaluate the accuracy of daily delivered treatment doses. In our facility, the daily delivered dose accuracy of carbon ion therapy for prostate cancer was mainly affected by the spot size deviation in terms of the machine delivery part.
Backward error analysis of specified eigenpairs for sparse matrix polynomials
Authors: Ahmad Sk Safique , Kanhya Prince 
Published: November 2022

AbstractThis article studies the unstructured and structured backward error analysis of specified eigenpairs for matrix polynomials. The structures we discuss include ‐symmetric, ‐skew‐symmetric, Hermitian, skew Hermitian, ‐even, ‐odd, ‐even, ‐odd, ‐palindromic, ‐anti‐palindromic, ‐palindromic, and ‐anti‐palindromic
matrix polynomials. Minimally structured perturbations are constructed with respect to Frobenius norm such that specified eigenpairs become exact eigenpairs of an appropriately perturbed matrix polynomial that also preserves sparsity. Further, we have used our results to solve various quadratic inverse eigenvalue problems that arise from real‐life applications.
Nonprofits' external stakeholder engagement and collaboration for innovation: A typology and comparative analysis
Authors: Woo DaJung , Actis Kiara , Fu Jiawei Sophia 
Published: November 2022

AbstractNonprofit organizations (NPOs) increasingly consider how to engage external stakeholders, such as clients and partners, in their efforts to adapt to the fast‐changing and highly competitive environment through innovation. Although the existing literature offers evidence that stakeholder engagement can help promote organizational innovation, much of the discussion focuses on top‐down strategies of stakeholder identification and management. Drawing on in‐depth interviews with executive directors from 38 different NPOs, we developed a typology of stakeholder engagement to capture the repertoire of approaches grounded in data including: targeted feedback seeking, intentional exploration, engineered empowerment, and emergent engagement. Findings demonstrate how these four approaches contributed to NPO innovation and were related to NPO leaders' beliefs. This typology's inclusion of the emergent engagement approach suggests that external stakeholders can drive NPO innovation not only by participating in organizationally planned top‐down processes but also by offering unsolicited inputs proactively when they recognize the need or opportunity for new services or collaborative partnerships. Other conceptual implications and practical suggestions are discussed.
A theoretical study on blue‐green phosphorescent iridium (III) complexes with low‐efficiency roll‐off properties
Authors: Chi Hao‐Yuan , Xi Guo‐Qing , Liu Xiang , Zhang Hai‐Han , Ji Ye , Liu Xu‐Hui , Song Ming‐Xing , Zhang Yong‐Ling , Qin Zheng‐Kun , Zhang Hong‐Jie 
Published: November 2022

AbstractHere, eight phosphorescent heteroleptic cyclometalated Ir (III) complexes were theoretically designed to identify some suitable organic light‐emitting diode materials. (F2‐PYBPY)2Ir (acac) (marked 1), (F2‐PYBPY)2Ir (tpip) (marked 2), (PYBPY)2Ir (acac) (marked 3), (PYBPY)2Ir (tpip) (marked 4), (F2‐PYPY)2Ir (acac) (marked 5), (F2‐PYPY)2Ir (tpip) (marked 6), (PYPY)2Ir (acac) (marked 7), and (PYPY)2Ir (tpip) (marked 8) were studied via density functional theory (DFT) and time‐dependent density functional theory (TD‐DFT) methods. Here, acac denotes acetylacetonate, tpip denotes tetraphenylimido‐diphosphinate, F2‐PYBPY denotes 3‐(4‐tert‐butylpyridin‐2‐yl)‐2,6‐difluoropyridine, PYBPY denotes 4‐tert‐butyl‐2‐(pyridin‐3‐yl) pyridine, F2‐PYPY denotes 2,6‐difluoro‐3‐(pyridin‐2‐yl) pyridine, and PYPY denotes 2‐(pyridin‐3‐yl) pyridine. Further, we discuss the value of these materials from the electronic structure, spectral properties, ionization potentials, electron affinities, and application prospects of the complexes. We hope that these light‐emitting materials contribute to the organic light‐emitting diode sector. This theoretical study included the energy transfer mechanism of the complexes with acac and tpip substituents as auxiliary ligands: We analyzed the possibilities and inevitability of the results in the experiments as well as evaluated the underlying mechanism for these materials' low‐efficiency roll‐off.