bluuebunny/crossref_metadata_2025_split huggingface dataset:
Asynchronous phylogeographic and demographic dynamics of rodent community in the low latitude Asia
Authors: Liu Gaoming , Shi Cheng-Min , Teng Huajing , Zhang Jian-Xu , Liu Quansheng 
Published: March 2023

AbstractIt is increasing evident that demographic history and phylogeographic consequences of past climate changes were unfolded locally and varied from region to region. Despite the high Murinae rodent species richness and endemism in the low latitude Asia, how the past climatic fluctuations shaped the phylogeographic and demographic history in this area remains unknown. Here we trapped 253 field Murine individuals and successfully amplified COI gene sequence for DNA barcoding. The phylogenetic tree showed the Murinae diversification included ten species belong to Rattini and Murini tribes. The divergence dating suggested that the most common ancestor (TMRCA) of each rodent species was estimated in Early or Middle Pleistocene. Bayesian skyline plot (BSP) exhibited the onset of population growth of seven Murinae rodents occurred at penultimate or last glaciation, and whileR. loseaandR. norvegicuskeep effective population size constant through their elapsed time. Additionally, the six rodent species range of refugia area in the LGM projected by ecological niche models (ENMs) exhibited expander than the suitable area on present, meanwhile the remaining four rodent species showed contracted refugia regions. Hence, our results suggested that the rodent community displayed the asynchronous demographic and phylogeographic dynamics in the low latitude Asia.
CellDeathPred: A Deep Learning framework for Ferroptosis and Apoptosis prediction based on cell painting
Authors: Schorpp Kenji , Bessadok Alaa , Biibosunov Aidin , Rothenaigner Ina , Strasser Stefanie , Peng Tingying , Hadian Kamyar 
Published: March 2023

AbstractCell death, such as apoptosis and ferroptosis, play essential roles in the process of development, homeostasis, and pathogenesis of acute and chronic diseases. The increasing number of studies investigating cell death types in various diseases, particularly cancer and degenerative diseases, has raised hopes for their modulation in disease therapies. However, identifying the presence of a particular cell death type is not an obvious task, as it requires computationally intensive work and costly experimental assays. To address this challenge, we present CellDeathPred, a novel deep learning framework that uses high-content-imaging based on cell painting to distinguish cells undergoing ferroptosis or apoptosis from healthy cells. In particular, we incorporate a deep neural network that effectively embeds microscopic images into a representative and discriminative latent space, classifies the learned embedding into cell death modalities and optimizes the whole learning using the supervised contrastive loss function. We assessed the efficacy of the proposed framework using cell painting microscopy datasets from human HT-1080 cells, where multiple inducers of ferroptosis and apoptosis were used to trigger cell death. Our model confidently separates ferroptotic and apoptotic cells from healthy controls, with an averaged accuracy of 95% on non-confocal datasets, supporting the capacity of the CellDeathPred framework for cell death discovery.
Age-dependent roles of cardiac remodeling in sepsis defense and pathogenesis
Authors: Sanchez Karina K. , McCarville Justin L. , Stengel Sarah J. , Snyder Jessica M. , Williams April E. , Ayres Janelle S. 
Published: March 2023

SummaryDisease tolerance is a defense strategy essential for survival of infections, limiting physiological damage without killing the pathogen. The disease course and pathology a pathogen may cause can change over the lifespan of a host due to the structural and functional physiological changes that accumulate with age. Since successful disease tolerance responses require the host to engage mechanisms that are compatible with the disease course and pathology caused by an infection, we predicted that this defense strategy would change with age. Animals infected with a lethal dose 50 (LD50) of a pathogen often display distinct health and sickness trajectories due to differences in disease tolerance, and thus can be used to delineate tolerance mechanisms. Using a polymicrobial sepsis model, we found that despite having the same LD50, old and young susceptible mice exhibited distinct disease courses. Young survivors employed a cardioprotective mechanism via FoxO1-mediated regulation of the ubiquitin-proteosome system that was necessary for survival and protection from cardiomegaly. This same mechanism was a driver of sepsis pathogenesis in aged hosts, causing catabolic remodeling of the heart and death. Our findings have implications for the tailoring of therapy to the age of an infected individual and suggest that disease tolerance alleles may exhibit antagonistic pleiotropy.
The effect of hashrate, transaction volume, social media and macroeconomics on Bitcoin before and during the COVID-19 pandemic
Authors: Sun Yen , Amanda Citra , Centana Berty Caroline 
Published: March 2023

PurposeThis research aims to determine the factors that affected Bitcoin price return in the period before and during the COVID-19 pandemic.Design/methodology/approachThe independent variables used in this study are hashrate, transaction volume, social media and some macroeconomics variables. The data are processed using the vector error correction model (VECM) to determine the short-term and long-term relationships between variables.FindingsThe research shows that (1) Twitter and Gold significantly affected Bitcoin in the short term before the COVID-19 pandemic; (2) hashrate, transaction volume, Twitter and the financial stress index had a significant effect on Bitcoin in the long term before the COVID-19 pandemic; (3) the volatility index had a significant effect on Bitcoin in the short term during the COVID-19 pandemic; and (4) hashrate, transaction volume, Twitter and CHF/USD had a significant effect on Bitcoin in the long term during the COVID-19 pandemic.Research limitations/implicationsThis research provides explanation about factors affecting Bitcoin so investors and regulators can pay more attention and prepare for the potential risks as well as to get a good understanding of market conditions for greater crypto adoption in the future.Originality/valueThe novelty in this study is the various factors driving the Bitcoin price were analyzed before and during the COVID-19 pandemic including the social media, as sentiment, interestingly, is being a predictive power for Bitcoin price return.
Green product purchase decision: a conceptual model of factors influencing the decision of Indian consumers
Authors: Mishra Vinayak , Kulshreshtha Kushagra 
Published: March 2023

PurposeMany studies conducted on green consumer behaviour are related to environmental concerns, the motives behind green consumer behaviour and the impact of demographic characteristics on purchase decisions are not studied yet in the Indian context. Hence, this study aims to analyse the green product purchase decision and factors influencing the decision of Indian consumers along with demographic characteristics.Design/methodology/approachPresent study utilise survey-based research method. Primary data were collected from 367 consumers in Hyderabad using a snowball sampling method. A structural equation modelling approach was employed to test the hypothesis.FindingsFindings confirm that supporting environmental protection, drive for environmental responsibility, green product experience, environmental friendliness of companies, social appeal and motives behind green product purchase significantly influence the green product purchase decision. Meanwhile, control variables such as gender, qualification and income also have a significant effect on the green product purchase decision.Research limitations/implicationsResults discussed in this paper will help policymakers to formulate their policies in lieu of variables affecting the purchase decision. Further, the findings of the current study can be utilised by managers to study the buying behaviour of green purchasers. This will help them to remain competitive in the Indian market.Originality/valueThis research presents a novel conceptual framework for the present study influenced by literature. The present study expanded the framework by adding a new independent variable: motives behind green product purchases and a control variable: demographic characteristics of Indian consumers.
Proactive personality and job performance during cross-cultural service encounters: a moderated mediation model
Authors: Köksal Onur , Güler Murat , Çetin Fatih , Şahin Faruk 
Published: March 2023

PurposeDrawing on the person-environment fit theory, in this paper the authors aim to propose and test a moderated mediation model that examines the relationships among proactive personality and job performance, cultural intelligence and emotional intelligence.Design/methodology/approachThe authors collected the multisource data from a total of 120 hotel service employees and the employees' immediate supervisors. The authors used the PROCESS, an SPSS macro, to conduct multiple regression analyses to test this moderated mediation model.FindingsThe results suggest that cultural intelligence mediates the relationship between proactive personality and job performance during cross-cultural service encounters. Furthermore, the indirect effect of proactive personality on job performance during cross-cultural service encounters via cultural intelligence is stronger for service employees who are high in emotional intelligence.Practical implicationsThis study has several implications for hospitality management in terms of developing effective strategies to foster cultural and emotional intelligence of service employees and improve the employees' performance.Originality/valueConsidering the limited number of studies showing why, how and in which situations personality can enhance performance, this study contributes to the literature by revealing the effect of proactive personality on the performance of service employees through important constructs such as cultural intelligence and emotional intelligence.
Implementing solar photovoltaic systems in buildings: a case of systemic innovation in the construction sector
Authors: Winkler Charlotta 
Published: March 2023

Purpose
This paper aims to explore the process of implementing solar photovoltaic (PV) systems in construction to contribute to the understanding of systemic innovation in construction.

Design/methodology/approach
The exploratory research presented is based on qualitative data collected in workshops and interviews with 76 construction- and solar-industry actors experienced in solar PV projects. Actor-specific barriers were identified and analysed using an abductive approach.

Findings
In light of established definitions of systemic innovation, the process of implementing solar PV systems in construction involves challenges regarding technical and material issues, competencies, and informal and formal institutions. The specificities of this case highlight the necessity of paying attention to details in the process and to develop knowledge of systemic innovation in construction since the industry’s involvement in addressing societal challenges related to the energy transition will require implementing such innovations much more in the future.

Practical implications
New knowledge of solar PV systems as an innovation in professional construction is collected, enabling the adaptation of management strategies for its implementation. This knowledge can also be applied generally to other challenges encountered in highly systemic innovation implementation. Solar industry actors can gain an understanding of solar-specific challenges for the construction industry, challenges for which they must adapt their activities.

Originality/value
The exploration of actor-specific experiences of solar PV projects has resulted in a novel understanding of this specific innovation and its implementation. The findings illustrate a case of a high level of systemic innovation and the need to use a finer-grained scale for classification when studying innovation in construction.
An investigation on the influencing factors of elderly people's intention to use financial AI customer service
Authors: Cheng Xusen , Qiao Liyang , Yang Bo , Li Zikang 
Published: March 2023

PurposeWith the great changes brought by information technology, there is also a challenge for the elderly's acceptance. This study aimed to determine the antecedents of elderly people's usage intention of financial artificial intelligent customer service (FAICS) and to examine the relationships between various factors and thus to help them better adapt to the digital age.Design/methodology/approachA mixed method, including the qualitative and quantitative study, was utilized to explore answers of the research questions. As the qualitative study, the authors used semi-structured interviews and data coding to uncover the influencing factors. As the quantitative study, the authors collected data through questionnaires and tested hypotheses using structural equation modeling.FindingsThe results of data analysis from interviews and questionnaires suggested that perceived anthropomorphism and virtual identity of elderly users have a positive impact on their perceived ease of use, and the perceived intelligence of elderly users positively influences their perceived ease of use, satisfaction and perceived usefulness. Additionally, the elderly's cognition age can moderate the effects of perceived usefulness and satisfaction on their usage intention of FAICS.Originality/valueThis study contributes to the literature by taking the elderly group as the research participants and combining those influencing factors with technology acceptance model and information systems success model. The findings provide a basis for accelerating the promotion of FAICS and help address the problem that the elderly have difficulty adapting to a new technology.
Intellectual capital and non-performing assets: the role of knowledge assets in improving credit quality of Indian banking sector
Authors: Gaur Dolly , Gupta Kanishka 
Published: March 2023

Purpose
Intellectual capital (IC) is beneficial to the improved performance of businesses, irrespective of their industry. The present study proposes to check if the use of IC can also help in improving the asset quality of banks. Thus, this study aims to examine the impact of IC and its components on non-performing assets (NPAs).

Design/methodology/approach
The study has been conducted with a sample of 30 Indian commercial banks and analysed over a time frame of 15 years (2004–2005 to 2018–2019). The modified value-added intellectual coefficient model has been used to measure the independent variables, IC, and its components. The dependent variable, NPA, has been represented by the net NPA ratio. Two-step system generalized methods of moments (SGMMs) have been applied for the regression analysis. Along with the short-term estimates provided by the SGMM approach, the long-term impact of explanatory variables on the dependent variables has also been seen.

Findings
The results of the study show that IC and its components are indeed helpful for the management of NPA, as they impact the problem loans negatively. Furthermore, the long-term benefits of IC in enhancing bank credit quality are more substantial.

Practical implications
The results from the present study can be used by bank management. The bank managers can draw inferences that the efficient application of IC can help them reduce their loan losses. Developing skills and knowledge of employees, maintaining close relations with stakeholders, significantly the customers, and putting more sophisticated processes and infrastructure to use can help banks to control their loan losses.

Originality/value
A major proportion of studies examining the role of intangible assets in various aspects of the banking sector focuses on the association between IC and the financial performance of banking entities. However, for banking institutions, apart from financial performance, improving credit quality is also imperative for staying afloat. Thus, to the best of the authors’ knowledge, the present study is one of the first to examine the relationship between knowledge-based assets (i.e. IC) and bank credit quality.
‘Friend or Foe?’: Brexit and French Bashing in the Conservative Parliamentary Party (2016–2022)
Authors: Alexandre‐Collier Agnès 
Published: March 2023

AbstractThis article explores the extent of anti‐French rhetoric in Conservative parliamentary discourse since 2016. It argues that up to the end of Liz Truss's extremely brief period of power, a fair number of Conservative MPs embarked on an escalation of tabloid‐like anti‐French bashing after the election of Boris Johnson, in an attempt to mimic the dramaturgy staged by their leader, while those who tried to provide a more positive discourse were left crying in the wilderness. Moreover, positive attempts to renew the relationship essentially came from MPs who had specific interests to defend, either in terms of representation of French residents in their constituencies or out of loyalty to family connections. Post‐Johnson, a more realistic and sensible discourse is anticipated, but damaging traces of this populist drift are likely to continue.
MRI‐based deep learning techniques for the prediction of isocitrate dehydrogenase and 1p/19q status in grade 2–4 adult gliomas
Authors: Kalaroopan Dinusha , Lasocki Arian 
Published: March 2023

SummaryMolecular biomarkers are becoming increasingly important in the classification of intracranial gliomas. While tissue sampling remains the gold standard, there is growing interest in the use of deep learning (DL) techniques to predict these markers. This narrative review with a systematic approach identifies and synthesises the current published data on DL techniques using conventional MRI sequences for predicting isocitrate dehydrogenase (IDH) and 1p/19q‐codeletion status in World Health Organisation grade 2–4 gliomas. Three databases were searched for relevant studies. In all, 13 studies met the inclusion criteria after exclusions. Key results, limitations and discrepancies between studies were synthesised. High accuracy has been reported in some studies, but the existing literature has several limitations, including generally small cohort sizes, a paucity of studies with independent testing cohorts and a lack of studies assessing IDH and 1p/19q together. While DL shows promise as a non‐invasive means of predicting glioma genotype, addressing these limitations in future research will be important for facilitating clinical translation.
Effects of Spin Transition and Cation Substitution on the Optical Properties and Iron Partitioning in Carbonate Minerals
Authors: HU Jun , XU Liangxu , LIU Jin , YUE Donghui 
Published: March 2023

AbstractThe high‐pressure behavior of deep carbonate dictates the state and dynamics of oxidized carbon in the Earth's mantle, playing a vital role in the global carbon cycle and potentially influencing long‐term climate change. Optical absorption and Raman spectroscopic measurements were carried out on two natural carbonate samples in diamond‐anvil cells up to 60 GPa. Mg‐substitution in high‐spin siderite FeCO3 increases the crystal field absorption band position by approximately 1000 cm–1 but such an effect is marginal at >40 GPa when entering the low‐spin state. The crystal field absorption band of dolomite cannot be recognized upon compression to 45.8 GPa at room temperature but, in contrast, the high‐pressure polymorph of dolomite exhibits a strong absorption band at frequencies higher than (Mg,Fe)CO3 in the low‐spin state by 2000–2500 cm–1. Additionally, these carbonate minerals show more complicated features for the absorption edge, decreasing with pressure and undergoing a dramatic change through the spin crossover. The optical and vibrational properties of carbonate minerals are highly correlated with iron content and spin transition, indicating that iron is preferentially partitioned into low‐spin carbonates. These results shed new light on how carbonate minerals evolve in the mantle, which is crucial to decode the deep carbon cycle.
Deciphering the Origin of Abiotic Organic Compounds on Earth: Review and Future Prospects
Authors: WANG Chao , TAO Renbiao , WALTERS Jesse B. , REN Tianshi , NAN Jingbo , ZHANG Lifei 
Published: March 2023

AbstractThe geologic production of abiotic organic compounds has been the subject of increasing scientific attention due to their use in the global carbon flux balance, by chemosynthetic biological communities, and for energy resources. Extensive analysis of methane (CH4) and other organics in diverse geologic settings, combined with thermodynamic modelings and laboratory simulations, have yielded insights into the distribution of specific abiotic organic molecules on Earth and the favorable conditions and pathways under which they form. This updated and comprehensive review summarizes published results of petrological, thermodynamic, and experimental investigations of possible pathways for the formation of particular species of abiotic simple hydrocarbon molecules such as CH4, and of complex hydrocarbon systems, e.g., long‐chain hydrocarbons and even solid carbonaceous matters, in various geologic processes, distinguished into three classes: (1) pre‐ to early planetary processes; (2) mantle and magmatic processes; and (3) the gas/water‐rock reaction processes in low‐pressure ultramafic rock and high‐pressure subduction zone systems. We not only emphasize how organics are abiotically synthesized but also explore the role or changes of organics in evolutionary geological environments after synthesis, such as phase transitions or organic‐mineral interactions. Correspondingly, there is an urgent need to explore the diversity of abiotic organic compounds prevailing on Earth.
UHMK1 promotes lung adenocarcinoma oncogenesis by regulating the PI3K/AKT/mTOR signaling pathway
Authors: Li Yongmeng , Wang Shuai , Jin Kai , Jin Wenxing , Si Libo , Zhang Huiying , Tian Hui 
Published: March 2023

AbstractBackgroundEffective targeted therapy for lung adenocarcinoma (LUAD), the number one cancer killer worldwide, continues to be a difficult problem because of the limitation of number of applicable patients and acquired resistance. Identifying more promising drug targets for LUAD treatment holds immense clinical significance. Recent studies have revealed that the U2 auxiliary factor (U2AF) homology motif kinase 1 (UHMK1) is a robust pro‐oncogenic factor in many cancers. However, its biological functions and the underlying molecular mechanisms in LUAD have not been investigated.MethodsThe UHMK1 expression in LUAD cells and tissues was evaluated by bioinformatics analysis, immunohistochemistry (IHC), western blotting (WB), and real time quantitative polymerase chain reaction (RT‐qPCR) assays. A series of gain‐ and loss‐of‐function experiments for UHMK1 were carried out to investigate its biological functions in LUAD in vitro and in vivo. The mechanisms underlying UHMK1's effects in LUAD were analyzed by transcriptome sequencing and WB assays.ResultsUHMK1 expression was aberrantly elevated in LUAD tumors and cell lines and positively correlated with tumor size and unfavorable patient prognosis. Functionally, UHMK1 displayed robust pro‐oncogenic capacity in LUAD and mechanistically exerted its biological effects via the phosphoinositide 3‐kinase (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR) signaling pathway.ConclusionUHMK1 is a potent oncogene in LUAD. Targeting UHMK1 may significantly improve the effect of LUAD treatment via inhibiting multiple biological ways of LUAD progression.