bluuebunny/crossref_metadata_2025_split huggingface dataset:
Natural selection acting on complex traits hampers the predictive accuracy of polygenic scores in ancient samples
Authors: Añorve-Garibay Valeria , Huerta-Sanchez Emilia , Sohail Mashaal , Ortega-Del Vecchyo Diego 
Published: September 2024

AbstractThe prediction of phenotypes from ancient humans has gained interest due to its potential to investigate the evolution of complex traits. These predictions are commonly performed using polygenic scores computed with DNA information from ancient humans along with genome-wide association studies (GWAS) data from present-day humans. However, numerous evolutionary processes could impact the prediction of phenotypes from ancient humans based on polygenic scores. In this work we investigate how natural selection impacts phenotypic predictions on ancient individuals using polygenic scores. We use simulations of an additive trait to analyze how natural selection impacts phenotypic predictions with polygenic scores. We simulate a trait evolving under neutrality, stabilizing selection and directional selection. We find that stabilizing and directional selection have contrasting effects on ancient phenotypic predictions. Stabilizing selection accelerates the loss of large-effect alleles contributing to trait variation. Conversely, directional selection accelerates the loss of small and large-effect alleles that drive individuals farther away from the optimal phenotypic value. These effects result in specific shared genetic variation patterns between ancient and modern populations which hamper the accuracy of polygenic scores to predict phenotypes. Furthermore, we conducted simulations that include realistic strengths of stabilizing selection and heritability estimates to show how natural selection could impact the predictive accuracy of ancient polygenic scores for two widely studied traits: height and body mass index. We emphasize the importance of considering how natural selection can decrease the reliability of ancient polygenic scores to perform phenotypic predictions on an ancient population.
Discovery of a new species of subterranean eel loach from southern India
Authors: Sreenath K.R. , Pradeep B. , Aju K. R. , Sukumaran Sandhya , Sebastian Wilson , Anto Alvin 
Published: September 2024

AbstractPangio juhuaesp nov, a new species of subterranean eel loach, is described from Kerala, India. It is distinguished from its subterranean congeners by the presence of a dorsal fin, four pectoral rays and five segmented anal fin rays. Genetic analyses suggest thatP. juhuaeis closely related toP. bhujiabut is distinct in morphology, particularly by the presence of a dorsal fin. The low genetic distance and significant morphological difference between these twoPangiospecies suggest that they have diverged from an immediate common ancestor and evolved distinct adaptations to subterranean niches.P. juhuaeexhibits less evolved troglobitic traits compared toP. bhujiaandP. pathala, suggesting it could be a connecting species in the evolutionary transition from terrestrial to subterranean loaches. This discovery provides evidence for possible subterranean speciation of fishes in underground habitats.
Kinetics of reformation of the S0state capable of progressing to the S1state after the O2release by Photosystem II
Authors: Boussac Alain , Sellés Julien , Sugiura Miwa 
Published: September 2024

AbstractThe active site for water oxidation in Photosystem II (PSII) comprises a Mn4CaO5cluster adjacent to a redox-active tyrosine residue (TyrZ). During the water-splitting process, the enzyme transitions through five sequential oxidation states (S0to S4), with O2evolution occurring during the S3TyrZ•to S0TyrZtransition. Chloride also plays a role in this mechanism. Using PSII fromThermosynechococcus vestitus, where Ca and Cl were replaced with Sr and Br to slow the S3TyrZ•to S0TyrZ+ O2transition (t1/2∼ 5 ms at room temperature), it was observed that the recovery of a S0state, defined as the state able to progress to S1, exhibits similar kinetics (t1/2∼ 5 ms). This suggests that in CaCl-PSII, the reformation of the functional S0state directly follows the S3TyrZ•to S0TyrZ+ O2transition, with no additional delay required for the insertion of a new substrate water molecule (O5) and associated protons.
A circular engineered sortase for interrogating histone H3 in chromatin
Authors: Whedon Samuel D. , Lee Kwangwoon , Wang Zhipeng A. , Zahn Emily , Lu Congcong , Yapa-Abeywardana Maheeshi , Fairall Louise , Nam Eunju , Dubois-Coyne Sarah , De Ioannes Pablo , Sheng Xinlei , Andrei Adelina , Lundberg Emily , Jiang Jennifer , Armache Karim-Jean , Zhao Yingming , Schwabe John W. R. , Wu Mingxuan , Garcia Benjamin A. , Cole Philip A. 
Published: September 2024

AbstractReversible modification of the histone H3 N-terminal tail is critical in regulating chromatin structure, gene expression, and cell states, while its dysregulation contributes to disease pathogenesis. Understanding the crosstalk between H3 tail modifications in nucleosomes constitutes a central challenge in epigenetics. Here we describe an engineered sortase transpeptidase, cW11, that displays highly favorable properties for introducing scarless H3 tails onto nucleosomes. This approach significantly accelerates the production of both symmetrically and asymmetrically modified nucleosomes. We demonstrate the utility of asymmetrically modified nucleosomes produced in this way in dissecting the impact of multiple modifications on eraser enzyme processing and molecular recognition by a reader protein. Moreover, we show that cW11 sortase is very effective at cutting and tagging histone H3 tails from endogenous histones, facilitating multiplex “cut-and-paste” middle down proteomics with tandem mass tags. This cut-and-paste proteomics approach permits the quantitative analysis of histone H3 modification crosstalk after treatment with different histone deacetylase inhibitors. We propose that these chemoenzymatic tail isolation and modification strategies made possible with cW11 sortase will broadly power epigenetics discovery and therapeutic development.
Ferrimagnetic structure in the high-pressure phase of
α−Mn
Authors: Araki Shingo , Iwamoto Kaisei , Akiba Kazuto , Kobayashi Tatsuo C. , Munakata Koji , Kaneko Koji , Osakabe Toyotaka 
Published: September 2024

The α−Mn phase exhibits a large anomalous Hall effect (AHE) in its pressure-induced weak ferromagnetic (WFM) state, despite its relatively small spontaneous magnetization of ∼0.02μB/Mn. To understand the underlying mechanism behind this AHE, we performed single crystal neutron diffraction measurements at 2.0 GPa to determine the magnetic structure of the WFM phase. Our investigation reveals a ferrimagnetic structure characterized by nearly collinear magnetic moments aligned along the [001] direction at sites I, II, III-1, and IV-1. In contrast, the small moments at sites III-2 and IV-2 lie within the (001) plane. The calculated net magnetization of this magnetic structure, (−0.08±0.10)μB/Mn atom, is in agreement with the experimentally determined spontaneous magnetization. The observation of a magnetic reflection at q=(0,0,0) satisfies a key condition for the emergence of the AHE.

Published by the American Physical Society
2024
Dynamical Correlations and Order in Magic-Angle Twisted Bilayer Graphene
Authors: Rai Gautam , Crippa Lorenzo , Călugăru Dumitru , Hu Haoyu , Paoletti Francesca , de’ Medici Luca , Georges Antoine , Bernevig B. Andrei , Valentí Roser , Sangiovanni Giorgio , Wehling Tim 
Published: September 2024

The interplay of dynamical correlations and electronic ordering is pivotal in shaping phase diagrams of correlated quantum materials. In magic-angle twisted bilayer graphene, transport, thermodynamic, and spectroscopic experiments pinpoint a competition between distinct low-energy states with and without electronic order, as well as between localized and delocalized charge carriers. In this study, we utilize dynamical mean-field theory on the topological heavy fermion model of twisted bilayer graphene to investigate the emergence of electronic correlations and long-range order in the absence of strain. We contrast moment formation, Kondo screening, and ordering on a temperature basis and explain the nature of emergent correlated states based on three central phenomena: (i) the formation of local spin and valley isospin moments around 100 K, (ii) the ordering of the local isospin moments around 10 K preempting Kondo screening, and (iii) a cascadic redistribution of charge between localized and delocalized electronic states upon doping. At integer fillings, we find that low-energy spectral weight is depleted in the symmetric phase, while we find insulating states with gaps enhanced by exchange coupling in the zero-strain ordered phases. Doping away from integer filling results in distinct metallic states: a “bad metal” above the ordering temperature, where scattering off the disordered local moments suppresses electronic coherence, and a “good metal” in the ordered states with coherence of quasiparticles facilitated by isospin order. This finding reveals coherence from order as the microscopic mechanism behind the Pomeranchuk effect observed experimentally by Rozen [] and by Saito []. Upon doping, there is a periodic charge reshuffling between localized and delocalized electronic orbitals leading to cascades of doping-induced Lifshitz transitions, local spectral weight redistributions, and periodic variations of the electronic compressibility ranging from nearly incompressible to negative. Our findings highlight the essential role of charge transfer, hybridization, and ordering in shaping the electronic excitations and thermodynamic properties in twisted bilayer graphene and provide a unified understanding of the most puzzling aspects of scanning tunneling spectroscopy, transport, and compressibility experiments.

Published by the American Physical Society
2024
Overcoming organizational politics and unlocking meaningful work through ethical leadership
Authors: Mosquera Pilar , Tigre Fernanda Bethlem , Alegre Miriam 
Published: September 2024

Purpose
New generations actively seek employment in organizations that resonate with their values, mission and sense of purpose. However, perceptions of organizational politics (POP) associated with unethical practices detrimentally affects meaningful work experiences and employee retention. Ethical leadership emerges as a critical factor in mitigating these negative effects. This study aims to propose a comprehensive model that examines the impact of ethical leadership on two crucial work outcomes: meaningful work and turnover intention. The mediating role of POP is explored, shedding light on the intricate dynamics within organizational contexts.

Design/methodology/approach
To test the model, the authors use a sample of 261 respondents who completed an online questionnaire shared on social networks. Partial least squares is used for data analysis.

Findings
Results evidence that ethical leadership reduces employees’ POP, increases meaningful work and reduces turnover intention. One dimension of POP – communication – mediates the relationship between ethical leadership and work outcomes. Furthermore, meaningful work mediates the relationship between ethical leadership and turnover intention.

Practical implications
The study offers practical suggestions for managers to mitigate the negative impact of POP on meaningful work and employee retention.

Originality/value
This study adds to previous research by analyzing the separate and combined effects of ethical leadership on five dimensions of POP – communication, resources, decisions, reputation and relationships. Furthermore, this study adds empirical evidence on how POP influence meaningful work and employee retention.
Learning organization culture and knowledge sharing: the mediating role of social capital
Authors: Lee Sumi , Han Seung-hyun 
Published: September 2024

Purpose
This study aims to examine the underlying process through which learning organization culture positively influences knowledge sharing. It specifically explored the mediating role of social capital, underscoring its critical impact on enhancing both knowledge sharing and fostering learning organization culture.

Design/methodology/approach
To test the proposed hypotheses, structural equation modeling (SEM) analysis was conducted with a sample of 231 employees from a manufacturing firm in South Korea.

Findings
The results of this study indicate significant direct effects of learning organization culture on social capital. Also, social capital indicates a positive effect on knowledge sharing. Although learning organization culture had no direct effect on knowledge sharing, it indirectly affected learning organization culture and knowledge sharing by mediating social capital.

Practical implications
This study proposes that a learning organization culture will be interconnected with social capital and knowledge sharing. Organizations that can effectively harness the wealth of knowledge unlocked by social capital, and subsequently integrate this knowledge into their activities, are poised for competitive advantage.

Originality/value
First, this study places a special emphasis on the mediating role of social capital between learning organization culture and knowledge sharing. Despite extensive research exploring diverse knowledge-sharing factors (Wang and Noe, 2010), it is plausible that examining social capital as a mediator could offer insights for facilitating knowledge sharing through its structural, relational and cognitive dimensions. Second, while a plethora of literature examines knowledge sharing, this study also seeks to unravel the multifaceted pathways through which the learning organization culture influences knowledge sharing and how these processes could be optimized in organizations.
Hybrid price prediction method combining TCN-BiGRU and attention mechanism for battery-grade lithium carbonate
Authors: Peng Zhanglin , Yin Tianci , Zhu Xuhui , Lu Xiaonong , Li Xiaoyu 
Published: September 2024

PurposeTo predict the price of battery-grade lithium carbonate accurately and provide proper guidance to investors, a method called MFTBGAM is proposed in this study. This method integrates textual and numerical information using TCN-BiGRU–Attention.Design/methodology/approachThe Word2Vec model is initially employed to process the gathered textual data concerning battery-grade lithium carbonate. Subsequently, a dual-channel text-numerical extraction model, integrating TCN and BiGRU, is constructed to extract textual and numerical features separately. Following this, the attention mechanism is applied to extract fusion features from the textual and numerical data. Finally, the market price prediction results for battery-grade lithium carbonate are calculated and outputted using the fully connected layer.FindingsExperiments in this study are carried out using datasets consisting of news and investor commentary. The findings reveal that the MFTBGAM model exhibits superior performance compared to alternative models, showing its efficacy in precisely forecasting the future market price of battery-grade lithium carbonate.Research limitations/implicationsThe dataset analyzed in this study spans from 2020 to 2023, and thus, the forecast results are specifically relevant to this timeframe. Altering the sample data would necessitate repetition of the experimental process, resulting in different outcomes. Furthermore, recognizing that raw data might include noise and irrelevant information, future endeavors will explore efficient data preprocessing techniques to mitigate such issues, thereby enhancing the model’s predictive capabilities in long-term forecasting tasks.Social implicationsThe price prediction model serves as a valuable tool for investors in the battery-grade lithium carbonate industry, facilitating informed investment decisions. By using the results of price prediction, investors can discern opportune moments for investment. Moreover, this study utilizes two distinct types of text information – news and investor comments – as independent sources of textual data input. This approach provides investors with a more precise and comprehensive understanding of market dynamics.Originality/valueWe propose a novel price prediction method based on TCN-BiGRU Attention for “text-numerical” information fusion. We separately use two types of textual information, news and investor comments, for prediction to enhance the model's effectiveness and generalization ability. Additionally, we utilize news datasets including both titles and content to improve the accuracy of battery-grade lithium carbonate market price predictions.
Revenue management method and critical techniques of railway passenger transport
Authors: Shan Xinghua , Lv Xiaoyan , Wu Jinfei , Zhao Shuo , Zhang Junfeng 
Published: September 2024

PurposeRevenue management (RM) is a significant technique to improve revenue with limited resources. With the macro environment of dramatically increasing transit capacity and rapid railway transport development in China, it is necessary to involve the theory of RM into the operation and decision of railway passenger transport.Design/methodology/approachThis paper proposes the theory and framework of generalized RM of railway passenger transport (RMRPT), and the thoughts and methods of the main techniques in RMRPT, involving demand forecasting, line planning, inventory control, pricing strategies and information systems, are all studied and elaborated. The involved methods and techniques provide a sequential process to help with the decision-making for each stage of RMRPT. The corresponding techniques are integrated into the information system to support practical businesses in railway passenger transport.FindingsThe combination of the whole techniques devotes to railway benefit improvement and transit resource utilization and has been applied into the practical operation and organization of railway passenger transport.Originality/valueThe development of RMRPT would provide theoretical and technical support for the improvement of service quality as well as railway benefits and efficiency.
Soil seedbanks are shaped by the timing of fires in a Mediterranean‐type ecosystem
Authors: Plumanns Pouton Ella , Kasel Sabine , Penman Trent D. , Swan Matthew , Kelly Luke T. 
Published: September 2024

Abstract

Many plants rely on soil seedbanks to persist in fire‐prone ecosystems. However, knowledge of plant responses to fire is largely based on above‐ground dynamics. Quantifying how fire influences the seedbank of a diverse range of species will improve fire management.

Here, we aim to understand how the timing of fires influences species occurrence in the soil seedbank, and how this relates to species traits, in a Mediterranean‐type ecosystem. We sampled the soil seedbank across 57 sites that represent a range of fire frequencies (1–9 fires in 81 years) and time since fire (1–81 years). Through a 15‐month germination experiment, we identified 39,701 germinates from 245 plant species. Using nonlinear models, we quantified the responses of 75 species' soil seedbanks to fire history and compared these to above‐ground responses.

Fire influenced species' soil seedbanks according to seed longevity and species' life‐history traits. We observed a response of 15 species' seedbanks to time since fire: All were species with long‐lived seed, including eight annuals, five resprouters and an obligate seeder. Similarly, we observed a response of 17 species' seedbanks to fire frequency, 16 of which had long‐lived seed. Extensive periods without fire (>40 years) increase seedbank availability for annuals that form a long‐lived seedbank, and frequent fire (every ≤15 years) depletes it. We did not detect a consistent influence of fire on species from several other functional types. Many (53%) species found in the soil seedbank were not found in the above‐ground vegetation, and seven of the 22 modelled displayed an above‐ground influence of fire.

Synthesis and applications: Fire frequency influences the probability of species occurrence in the soil seedbank. Frequent fire depletes seed availability of species that depend on long‐lived soil seedbanks for persistence. Yet, other species, including perennials with short‐lived seed storage, appear to be resilient to the frequency of fires experienced to date. We suggest fire management should aim to generate variation in fire frequencies within the landscape, including areas of low fire frequency, tailored to maintain rich plant diversity within the soil seedbank.
Knowledge brokering for public sector reform
Authors: Cuffe Honae 
Published: September 2024

AbstractBetter use of evidence is at the centre of the ambitious Australian Public Sector Reform agenda, providing an authorising environment in which to test new ideas, tools, and approaches to bridge the research–practice gap. As the interlocutors between research and practice, knowledge brokers have a critical role to play in promoting the structural and behavioural changes necessary to build the knowledge networks and new capabilities that enable an evidence ecosystem. In particular, this article makes a case for harnessing the relational nature of knowledge brokering and trialling new mechanisms for research–practitioner collaboration and evidence innovation. It is hoped that this article can serve as the foundation for a future research and practice agenda examining how knowledge brokering operates and where university‐produced research can best support evidence‐based reform.Points for practitioners
As the interlocutors between research and practice, knowledge brokers can encourage the cross‐boundary thinking, genuine partnerships, and new capabilities to support evidence‐based reform.
The Australian Public Sector Reform agenda provides a unique opportunity to trial new mechanisms and approaches to expand understanding of how knowledge brokering operates in practice and the conditions that support successful research–practice collaboration.
Mechanisms should be formal and accompanied by bureaucratic‐level support and incentives, providing them with the legitimacy needed to embed new mindsets, capabilities, and ways of working.
A key consideration for public sector practitioners is how to establish arrangements and incentives that are mutually beneficial for researchers and practitioners alike and monitor the effectiveness of these initiatives over time.
Evaluating cardiac risks of TASER: An in‐depth case study through probable current analysis
Authors: Seo Hojeong , Park Saehan , Kim Sanghee , Lee Sookyoung , Choi Changho 
Published: September 2024

AbstractThis study investigates the cardiac safety concerns related to TASER discharges centering on a pivotal case that marked the first TASER‐related fatality in South Korea. Employing Pratt et al.'s theoretical framework, the research evaluates the potential for ventricular fibrillation (VF) from these discharges. The methodology incorporated a high‐resolution waveform analysis using sophisticated equipment and considered specific incident details, including dart impact locations verified through a forensic examination. A human body impedance of 500 Ω, chosen based on empirical studies and coupled with non‐inductive resistance for high‐voltage handling, was utilized in the model. By applying a heart‐current factor from IEC 60479 standards, the study found a VF risk of up to 5% depending on the impact location and current pathways. In this specific case, although the calculated risk did not exceed critical thresholds, the VF risk was high enough to suggest that TASER discharges played a role in the fatal outcome. This study underscores the importance of dart impact location in TASER safety evaluations, contributing to a broader understanding of TASER cardiac risks and providing a basis to advocate for rigorous safety protocols.