bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Roles of Relational Leadership and Employee Satisfaction in the Linkage Between Social Capital and Employee Turnover: A Moderated‐Mediation Analysis
Authors: Aditchere James , Angmortey R. 
Published: February 2025

ABSTRACTContrary to the prevailing assumption that social capital inherently fosters job satisfaction within work environments, this study posits that the formation of social groups and interpersonal ties may, in fact, lead to workplace isolation for employees whose belief systems and values diverge from those of dominant social groups. This isolation creates a hostile and unaccommodating environment which dampens work spirit, heightens emotional and psychological exhaustion, and engenders high levels of turnover intentions among workers. In addressing this challenge, the study proposes relational leadership as a crucial management approach that creates a conducive environments where open communication, trust, and collaboration can flourish. The study tests these assumptions on 153 responses from employees working within public and private legal firms in sub‐Saharan Africa–Ghana drawing on the tenets of the social capital theory and the theory of reasoned action. The data were analyzed using OLS regression in SPSS and found that social capital positively influences employee satisfaction. Additionally, relational leadership is found not to condition the relationship between social capital and employee satisfaction. Interestingly, employee satisfaction is found to fully mediate the social capital–employee turnover intention relationship. Theoretical and managerial implications of the study are presented in the latter section of the document, as well as avenues for future research.
GLP‐1RA‐induced delays in gastrointestinal motility: Predicted effects on coadministered drug absorption by PBPK analysis
Authors: Hooper Levi , Liu Shuhan , Pai Manjunath P. 
Published: February 2025

AbstractBackgroundGlucagon‐like peptide‐1 receptor agonists (GLP‐1RAs) are breakthrough medicines for obesity treatment and have rapidly gained widespread clinical application. Although GLP‐1RAs are generally not associated with drug–drug interactions (DDIs) via drug metabolism or transporter pathways, their effects on reduced gastrointestinal (GI) motility could influence the pharmacokinetics of coadministered oral medications.ObjectivesThis study uses physiologically based pharmacokinetic (PBPK) modeling to evaluate the DDI potential of GLP‐1RA‐induced GI motility delays.MethodsUsing Certara's Simcyp™ Simulator V23, we modeled the pharmacokinetics of atorvastatin, metformin, metoprolol, ethinyl estradiol, and digoxin in a virtual cohort of obese adults (n = 1000). GLP‐1RA‐related gastric emptying delays were simulated based on capsule endoscopy data from liraglutide‐treated patients. Results were compared with clinical data from semaglutide and liraglutide users. Additionally, exploratory analyses were conducted on frequently coadministered drugs identified from the 2022 Medical Expenditure Panel Survey, including rosuvastatin and dabigatran.ResultsGLP‐1RA‐induced gastric emptying delays led to increased area under the concentration–time curve (AUC) and prolonged time to maximum concentration (Tmax) for several medications. The model outputs for rosuvastatin, valsartan, and dabigatran indicate increases in AUC by 64%, 90%, and 205%, respectively. Dabigatran, a narrow therapeutic index anticoagulant, exhibited the most significant changes, raising potential concerns of higher drug exposure.ConclusionsPBPK modeling suggests that GLP‐1RAs can influence the pharmacokinetics of oral medications by delaying gastric emptying, potentially leading to clinically relevant DDIs. While further clinical validation and pharmacovigilance is needed, these findings highlight the importance of PBPK tools in predicting and potentially mitigating risks associated with GLP‐1RA use.
Relative Efficacy, Effectiveness and Safety of Newer and/or Enhanced Seasonal Influenza Vaccines for the Prevention of Laboratory‐Confirmed Influenza in Individuals Aged 18 years and Over: Update of a Systematic Review
Authors: Askar Mona , Ali Karam Adel , Batke Madeleine , Brugger Timo , Falman Annika , Robertson Anna Hayman , Pérez Jaime Jesús , Johansen Kari , de Jonge Jorgen , Krause Tyra Grove , Külper‐Schiek Wiebe , Meerpohl Joerg J. , Melidou Angeliki , Nohynek Hanna , Olmedo Carmen , Olsson Kate , Pavlopoulou Ioanna , Piechotta Vanessa , Rubin Johanna , Schlaberg Johanna , Schmucker Christine , Siemens Waldemar , Stratil Jan , Učakar Veronika , Wichmann Ole , Harder Thomas 
Published: February 2025

ABSTRACTWe performed an update (last search: 24 July 2023) of a systematic review on relative efficacy/effectiveness (rVE) and safety of newer/enhanced seasonal influenza vaccines in comparison with standard influenza vaccine or in head‐to‐head comparison. Eligible studies investigated adults aged ≥ 18 years, analysed the MF59‐adjuvanted or high‐dose or cell‐based or recombinant or mRNA‐based influenza vaccine and reported rVE or safety in randomised controlled trials (RCT) or non‐randomised studies of interventions (NRSI). Of 1561 new entries identified, 17 studies were included. Together with 42 studies identified in the previous primary review they added up to 59 studies, all comparing newer/enhanced with standard seasonal influenza vaccines. Relative VE against laboratory‐confirmed influenza was −30% (95%CI: −146% to 31%) to 88% (51%–100%; 7 NRSI) for the MF59‐adjuvanted vaccine (low certainty of evidence, CoE); 24.2% (9.7%–36.5%; 1 RCT) and −9% (−158% to 54%) to 19% (−27% to 48%; 1 NRSI) for the high‐dose vaccine (moderate CoE); −5.8% (−36.1% to 17.7%) to 21.4% (−7.3% to 42.4%; 2 NRSI) for the cell‐based vaccine (low CoE); 30% (10%–47%; 1 RCT) and 3% (−31% to 28%) to 19% (−27% to 48%; 1 NRSI) for the recombinant vaccine (moderate CoE), respectively. Relative VE against laboratory‐confirmed influenza‐related hospitalisation was 59.2% (14.6%–80.5%; 1 NRSI) for the MF59‐adjuvanted (moderate CoE); 27% (−1 to 48%; 1 NRSI) for the high‐dose (low CoE); 8.5% (−75.9% to 52.3%; 1 NRSI) for the cell‐based (low CoE); −7.3% (−52.1% to 24.4%) to 16.3% (−8.7% to 35.5%; 1 RCT) for the recombinant vaccine. No increased risk of serious adverse events was detected for any vaccine (12 RCT, 7 NRSI; low CoE). While all have a favourable safety profile, evidence on rVE of newer/enhanced vaccines is still limited, warranting further studies.
The case for static range nitrogen management in Idaho sugarbeet production
Authors: Tarkalson David D. , Olsen Davey , Bjorneberg David L. , Rogers Christopher W. 
Published: February 2025

AbstractNitrogen (N) management is important in sugarbeet production because it affects yield and quality. As Idaho sugarbeet yields continued to increase over the preceding decades, crop response data suggested that the established and utilized yield goal N management (YGNM) method for determining N requirements was leading to the overapplication of N fertilizer. This paper evaluates N supply effects on sugarbeet yields from 26 research site‐years from 2005 to 2021. The use of an alternate static range N management (SRNM) approach was compared to the historically used YGNM approach. Data from 1977 to 2021 show that the N supply needed to produce maximum yields is within a narrow range. For N responsive sites, the N supply range required to produce maximum root and sucrose yields was 202–222 kg N ha−1. Our analysis shows that over time the YGNM approach has increasingly over recommended N supply. At the 12 N responsive site‐years, the YGNM N recommendations supplied an average of 61 kg N ha−1 more than needed to maximize yield. Over 80% of fields in the Amalgamated Sugar Company growing area are oversupplying N relative to the SRNM range. Data suggest N supply affects sugarbeet quality factors to a lesser degree than historically thought. Nitrogen supply did not affect root yields in 14 of the 26 site‐years, likely a result of high in‐season N mineralization and other microbiome effects. We recommend that SRNM (200–225 kg N ha−1) replace YGNM for sugarbeet production in Idaho.
Organic Representation as a Critical Media Approach to Leadership Studies in Popular Culture
Authors: Sarkissian Raffi 
Published: February 2025

ABSTRACTThis article applies the critical media concept of organic representation to leadership studies as an analytic of how various creators in popular culture today are not just writing inclusive storytelling but, more notably, modeling new modes of production and self‐presentation that are actively challenging hegemonic industry practices and larger cultural ideologies around power, equity, leadership, and success. In conversation with leadership for liberation (see Patterson‐Stephens et al. in this issue), I employ an interdisciplinary approach that bridges critical leadership models with critical media analysis to place their aligned perspectives in direct conversation with one another. In pursuant of adding critical media analysis to the leadership studies toolkit, this article applies organic representation to an original analysis of the television series Reservation Dogs and advocates for a critical interrogation of media storytelling, production, and distribution to better understand represented communities also as stakeholders in pop culture narratives.
Yeast Genome Mutagenesis With Multi‐Mismatch PCR: A Rapid and Efficient Strategy for Site‐Directed Mutagenesis in Saccharomyces cerevisiae
Authors: Cao Shuaihua , Ding Yixin , Li Mingtao , You Xiaoyu , Xu Jingfei , Mei Kunrong 
Published: February 2025

ABSTRACTSaccharomyces cerevisiae (S. cerevisiae) provides an array of cost‐effective and time‐efficient methods for diverse genome modifications. Among these techniques, site‐directed mutagenesis of target genes is a powerful strategy to elucidate intricate structure–function relationships and create specific mutations. While various PCR‐based and CRISPR/Cas9‐based methods have been developed for introducing point mutations into the S. cerevisiae genome, they often involve multiple steps. In this study, we presented a rapid and effective site‐directed mutagenesis strategy using one‐step multi‐mismatch PCR, termed Yeast Genome Mutagenesis with Multi‐mismatch PCR (YGMMP). YGMMP incorporated multiple synonymous mutations proximal to the target point mutations, along with a selection marker cassette and flanking homologous sequences, into the gene segment spanning from the desired mutation to the gene's terminus through overlap PCR. The resulting PCR product was introduced into yeast cells to facilitate the selection of target variants. As a proof of concept, we applied YGMMP to generate an ADE2 mutant. The results demonstrated that the introduction of five and nine synonymous mutations, in addition to the desired single‐point mutation, yielded mutagenesis efficiencies of approximately 20% and 30%, respectively. This rapid, straightforward, and efficient method has the potential to greatly simplify site‐specific modifications within the S. cerevisiae genome.
An Adversarial Attack Method for Multivariate Time Series Classification Based on AdvGAN
Authors: Wang Yubo , He Hui , Zhang Peng , Ma Yuanchi , Lei Zhongxiang , Niu Zhendong 
Published: February 2025

Abstract
Considering the complexity of time series data and real-world applications, multivariate time series classification models are vulnerable to adversarial attacks. Although existing white-box attack strategies have made progress in generating adversarial samples, they rely on access to the target model’s parameters, training data, and gradients. Therefore, we apply AdvGAN framework for multivariate time series classification. AdvGAN is designed as a framework based on Generative Adversarial Networks (GANs), encompassing a generator, discriminator. The generator creates multivariate perturbations, and the perturbations combine with original data to form adversarial samples. The discriminator assesses the authenticity of these samples. These samples are then used to evaluate the security of the target model. We conducts experiments across three University of East Anglia (UEA) and University of California Riverside (UCR) datasets, employing the Multivariate Long Short Term Memory Fully Convolutional Network (MLSTM_FCN) as the target model for adversarial attack testing. The results indicate that our designed attack method effectively enhances the success rate of adversarial attacks while maintaining a similar level of Mean Squared Error (MSE) between the generated adversarial samples and the original samples.
EffiNet: An Efficient, Low-Complexity Neural Network for Monocular Depth Estimation on Embedded Devices
Authors: Tu Xiaohan , Zhang Chuanhao , Zhuang Haiyan , Sang Zhen , Liu Mengran 
Published: February 2025

Abstract
Monocular Depth Estimation (MDE) plays an important role in many fields. However, current MDE requires complex models that are computationally intensive and unsuitable for real-time applications. Some MDE methods also have a high memory access frequency (MAF), leading to substantial data transfer demands. This paper presents EffiNet, a novel network structure designed for MDE. We emphasize high performance and lightweight computing. EffiNet significantly reduces computational complexity while maintaining accurate depth estimation by utilizing MobileNetV2 as the backbone for the encoder. The newly designed decoding algorithm optimizes the model by implementing block processing strategies, efficient upsampling, and point convolution operations. The decoder enhances performance under various scene conditions while keeping computational costs low. This approach also minimizes MAF, thereby reducing data transmission requirements and improving execution speed and energy efficiency. Experimental results demonstrate that EffiNet achieves a reduction in inference time by at least 18.18% on Jetson Nano and 24.39% on Jetson TX2, and a maximum 96.07% reduction in computational complexity (FLOPs), compared to existing methods. Additionally, the accuracy index

$$\delta _1$$

δ
1

shows an improvement of 0.44% to 65.70%. These results validate the superior performance and suitability of resource-constrained mobile and edge computing devices. These advancements position EffiNet as an innovative solution in the field of MDE, capable of delivering high efficiency and reducing resource consumption.
A Review on the Large Language Model Augmented Knowledge Graph Question Answer: Task, Model, Advance and Outlook
Authors: Yu Rongdong , Wang Dou , Jia Xiaoyan , Jiang Zhifeng , Zhang Zhenwei 
Published: February 2025

Abstract
The development of Large Language Models (LLMs) has sparked a new wave in the domain of knowledge engineering. To gain deeper insights into the transformations catalyzed by LLMs to the field of Knowledge Graphs, this paper conducted a research around Knowledge Graph Question Answer (KGQA) task, and summarized the application forms of LLMs in KGQA task as well as the performance enhancement they brought. First, the paper provided a concise and comprehensive introduction to the KGQA task, focusing on its definition, methods, datasets, and evaluation metrics. Then the application of LLMs in KGQA task was discussed. Next, using three typical KGQA datasets as references, the accuracy improvement of LLM-augmented KGQA methods was visually demonstrated. From the comparison of results, it could be found that using LLM as a module in the general framework of KGQA methods could effectively improve the accuracy of the answers. Moreover, with the advancement of technology, LLMs were expected to be break away from the general framework of KGQA methods and directly answer the KGQA questions in zero-shot scenarios. Finally, this paper provides an outlook on the challenges that exist when LLMs applied to KGQA task.
Digital Twin for Power Load Forecasting
Authors: Wang Zhijun , Cong Riyu , Wang Ruihong , Wang Zhihui 
Published: February 2025

Abstract
In this work, a novel Digital Twin model using attention mechanism integrated with LSTM to forecast the future power load of a specific user is developed. The power load prediction research is done in detail by taking into account important factors such as temperature, humidity, and the price of electricity. Therefore, LSTM networks are adopted for deep learning of the historical power load data, while the attention mechanism is used to assign weights to the significance of various factors that affect the power load and make better predictions of the future power load. The results of the presented experiment show the improved prediction accuracy and stability of the model in comparison with the existing power load prediction models. The present study also introduces a new and effective method for the power load forecasting.
Application of Quality Function Deployment in Assessing Unmanned Assault Capabilities for Mountain Counter-Terrorism Operations
Authors: Yang Jianrong , Li Qixiang , Zhang Shubing 
Published: February 2025

Abstract
Employing the Quality Function Deployment (QFD) method, this study systematically analyzes the assault capabilities required of unmanned equipment in mountain counter-terrorism operations.The complex requirements of counter-terrorism missions were transformed into specific equipment capability requirements, and the main tactical indicators that should be possessed in unmanned equipment assault in mountain counter-terrorism were clarified. This method helps researchers to more accurately grasp the essence of anti-terrorism tasks and ensure that the equipment developed can meet the needs of actual combat.
Lipidomic insights on abdominal aortic aneurysm and peripheral arterial disease
Authors: Ferreira Helena Beatriz , Trindade Fábio , Nogueira-Ferreira Rita , Leite-Moreira Adelino , Ferreira Rita , Dias-Neto Marina , Domingues M. Rosário 
Published: February 2025

Abstract
Abdominal aortic aneurysm (AAA) and peripheral arterial disease (PAD) are two cardiovascular diseases associated with considerable morbidity, mortality and quality of life impairment. As they are multifactorial diseases, several factors contribute to their pathogenesis, including oxidative stress and lipid peroxidation, and these may have key roles in the development of these pathologies. Alterations of the lipid metabolism and lipid profile have been reported in cardiovascular diseases but to a lesser extent in AAA and PAD. Modifications in the profile of some molecular lipid species, in particular, native phospholipid and triglyceride species were mainly reported for AAA, while alterations in the fatty acid profile were noticed in the case of PAD. Oxidized phospholipids were also reported for AAA. Although AAA and PAD have a common atherosclerotic root, lipidomics demonstrates the existence of distinct lipid. Lipidomic research regarding AAA and PAD is still scarce and should be set in motion to increase the knowledge on the lipid changes that occur in these diseases, contributing not only to the discovery of new biomarkers for diagnosis and prognosis assessment but also to tailor precision medicine in the clinical field.
Design, fabrication, and characterization of dual-wavelength inhibited-coupling guiding hollow-core fibers
Authors: Chen Bowen , Kühlthau Tim , Kleem Götz , Graf Thomas , Abdou Ahmed Marwan 
Published: February 2025

Abstract
The present paper reports on the design, fabrication, and characterization of an 8-tube inhibited-coupling guiding hollow-core photonic crystal fiber (IC-HCPCF) capable of guiding both the beam emitted from an Yb:YAG laser at the fundamental wavelength of

$$\lambda =1030 \text{nm}$$

λ
=
1030
nm

and its second harmonic at

$$\lambda =515 \text{nm}$$

λ
=
515
nm

. By controlling the strut thickness of the glass capillaries to approximately

$$362 \text{nm}$$

362
nm

, the transmission of laser radiation at both wavelengths was possible with low losses. Optimizing the outer diameter of the glass capillaries mitigates the bending-induced increase of the confinement loss at the wavelength of

$$515 \text{nm}$$

515
nm

without compromising the optical performance of the fiber at the wavelength of

$$1030 \text{nm}$$

1030
nm

. Experimental results confirm the near to diffraction-limited beam quality

$$\left({M}^{2}<1.15\right)$$

M

2

<
1.15

of the laser beams exiting the fiber at both operational wavelengths. Operating in the first transmission band at the wavelength of

$$1030 \text{nm}$$

1030
nm

, the calculated chromatic dispersion is

$$1.02 \text{ps}/(\text{nm}\bullet \text{km})$$

1.02
ps
/
(
nm
∙
km
)

, despite a diameter of the hollow core of

$$40 \mu \text{m}$$

40
μ
m

. At the wavelength of

$$515 \text{nm}$$

515
nm

this value amounts to

$$0.62 \text{ps}/(\text{nm}\bullet \text{km})$$

0.62
ps
/
(
nm
∙
km
)

. The measured losses are

$$27.5\pm 0.3 \text{dB}/\text{km}$$

27.5
±
0.3
dB
/
km

at the wavelength of

$$515\text{ nm}$$

515

nm

and

$$25.7\pm 0.7 \text{dB}/\text{km}$$

25.7
±
0.7
dB
/
km

at the wavelength of

$$1030\text{ nm}$$

1030

nm

, which is comparable to the loss of state-of-the-art IC-HCPCFs with tubular cladding structures. The measured bending-induced increase of the confinement losses confirms the potential of the proposed approach for flexible, low-loss guiding of ultrashort laser pulses at the two wavelengths using a single fiber. This gained flexibility can significantly enhance the options for wavelength selection in laser material processing applications.
Assessing the influence of bias correction of boundary conditions, spectral nudging and model parameterisation on model errors and climate change signals for regional climate model simulations
Authors: Wamahiu Karuru , Kala Jatin , Evans Jason 
Published: February 2025

Abstract
Some of the most important considerations when undertaking dynamical downscaling of global climate models (GCMs) using regional climate models are the choice of model physical parameterisations, the use of spectral nudging, and whether to bias correct the driving GCMs prior to downscaling. While each of these factors have been extensively examined, very few studies have compared the effect of all 3 on model biases against independent observations during the historical period, as well as the change in future climate. We carry out this analysis and focus on the CORDEX-Australasia domain with all simulations driven using a common GCM. We found that the choice of model parameterisaton schemes had by far the largest influence on model biases and the change in climate, especially for precipitation during summer. While bias correction reduced large systematic biases for some variables in some regions, it also increased biases elsewhere, and results were not consistent for all variables. Our results show that it is important to first assess the performance of non-corrected GCM-driven simulations against the reference re-analysis driven simulations, as bias correction may not be necessary if the GCM-driven simulation already performs well compared to the reference simulation. Spectral nudging had a limited influence on both model biases and the change in climate, except for summer precipitation in the tropics. While we only use a single RCM and a single GCM, our key finding is that given limited computational and data resources, regional climate modelling groups should prioritize a multi-physics ensemble of the RCM to better account for internal physics-driven variability, over the use of bias-correction or spectral nudging.