bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Empirical Study on the Role of Authentic Leadership in Strategic Agile Operations, Organizational Sustainability, and Business Performance
Authors: Rauniar Rupak , Cao Ray 
Published: February 2025

Abstract
Achieving organizational agility, both strategically and operationally, has become necessary for businesses to maintain competitiveness through effective value co-creation and sustainability initiatives. This requires unwavering and continuous support from management, coupled with effective leadership. In this empirical survey study, we investigate the role of authentic leadership in strategic agile operations (SAO) and sustainability. Based on authentic leadership theory (ALT) and literature on SAO and sustainability, our research explores the intricate relationships among SAO, authentic leadership, organizational sustainability (OS), and business performance (BP). Our empirical findings indicate that in SAO, authentic leadership can exert a positive influence on enhancing sustainability and business performance. Moreover, the study reveals that authentic leadership plays a mediating role in the relationship between SAO and sustainability. The findings underscore the importance of leadership integrity and operational adaptability in navigating complex business environments and achieving sustainable success and, ultimately, business performance.
Tailoring the Reversible Phase Transition of Perovskite Nanofiber Electrodes for High-Performance and Durable Reversible Solid Oxide Cells
Authors: Yin Chaofan , Yang Jiaming , Feng Jiangyuan , Sun Yueyue , Liu Zhengrong , Wang Junkai , Cui Jiajia , Xue Zixuan , Zhang Liang , Zhou Yucun , Zhou Jun , Xu Liangfei , Wu Kai , Li Jianqiu 
Published: February 2025

Abstract
Reversible solid oxide cells (RSOCs) are capable of converting various energy resources, between electricity and chemical fuels, with high efficiency and flexibility, making them suitable for grid balancing and renewable energy consumption. However, the practical application of RSOCs is still limited by the insufficient activity and stability of the electrodes in different operating modes. Herein, a highly efficient symmetrical electrode composed of La0.3Sr0.6Ti0.1Co0.2Fe0.7O3−δ
(LSTCF) nanofibers and in situ exsolved Co3Fe7 nanoparticles is developed for boosting the performance of RSOCs. The reversible phase transition, high activity and stability of the electrode have been confirmed by a combination of experimental (e.g., transmission electron microscopy and X-ray absorption fine structure) and computational studies. Electrolyte-supported RSOCs with the symmetrical electrode demonstrate excellent catalytic activity and stability, achieving a high peak power density of 0.98 W cm−2 in the fuel cell mode using H2 as the fuel (or 0.53 W cm−2 using CH4 as the fuel) and a high current density of 1.09 A cm−2 at 1.4 V in the CO2 electrolysis mode (or 1.03 A cm−2 at 1.3 V for H2O electrolysis) at 800 °C while maintaining excellent durability for over 100 h.
A Transparent Polymer-Composite Film for Window Energy Conservation
Authors: Liu Xianhu , Zhang Haoyu , Pan Yamin , Ma Jun , Liu Chuntai , Shen Changyu 
Published: February 2025

Abstract
As living standards improve, the energy consumption for regulating indoor temperature keeps increasing. Windows, in particular, enhance indoor brightness but also lead to increased energy loss, especially in sunny weather. Developing a product that can maintain indoor brightness while reducing energy consumption is a challenge. We developed a facile, spectrally selective transparent ultrahigh-molecular-weight polyethylene composite film to address this trade-off. It is based on a blend of antimony-doped tin oxide and then spin-coated hydrophobic fumed silica, achieving a high visible light transmittance (> 70%) and high shielding rates for ultraviolet (> 90%) and near-infrared (> 70%). When applied to the acrylic window of containers and placed outside, this film can cause a 10 °C temperature drop compared to a pure polymer film. Moreover, in building energy simulations, the annual energy savings could be between 14.1% ~ 31.9% per year. The development of energy-efficient and eco-friendly transparent films is crucial for reducing energy consumption and promoting sustainability in the window environment.
Financial literacy and environmental sustainability in SMEs: process innovation as an association mechanism
Authors: Molina-García Antonio , Galache-Laza M Teresa , González-García Vicente , Diéguez-Soto Julio 
Published: February 2025

Abstract
Despite receiving little attention in academia, understanding the factors that facilitate SMEs in becoming more environmentally responsible is a crucial challenge in today’s world. This article analyses the influence of CEOs’ financial literacy on environmental sustainability in an SME environment. Based on a random sample of 318 Spanish SMEs, our results show that CEOs’ financial literacy is an important driver of environmental sustainability. Moreover, this relationship emerges entirely through process innovation. Thus, CEOs who are financially literate are more engaged in process innovations, which facilitates them to embrace more environmentally sustainable practices. These findings offer fresh evidence of the relevance of CEOs’ capabilities in preserving natural resources.
Partial transport for point-cloud registration
Authors: Bai Yiku , Tran Huy , Damelin Steven B. , Kolouri Soheil 
Published: February 2025

Abstract
Point cloud registration is an important task in fields like robotics, computer graphics, and medical imaging, involving the determination of spatial relationships between point sets in 3D space. Real-world challenges, such as non-rigid movements and partial visibility, including occlusions and sensor noise, make non-rigid registration particularly difficult. Traditional methods are often computationally intensive, exhibit unstable performance, and lack strong theoretical guarantees. Recently, the optimal transport problem, including its unbalanced variations like the optimal partial transport problem, has emerged as a powerful tool for point-cloud registration. These methods treat point clouds as empirical measures and provide a mathematically rigorous framework to quantify the correspondence between transformed source and target points. In this paper, we address the non-rigid registration problem using optimal transport theory and introduce a set of non-rigid registration methods based on the optimal partial transportation problem. Additionally, by leveraging efficient solutions to the one-dimensional optimal partial transport problem and extending them via slicing, we achieve significant computational efficiency, resulting in fast and robust registration algorithms. We validate our methods by comparing baselines on various 3D and 2D non-rigid registration problems with noisy point clouds.
An inpatient antimicrobial stewardship team driven penicillin allergy delabeling protocol for minimal and low-risk penicillin allergic patients
Authors: Shankaran Shivanjali , Adochio Emily , Petrak Robert , Goldenberg Benjamin , Herald Fischer , Lunn Christy , Hodgson Hayley , Won Sarah 
Published: February 2025

Abstract
Inappropriate penicillin allergy labeling results in suboptimal or excessive broad spectrum antibiotic use. In this multidisciplinary project, the antimicrobial stewardship team safely delabeled 71.4% of hospitalized patients approached. Similar programs may also be able to delabel minimal or low-risk penicillin allergic patients without formal allergy consultation.
Exploring context, mechanisms and outcomes in group interpersonal therapy for adolescents with depression in Nepal: a qualitative realist analysis
Authors: Atmore Katie H. , Bonell Chris , Luitel Nagendra P. , Pradhan Indira , Shrestha Pragya , Verdeli Helen , Rose-Clarke Kelly 
Published: February 2025

Abstract
Interpersonal Psychotherapy (IPT) is an evidence-based treatment for adolescent depression. However, since it does not work for all adolescents in all settings, more research on its heterogeneous effects is needed. Using a realist approach, we aimed to generate hypotheses about mechanisms and contextual contingencies in adolescent group IPT in Nepal. We analysed 26 transcripts from qualitative interviews with IPT participants aged 13–19, facilitators, supervisors and trainers. We analysed data using the Framework Method. The qualitative analytical framework was based on the VICTORE checklist, a realist tool to explore intervention complexity. Sharing, problem-solving, giving and receiving support, managing emotions and negotiating emerged as mechanisms through which adolescents improved their depression. Participants perceived that girls and older adolescents benefitted most from IPT. Girls had less family support than boys and therefore benefitted most from the group support. Older adolescents found it easier than younger ones to share problems and manage emotions. Adolescents exposed to violence and parental alcoholism struggled to overcome problems without family and school support. We formulated hypotheses on group IPT mechanisms and contextual interpersonal and school-level factors. Research is needed to test these hypotheses to better understand for whom IPT works and in what circumstances.
Helen Benedict’s Sand Queen: Female Combatants in the Iraq War
Authors: Almatwari Afrah 
Published: February 2025

Abstract
US authorities justified their invasion of Iraq, in part, by claiming to be liberating Iraqi women from patriarchal oppression. Helen Benedict’s Sand Queen challenges this assertion, exposing how the war embraced a colonial paradigm with which Iraq was long familiar. By documenting the gender-based violence a female American soldier faces from her own side, the book demonstrates contradictions in the liberation rhetoric of US authorities.
Unsteady Land‐Sea Breeze Circulations in the Presence of a Synoptic Pressure Forcing
Authors: Allouche Mohammad , Iipponen Juho , Bou‐Zeid Elie 
Published: February 2025

AbstractUnsteady land‐sea breezes (LSBs) that result from time‐varying surface temperature contrasts Δθ(t) are explored in the presence of a constant synoptic pressure forcing, Mg, oriented from sea to land (α = 0°) or land to sea (α = 180°). Large eddy simulations reveal the development of four distinctive regimes, depending on the joint interaction between Mg, α, and Δθ(t) in modulating the fine‐scale dynamics. Time lags, computed as the shifts that maximize correlation coefficients of the velocity between the unsteady and the corresponding steady scenarios at Δθ = Δθmax, are found to be significant and to extend 2 hr longer for α = 0° compared to α = 180°. These diurnal dynamics result in nonequilibrium conditions that are significantly affected by the flow history, and that behave differently over the two patches for the different α’s. Turbulence is found to be out of equilibrium with the mean flow, and the mean itself is found to be out of equilibrium with the thermal forcing. The sea surface heat flux is consistently more sensitive than its land counterpart to the time‐varying external forcing Δθ(t), and more so for synoptic forcing from land to sea (α = 180°). Hence, although the land reaches equilibrium faster, the sea patch is found to exert a stronger control on the turbulence‐mean flow equilibrium response. Finally, the vertical velocity profile at the shore and shore‐normal velocity transects at the first grid level are shown to encode the multiscale regimes of the LSBs evolution and can thus be used to identify these regimes using k‐means clustering.
Global Land‐Water Competition and Synergy Between Solar Energy and Agriculture
Authors: Curioni Maddalena , Galli Nikolas , Manzolini Giampaolo , Rulli Maria Cristina 
Published: February 2025

AbstractThe food and energy systems face mounting challenges due to increasing demands and sustainability constraints, which impact their ability to efficiently utilize natural resources, such as land and freshwater. Among these challenges, competition for land between large‐scale renewable energy production plants and agriculture poses a risk, especially for photovoltaics. Agrivoltaics offers an opportunity to synergistically use land for simultaneous production of energy and food. Recent studies have investigated the upscaling potential of agrivoltaics, moving from field scale analyses to larger‐scale suitability assessments. Yet, studies addressing the interaction between crop dynamics and local climatic factors, as well as explicitly investigating hydrological dynamics of agrivoltaics across crops and climates, are still limited. Here, we first superpose a spatial data set of existing photovoltaic farms with different land use/land cover maps to assess the magnitude of land use competition associated with photovoltaics. Then, we use a spatialized agro‐hydrological model to simulate the response to different levels of radiation attenuation of 22 non‐irrigated crops in their harvested areas across the globe. We find that 22%–35% of rainfed harvested areas globally would maintain their yields if converted to agrivoltaics, while 13%–16% of ground‐mounted photovoltaic plants globally are associated with a cropland to non‐cropland transition. While carrying the typical limitations and uncertainties of global studies, our results may offer novel possibilities for cross‐crop and cross‐location comparisons of agrivoltaic experiences, as well as a basis to have a deeper and cross‐scale understanding of the feasibility of photovoltaics.
Seismic Monitoring of Baseflow and Groundwater Changes in the Yellowstone National Park
Authors: Luo Bingxu , Zhu Hejun , Lumley David 
Published: February 2025

AbstractRelative seismic velocity changes are being increasingly used to monitor changes in groundwater. However, it remains challenging to verify its implementation in watersheds without direct groundwater well measurements. In this study, we conduct a 12‐year observation in a watershed of the Yellowstone National Park (YNP). We find that the seasonal fluctuations and long‐term trend of the measured are highly correlated with the estimated baseflow, which serves as a constraint for groundwater changes. We integrate the estimated baseflow into a poroelastic mechanism and conduct two simulations based on pressure diffusion. These simulations closely match with our observed variations. In addition, our analysis suggest that the measured is primarily influenced by hydrologic pressure diffusion rather than surface air temperature. We conclude that the baseflow analysis can further enhance the seismic monitoring of groundwater changes.
The Turbulent Pressure Spectrum Within the Roughness Sublayer of a Subarctic Forest Canopy
Authors: Aslan Toprak , Katul Gabriel G. , Aurela Mika 
Published: February 2025

AbstractThe turbulent static pressure spectrum as a function of longitudinal wavenumber in the roughness sublayer of forested canopies is of interest to a plethora of problems such as pressure transport in the turbulent kinetic energy budget, pressure pumping from snow or forest floor, and coupling between flow within and above canopies. Long term static pressure measurements above a sub‐arctic forested canopy for near‐neutral conditions during the winter and spring were collected and analyzed for three snow cover conditions: trees and ground covered with snow, trees are snow free but the ground is covered with snow, and snow free cover. In all three cases, it is shown that obeys the attached eddy hypothesis at low wavenumbers —with and Kolmogorov scaling in the inertial subrange at higher wavenumbers—with , where is the friction velocity at the canopy top, is the mean turbulent kinetic energy dissipation rate, is the distance from the snow top, and is the boundary layer depth. The implications of these two scaling laws to the normalized root‐mean squared pressure and its newly proposed logarithmic scaling with normalized wall‐normal distance are discussed for snow covered and snow free vegetation conditions. The work here also shows that the in the appears more extensive and robust than its longitudinal velocity counterpart.
1-octene polymerization catalyzed by titanium and zirconium complexes supported by [PN] or [NPN] ligands
Authors: Iwasaki Jin , Kasahara Yuzuki , Toda Tomoyuki , Takenaka Katsuhiko 
Published: February 2025

Abstract
Ligands in homogeneous complex polymerization catalysts are crucial not only for influencing polymerization activity but also for controlling the stereoselectivity of the resulting polymers. We designed ligands on the basis of the dibenzophosphole skeleton and investigated the structure and ethylene polymerization activity of titanium and zirconium complexes activated by dried modified methylaluminoxane. In this investigation, we selected 1-octene as an α-olefin monomer and polymerized it using five types of titanium and zirconium complexes. Then, we obtained information regarding the ligand structure, polymerization activity toward 1-octene, and tacticity control. The [NPN]-Zr complex, which exhibited the highest activity for ethylene polymerization, demonstrated negligible polymerization activity for 1-octene. Conversely, titanium and zirconium complexes with [PN] ligands as auxiliary ligands exhibited activity toward 1-octene, yielding isotactic-rich polyoctene.
Physics of swimming and its fitness cost determine strategies of bacterial investment in flagellar motility
Authors: Lisevich Irina , Colin Remy , Yang Hao Yuan , Ni Bin , Sourjik Victor 
Published: February 2025

Abstract
Microorganisms must distribute their limited resources among different physiological functions, including those that do not directly contribute to growth. In this study, we investigate the allocation of resources to flagellar swimming, the most prominent and biosynthetically costly of such cellular functions in bacteria. Although the growth-dependence of flagellar gene expression in peritrichously flagellated Escherichia coli is well known, the underlying physiological limitations and regulatory strategies are not fully understood. By characterizing the dependence of motile behavior on the activity of the flagellar regulon, we demonstrate that, beyond a critical number of filaments, the hydrodynamics of propulsion limits the ability of bacteria to increase their swimming by synthesizing additional flagella. In nutrient-rich conditions, E. coli apparently maximizes its motility until reaching this limit, while avoiding the excessive cost of flagella production. Conversely, during carbon-limited growth motility remains below maximal levels and inversely correlates with the growth rate. The physics of swimming may further explain the selection for bimodal resource allocation in motility at low average expression levels. Notwithstanding strain-specific variation, the expression of flagellar genes in all tested natural isolates of E. coli also falls within the same range defined by the physical limitations on swimming and its biosynthetic cost.
Diversity and pathogenicity of Fusarium species associated with Fusarium head blight in wheat and maize cropping systems in Sichuan Province
Authors: Sun Xiaofang , Yang Rui , Tang Huimin , Ma Miaomiao , Chen Huabao , Chang Xiaoli , Zhang Min , Gong Guoshu 
Published: February 2025

Abstract

Fusarium head blight (FHB) is a severe disease worldwide that leads to substantial economic losses. Wheat‒maize cropping is the dominant system in Sichuan Province, China. However, FHB has become increasingly severe in this system, and Fusarium rot disease is also becoming a severe threat to maize. To understand the composition and pathogenicity of the Fusarium species associated with FHB, samples of typical symptomatic wheat spikes were collected from wheat‒maize cropping fields in 16 administrative districts of Sichuan Province, and Fusarium perithecia were obtained from both wheat straw and maize stubble. Based on morphological and molecular identification, 175 isolates from symptomatic wheat spikes were identified as five Fusarium species: F. asiaticum, F. avenaceum, F. graminearum, F. meridionale, and F. proliferatum. Among them, F. asiaticum and F. graminearum were the dominant pathogenic species, with isolation frequencies of 75.43% and 20.57%, respectively. Additionally, 136 single-ascospore isolates from wheat straw or maize stubble were identified as F. asiaticum, F. equiseti, F. graminearum, F. meridionale, F. proliferatum, and F. temperatum. Pathogenicity assays revealed that the Fusarium strains from all sources could successfully infect wheat and maize. F. graminearum exhibited a high degree of pathogenicity towards both crops under investigation, while F. asiaticum demonstrated significantly greater pathogenicity towards wheat than maize. This work will help understand the cyclic infection caused by Fusarium species in wheat‒maize cropping systems and provide valuable data for the effectively controlling Fusarium rot disease in both wheat and maize.
Integrating D–S evidence theory and multiple deep learning frameworks for time series prediction of air quality
Authors: Feng Siling , Tang Le , Huang Mengxing , Wu Yuanyuan 
Published: February 2025

Abstract
Accurate prediction of air quality time series data is helpful to identify and warn air pollution events in advance. Although the current air quality prediction models have made some progress in improving the accuracy of prediction, due to the impact of specific pollutants or complex meteorological conditions, these models still have the problems of low prediction accuracy, robustness and generalization ability in univariate prediction. In order to solve these problems, this study proposes a framework that integrates D–S evidence theory and a variety of deep learning models. The air quality data of three representative cities with climate characteristics in China are obtained and five indicators on air pollutants are collected. The preprocessed data are divided by time length to form short-term, medium-term and long-term input data, and MLP, RNN, CNN, LSTM, BI-LSTM and GRU models are established respectively. By comparing the performance indicators of the six models, three most suitable models are selected to predict the short, medium and long-term data respectively. Taking the prediction results and reliability as the three evidence bodies of the theory, a fusion model based on D–S evidence theory is established. For the three performance indicators MAE, RMSE and MAPE of the model, the best result of the fusion model increases the performance by 7.42%, 4.25% and 12.82% compared with the sub optimal architecture. This shows that integrating D–S evidence theory and a variety of deep learning algorithms provides an effective method to accurately predict the long-term air quality level in most urban areas.