bluuebunny/crossref_metadata_2025_split huggingface dataset:
OMA1 mediates local and global stress responses against protein misfolding in CHCHD10 mitochondrial myopathy
Authors: Shammas Mario K. , Huang Xiaoping , Wu Beverly P. , Song Insung , Randolph Nicholas , Li Yan , Bleck Christopher K. E. , Springer Danielle A. , Fratter Carl , Barbosa Ines A. , Powers Andrew F. , Quirós Pedro M. , Lopez-Otin Carlos , Poulton Joanna , Narendra Derek P. 
Published: December 2021

AbstractMitochondrial stress triggers a response in the cell’s mitochondria and nucleus, but how these stress responses are coordinated in vivo is poorly understood. Here, we characterize a family with myopathy caused by a dominant p.G58R mutation in the mitochondrial protein CHCHD10. To understand the disease etiology, we developed a novel knock-in mouse model and found that mutant CHCHD10 aggregates in affected tissues, applying a toxic protein stress to the inner mitochondrial membrane. Unexpectedly, survival of CHCHD10 knock-in mice depended on a protective stress response mediated by OMA1. The OMA1 stress response acted both locally within mitochondria, inhibiting mitochondrial fusion, and signaled outside the mitochondria, activating the integrated stress response. We additionally identified an isoform switch in the terminal complex of the electron transport chain as a novel component of this response. Our results demonstrate that OMA1 is essential for neonatal survival conditionally in the setting of inner mitochondrial membrane stress, coordinating local and global stress responses to reshape the mitochondrial network and proteome.Graphical Abtract
Dynamic Distributed and Parallel Machine Learning algorithms for big data mining processing
Authors: Djafri Laouni 
Published: December 2021

PurposeThis work can be used as a building block in other settings such as GPU, Map-Reduce, Spark or any other. Also, DDPML can be deployed on other distributed systems such as P2P networks, clusters, clouds computing or other technologies.Design/methodology/approachIn the age of Big Data, all companies want to benefit from large amounts of data. These data can help them understand their internal and external environment and anticipate associated phenomena, as the data turn into knowledge that can be used for prediction later. Thus, this knowledge becomes a great asset in companies' hands. This is precisely the objective of data mining. But with the production of a large amount of data and knowledge at a faster pace, the authors are now talking about Big Data mining. For this reason, the authors’ proposed works mainly aim at solving the problem of volume, veracity, validity and velocity when classifying Big Data using distributed and parallel processing techniques. So, the problem that the authors are raising in this work is how the authors can make machine learning algorithms work in a distributed and parallel way at the same time without losing the accuracy of classification results. To solve this problem, the authors propose a system called Dynamic Distributed and Parallel Machine Learning (DDPML) algorithms. To build it, the authors divided their work into two parts. In the first, the authors propose a distributed architecture that is controlled by Map-Reduce algorithm which in turn depends on random sampling technique. So, the distributed architecture that the authors designed is specially directed to handle big data processing that operates in a coherent and efficient manner with the sampling strategy proposed in this work. This architecture also helps the authors to actually verify the classification results obtained using the representative learning base (RLB). In the second part, the authors have extracted the representative learning base by sampling at two levels using the stratified random sampling method. This sampling method is also applied to extract the shared learning base (SLB) and the partial learning base for the first level (PLBL1) and the partial learning base for the second level (PLBL2). The experimental results show the efficiency of our solution that the authors provided without significant loss of the classification results. Thus, in practical terms, the system DDPML is generally dedicated to big data mining processing, and works effectively in distributed systems with a simple structure, such as client-server networks.FindingsThe authors got very satisfactory classification results.Originality/valueDDPML system is specially designed to smoothly handle big data mining classification.
Adoption of innovative technologies in the South African construction industry
Authors: van Wyk Liané , Kajimo-Shakantu Kahilu , Opawole Akintayo 
Published: December 2021

PurposeThe South African construction industry appears to be lagging behind other industries in the country in terms of implementation and adoption of innovative technologies. Moreover, sufficient empirical data on the adoption of innovative technologies, especially, in developing countries are not readily available. The aim of this study is therefore to assess the adoption and implementation of innovative technologies in the South African construction industry with a view to improving the industry's performance.Design/methodology/approachA survey was undertaken using a questionnaire, administered to construction professionals primarily in project management, quantity surveying and architectural firms.FindingsThe key findings show that there are some innovative technologies such as building information modelling, 3-dimensional mapping, drones, 3-dimensional printing and virtual reality that have been deployed. However, limited adoption of innovative technologies within the industry and low levels of knowledge of its benefits among the respondents were reported. This low implementation of innovative technologies was due to critical barriers such as high cost, limited knowledge, time requirement, fear of change, lack of interest, nature of construction processes and lack of team dynamics. Key drivers of innovation were found to include globalization and competition.Practical implicationsThe current level of implementation of innovative technologies indicated that they are not yet optimized in the South African construction industry and suggests implications for change, adaptation and growth. The study recommends that firms should consider investing in research and development in order to exploit the potential of innovation for organizations and the industry at large.Originality/valueThe drivers and barriers indicated will help to prioritize the direction of adoption and growth which could help to improve the industry.
Managing competing institutional logics in governance of public-sector entities in Tanzania
Authors: Mzenzi Siasa Issa , Gaspar Abeid Francis 
Published: December 2021

PurposeThe paper aims to investigate how the governance practices of public-sector entities (PSEs) in Tanzania are shaped by competing institutional logics and strategies used to manage the logics.Design/methodology/approachIn the paper, empirical evidence was gathered through documentary sources, non-participant observations and in-depth interviews with members of boards of directors (BoDs), chief executive officers (CEOs), internal and external auditors, senior executives and ministry officials. The data were analyzed using thematic and pattern-matching approaches.FindingsThe paper shows that bureaucratic and market logics co-exist and variations in governance practices within and across categories of PSEs. These are reflected in CEO appointments, multiple roles of CEOs, board member appointments, board composition, multiple board membership, board roles and evaluation of board performance. External audits also foster market logic in governance practices. The two competing logics are managed by actors through selective coupling, compromise, decoupling and compartmentalization. Despite competing logics, the bureaucratic logic remains dominant and is largely responsible for variations between the underlying logics and governance practices.Practical implicationsThe findings suggest that public-sector reforms in emerging economies (EEs) must account for the fact that governance practices in PSEs are shaped by different institutional logics embedded in socioeconomic, political and organizational contexts and their corresponding management strategies.Originality/valueFew previous studies explicitly report relationships between institutional logics and the governance practices of PSEs in EEs. The current study is one of few empirical studies to connect competing institutional logics and the associated management strategies, as well as governance practices in EEs in the context of public-sector reforms.
Exploring the role of corruption and money laundering (ML) on bank’s loan portfolio quality: a cross-country investigation
Authors: Hussain Nadir , Sheikh Salman Masood , Shah Ijaz Hussain 
Published: December 2021

Purpose
Corruption and money laundering (ML) are severe concerns for both developing and developed countries. According to international organizations, such as Transparency International, the Basel Institute on Governance and the International Country Risk Guide, corruption and ML exist in every country. This research aims to investigate the impact of corruption and ML on the loan portfolio quality of banks.

Design/methodology/approach
From 2013 to 2019, this study used the panel data of 132 countries, including 87 highly corrupt and 45 least corrupt countries: the fixed effect and random effect econometric regression techniques for data analysis. Additionally, this study used the generalized methods of moment technique to check the result’s robustness.

Findings
This study shows that corruption and ML have diverse relationships with non-performing loans in highly corrupt and low corrupt countries. It is potentially because of the differences in the regulatory structure of a highly corrupt and least corrupt environment.

Originality/value
To the best of the authors’ knowledge, this study is the first attempt that provides a unique perspective on corruption, ML and its effect on the loan’s portfolio quality of banks. Furthermore, this study suggests that governments in highly corrupt environments develop robust anti-corruption and anti-ML regulations.
Real Estate Insights Grand ideas or delusions of grandeur? Placing big thinkers and essential theories in property economics research
Authors: Squires Graham 
Published: December 2021

PurposeThis article is looking to reflect on the various important touchstones of “grand theory” and “big thinkers” that can be framed when engaging empirical evidence in property economics research.Design/methodology/approachThe paper is reflexive in nature, using experiential reflection to consider theory in property economics. The importance of “methodology” is emphasised rather than “method”.FindingsUsing reflexive mode, the paper does not have “findings” as such: if the views expressed are accepted, then a research agenda to better understand property economics research is implied.Research limitations/implicationsThe nature of reflection is that it follows from the writer's experiential processes and interpretations. The reader may come from a different stance. Broadly accepting the propositions, there is a call for property economics research to be formulated in reason and logic, particularly as humans do not reason from facts alone. Such reasoned thinking could for example be in the property economic concepts of space and place, contracts and justice, capital and financialisation.Practical implicationsTo engage with such theory would provide some depth of philosophical roots for property as a discipline. Elevating property as a “real-world” discipline rather than simply an applied mathematics discipline.Social implicationsThe paper enables an understanding of how property economics research can benefit from more ontology and more inductive reasoning.Originality/valueThe paper reflects the views and experience of the author based on over 15 years of research in property economics.
Real Estate Insights Data intelligence and real estate – machines are the real game changer
Authors: Cajias Marcelo , Wins Anett 
Published: December 2021

PurposeThe paper shows with two concrete examples about how algorithms are used in active real estate management. The paper also highlights that the discussion about the adoption of new technologies is crucial for market players.Design/methodology/approachThe authors review the current status quo about new technologies in real estate and provide two examples of how algorithms can be used to understand locations and the value drivers of rents.FindingsLocation, location, location is nowadays data, data, data coupled with the knowledge of how to create life out of data. Algorithm can help to understand the value drivers of rents and can also help to evaluate the attractiveness of a location.Practical implicationsReal estate management will adapt to new technologies fast. This change has the potential to disrupt exiting strategies due to the increase in efficiency, insights, transparency and location knowledge. Investment managers walking this talk will definitely benefit in future.Originality/valueThe paper makes usage of the latest machine learning technologies applied to real estate investment cases. This is a unique opportunity on bringing light on the discussion about transparency in real estate.
Commentary: the moral limits of service markets – just because we can, should we?
Authors: Raciti Maria , Badejo Foluké Abigail , Previte Josephine , Schuetz Michael 
Published: December 2021

Purpose
This commentary extends our 2020 11th SERVSIG Panel The moral limits of service markets: Just because we can, should we?, inspired by Michael J. Sandel’s book What Money Can’t Buy: The Moral Limits of Markets. In Sandel’s (2012) book, the pursuit of “the good life” is a common motivation for pushing the moral boundaries of markets and “the good life” is dominated by service consumption.

Design/methodology/approach
Like Sandel (2012), this commentary begins with a provocation regarding the need for moral development in services marketing. Next, we present three real-life case studies about a modern slavery survivor service, aged care services and health-care services as examples of moral limits, failings and tensions.

Findings
The commentary proposes four guidelines and a research agenda. As service marketers, we must reignite conversations about ethics and morality. Taking charge of our professional moral development, exercising moral reflexivity, promoting an ethics of care and taking a bird’s-eye perspective of moral ecologies are our recommended guidelines. Morality is an essential condition – a sine qua non – for service marketers. Hence, our proposed research agenda focuses first on the service marketer and embeds a moral gaze as a universal professional protocol to engender collective moral elevation.

Originality/value
This commentary highlights the need for a moral refresh in services marketing and proposes ways to achieve this end.
Conditional filamentation as an adaptive trait of bacteria and its ecological significance in soils
Authors: Karasz David C. , Weaver Anna I. , Buckley Daniel H. , Wilhelm Roland C. 
Published: December 2021

SummaryBacteria can regulate cell morphology in response to environmental conditions, altering their physiological and metabolic characteristics to improve survival. Conditional filamentation, in which cells suspend division while continuing lateral growth, is a strategy with a range of adaptive benefits. Here, we review the causes and consequences of conditional filamentation with respect to bacterial physiology, ecology and evolution. We describe four major benefits from conditional filamentation: stress tolerance, surface colonization, gradient spanning and the facilitation of biotic interactions. Adopting a filamentous growth habit involves fitness trade‐offs which are also examined. We focus on the role of conditional filamentation in soil habitats, where filamentous morphotypes are highly prevalent and where environmental heterogeneity can benefit a conditional response. To illustrate the use of information presented in our review, we tested the conditions regulating filamentation by the forest soil isolate Paraburkholderia elongata 5NT. Filamentation by P. elongata was induced at elevated phosphate concentrations, and was associated with the accumulation of intracellular polyphosphate, highlighting the role of filamentation in a phosphate‐solubilizing bacterium. Conditional filamentation enables bacteria to optimize their growth and metabolism in environments that are highly variable, a trait that can impact succession, symbioses, and biogeochemistry in soil environments.
Leveraging Big Data to Study Information Dissemination of Material Firm Events
Authors: LI BIN , VENKATACHALAM MOHAN 
Published: December 2021

ABSTRACTCould real‐time big data help unravel material firm events? How would it compare with firm disclosure and traditional media in terms of timeliness and completeness? Could big data provide incremental value‐relevant information for investors? With these questions in mind, we use a novel data set of cell phone “pings” (i.e., geolocation signals from mobile devices) to track production disruptions (outages)––material events for U.S. oil refineries. We first validate the construct by examining the effects of outages on local gas prices and firms’ accounting performance. Our main analyses show that (1) refining firms do not voluntarily disclose refinery outages identified by cell phone pings; (2) traditional media cover only a small portion of ping‐based outages; (3) the stock market finds ping‐based outages to be value relevant but incorporates the information with delay. Further analysis suggests that given the incomplete media coverage and lack of firm disclosure, investors appear to learn the financial impact of such outages through subsequent earnings announcements. Our evidence has implications for regulators such as the U.S. Energy Information Administration and the Securities and Exchange Commission as they continue to evaluate both the compliance and usefulness of disclosures for material firm events such as production disruptions.
Choosing among correlative, mechanistic, and hybrid models of species’ niche and distribution
Authors: TOURINHO Luara , VALE Mariana M. 
Published: December 2021

AbstractDifferent models are available to estimate species’ niche and distribution. Mechanistic and correlative models have different underlying conceptual bases, thus generating different estimates of a species’ niche and geographic extent. Hybrid models, which combining correlative and mechanistic approaches, are considered a promising strategy; however, no synthesis in the literature assessed their applicability for terrestrial vertebrates to allow best‐choice model considering their strengths and trade‐offs. Here, we provide a systematic review of studies that compared or integrated correlative and mechanistic models to estimate species’ niche for terrestrial vertebrates under climate change. Our goal was to understand their conceptual, methodological, and performance differences, and the applicability of each approach. The studies we reviewed directly compared mechanistic and correlative predictions in terms of accuracy or estimated suitable area, however, without any quantitative analysis to support comparisons. Contrastingly, many studies suggest that instead of comparing approaches, mechanistic and correlative methods should be integrated (hybrid models). However, we stress that the best approach is highly context‐dependent. Indeed, the quality and effectiveness of the prediction depends on the study's objective, methodological design, and which type of species’ niche and geographic distribution estimated are more appropriate to answer the study's issue.
Late‐life exercise mitigates skeletal muscle epigenetic aging
Authors: Murach Kevin A. , Dimet‐Wiley Andrea L. , Wen Yuan , Brightwell Camille R. , Latham Christine M. , Dungan Cory M. , Fry Christopher S. , Watowich Stanley J. 
Published: December 2021

AbstractThere are functional benefits to exercise in muscle, even when performed late in life, but the contributions of epigenetic factors to late‐life exercise adaptation are poorly defined. Using reduced representation bisulfite sequencing (RRBS), ribosomal DNA (rDNA) and mitochondrial‐specific examination of methylation, targeted high‐resolution methylation analysis, and DNAge™ epigenetic aging clock analysis with a translatable model of voluntary murine endurance/resistance exercise training (progressive weighted wheel running, PoWeR), we provide evidence that exercise may mitigate epigenetic aging in skeletal muscle. Late‐life PoWeR from 22–24 months of age modestly but significantly attenuates an age‐associated shift toward promoter hypermethylation. The epigenetic age of muscle from old mice that PoWeR‐trained for eight weeks was approximately eight weeks younger than 24‐month‐old sedentary counterparts, which represents ~8% of the expected murine lifespan. These data provide a molecular basis for exercise as a therapy to attenuate skeletal muscle aging.
Importance of cardiac rehabilitation in rural and remote areas of Australia
Authors: Field Patricia , Franklin Richard C. , Barker Ruth , Ring Ian , Leggat Peter , Canuto Karla 
Published: December 2021

AbstractObjectiveTo assess implementation of in‐patient cardiac rehabilitation (Phase‐1‐cardiac rehabilitation), impact on people in rural and remote areas of Australia and potential methods for addressing identified weaknesses.DesignExploratory case study methodology using qualitative and quantitative methods. Qualitative data collection via semi‐structured interviews, using thematic analysis, augmented by quantitative data collection via a medical record audit.SettingFour regional hospitals (2 Queensland Health and 2 private) providing tertiary health care.Participants(a) Hospital in‐patients with heart disease ≥18 years. (b) Staff responsible for their care.Outcome MeasuresImplementation of Phase‐1‐cardiac rehabilitation in tertiary hosptials in North Queensland and the impact on in‐patients discharge planning and post discharge care. Recommentations and implications for practice are proposed to address deficits.ResultsPhase‐1‐cardiac rehabilitation implementation rates, in‐patient understanding and multidisciplinary team involvement were low. The highest rates of Phase‐1‐cardiac rehabilitation were for in‐patients with a length of stay three days or more in cardiac units with cardiac educators. Rates were lower in cardiac units with no cardiac educators, and lowest for in‐patients in all areas of all hospitals with length of stay of two days or less days. Low Phase‐1‐cardiac rehabilitation implementation rates resulted in poor in‐patient understanding about their disease, treatment and post‐discharge care. Further, medical discharge summaries rarely mentioned cardiac rehabilitation/secondary prevention or risk factor management resulting in a lack of information for health care providers on cardiac rehabilitation and holistic health care.ConclusionImplementation of Phase‐1‐cardiac rehabilitation in regional hospitals in this study fell short of recommended best practice, resulting in patients' poor preparation for discharge, and insufficient information on holistic care for health care providers in rural and remote areas. These factors potentially impact on holistic care for people returning home following treatment for heart disease.