bluuebunny/crossref_metadata_2025_split huggingface dataset:
Surface-active antibiotic production is a multifunctional adaptation for postfire microbes
Authors: Liu Mira D. , Du Yongle , Koupaei Sara K. , Kim Nicole R. , Zhang Wenjun , Traxler Matthew F. 
Published: August 2023

AbstractWildfires affect soils in multiple ways, leading to numerous challenges for colonizing microbes. While it is thought that fire-adapted microbes lie at the forefront of postfire ecosystem recovery, the specific strategies that these microbes use to thrive in burned soils remain largely unknown. Through bioactivity screening of bacterial isolates from burned soils, we discovered that severalParaburkholderia spp.isolates produced a set of unusual rhamnolipid surfactants with a natural methyl ester modification. These rhamnolipid methyl esters (RLMEs) exhibited enhanced antimicrobial activity against other postfire microbial isolates, including pyrophilousPyronemafungi andAmycolatopsisbacteria, compared to the typical rhamnolipids made by organisms such asPseudomonas spp. RLMEs also showed enhanced surfactant properties and facilitated bacterial motility on agar surfaces.In vitroassays further demonstrated that RLMEs improved aqueous solubilization of polycyclic aromatic hydrocarbons, which are potential carbon sources found in char. Identification of the rhamnolipid biosynthesis genes in the postfire isolate,Paraburkholderia caledonicastr. F3, led to the discovery ofrhlM, whose gene product is responsible for the unique methylation of rhamnolipid substrates. RhlM is the first characterized bacterial representative of a large class of integral membrane methyltransferases that are widespread in bacteria. These results indicate multiple roles for RLMEs in the postfire lifestyle ofParaburkholderiaisolates, including enhanced dispersal, solubilization of potential nutrients, and inhibition of competitors. Our findings shed new light on the chemical adaptations that bacteria employ in order to navigate, grow, and outcompete other soil community members in postfire environments.Significance StatementWildfires are increasing in frequency and intensity at a global scale. Microbes are the first colonizers of soil after fire events, but the adaptations that help these organisms survive in postfire environments are poorly understood. In this work, we show that a bacterium isolated from burned soil produces an unusual rhamnolipid biosurfactant that exhibits antimicrobial activity, enhances motility, and solubilizes potential nutrients derived from pyrolyzed organic matter. Collectively, our findings demonstrate that bacteria leverage specialized metabolites with multiple functions to meet the demands of life in postfire environments. Furthermore, this work reveals the potential of probing perturbed environments for the discovery of unique compounds and enzymes.
Complementary roles of orbitofrontal and prelimbic cortices in adaptation of reward motivated actions to learned anxiety
Authors: Jacobs David S. , Bogachuk Alina P. , Moghaddam Bita 
Published: August 2023

AbstractBackgroundAnxiety is a common symptom of several mental health disorders and adversely affects motivated behaviors. Anxiety can emerge from associating risk of future harm while engaged in goal-guided actions. Using a recently developed behavioral paradigm to model this aspect of anxiety, we investigated the role of two cortical subregions, the prelimbic medial frontal cortex (PL) and lateral orbitofrontal cortex (lOFC), which have been implicated in anxiety and outcome expectation, in flexible representation of actions associated with harm risk.MethodsA seek-take reward-guided instrumental task design was used to train animals to associate the seek action with a variable risk of punishment. After learning, animals underwent extinction training for this association. Fiber photometry was used to measure and compare neuronal activity in PL and lOFC during learning and extinction.ResultsAnimals increased action suppression in response to punishment contingencies. This increase dissipated after extinction training. These behavioral changes were associated with region specific changes in neuronal activity. PL neuronal activity preferentially adapted to threat of punishment whereas lOFC activity adapted to safe aspects of the task. Moreover, correlated activity between these regions was suppressed during actions associated with harm risk suggesting that these regions may guide behavior independently under anxiety.ConclusionsThese findings suggest the PL and lOFC serve distinct but complementary roles in the representation of learned anxiety. This dissociation may provide a mechanism for how overlapping cortical systems are implicated in reward-guided action execution during anxiety.
A neural network model for the evolution of learning in changing environments
Authors: Kozielska Magdalena , Weissing Franz J. 
Published: August 2023

AbstractThe ability to learn from past experience is an important adaptation, but how natural selection shapes learning is not well understood. Here, we present a novel way of modelling learning using small neural networks and a simple, biology-inspired learning algorithm. Learning affects only part of the network, and it is governed by the difference between expectations and reality. We used this model to study the evolution of learning under various environmental conditions and different scenarios for the trade-off between exploration (learning) and exploitation (foraging). Efficient learning regularly evolved in our individual-based simulations. However, in line with previous studies, the evolution of learning was less likely in relatively constant environments (where genetic adaptation alone can lead to efficient foraging) or in the case of short-lived organisms (that cannot afford to spend much of their lifetime on exploration). Once learning did evolve, the characteristics of the learning strategy (the duration of the learning period and the learning rate) and the average performance after learning were surprisingly little affected by the frequency and/or magnitude of environmental change. In contrast, an organism’s lifespan and the distribution of resources in the environment had a strong effect on the evolved learning strategy. Interestingly, a longer learning period did not always lead to better performance, indicating that the evolved neural networks differ in the effectiveness of learning. Overall, however, we showed that a biologically inspired, yet relatively simple, learning mechanism can evolve to lead to an efficient adaptation in a changing environment.Author SummaryThe ability to learn from experience is an important adaptation. However, it is still unclear how learning is shaped by natural selection. Here, we present a novel way of modelling the evolution of learning using small neural networks and a simple, biology-inspired learning mechanism. Computer simulations reveal that efficient learning readily evolves in this model. However, the evolution of learning is less likely in relatively constant environments (where evolved inborn preferences can guide animal behaviour) and in short-lived organisms (that cannot afford to spend much of their lifetime on learning). If learning does evolve, the evolved learning strategy is strongly affected by the lifespan and environmental richness but surprisingly little by the rate and degree of environmental change. In summary, we show that a simple and biologically plausible mechanism can help understand the evolution of learning and the structure of the evolved learning strategies.
A dissociation between the use of implicit and explicit priors in perceptual inference
Authors: Bévalot Caroline , Meyniel Florent 
Published: August 2023

AbstractThe brain constantly uses prior knowledge of the statistics of its environment to shape perception. These statistics are often implicit (not directly observable) and gradually learned from observation; but they can also be explicitly communicated to the observer, especially in humans. In value-based decision-making, these priors are treated differently depending on their implicit or explicit origin creating the “experience-description gap”. Here, we show that the same distinction also applies to perception. We created a pair of categorization tasks with implicit and explicit priors respectively, and manipulated the strength of priors and sensory likelihood within the same human subjects. Perceptual decisions were influenced by priors in both tasks, and subjects updated their priors in the implicit task as the true statistics changed. Using Bayesian models of learning and perception, we found that the weight of the sensory likelihood in perceptual decisions was highly correlated across subjects between tasks, and slightly stronger in the implicit task. By contrast, the weight of priors was much less correlated across tasks, and it increased markedly from the explicit task to the implicit task. The same conclusion holds when using the subjects’ reported priors. Model comparison also showed that different computations underpinned perceptual decisions depending on the origin of the priors. Taken together, those results support a dissociation in perceptual inference between the use of implicit and explicit priors. This conclusion could resolve conflicting results generated by the indiscriminate use of implicit and explicit priors when studying perception in healthy subjects and patients.Significance StatementThe use of prior knowledge is ubiquitous in brain processes. However, this use is not always appropriate, and the weights assigned to priors in perceptual decisions are quite heterogeneous across studies. Here, we tested whether the origin of priors can partially explain this heterogeneity. Priors that are explicitly communicated (e.g., a road sign indicating the likely presence of wildlife) appear to be used differently from priors that remain implicit and are learned from experience (e.g., previous encounters with wildlife). We show that the use of implicit and explicit priors is unrelated across subjects. This dissociation may explain why previous findings on the use of explicit and implicit priors (e.g. abnormally strong or weak priors) are often inconsistent.
Sociodemographic differences and experienced effects of young adults who use cannabis mainly for self-medication versus recreationally in Finland
Authors: Hupli Aleksi , Unlu Ali , Jylkkä Jussi , Oksanen Atte 
Published: August 2023

Purpose
Cannabis use continues to increase worldwide, and a number of nation states are changing their cannabis policies. Policy changes require research into key populations, namely, people who use cannabis. This study aims to examine sociodemographic differences of young Finns who reported using cannabis mainly for self-medication versus mainly recreationally, as well as their reported effects of cannabis use.

Design/methodology/approach
The data come from an anonymous online survey (N = 247, 70.0% males, 25.9% females, 4.1% other) that was analysed using multiple logistic regression. The authors focused on whether various demographic indicators differed between those who reportedly used cannabis mainly for recreational purposes and mainly for self-medicinal purposes. The authors also qualitatively examined the respondents’ experienced effects of cannabis, both desired and undesired.

Findings
Being older and female, living in a smaller city and earlier age of initiation of cannabis use were statistically significant in predicting the medicinal use of cannabis. The majority of recreational effects were related to themes such as relaxation and pleasure, but many participants also reported desired medical effects. Similarly, many participants reported several undesired effects.

Research limitations/implications
Understanding especially young people’s motivations to use cannabis, which include using it for various medical effects, can improve the design of harm reduction and treatment programmes as well as enhance the well-being of people who use cannabis.

Originality/value
This study gives a nuanced account of sociodemographic factors and motivations of young people who use cannabis in Finland as well as the reported effects it has on them, which complements data from national drug surveys.
Ransys Partners Ltd: digitalizing supply chain
Authors: Sinha Ranit , Padhi Sidhartha S. , Dhaigude Amol S. 
Published: August 2023

Learning outcomes
The case depicts an opportunity for undergraduate and postgraduate students to be exposed to the basic digitization of supply chain management, technology adoption, change management and cost-benefit analysis concepts. The study aims to encourage them to use the data given in the case and exhibits to compare and contrast physical and digital supply chains (SC); design the digitized version of the traditional SC; examine the nitty-gritty of technology adoption in the SC context; develop the change management plans for the successful adoption and implementation of SC digitization; design the risk register and Explore the business process management; and conduct the return on investment analysis.

Case overview/synopsis
Amber Yen, Chief Operating Officer Apparel Sourcing at Ransys Partners Ltd (RSL), was presented with the task of reducing physical sample production cost and time without impeding order pipeline. RSL was experiencing significant capacity constrain during the COVID-19 crisis, failing to deliver physical samples to international brands. To win large export orders, RSL had to adopt a new innovative way to reduce the sample approval process while meeting customer requirements. Ms Yen wanted to convert the entire sample approval process into a digital mode. She was facing multiple challenges related to the design, implementation and adoption of the digital sample approval process to coordinate the entire SC. She had limited time and was grappling with other impending constraints such as increasing cost, intense competition, demanding customers, shortage of labor due to COVID-19, reducing the bottom line. It was her time to test the idiom “necessity is the mother of innovation”.

Complexity academic level
The target audience for this case is management or business school students. This case can be used to teach digitization of SC, operations management, organization behavior, digitization of enterprises, IT for business, new service development, supplier management technology adoption, and change management in management or business schools.

Supplementary material
Teaching notes are available for educators only.

Subject code
CSS 9: Operations and Logistics.
The impact of corporate governance mechanisms on corporate failure: an empirical evidence from Palestine Exchange
Authors: Nour Abdulnaser Ibrahim , Najjar Mohammad , Al Koni Saed , Abudiak Abullateef , Noor Mahmoud Ibrahim , Shahwan Rani 
Published: August 2023

PurposeThe purpose of this research is to examine the impact of governance mechanisms on corporate failure.Design/methodology/approachThis study used a hypothesis-testing research design to collect data from the annual reports of 35 companies listed on Palestine Exchange from 2010 to 2019. Descriptive and inferential statistics were employed, along with correlation analysis to evaluate linear relationships between variables. The variance inflation factor was used to test multicollinearity, and binary logistic regression was utilized to develop the research model.FindingsThere is a significant positive relationship between board of directors' independency, institutional ownership and the quality of external audit, and corporate failure reduction. No significant relationship has been found among corporate governance variables such as board size, board meetings' frequency, board members' remuneration and audit committee existence, and corporate failure reduction.Research limitations/implicationsSeveral empirical research studies have developed models to predict corporate failure using accounting and financial data. However, limited research has empirically investigated the impact of the different mechanisms of governance on corporate failure prediction.Practical implicationsThe research highlighted the significance of companies' commitment to governance principles and their impact on predicting failure. The study suggests that decision-makers and managers can adopt different governance mechanisms to support corporate success and avoid those that may lead to negative consequences and failure.Originality/valueThis research is the first in Palestine to use a comprehensive list of corporate governance mechanisms to predict the failure of companies listed on the Palestine Stock Exchange between 2010 and 2019.
AI-driven disinformation: a framework for organizational preparation and response
Authors: Karinshak Elise , Jin Yan 
Published: August 2023

PurposeDisinformation, false information designed with the intention to mislead, can significantly damage organizational operation and reputation, interfering with communication and relationship management in a wide breadth of risk and crisis contexts. Modern digital platforms and emerging technologies, including artificial intelligence (AI), introduce novel risks in crisis management (Guthrie and Rich, 2022). Disinformation literature in security and computer science has assessed how previously introduced technologies have affected disinformation, demanding a systematic and coordinated approach for sustainable counter-disinformation efforts. However, there is a lack of theory-driven, evidence-based research and practice in public relations that advises how organizations can effectively and proactively manage risks and crises driven by AI (Guthrie and Rich, 2022).Design/methodology/approachAs a first step in closing this research-practice gap, the authors first synthesize theoretical and technical literature characterizing the effects of AI on disinformation. Upon this review, the authors propose a conceptual framework for disinformation response in the corporate sector that assesses (1) technologies affecting disinformation attacks and counterattacks and (2) how organizations can proactively prepare and equip communication teams to better protect businesses and stakeholders.FindingsThis research illustrates that future disinformation response efforts will not be able to rely solely on detection strategies, as AI-created content quality becomes more and more convincing (and ultimately, indistinguishable), and that future disinformation management efforts will need to rely on content influence rather than volume (due to emerging capabilities for automated production of disinformation). Built upon these fundamental, literature-driven characteristics, the framework provides organizations actor-level and content-level perspectives for influence and discusses their implications for disinformation management.Originality/valueThis research provides a theoretical basis and practitioner insights by anticipating how AI technologies will impact corporate disinformation attacks and outlining how companies can respond. The proposed framework provides a theory-driven, practical approach for effective, proactive disinformation management systems with the capacity and agility to detect risks and mitigate crises driven by evolving AI technologies. Together, this framework and the discussed strategies offer great value to forward-looking disinformation management efforts. Subsequent research can build upon this framework as AI technologies are deployed in disinformation campaigns, and practitioners can leverage this framework in the development of counter-disinformation efforts.
Globalization–health outcomes nexus and institutional intermediation in Nigeria
Authors: Omosuyi Oluseyi 
Published: August 2023

PurposeThe role institutional quality plays in the rising pace of globalization and its associated health effects remain unclear in the literature. This study, therefore, empirically examined the moderating role of institutional quality on the globalization-health outcomes nexus in Nigeria, a country with a relatively weak health system.Design/methodology/approachThe study employed Dynamic Ordinary Least Square (DOLS) to estimate the empirical models. The Fully Modified Ordinary Least Square (FMOLS) and Canonical Cointegration Regression (CCR) techniques were thereafter used to check the consistency and robustness of our results. Annual time-series data spanning from 1984 to 2020 were sourced from the World Development Indicator, KOF Globalization Index, International Countries Risk Guide (ICRG) and Central Bank of Nigeria Statistical Bulletin databases.FindingsThe results revealed that overall globalization and its three dimensional components (economic, political and social globalization) adversely affect life expectancy in their separate models, but increased life expectancy significantly after their interaction with government effectiveness. Also, real GDP, health aids, government recurrent health expenditure are other determinants of life expectancy in Nigeria.Practical implicationsThe Nigerian government should put in place appropriate mechanisms directed toward building and sustaining government effectiveness. This will help mitigate the negative effects of globalization and utilize its net positive benefits to improve life expectancy in Nigeria.Originality/valueThe research is the first to comprehensively examine the moderating impact of institutional quality on the nexus between overall globalization as well as its three dimensional components (economic, political and social) on health outcomes in Nigeria.
Performance differentials of necessity and opportunity entrepreneurs: through the lens of motivation to learn and female entrepreneurial competencies
Authors: Lingappa Anasuya Kulshekar , Rodrigues Lewlyn Lester Raj , Shetty Dasharathraj K. 
Published: August 2023

PurposeWomen entrepreneurs are often categorized and assessed for various outcomes based on their start-up motivations. It is generally assumed that entrepreneurs with opportunity motivation have better performance when compared to necessity entrepreneurs. This study aims to test these suppositions through the lens of the entrepreneur’s motivation to learn (MTL) and level of female entrepreneurial competencies (FECs), namely, business and management, entrepreneurial, human relations (HR) and personal.Design/methodology/approachData collected from 344 respondents through a survey questionnaire was analyzed using the structural equation modelling – partial least squares method using SmartPLS 4.FindingsThe findings highlight the need of recognizing the differentials between necessity and opportunity entrepreneurs as they were found to influence performance and learning outcomes. Opportunity entrepreneurship was found to significantly impact both MTL and the FECs. The authors also observed that business and management skills along with HR competencies played a greater role in the firm performance.Practical implicationsThe findings demonstrate a case for specialized, tailor-made policy approaches rather than the “one size fits all” approach as evident in many government programs. As necessity entrepreneurs form a vital part of the Indian entrepreneurial ecosystem, apart from mentoring, need-based competency development programs may be looked at. Opportunity entrepreneurs may need support and encouragement through advanced skilling and uncomplicated funding options.Originality/valueTo the best of the authors’ knowledge, empirical studies related to women-owned micro, small and medium enterprises in India establishing the relationship between start-up motivation and business performance are scarce. Even in the global context, this is one of the initial studies to examine the relationship through the lens of MTL and competencies.