bluuebunny/crossref_metadata_2025_split huggingface dataset:
A product innovation game with managerial delegation
Authors: Fanti Luciano , Gori Luca 
Published: November 2023

AbstractThis research introduces sales delegation in a product innovation game by considering Cournot and Bertrand duopolies. The article first revisits the existing results with profit‐maximising firms, showing that a prisoner's dilemma with undifferentiated products cannot occur in a Bertrand rivalry setting. Then, by considering the separation between ownership and control, the work shows, when managers are delegated to choose only over quantity or price in the product market, that sales delegation (1) increases (resp. reduces) the likelihood to innovate (not to innovate) under Cournot competition, and (2) increases the likelihood to innovate under Bertrand competition compared to the profit‐maximising setting. Unlike this, if managers are delegated to choose over quantity or price in the product market and product innovation is in the decision‐making stage, sales delegation reduces the likelihood of innovation in both Cournot and Bertrand rivalry settings. Overall, results pinpoint the importance of the managerial delegation in affecting investments in product innovation compared to the profit‐maximising model.
K‐t PCA accelerated in‐plane balanced steady‐state free precession phase‐contrast (PC‐SSFP) for all‐in‐one diastolic function evaluation
Authors: Xiang Jie , Lamy Jerome , Qiu Maolin , Galiana Gigi , Peters Dana C. 
Published: November 2023

AbstractPurposeDiastolic function evaluation requires estimates of early and late diastolic mitral filling velocities (E and A) and of mitral annulus tissue velocity (e′). We aimed to develop an MRI method for simultaneous all‐in‐one diastolic function evaluation in a single scan by generating a 2D phase‐contrast (PC) sequence with balanced steady‐state free precession (bSSFP) contrast (PC‐SSFP). E and A could then be measured with PC, and e′ estimated by valve tracking on the magnitude images, using an established deep learning framework.MethodsOur PC‐SSFP used in‐plane flow‐encoding, with zeroth and first moment nulling over each TR. For further acceleration, different k‐t principal component analysis (PCA) methods were investigated with both retrospective and prospective undersampling. PC‐SSFP was compared to separate balanced SSFP cine and PC‐gradient echo acquisitions in phantoms and in 10 healthy subjects.ResultsPhantom experiments showed that PC‐SSFP measured accurate velocities compared to PC‐gradient echo (r = 0.98 for a range of pixel‐wise velocities −80 cm/s to 80 cm/s). In subjects, PC‐SSFP generated high SNR and myocardium‐blood contrast, and excellent agreement for E (limits of agreement [LOA] 0.8 ± 2.4 cm/s, r = 0.98), A (LOA 2.5 ± 4.1 cm/s, r = 0.97), and e′ (LOA 0.3 ± 2.6 cm/s, r = 1.00), versus the standard methods. The best k‐t PCA approach processed the complex difference data and substituted in raw k‐space data. With prospective k‐t PCA acceleration, higher frame rates were achieved (50 vs. 25 frames per second without k‐t PCA), yielding a 13% higher e′.ConclusionThe proposed PC‐SSFP method achieved all‐in‐one diastolic function evaluation.
Rapid motion estimation and correction using self‐encoded FID navigators in 3D radial MRI
Authors: Wallace Tess E. , Piccini Davide , Kober Tobias , Warfield Simon K. , Afacan Onur 
Published: November 2023

AbstractPurposeTo develop a self‐navigated motion compensation strategy for 3D radial MRI that can compensate for continuous head motion by measuring rigid body motion parameters with high temporal resolution from the central k‐space acquisition point (self‐encoded FID navigator) in each radial spoke.MethodsA forward model was created from low‐resolution calibration data to simulate the effect of relative motion between the coil sensitivity profiles and the underlying object on the self‐encoded FID navigator signal. Trajectory deviations were included in the model as low spatial‐order field variations. Three volunteers were imaged at 3 T using a modified 3D gradient‐echo sequence acquired with a Kooshball trajectory while performing abrupt and continuous head motion. Rigid body‐motion parameters were estimated from the central k‐space signal of each spoke using a least‐squares fitting algorithm. The accuracy of self‐navigated motion parameters was assessed relative to an established external tracking system. Quantitative image quality metrics were computed for images with and without retrospective correction using external and self‐navigated motion measurements.ResultsSelf‐encoded FID navigators achieved mean absolute errors of 0.69 ± 0.82 mm and 0.73 ± 0.87° relative to external tracking for maximum motion amplitudes of 12 mm and 10°. Retrospective correction of the 3D radial data resulted in substantially improved image quality for both abrupt and continuous motion paradigms, comparable to external tracking results.ConclusionsAccurate rigid body motion parameters can be rapidly obtained from self‐encoded FID navigator signals in 3D radial MRI to continuously correct for head movements. This approach is suitable for robust neuroanatomical imaging in subjects that exhibit patterns of large and frequent motion.
Current status in spatiotemporal analysis of contrast‐based perfusion MRI
Authors: Shalom Eve S. , Khan Amirul , Van Loo Sven , Sourbron Steven P. 
Published: November 2023

AbstractIn perfusion MRI, image voxels form a spatially organized network of systems, all exchanging indicator with their immediate neighbors. Yet the current paradigm for perfusion MRI analysis treats all voxels or regions‐of‐interest as isolated systems supplied by a single global source. This simplification not only leads to long‐recognized systematic errors but also fails to leverage the embedded spatial structure within the data. Since the early 2000s, a variety of models and implementations have been proposed to analyze systems with between‐voxel interactions. In general, this leads to large and connected numerical inverse problems that are intractible with conventional computational methods. With recent advances in machine learning, however, these approaches are becoming practically feasible, opening up the way for a paradigm shift in the approach to perfusion MRI. This paper seeks to review the work in spatiotemporal modelling of perfusion MRI using a coherent, harmonized nomenclature and notation, with clear physical definitions and assumptions. The aim is to introduce clarity in the state‐of‐the‐art of this promising new approach to perfusion MRI, and help to identify gaps of knowledge and priorities for future research.
High‐resolution spiral real‐time cardiac cine imaging with deep learning‐based rapid image reconstruction and quantification
Authors: Wang Junyu , Awad Marina , Zhou Ruixi , Wang Zhixing , Wang Xitong , Feng Xue , Yang Yang , Meyer Craig , Kramer Christopher M. , Salerno Michael 
Published: November 2023

AbstractThe objective of the current study was to develop and evaluate a DEep learning‐based rapid Spiral Image REconstruction (DESIRE) and deep learning (DL)‐based segmentation approach to quantify the left ventricular ejection fraction (LVEF) for high‐resolution spiral real‐time cine imaging, including 2D balanced steady‐state free precession imaging at 1.5 T and gradient echo (GRE) imaging at 1.5 and 3 T. A 3D U‐Net–based image reconstruction network and 2D U‐Net–based image segmentation network were proposed and evaluated. Low‐rank plus sparse (L+S) served as the reference for the image reconstruction network and manual contouring of the left ventricle was the reference of the segmentation network. To assess the image reconstruction quality, structural similarity index, peak signal‐to‐noise ratio, normalized root‐mean‐square error, and blind grading by two experienced cardiologists (5: excellent; 1: poor) were performed. To assess the segmentation performance, quantification of the LVEF on GRE imaging at 3 T was compared with the quantification from manual contouring. Excellent performance was demonstrated by the proposed technique. In terms of image quality, there was no difference between L+S and the proposed DESIRE technique. For quantification analysis, the proposed DL method was not different to the manual segmentation method (p > 0.05) in terms of quantification of LVEF. The reconstruction time for DESIRE was ~32 s (including nonuniform fast Fourier transform [NUFFT]) per dynamic series (40 frames), while the reconstruction time of L+S with GPU acceleration was approximately 3 min. The DL segmentation takes less than 5 s. In conclusion, the proposed DL‐based image reconstruction and quantification techniques enabled 1‐min image reconstruction for the whole heart and quantification with automatic reconstruction and quantification of the left ventricle function for high‐resolution spiral real‐time cine imaging with excellent performance.
Impact of home confinement due to the COVID‐19 outbreak on vitamin D levels and trends among children with pneumonia aged 1–35 months
Authors: Wang Xueer , Chen Jianchuan , Huang Runting , Gong Ting , Zhu Lin , Luo Tingting , Yang Shu , Yan Li , Geng Gang , Dai Jihong , Li Xiaoqiang , Tian Daiyin 
Published: November 2023

AbstractVitamin D plays a vital role in immunity and is related to susceptibility and the severity of pneumonia. The home confinement caused by the novel coronavirus disease (COVID‐19) decreased sunlight exposure derived from outdoor activities in children, thereby possibly exerting an influence on 25‐hydroxyvitamin D [25(OH)D] levels. The aim of this study is to quantify vitamin D level changes and trends among infants and toddlers with community‐acquired pneumonia (CAP) during and post the home confinement period. This study included children who were hospitalized in the respiratory department of the Children's Hospital of Chongqing Medical University with CAP between February 1 and July 31 from 2020 to 2022 (N = 397). We used propensity score matching to control the confounding bias. The levels and trends of the children's serum 25(OH)D concentrations overall and by age groups were compared between the different periods. The serum 25(OH)D concentration during the home confinement period was lower (p < 0.05) but was still at the vitamin D sufficiency level. There was a gradual decrease in the 25(OH)D concentrations in the subsequent several months after the beginning of home confinement, and the recovery time was delayed. When analyzed by age group, the serum 25(OH)D concentration of the toddler group changed more significantly than that of the infant group between the different periods. The insufficiency of sunlight exposure caused by home confinement resulted in a slight and gradual decrease in vitamin D levels among children with CAP. In addition, the impact was more significant for toddlers.
Development and validation of a model to predict acute kidney injury following high‐dose methotrexate in patients with lymphoma
Authors: Rice Mikhaila L. , Barreto Erin F. , Rule Andrew D. , Martin Catherine E. , Truong Huong L. , Mara Kristin C. , Kashani Kianoush B. , Thompson Carrie A. , Witzig Thomas E. , Barreto Jason N. 
Published: November 2023

AbstractStudy ObjectiveTo develop and validate a model for predicting acute kidney injury (AKI) after high‐dose methotrexate (HDMTX) exposure.DesignRetrospective analysis.SettingMultisite integrated health system throughout Minnesota and Wisconsin.PatientsAdult patients with lymphoma who received HDMTX as a 4‐h infusion.Measurements and Main ResultsLASSO methodology was used to identify factors available at the outset of therapy that predicted incident AKI within 7 days following HDMTX. The model was then validated in an independent cohort. The incidence of AKI within 7 days following HDMTX was 21.6% (95% confidence interval (CI) 18.4%‐24.8%) in the derivation cohort (435 unique patients who received a total of 1642 doses of HDMTX) and 15.6% (95% CI 5.3%‐24.8%) in the validation cohort (55 unique patients who received a total of 247 doses of HDMTX). Factors significantly associated with AKI after HDMTX in the multivariable model included age ≥ 55 years, male sex, and lower HDMTX dose number. Other factors that were not found to be significantly associated with AKI on multivariable analysis, but were included in the final model, were body surface area, Charlson Comorbidity Index, and estimated glomerular filtration rate. The c‐statistic of the model was 0.72 (95% CI 0.69‐0.75) in the derivation cohort and 0.72 (95% CI 0.60‐0.84) in the validation cohort.ConclusionThis model utilizing identified sociodemographic and clinical factors is predictive of AKI following HDMTX administration in adult patients with lymphoma.
Administrators' perception concerning the auxiliary (janitorial) staff: The hidden heroes of education
Authors: Karatas Suleyman , Caner Mustafa 
Published: November 2023

AbstractThe present study examined administrators' views on the working status, contributions to the education process, performance status, and employment processes of the school auxiliary staff. The research was conducted in a holistic multiple‐case study design, one of the qualitative research methods. The study group consisted of 22 school administrators who work in various K12 school settings in the central districts of a city in Turkey and voluntarily participated in the study. A maximum diversity sampling strategy, one of the purposeful sampling techniques, was employed in sample selection. The study's data were obtained using a semistructured interview conducted by the researchers. An inductive content analysis technique was utilized to analyze the data, and the results were interpreted accordingly. The study's findings revealed that administrators felt that their role is a very insignificant position in the recruitment of auxiliaries, the auxiliary staff has direct and indirect contributions to the education process, and they cause some unfavorable circumstances in some cases. In addition, it was found that school administrators think that the auxiliary staff could be efficient when employed through temporary recruitment procedures and if they have an active role in their recruitment.
Promoting organic room temperature phosphorescence through in situ polymerization
Authors: Yao Wanni , Xiong Haowei , Liao Qiuyan , Huang Arui , Li Qianqian , Li Zhen 
Published: November 2023

AbstractOrganic room temperature phosphorescence materials (RTP) have attracted much attention for their wide application in organic light‐emitting diodes, anti‐counterfeiting, and sensors. In this work, a series of organic luminogens containing carbonyl and aromatics were fixed in a three‐dimensional polymethyl methacrylate (PMMA) network by in situ polymerization. All organic luminogens‐doped in situ PMMA (s‐PMMA) columns achieved longer RTP lifetimes than those of doped commercial PMMA (c‐PMMA) films, especially, the RTP lifetime of NMP2O in these PMMA matrixes increased from 1.82 ms to 156.34 ms by about 86 times. It is mainly due to the restriction of molecular motions by highly entangled polymer chains and rigid environments to efficiently inhibit the non‐radiative transitions. Also, the excellent shielding effect toward oxygen by the in situ polymerization process can avoid possible quenching effects on triplet excited states, beneficial to RTP emission. Thus, it affords an efficient approach to achieving persistent RTP for three‐dimensional displaying applications.
Bioinspired total synthesis and biological activity of Pegaharine A
Authors: Liu Qichang , Zuo Mei , Song Yi , He Shuzhong , Huang Jian , Chen Yang 
Published: November 2023

AbstractBACKGROUNDPhytopathogens cause various diseases by parasitizing crops, reducing crop yield and resulting in substantial economic losses in agricultural production. A novel type isolated from the perennial herbaceous Peganum harmala L. seeds, β‐carboline alkaloids pegaharine A (PA), has become a hot topic in developing plant‐originated green pesticides owing to their significant physiological activities.RESULTSA scalable bioinspired total synthesis of PA is accomplished in the present work. The systematical biological assay study showed that PA exhibited moderate inhibitory activity against nine tested plant pathogenic fungi and showed significant inhibitory activity in vitro against the three tested plant pathogenic bacteria. Most noteworthy is the inhibitory rates of PA on Xanthomonas oryzae pv. oryzae (Xoo), X. oryzae pv. oryzicola (Xoc) and X. axonopodis pv. citri (Xac) of 93.6%, 92.1% and 86.1%, respectively, which are better than the control drug, bismerthiazol (63.4%, 61.2% and 53.7% at 100 μg mL−1 concentration). Furthermore, the EC50 value of PA against Xoo, Xoc and Xac was 52.2, 60.0 and 65.1 μg mL−1, respectively, superior to 72.9, 64.2 and 70.1 μg mL−1 of the control drug. Moreover, the anti‐Xoo mechanistic studies revealed that PA exerted its antibacterial effects by increasing the permeability of the bacterial membrane, reducing the extracellular polysaccharide content and inducing morphological changes in bacterial cells.CONCLUSIONA novel β‐carboline alkaloid, PA, was prepared by biomimetic total synthesis. Its significant antibacterial activity was closely related to the permeation of bacterial cell membranes, which was confirmed by anti‐Xoo mechanistic studies. More importantly, the structure could be regarded as a model for developing novel bactericides. © 2023 Society of Chemical Industry.
Management of pulmonary hypertension associated with valvular heart disease with angiotensin‐receptor neprilysin inhibitor
Authors: Ali Hyeon‐Ju Ryoo , Thomas Jerome , Sahay Sandeep , Guha Ashrith 
Published: November 2023

AbstractPulmonary hypertension secondary to left‐sided valvular disease (VHD‐PH) is associated with high morbidity and mortality. Angiotensin‐receptor neprilysin inhibitor (ARNI) is a novel pharmacotherapy, which reduces afterload with natriuresis and peripheral vasodilation. Our cases demonstrate that ARNI may also have a role in the treatment of combined pre‐ and postcapillary pulmonary hypertension that is independent of its effect on pulmonary capillary wedge pressure and cardiac output. Future prospective trials are needed to evaluate role of ARNIs in treatment of VHD‐PH.
Machine learning based post‐processing of model‐derived near‐surface air temperature – A multimodel approach
Authors: Stachura Gabriel , Ustrnul Zbigniew , Sekuła Piotr , Bochenek Bogdan , Kolonko Marcin , Szczęch‐Gajewska Małgorzata 
Published: November 2023

AbstractIn this article, a machine‐learning‐based tool for calibrating numerical forecasts of near‐surface air temperature is proposed. The study area covers Poland representing a temperate type of climate with transitional features and highly variable weather. The direct output of numerical weather prediction (NWP) models is often biased and needs to be adjusted to observed values. Forecasters have to reconcile forecasts from several NWP models during their operational work. As the proposed method is based on deterministic forecasts from three short‐range limited‐area models (ALARO, AROME and COSMO), it can support them in their decision‐making process. Predictors include forecasts of weather elements produced by the NWP models at synoptic weather stations across Poland and station‐embedded data on ambient orography. The Random Forests algorithm (RF) has been used to produce bias‐corrected forecasts on a test set spanning one year. Its performance was evaluated against the NWP models, a linear combination of all predictors (multiple linear regression, MLR) as well as a basic Artificial Neural Network (ANN). Detailed evaluation was done to identify potential strengths and weaknesses of the model at the temporal and spatial scale. The value of RMSE of a forecast obtained by the RF model was 11% and 27% lower compared to the MLR model and the best‐performing NWP model respectively. The ANN model turned out to be even superior, outperforming RF by around 2.5%. The greatest improvement occurred for warm bias during the nighttime from July to September. The largest difference in forecast accuracy between RF and ANN appeared for temperature drops inApril nights. Poor performance of RF for extreme temperature ranges may be suppressed by training the model on forecast error instead of observed values of the variable.
A comparative analysis of motivational techniques in public and private schools: Implications for secondary education
Authors: Akram Shahla , Hameed Ume Ruman , Pervaiz Zahid 
Published: November 2023

AbstractThis study examines and compares the motivational techniques employed in public and private secondary schools. The study was conducted in Faisalabad, Pakistan. A mixed‐method approach was used by utilising qualitative as well as quantitative data collected through questionnaires filled out by students and interviews conducted with teachers from 12 secondary schools in the public and private sectors. Findings indicate that private schools outperform public schools in the use of effective motivational strategies. Lack of resources, large class sizes, limited access to professional development and the scarcity of technological resources were identified as some of the important challenges that teachers face in implementing motivation strategies. The research offers valuable insights for educators, policy makers, and stakeholders regarding the significance of motivation in education. The study recommends that resource constraints should be abolished, class sizes should be reduced to the optimal level and access to modern technology must be ensured, particularly in public schools, to enrich the learning environment.
An efficient conjugate gradient based Cholesky CMA‐ES estimation algorithm for nonlinear systems
Authors: Mao Yawen , Xu Chen , Chen Jing , Pu Yan 
Published: November 2023

AbstractThis article studies the parameter estimation problems of nonlinear systems with colored noise using the covariance matrix adaptation evolution strategy (CMA‐ES), which is one of the most competitive evolutionary algorithms available and has been applied in the area of reinforcement learning and process control. However, a major limitation that impedes the application of the CMA‐ES is the high computational complexity caused by matrix decomposition. To solve this problem, an efficient Cholesky CMA‐ES which uses the Cholesky factor instead of the covariance matrix to reduce the computational complexity, and updates the search direction and distribution mean based on the conjugate gradient method to improve the search accuracy is proposed. By using the auxiliary model identification idea, the Cholesky CMA‐ES can be applied to solve the parameter estimation problems of the Hammerstein nonlinear systems with colored noise. Two simulation examples are provided to demonstrate its effectiveness.