bluuebunny/crossref_metadata_2025_split huggingface dataset:
Can centralization of environmental regulations reduce firm emissions? Evidence from county‐prefecture centralization reforms in China
Authors: Cao Xun , Wu Mingqin 
Published: February 2025

AbstractDrawing on a natural experiment generated by prefecture‐level centralization reforms in China in the early 2000s, we study whether a centralized regulatory system delivers better environmental outcomes in a developing country context. We examine the impact of centralization reforms on firm air pollution emissions using a difference‐in‐differences estimation strategy. We find that centralization reform reduces firm air pollution intensities in total waste air, SO2, and soot. This effect is robust when we control for contemporaneous environmental policy changes and SOE reforms and when we use alternative differences‐in‐differences estimations. We perform placebo tests to further demonstrate that the relationship is unlikely a function of a selection effect and omitted variables. Empirical tests on mechanisms reveal that pollution reduction is mainly due to increased pollution removals during the end‐of‐pipe treatment stage while there is little evidence that centralization increases firm scale of production, productivity, efficiency, and innovation efforts. We show that such firm responses are likely a function of increased regulatory enforcement brought by the reform. Finally, we test whether a centralization reform drives local firms away (i.e., a spillover effect) and we find no supporting evidence.
Enhancing child–nature interactions through design: An empirical study of the emotions, perspectives and experiences of nature among South Korea's urban Generation Alpha children
Authors: Myung Jaeyoung , Choe Min , Baek Joon Sang 
Published: February 2025

Abstract

Urban Generation Alpha faces challenges in forming nature connection because of limited access to green spaces and high digital media exposure. Although childhood experiences with nature are crucial for developing a sense of nature connection, there is a limited theoretical and methodological foundation for child–nature interaction design specifically geared towards fostering a sense of nature connection.

To address this gap, this study aimed to understand how urban Generation Alpha in South Korea perceives their nature connection and explore design opportunities to enhance it. We conducted qualitative research in Seoul and Incheon, using semi‐structured interviews with 47 children and 15 parents to explore the sense of nature connection and nature experiences of Generation Alpha.

The results showed that a mismatch between the children's and parents' perceived nature connection, limited and negative nature experiences, and anthropocentric value systems hinder children's sense of nature connection.

In response to this, we proposed the following design opportunities: integrating virtual and vicarious nature experiences with direct experiences could supplement the limited exposure of Generation Alpha to nature and help develop a stronger sense of nature connection; a ludic design tailored to the attitude of children towards nature can overcome negative emotions such as fear or disgust, enhancing positive feelings through playful engagement; and a speculative design that encourages critical thinking can equip Generation Alpha to confront information about environmental problems with ecocentric views and constructive hope.

This research contributes to human–nature interaction design by highlighting the limitations of existing research and informing the development of effective programs and strategies to engage children with nature and foster their sense of nature connection.
Carbohydrate Polymers, Polymeric Nano Drugs, and Nanoparticles Are Used for Advanced Drug Delivery and Therapeutics in Ocular Diseases
Authors: Hatamie Shadie , Shih Po‐Jen , Chen Bo‐Wei , Hatami Niloofar 
Published: February 2025

ABSTRACTNanotechnology has recently attracted research attention, given its wide applications in biomedicine. Novel nontoxic nano drugs functionalized with carbohydrate polymers are widely used in in vivo bioresearch, but their application to the ocular system remains challenging. Nanostructured materials and nanoparticles functionalized with carbohydrate polymers and other biological macromolecules are clinically used as nano eye drops, incorporated into therapeutic contact lenses, and used as nano wafers and nanofibers. Moreover, they can be used as drug delivery, therapeutic, and bioimaging systems for eye diseases. In this review, nano ophthalmology therapeutic and drug delivery systems based on nanostructured materials and nanoparticles conjugated with carbohydrate polymers were investigated. Meanwhile, increasing the effect of the nano‐drug mucoadhesion by using the polymer complexes and polysaccharides is discussed. The design of pioneering nanomaterials has enabled the development of effective therapies in ophthalmology.
Inhaled Epoprostenol in Children With Pediatric Acute Respiratory Distress Syndrome: A Single‐Center Retrospective Study
Authors: Scalone Eleanor J. , Woodruff Alan G. , Saha Amit K. , Wright John M. , Dixon Kristopher L. , Bass Andora L. , Walsh Michael J. , McCrory Michael C. 
Published: February 2025

ABSTRACTBackgroundInhaled epoprostenol (iEpo) may improve oxygenation in adults with hypoxic respiratory failure, but any effect in children with pediatric acute respiratory distress syndrome (pARDS) is unknown.MethodsRetrospective observational cohort study 2017–2022 at a single pediatric intensive care unit (PICU) of children who met criteria for pARDS and received iEpo for ≥ 6 h.Results18 children were included, with a median age of 2.9 years (IQR 1.4–7.9), severe pARDS in 14/18 (78%), and pulmonary hypertension in 8/18 (44%). Median OSI immediately pre‐iEpo initiation was 22.9 (IQR 16.1–27.3), at 6 h was 16.8 (IQR 12.6–27.5, p = 0.57 vs. pre‐initiation) and at 12 h was 15.1 (IQR 10.7–27.5, p = 0.48 vs. pre‐initiation). Discontinuity regression demonstrated a change in the slope (rate of change) of OSI from increasing slope of +0.60/hr to decreasing slope of −1.38/hour in the 12 h pre‐ versus post‐ iEpo initiation (p < 0.001). At 6 h after iEpo initiation, most patients (12/18, 67%) had a decrease in OSI and 5/18 (28%) were responders with a decrease of ≥ 20%. Responders did not differ significantly by presence of pulmonary hypertension, severity of pARDS, or age. The majority of responders (4/5, 80%) had improvement in OSI by 1 h after initiation of iEpo and all (5/5, 100%) had improvement by 4 h after iEpo initiation.ConclusionRate of change of OSI improved significantly after initiation of iEpo in a cohort children with pARDS, with heterogeneity of response that was not associated with pHTN or other clinical factors evaluated. Improvement in OSI was seen by 4 h in all responders.
Construction of Novel Neutral Polymer Bonding Agent by Grafting Multifunctional Pendants for Strengthening the Mechanical Properties of F2313/DAAF‐based PBX
Authors: Dong Kongyu , Li Xiaodong , Han Xu , Ji Yumei , Yang Yike , Liu Feng 
Published: February 2025

ABSTRACTThe weaker interface interaction between fluoropolymer binder matrix (F2313) and 3,3ʹ‐diamino‐4,4ʹ‐azoxyfurazan (DAAF) energetic solid particles tends to the formation of “de‐wetting” during fabrication, transportation, and storage, causing solid grain collapse, further leading to unsatisfactory explosion effect on the polymer bonded explosive (PBX). Adding neutral polymer bonding agent (NPBA) modified with multiple polar groups is currently the most effective way for reinforcing the composite interface of PBX to inhibit de‐wetting. In this contribution, a series of novel NPBA, named 3%FTDI‐NPBA, 5%FTDI‐NPBA, and 10%FTDI‐NPBA, were designed for an F2313/DAAF system by grafting multifunctional FTDI pendants consisting of perfluorobutyl and urethane groups on the side chains of classical NPBA‐1. The chemical structure, thermal stability, interfacial properties, and bonding performances of all FTDI‐NPBA were systematically investigated. As expected, the introduction of multifunctional pendants could effectively bridge the interface gap between F2313 and DAAF. F2313/DAAF/5%FTDI‐NPBA exhibited the best mechanical properties with the Brazilian Disk strength and modulus of 8.16 ± 0.02 MPa and 5.76 ± 0.02 GPa, respectively, 29.52% and 12.50% higher than the system with NPBA‐1. Our multifunctional pendants grafting strategy will provide a viable guide for optimizing NPBA.
Versatile Features of an Antibody Mimetic Peptide and Its Variants
Authors: Dolles Simon , Leukel Simon , Gensberger‐Reigl Sabrina , Rohrhofer Anette , Rauch‐Wirth Lena , Kaygisiz Kübra , Synatschke Christopher V. , Münch Jan , Schmidt Barbara , Pischetsrieder Monika , Eichler Jutta 
Published: February 2025

ABSTRACTAntibody mimetic peptides have evolved as versatile tools for biomedical applications, based on their ability to interfere with protein–protein interactions. We had previously designed a functional mimic of the broadly neutralizing HIV‐1 antibody b12 that recognizes the CD4 binding site of the HIV‐1 envelope glycoprotein gp120. The molecular details of the interaction of a linear variant of this peptide (H1H3s) with gp120 have now been characterized through cross‐linking mass spectrometry, confirming the proposed involvement of the CD4 binding site of gp120 in the interaction. In addition, a variant of the b12 mimetic peptide composed mostly of D‐amino acids was shown to be stable towards proteolytic degradation, while the binding and HIV‐1 neutralizing properties were largely preserved. Furthermore, a peptide variant in which aspartate residues were replaced with lysine was shown to strongly enhance infection of cells with HIV‐1 and GALV glycoprotein pseudotyped viral vectors, respectively, introducing this peptide as a tool to facilitate retroviral gene transfer. Collectively, the presented results highlight the versatile potential therapeutic and gene transfer applications of H1H3s and its variants in particular, as well as antibody mimetic peptides in general.
New Method for Remaining Useful Life Prediction Based on Recurrence Multi‐Information Time‐Frequency Transformer Networks
Authors: Lv Shuai , Liu Shujie , Li Hongkun 
Published: February 2025

ABSTRACTAs the critical technology of prognostics and health management (PHM), the remaining useful life (RUL) prediction has received much attention. Deep learning algorithms based on data‐driven stand out among various methods. However, convolutional neural networks/recurrent neural networks (CNNs/RNNs) suffer from design gaps, making it challenging to achieve parallel processing of long‐time series data. In addition, most methods focus only on point prediction but lack uncertainty assessment of prediction results. Therefore, a recurrence multi‐information time‐frequency (RMTF) Transformer network is proposed in this paper, which is a kind of Transformer network based on a slice memory recurrence mechanism (SMRM), with multiple feature extraction encoders, and has the ability to extract time‐frequency features. RMTF Transformer network can realize effective extraction and fusion of long time series information, cross‐time period information, multi‐source information, and time‐frequency information. In addition, a Bayesian neural network (BNN) based on variational inference is used to predict the interval of RUL. The advancedness of our proposed method is verified and compared by the aero‐engines dataset and tool wear dataset. In particular, the RMTF Transformer demonstrates significant advantages over mainstream advanced models under complex operating conditions in two sub‐datasets of CMAPSS, FD002, and FD004. Specifically, for the FD002 dataset, the RMSE is reduced by 8.66%, and the SF is reduced by 23.37%. For the FD004 dataset, the RMSE is lowered by 6.36%, and the SF is decreased by 13.83%. The experimental results show that the proposed method can effectively predict RUL and assess the uncertainty of the prediction results.
Part B: SLICE‐MSI—A Machine Learning Interface for System Suitability Testing of Mass Spectrometry Imaging Platforms
Authors: Kibbe Russell R. , Mills Quinn , Sohn Alexandria L. , Muddiman David C. 
Published: February 2025

ABSTRACTRationaleThe field of mass spectrometry imaging is currently devoid of standardized protocols or commercially available products designed for system suitability testing of MSI platforms. Machine learning is an approach that can quickly and effectively identify complex patterns in data and use them to make informed classifications, but there is a technical barrier to implementing these algorithms. Here we package the machine learning algorithms into a user‐friendly interface to make community‐wide implementation of this protocol possible.MethodsThe software package is built entirely in the Python language using the PySimpleGUI library for the construction of the interface, Pandas and Numpy libraries for data formatting and manipulation, and the Scikit‐Learn library for the implementation of machine learning algorithms. Training data is collected on an instrument under clean and compromised conditions that can then be used to evaluate model performance and to train models prior to interrogating unknown samples before, during, or after experiments.ResultsDetailed instructions are provided for the effective use of the SLICE‐MSI software package to use machine learning to evaluate instrument condition of MSI platforms. File formatting and generalizable steps are clearly described to make the implementation of this package easy for multiple labs and different MSI platform configurations.ConclusionsIn this protocol, we demonstrate SLICE‐MSI, a machine learning graphical user interface for efficient and easy implementation of QC instrument classification of mass spectrometry imaging platforms.
Speculators and time series momentum in commodity futures markets
Authors: Uhl Björn 
Published: February 2025

AbstractIn this paper, we analyze the relationship between speculators in commodity futures markets and generic time series momentum (TSMOM) traders as well as the impact of this relationship on the subsequent TSMOM strategy performance. We find strong empirical evidence across all commodity markets that speculators in commodity markets tend to trade a TSMOM strategy, which confirms the results found by Boos and Grob (Journal of Financial Markets 64, 100774). On the basis of this result, we also ascertain whether the degree of such alignment has an impact on the performance of the TSMOM strategy. We find that there is weak, but statistically significant and robust evidence to suggest that the higher the degree of alignment between speculators and a generic TSMOM strategy, the lower the realized performance of trading TSMOM in these markets. Albeit we find little evidence that this can be exploited in a dynamic investment strategy, this negative relationship suggests that if a Commodity Trading Advisor (CTA) trades commodity futures markets which are less commonly traded by other CTAs, these markets may not only increase the internal diversification of their fund but these markets may also have a higher TSMOM Sharpe ratio by themselves. Consequently, our analysis provides valuable insights into improving the portfolio construction of CTAs.
Bayesian Hierarchical Penalized Spline Models for Immediate and Time‐Varying Intervention Effects in Stepped Wedge Cluster Randomized Trials
Authors: Wu Danni , Park Hyung G. , Grudzen Corita R. , Goldfeld Keith S. 
Published: February 2025

ABSTRACTStepped wedge cluster randomized trials (SWCRTs) often face challenges related to potential confounding by time. Traditional frequentist methods may not provide adequate coverage of an intervention's true effect using confidence intervals, whereas Bayesian approaches show potential for better coverage of intervention effects. However, Bayesian methods remain underexplored in the context of SWCRTs. To bridge this gap, we propose two innovative Bayesian hierarchical penalized spline models. Our first model accommodates large numbers of clusters and time periods, focusing on immediate intervention effects. To evaluate this approach, we compared this model to traditional frequentist methods. We then extend our approach to account for time‐varying intervention effects, conducting a comprehensive comparison with an existing Bayesian monotone effect curve model and alternative frequentist methods. The proposed models were applied in the Primary Palliative Care for Emergency Medicine stepped wedge trial to evaluate the effectiveness of the intervention. Through extensive simulations and real‐world application, we demonstrate the robustness of our proposed Bayesian models. Notably, the Bayesian immediate effect model consistently achieves the nominal coverage probability, providing more reliable interval estimations while maintaining high estimation accuracy. Furthermore, our proposed Bayesian time‐varying effect model represents a significant advancement over the existing Bayesian monotone effect curve model, offering improved accuracy and reliability in estimation while also achieving higher coverage probability than alternative frequentist methods. To the best of our knowledge, this marks the first development of Bayesian hierarchical spline modeling for SWCRTs. Our proposed models offer promising tools for researchers and practitioners, enabling more precise evaluation of intervention impacts.
Adaptive Use of Co‐Data Through Empirical Bayes for Bayesian Additive Regression Trees
Authors: Goedhart Jeroen M. , Klausch Thomas , Janssen Jurriaan , van de Wiel Mark A. 
Published: February 2025

ABSTRACTFor clinical prediction applications, we are often faced with small sample size data compared to the number of covariates. Such data pose problems for variable selection and prediction, especially when the covariate‐response relationship is complicated. To address these challenges, we propose to incorporate external information on the covariates into Bayesian additive regression trees (BART), a sum‐of‐trees prediction model that utilizes priors on the tree parameters to prevent overfitting. To incorporate external information, an empirical Bayes (EB) framework is developed that estimates, assisted by a model, prior covariate weights in the BART model. The proposed EB framework enables the estimation of the other prior parameters of BART as well, rendering an appealing and computationally efficient alternative to cross‐validation. We show that the method finds relevant covariates and that it improves prediction compared to default BART in simulations. If the covariate‐response relationship is non‐linear, the method benefits from the flexibility of BART to outperform regression‐based learners. Finally, the benefit of incorporating external information is shown in an application to diffuse large B‐cell lymphoma prognosis based on clinical covariates, gene mutations, DNA translocations, and DNA copy number data.
Ruthenium‐Catalyzed α‐Alkylation of Arylacetonitriles with Primary Alcohols: N‐heterocyclic Carbene‐Amine's Promotional Influence
Authors: Wei Xurui , Cai Xiuju , Huang Ming 
Published: February 2025

AbstractTransition‐metal‐catalyzed α‐alkylation of nitriles with alcohols is an environmentally benign reaction, and the development of simple and efficient catalysts for this transformation is a growing area of research. In this study, we report a serial of bidentate N‐heterocyclic carbene (NHC) ruthenium complexes with different extra donors for the α‐alkylation of nitriles with alcohols. Through adjusting extra donors and backbone of the NHC ligands, the catalytic activities of these complexes could be controlled. The ruthenium complex (Ru3) bearing an amine donor and a benzimidazolium backbone exhibited the highest catalytic activity. A large variety of α‐alkylated nitriles were obtained in 30%–88% yields, by using 1 mol% ruthenium complex (Ru3) and a catalytic amount of Cs2CO3 (20 mol%). Detailed control experiments and deuterium‐labeling experiments suggested that the reaction proceeds via borrowing hydrogen pathway.
A Sustainable Approach to Improve Properties of PVC‐CNT Nanocomposites Using Waste Eggshell as Biofiller and Heat Stabilizer
Authors: Dutta Nipu , Nath Saurav Sankar , Dutta Riku , Baishya Jurita , Borah Nupur , Maji Tarun Kumar 
Published: February 2025

AbstractBio‐based polymer nanocomposites were prepared using polyvinyl chloride, waste eggshell, and carbon nanotube via melt mixing followed by compression molding technique. The eggshell and the complex of tannic acid with calcium oxide derived from eggshell were used as biofiller and heat stabilizer respectively. Functionalized multiwalled carbon nanotube (f‐MWCNT) and epoxidized soyabean oil were employed as inforcing nanofiller and compatibilizer during the preparation of the nanocomposite. The ratio of Polymer to biofiller was maintained at 60:40 and the amount of nanofiller varied from 0 to 0.75 phr. The nanocomposites were characterized by Fourier transform infrared (FTIR) spectroscopy, X‐ray diffraction (XRD), and scanning electron microscope (SEM) study. Thermal analysis, mechanical properties, chemical resistance, and water absorption tests were also done for the nanocomposites. Nanocomposite with 0.25 phr loaded functionalized carbon nanotube showed maximum improvement in overall properties.
Enhancing Military Performance and Stress Management Through Mindfulness Training: The Role of Fronto‐Limbic Network and Sequential Mediation Analysis
Authors: Kim Jin Hyung , Kim Hakseung , Lee Seho , Kim Sung Ha , Park Sung Soo , Hong Chang Woo , Kwon Ki Tae , Lee Seung Hun , Kim Hyun‐Ji , Kim Kyoung Soo , Kim Jung Bin , Choi Hoon , Kim Dong‐Joo 
Published: February 2025

ABSTRACTMindfulness training (MT) has been shown to be effective at managing emotions and stress. However, the underlying neural mechanism of MT is yet unclear and attempts to explore the effects of MT on both psychological factors and performance outcomes remain unexplored. Physiological questionnaire, performance measures, and EEG‐based Functional connectivity (FC) in the fronto‐limbic network were analyzed in both the MT (N = 39) and control (N = 43) groups. Statistical analyses were conducted to evaluate group‐wise differences, within‐group longitudinal change, and sequential mediation effects. MT group maintained their stress coping capacity and demonstrated improved performance during the military training weeks. There was an increase in FC between the frontal and limbic regions in all frequency bands (i.e., delta, theta, alpha, and beta) in the MT group, yielding a higher FC than the control group in the final week. Furthermore, changes in these FC and changes in stress coping capacities played a sequential mediation role in the association between the MT and changes in military performance. This study demonstrated that MT was effective for military personnel under stressful conditions, in terms of managing stress coping capacity via changes in fronto‐limbic FC, and improving task performance.