bluuebunny/crossref_metadata_2025_split huggingface dataset:
Switchable client specificity in a dual functional chaperone coordinates light harvesting complex biogenesis
Authors: Siegel Alex R. , Kroon Gerard , Wright Peter E. , Shan Shu-ou 
Published: November 2024

AbstractThe proper assembly of light harvesting complexes (LHCs) is critical for photosynthesis and requires the biogenesis of light-harvesting chlorophyll a,b-binding proteins (LHCPs) to be coordinated with the biosynthesis of chlorophylls (Chl). The mechanism underlying this coordination is not well understood. Here we show that a conserved molecular chaperone in chloroplasts, cpSRP43, provides a molecular thermostat that helps maintain this coordination. cpSRP43 undergoes a conformational rearrangement between a well-foldedclosedstate and a partially disorderedopenstate.ClosedcpSRP43 is dedicated to thede novobiogenesis of LHCPs, whereasopencpSRP43 protects multiple Chl biosynthesis enzymes from heat-induced destabilization. Rising temperature shifts cpSRP43 to theopenstate and thus enables it to protect Chl biosynthesis enzymes that are heat-destabilized. Our results reveal the molecular basis of a post-translational mechanism for the thermo-adaptation of LHC biogenesis. They also demonstrate how an ATP-independent chaperone uses conformational dynamics to switch its activity and client selectivity, thereby adapting to different proteostatic demands under shifting environmental conditions.TeaserA thermo-switchable molecular chaperone helps coordinate light harvesting complex assembly during photosynthesis.
Exploring the Neural Basis and Validity of Ordinal Emotion Representation through EEG
Authors: Chen Xuyang , Xu Xin , Zhang Dan , Liu Quanying , Shen Xinke 
Published: November 2024

AbstractAccurately measuring emotion is a major challenge in advancing the understanding of human emotion and developing emotional artificial intelligence. In many existing studies, participants’ emotional ratings in interval scales are considered the true reflection of their emotional experiences. However, recent research suggests that ordinal annotations of emotions can more accurately capture the emotional expression process, providing a potential method for more precise emotion measurement. However, our understanding of the characteristics and validity of this new form of emotion representation is still relatively lacking. In particular, there is a lack of research using neural signals to explore the validity and neural basis of ordinal emotion representation. In this study, we used a video-elicited EEG dataset (n = 123) to identify the neural basis of ordinal emotion representation and demonstrate its validity from a neural perspective. Furthermore, we explored various characteristics of ordinal emotion representation, showing how it is superior to the interval form. First, we conducted inter-situation representational similarity analysis (RSA) and inter-subject RSA to test the degree to which ordinal representation captures both group commonalities and individual differences of emotion. Next, we investigated the characteristics of ordinal representation under different combinations of emotion items, including uni-variate and multivariate emotions, positive and negative emotions. Our results show that both group commonalities and inter-subject variations in EEG features are better explained by ordinal emotion representations than by interval ones. Multivariate ordinal representations showed better inter-subject reliability and higher representational similarity with EEG features compared to univariate counterparts, highlighting the co-occurrence nature of human emotions. Compared to negative emotions, ordinal representation showed greater improvements for positive emotions, suggesting that the complexity of positive emotions is well captured by ordinal representations. Taken together, these findings demonstrate that multivariate ordinal emotion ratings provide a more accurate measure of real emotional experience, which is crucial for enabling machines to precisely understand and express human emotions.
Production of P2D1 tailocins byDickeya dadantii3937: a temporal relationship between the stressor onset, gene expression, and the concentration of active particles
Authors: Sobolewska Marta , Krzyżanowska Dorota M. , Borowicz Marcin , Czajkowski Robert 
Published: November 2024

AbstractTailocins are bacteriocins resembling bacteriophage tails. Previously, we reported the production of P2D1 tailocins in the plant pathogenDickeya dadantii3937, the synthesis of which was upregulated upon treatment with mitomycin C. In the current study, we characterized the temporal relationship between the inducer onset, activation of expression of tailocin-related genes, the concentration of tailocin particles, and the titer of viable producer cells. Using a newly established RT-qPCR assay, we found that the expression of P2D1 structural genes peaks two hours after the addition of mitomycin C. Simultaneous measurement of the titer of tailocins showed that the maximum concentration of these particles in the culture supernatant was reached 6 hours post induction and remained stable till the termination of the experiment (18 hours). Progressing accumulation of tailocins between the second and the sixth-hour post mitomycin C treatment correlated with a sharp drop in the count of viable cells (ca. five orders of magnitude). This effect was related to the mechanism by which tailocins are released from the cells, which involves cell lysis. Our study is the first detailed analysis of the timing of events during P2D1 tailocin synthesis inDickeyaspp.
Alphafold2 refinement improves designability of large de novo proteins
Authors: Frank Christopher , Schiwietz Dominik , Fuß Lara , Ovchinnikov Sergey , Dietz Hendrik 
Published: November 2024

AbstractRecent advances in computational protein design have enabled the creation of novel proteins for a variety of purposes. The capability for producing custom-shape high-quality backbones for very large proteins would further expand the scope of protein design. To this end, here we introduce the AlphaFold2 (AF2) cycler (af2cycler) design pipeline. AF2cycler is used to refine draft protein backbone geometries of arbitrary shape created by the Chroma diffusion model or other methods, using a combination of AF2 and ProteinMPNN to achieve high designability with minimal deviations from the initial target structure. In silico testing on multiple protein designs (100-1000 amino acids) demonstrated improvements in structural integrity and designability after af2cycling confirmed by enhanced ESMFold repredictions. Experimental wet lab validation through the design of a variety of test proteins with distinct shapes, each comprising 1000 amino acids, showed structural agreement between in silico predictions and transmission electron microscopy (TEM) imaging, establishing the af2cycler’s efficacy in translating designs into real-world results. Af2cycler provides a convenient and reliable protein design workflow, particularly for large proteins, with potential for expanding to applications in areas such as design of higher-order protein complexes and multi-state backbone optimization.
Structure of an ex vivo
Drosophila TOM complex determined by single-particle cryoEM
Authors: Periasamy Agalya , Ornelas Pamela , Bausewein Thomas , Mitchell Naomi , Zhao Jiamin , Quinn Leonie M. , Kuehlbrandt Werner , Gulbis Jacqueline M. 
Published: November 2024

Most mitochondrial precursor proteins are encoded in the cell nucleus and synthesized on cytoplasmic ribosomes. The translocase of the outer membrane (TOM) is the main protein-import pore of mitochondria, recognizing nascent precursors of mitochondrially targeted proteins and transferring them across the outer membrane. A 3.3 Å resolution map and molecular model of a TOM complex from Drosophila melanogaster, obtained by single-particle electron cryomicroscopy, is presented. As the first reported structure of a transgenic protein expressed and purified ex vivo from Drosophila, the method provides impetus for parallel structural and genetic analyses of protein complexes linked to human pathology. The core TOM complex extracted from native membranes of the D. melanogaster retina contains transgenic Tom40 co-assembled with four endogenous TOM components: Tom22, Tom5, Tom6 and Tom7. The Drosophila TOM structure presented here shows that the human and Drosophila TOM are very similar, with small conformational changes at two subunit interfaces attributable to variation in lipid-binding residues. The new structure provides an opportunity to pinpoint general features that differentiate the TOM structures of higher and unicellular eukaryotes. While the quaternary fold of the assembly is retained, local nuances of structural elements implicated in precursor import are indicative of subtle evolutionary change.
Mediating role of political interest on effects of internal control systems on financial management in local government authorities in Ghana
Authors: Gbambegu Umar Abubakar , Osman Adam Ibrahim , Dzang Alhassan Muftawu , Abdallah Abdul Salam , Nterful Joshua 
Published: November 2024

Purpose
This study aims to delve into the intricate dynamics within local government authorities in Ghana, exploring the mediating role of political interest in the relationship between internal control systems and financial management.

Design/methodology/approach
Using a hypothesized model grounded on the accountability theory and survey data from 701 respondents across local government authorities in Ghana, this study used Partial Least Squares Structural Equation Modeling as the data analysis approach.

Findings
The findings indicate that internal control systems have a positive influence on financial management. In addition, political interest was found to significantly mediate the relationship between internal control systems and financial management.

Research limitations/implications
The study was, however, limited by the reliance on survey data obtained from the respondents. Although this study used survey data, it was not feasible to cover the entire country because this study was constrained by resources and time. Future studies may therefore explore same linkages by considering the entire country and adding other moderating variables to examine the nexuses. Future research could explore the subcomponents of internal control systems, including the control environment, control activities, risk assessment, monitoring of controls and information and communication in financial management. This would offer a nuanced understanding of how each dimension contributes to effective financial management.

Practical implications
This study offers two crucial contributions from a practical standpoint. This is accomplished by first allowing practitioners and decision-makers to understand the effects of political interest on organisation’s internal control system and financial management. This information can help practitioners and policymakers develop better systems that will reduce the mediating effects of political interest on the linkage between the internal control system and financial management in the local government authorities. In addition, policymakers will be better informed on how to enact legislation, specifically including sections of autonomous operations by these public agencies in the country, which can be undermined by external pressures or the ruling party.

Originality/value
To the best of authors’ knowledge, this research is the first to investigate such a phenomenon in a developing country context, such as Ghana, and it provides insights into why some local government authorities with seemingly robust internal control systems struggle with financial management issues.
The role of objective and subjective knowledge in tourists’ environmentally conscious travel decisions
Authors: Pilgreen Daniel G. , Cho Seung Jin , Zou Suiwen (Sharon) , Viren Paige P. 
Published: November 2024

Purpose
The purpose of this study is to investigate the impact of tourists’ objective and subjective knowledge on their decision to use environmental best practices in tourism. This study targets the alignment between objective and subjective knowledge to identify under-confidence and over-confidence in climate knowledge and their impact on tourism decision-making.

Design/methodology/approach
A survey of early climate adopters (n = 752) from a US-based travel network and European-based carbon capture provider assessed tourists’ climate change knowledge, attitudes, previous travel behavior and future intentions to engage in environmentally conscious best practices in travel. Using structural equation modeling, a model was developed to explore the impact of objective and subjective knowledge calibration on climate attitudes, past pro-environmental behaviors during travel and future intentions to include best climate practices in travel decisions.

Findings
The results of this study revealed that overconfidence diminished tourists’ climate-related attitudes. Attitudes were positively linked to past actions and future intentions for climate-friendly travel planning. Overconfidence undermined knowledge translation into action by diminishing climate attitudes. The findings of this study suggested that cognitive biases might be significant in shaping climate-conscious tourism behaviors.

Originality/value
While objective and subjective knowledge have been extensively examined in the consumer behavior literature, more attention should be paid to these concepts in the tourism literature. This research addresses this gap in the literature and suggests that objective and subjective knowledge should be addressed separately in future research.
Gender quota laws and firm performance: is there a trade-off?
Authors: Bannò Mariasole , Filippi Emilia , Leggerini Chiara 
Published: November 2024

Purpose
The introduction of gender quota laws in many countries has garnered significant attention in the literature and in the political discourse. Proponents of this solution emphasise its potential to bolster opportunities for women, foster their participation on boards of directors and improve corporate governance, market value and firm performance. Conversely, opponents express concerns regarding the possibility of appointing less-qualified women, thereby diminishing board effectiveness and potentially leading to negative consequences on firm market value and performance. This study aims to address this ongoing debate by examining the impact of gender quota laws on firm performance.

Design/methodology/approach
The impact of gender quota laws on firm performance, measured through ROE, ROA and ROI, is evaluated using a database of 27,977 Italian firms and adopting a two-stage traditional treatment effect model.

Findings
The econometric analysis reveals a negative impact of the gender quota law on firm performance.

Originality/value
This study contributes to the academic debate on the pros and cons of imposing gender quota laws by providing empirical evidence on their impact on firm performance.
Antecedents of i-deals: a transaction cost economics perspective
Authors: Yin Yishuai , Zhang Yuxuan , Zhang Pengfei 
Published: November 2024

Purpose
Idiosyncratic deals (i-deals) are designed to benefit both the employees and employers. While plenty of previous studies uncover the outcomes of i-deals, little research has explored what drives organizations to adopt i-deals in the first place. Drawing on transaction cost economics theory, this paper aims to investigate how employee–employer exchange characteristics affect different types of i-deals.

Design/methodology/approach
Based on a two-wave questionnaire study of 385 employees from information technology industry in China, hierarchical regression analysis was conducted to test the hypotheses.

Findings
The authors found that human asset specificity and task interdependence are positively related to developmental i-deals, and task interdependence was negatively related to flexible i-deals. Furthermore, environmental uncertainty positively moderates the impact of human asset specificity and task interdependence on developmental i-deals.

Originality/value
This paper contributes to research on i-deals by providing a theoretically more comprehensive and balanced analysis of why and when i-deals are adopted in organizations.
Thrive or dive: navigating the waves of mandatory digital transformation
Authors: Brazo Pedro , Velicia-Martín Felix , Palos-Sanchez Pedro , Roldán José L. 
Published: November 2024

Purpose
The purpose of this study is to investigate the mediating influence of three digitalization antecedents on the links between digitalization and survival. It addresses the roots of digitalization to discover different patterns and foundations that contribute to higher survival rates. The article explores whether a learning strategy can attain survivability on its own or whether digitalization facilitates the function of learning in survival.

Design/methodology/approach
The study uses partial least squares structural equation modeling to analyze data from 483 firms to assess this study’s hypothesis. Additionally, necessary condition analysis (NCA) is used to specify the necessary conditions of survivability.

Findings
The authors find a positive relationship between digitalization and business survival, as well as evidence of the strong mediating effect of resilience and learning in survivability. In addition, the study reveals that digitalization can serve as a sufficient condition for survival but not a necessary one, as it may be replaced by the mediating variables.

Research limitations/implications
The research offers insights into digitalization’s impact on business survival but faces limitations such as geographic focus and reliance on self-reported data. Despite this, it contributes to theory and practice by exploring how digitalization, organizational capabilities and resilience intersect.

Practical implications
This study provides insights into the required parameters for survival and the elimination of outliers in NCA.

Originality/value
This work provides insights into different antecedents of digitalization and business survival.
Multi-targeted strength properties of recycled aggregate concrete through a machine learning approach
Authors: Manan Aneel , Pu Zhang , Ahmad Jawad , Umar Muhammad 
Published: November 2024

PurposeRapid industrialization and construction generate substantial concrete waste, leading to significant environmental issues. Nearly 10 billion metric tonnes of concrete waste are produced globally per year. In addition, concrete also accelerates the consumption of natural resources, leading to the depletion of these natural resources. Therefore, this study uses artificial intelligence (AI) to examine the utilization of recycled concrete aggregate (RCA) in concrete.Design/methodology/approachAn extensive database of 583 data points are collected from the literature for predictive modeling. Four machine learning algorithms, namely artificial neural network (ANN), random forest (RF), ridge regression (RR) and least adjacent shrinkage and selection operator (LASSO) regression (LR), in predicting simultaneously concrete compressive and tensile strength were evaluated. The dataset contains 10 independent variables and two dependent variables. Statistical parameters, including coefficient of determination (R2), mean square error (MSE), mean absolute error (MAE) and root mean square error (RMSE), were employed to assess the accuracy of the algorithms. In addition, K-fold cross-validation was employed to validate the obtained results, and SHapley Additive exPlanations (SHAP) analysis was applied to identify the most sensitive parameters out of the 10 input parameters.FindingsThe results indicate that the RF prediction model performance is better and more satisfactory than other algorithms. Furthermore, the ANN algorithm ranks as the second most accurate algorithm. However, RR and LR exhibit poor findings with low accuracy. K-fold cross-validation was successfully applied to validate the obtained results and SHAP analysis indicates that cement content and recycled aggregate percentages are the effective input parameter. Therefore, special attention should be given to sensitive parameters to enhance the concrete performance.Originality/valueThis study uniquely applies AI to optimize the use of RCA in concrete production. By evaluating four machine learning algorithms, ANN, RF, RR and LR on a comprehensive dataset, this study identities the most effective predictive models for concrete compressive and tensile strength. The use of SHAP analysis to determine key input parameters and K-fold cross-validation for result validation adds to the study robustness. The findings highlight the superior performance of the RF model and provide actionable insights into enhancing concrete performance with RCA, contributing to sustainable construction practice.
The efficacy of high-performance-work-practices (HPWPs) in enhancing employee engagement and service-oriented organisational citizenship behaviour: a qualitative study of hotel managers and employee
Authors: Odiaka Kikachukwu , Chang Kirk 
Published: November 2024

Purpose
Various employee engagement strategies are proposed to boost organisational performance and business prosperity. Interestingly scholars criticise that these strategies may not always work and mixed views are proposed, leaving a glaring knowledge gap. Drawing on the theories of high-performance-work-practices (HPWPs), this paper aims to conduct a qualitative study, aiming to explore how strategies affect employee engagement and analyse the underlying mechanism.

Design/methodology/approach
This paper gathers research data by interviewing five managers and 15 employees in the hospitality sector. It analyses data through thematic analysis and adopts “Abilities Motivation Opportunities” (AMO) model in improving the analytic rigour. Ethical practices are arranged throughout the project, including consent form, anonymity in participation, confidentiality in responses, freedom to withdraw and data protection.

Findings
Research findings have advanced employee engagement literatures in two ways. On the one hand, when managers recognise employees’ job ability and effort, employees support engagement strategies. On the other hand, however, if managers do not appreciate employees’ job ability and effort, engagement strategies may not necessarily work.

Practical implications
This paper suggests managers display a positive attitude towards subordinates, such as appreciating subordinates’ effort and showing trust and support, if they wish their engagement strategies maximise to the full potential, particularly when managers’ trust is perceived important by employees. Maintaining a healthy communication channel between managers and subordinates also benefits the employee engagement, working morale and overall performance.

Originality/value
To the best of the authors’ knowledge, the current research is the first in its kind, examining hotel employee engagement practice and its implications on performance management in the sector of Nigeria hospitality. Unlike prior studies which link HPWPs to performance directly, our research findings have clarified how HPWPs affect performance through the underlying factors. These are employee engagement and managers’ attitude towards employees.