Accurate identification of forest and grassland fire-prone areas is essential for effective fire management and ecosystem protection. This study aimed to evaluate the performance of two species distribution models, MaxEnt and Biomod2, in predicting forest grassland fire risks in Sichuan Province, and to accurately identify regions with high fire risk. Using fire occurrence data from 2011 to 2020 and relevant environmental variables, both models were applied to generate fire risk maps and identify key influencing factors. Model performance was assessed using the area under the receiver operating characteristic curve (AUC) and the true skill statistics (TSS). Results showed that the Biomod2 model outperformed MaxEnt, with the ensemble model EMwmean achieving the highest accuracy (AUC = 0.93, TSS = 0.71). Mean temperature and precipitation were the most influential variables, with human activity also playing a significant role. High-fire-risk areas were concentrated in southwestern Sichuan, the western populated zones, and the northern Sichuan Basin. We recommended that the MaxEnt model be considered when both model prediction accuracies are adequate for subsequent applications, or when only local fire point data are available and the global distribution must be predicted. Otherwise, the Biomod2 model is to be preferred.
This study conducts an in-depth review and Bowtie analysis of automation bias in AI-driven Clinical Decision Support Systems (CDSSs) within healthcare settings. Automation bias, the tendency of human operators to over-rely on automated systems, poses a critical challenge in implementing AI-driven technologies. To address this challenge, Bowtie analysis is employed to examine the causes and consequences of automation bias affected by over-reliance on AI-driven systems in healthcare. Furthermore, this study proposes preventive measures to address automation bias during the design phase of AI model development for CDSSs, along with effective mitigation strategies post-deployment. The findings highlight the imperative role of a systems approach, integrating technological advancements, regulatory frameworks, and collaborative endeavors between AI developers and healthcare practitioners to diminish automation bias in AI-driven CDSSs. We further identify future research directions, proposing quantitative evaluations of the mitigation and preventative measures.
In an economic environment characterized by rapid changes and significant technological innovations, the
printing industry in Romania is undergoing a period of transformation and adaptation. Although traditional, this
industry plays a vital role in the national economy by contributing to the production and distribution of cultural and
commercial goods. In the face of these transformations, risk management becomes a critical component for ensuring
the sustainability and competitiveness of firms in this sector. In our study, we will evaluate the economic performance
and associated risks of the top 20 companies operating in the Romanian printing industry, registered under the NACE
code 1812, selected based on their turnover in 2023. The analysis covers a seven-year period from 2017 to 2023,
providing a detailed assessment of the evolution of these companies. This comparison allows for a deep understanding
of the sector's dynamics and how different companies manage risks and optimize their financial performance. The
study is structured around three main classes of indicators: economic, profitability, and risk. Each class of indicators is
analyzed to identify significant trends and variations in company performance, as well as to assess the impact of risk
management strategies. Within the analysis of risk and profitability indicators, modern methods and techniques for risk
mitigation and profitability enhancement are introduced, aiming to provide practical and innovative solutions for
companies in the industry.
Commercial geography. Economic geography, Economics as a science
Landslides in mountainous regions are often triggered by vertical land movements induced by tectonics or seismic activities, emphasizing the importance of monitoring such motions for early intervention. This study investigates the impact of vertical land motion on landslide-prone districts in Himachal Pradesh, India. We employ Persistent Scatterer InSAR (PS-InSAR) technology to analyse vertical land motion in the region. Utilizing a dataset spanning six years (2017–2023), we provide precise measurements of land movements with millimetre-level accuracy. Our analysis reveals a range of deformation velocities, from −10 mm/year to +5 mm/year, with observed uplift of less than 31 mm and subsidence of up to 60 mm in the study area. These movements are attributed to prolonged wet conditions, illegal land mining, and ecological vulnerability. The findings underscore the necessity of continuous monitoring to mitigate landslide risks in mountainous regions, highlighting the efficacy of PS-InSAR technology in assessing such hazards.
Background. The relevance of the proposed methodology for recalling substandard products from the pharmaceutical market is determined by the requirements of GOST R ISO 9001-2015 and GOST R ISO 10393-2014. The aim of the work is to choose methods for identifying poor-quality products in the pharmaceutical market and develop a procedure for recalling them. Materials and methods. To solve this problem, the method of the matrix of consequences and probabilities was used according to the indicators "risk probability" and "risk impact level". Results. In the course of the work, a methodology was proposed for recalling poor-quality products from the pharmaceutical market, which is an integral part of the quality management system for pharmaceutical products. Conclusions. The positive results of the work open up the prospect of effective application of the methodology as a basis for organizing the recall management process in any pharmaceutical industry or for improving an existing process.
PurposeThis research addresses the lack of project management research into social procurement by exploring the risks and opportunities of social procurement from a cross-sector collaboration perspective.Design/methodology/approachA content analysis of five focus groups conducted with thirty-five stakeholders involved in the implementation of a unique social procurement initiative on a major Australian construction project is reported.FindingsResults show little collective understanding among project stakeholders for what social procurement policies can achieve, a focus on downside risk rather than upside opportunity and perceptions of distributive injustice about the way new social procurement risks are being managed. Also highlighted is the tension between the collaborative intent of social procurement requirements and the dynamic, fragmented and temporary project-based construction industry into which they are being introduced. Ironically, this can lead to opportunistic behaviours to the detriment of the vulnerable people these policies are meant to help.Practical implicationsThe paper concludes by presenting a new conceptual framework of project risk and opportunity management from a social procurement perspective. Deficiencies in the Project Management Body of Knowledge (PMBOK) are also highlighted around an expanded project management role in meeting these new project management requirements.Originality/valueSocial procurement is becoming increasingly popular in many countries as a collaborative mechanism to ensure construction and infrastructure projects contribute positively to the communities in which they are built. This research addresses the lack of project management research into social procurement by exploring the risks and opportunities of social procurement from a cross-sector collaboration perspective.
Muhammad Shafeeque, Arfan Arshad, Ahmed Elbeltagi
et al.
The strict lockdown measures not only contributed to curbing the spread of COVID-19 infection, but also improved the environmental conditions worldwide. The main goal of the current study was to investigate the co-benefits of COVID-19 lockdown on the atmosphere and aquatic ecological system under restricted anthropogenic activities in South Asia. The remote sensing data (a) NO2 emissions from the Ozone Monitoring Instrument (OMI), (b) Aerosol Optical Depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS), and (c) chlorophyll (Chl-a) and turbidity data from MODIS-Aqua Level-3 during Jan–Oct (2020) were analyzed to assess the changes in air and water pollution compared to the last five years (2015–2019). The interactions between the air and water pollution were also investigated using overland runoff and precipitation in 2019 and 2020 at a monthly scale to investigate the anomalous events, which could affect the N loading to coastal regions. The results revealed a considerable drop in the air and water pollution (30–40% reduction in NO2 emissions, 45% in AOD, 50% decline in coastal Chl-a concentration, and 29% decline in turbidity) over South Asia. The rate of reduction in NO2 emissions was found the highest for Lahore (32%), New Delhi (31%), Ahmadabad (29%), Karachi (26%), Hyderabad (24%), and Chennai (17%) during the strict lockdown period from Apr–Jun, 2020. A positive correlation between AOD and NO2 emissions (0.23–0.50) implies that a decrease in AOD is attributed to a reduction in NO2. It was observed that during strict lockdown, the turbidity has decreased by 29%, 11%, 16%, and 17% along the coastal regions of Karachi, Mumbai, Calcutta, and Dhaka, respectively, while a 5–6% increase in turbidity was seen over the Madras during the same period. The findings stress the importance of reduced N emissions due to halted fossil fuel consumption and their relationships with the reduced air and water pollution. It is concluded that the atmospheric and hydrospheric environment can be improved by implementing smart restrictions on fossil fuel consumption with a minimum effect on socioeconomics in the region. Smart constraints on fossil fuel usage are recommended to control air and water pollution even after the social and economic activities resume business-as-usual scenario.
Intensive pig production systems are a source of stress, which is linked to reduced animal welfare and increased antimicrobial use. As the gatekeepers of the welfare of the animals under their care, farmers are seen as the stakeholder responsible for improving animal welfare. The aim of this study was to explore the knowledge and attitudes of pig farmers towards pig welfare and the impact of such attitudes on farmers' selection of management strategies on the farm. We conducted in-depth semi-structured interviews with 44 pig farmers in one of the main pig producing regions of Brazil. Interviews covered knowledge and attitudes towards pig sentience and behaviour and welfare-related issues commonly observed in intensive pig farms (belly-nosing, fights, tail-biting, diarrhoea and castration without pain control) and farmers' conception and attitudes towards pig welfare. We identified many management and animal-based indicators of poor welfare, such as the use of painful and stressful management practices and use of environments that limit the expression of natural behaviours. However, most farmers were satisfied with animal welfare standards at their farms. Farmers' perceptions are aligned with their understanding of animal welfare. Although they identified all the dimensions that impact the welfare of a pig on a farm (affect, biological functioning and naturalness), their social reality, industry demands and available advice pushed them to perceive their range of action limited to biological and environmental aspects of the animals that do not necessarily benefit affective state. This precluded farmers from making associations between good health and the animal's ability to express a full behavioural repertoire, as well as from viewing abnormal behaviours as problems. The negative consequences for the welfare of the animals were commonly alleviated by routines that relied on constant use of medication, including high dependence on antibiotics. Expressions of estrangement from the production chain were common voices among the participants. This suggests that farmers may not be sufficiently informed or engaged in responding to consumers' expectations and commitments made by companies, which can pose a severe economic risk for farmers. The findings of this study indicate that economic, technical and social factors restrict farmers' autonomy and their ability to perform their role as stewards of animal welfare. (Re)connecting different human, animal and environmental interests may be a step to changing this scenario.
Francesca Coppola, Francesca Coppola, Lorenzo Faggioni
et al.
Artificial intelligence (AI) has seen dramatic growth over the past decade, evolving from a niche super specialty computer application into a powerful tool which has revolutionized many areas of our professional and daily lives, and the potential of which seems to be still largely untapped. The field of medicine and medical imaging, as one of its various specialties, has gained considerable benefit from AI, including improved diagnostic accuracy and the possibility of predicting individual patient outcomes and options of more personalized treatment. It should be noted that this process can actively support the ongoing development of advanced, highly specific treatment strategies (e.g., target therapies for cancer patients) while enabling faster workflow and more efficient use of healthcare resources. The potential advantages of AI over conventional methods have made it attractive for physicians and other healthcare stakeholders, raising much interest in both the research and the industry communities. However, the fast development of AI has unveiled its potential for disrupting the work of healthcare professionals, spawning concerns among radiologists that, in the future, AI may outperform them, thus damaging their reputations or putting their jobs at risk. Furthermore, this development has raised relevant psychological, ethical, and medico-legal issues which need to be addressed for AI to be considered fully capable of patient management. The aim of this review is to provide a brief, hopefully exhaustive, overview of the state of the art of AI systems regarding medical imaging, with a special focus on how AI and the entire healthcare environment should be prepared to accomplish the goal of a more advanced human-centered world.
The sustainability of the tour operators’ activity is the basis of this industry stability. In recent years, the crisis in the tourism industry manifested by a series of bankruptcies of major tour operators became apparent due to the fact that it badly affected a large number of Russian tourists, and this, in turn, caused a great resonance in the society. Development and promotion of travel products is private business. Under market conditions implementing of internal control within the management system of the tourist industry is an additional instrument of providing for financial and economic stability. The purpose of the article is to justify the necessity to formalize the approaches to tour operator internal control system functioning on the basis of the Russian legal requirements and international experience, which is mostly demanded in the frames of the risk-based government oversight. The theoretical basisof the research is the papers of economists on the related problems. The empirical base for the study is the Russian normative acts and international practice.
Sphiwe E. Mhlongo, Francis Amponsah-Dacosta, Confidence Muzerengi
et al.
Abandoned gold mine sites are generally characterised by severe environmental problems and physical hazards. Because of socio-economic problems confronting communities around abandoned mine sites, historic and abandoned gold mines have become hot-spots for artisanal and small-scale miners. These mining activities at times thwart the efforts of rehabilitation at these sites. This article details how artisanal mining operations have frustrated rehabilitation efforts of abandoned mine shafts in the Sutherland goldfield. The field investigation of abandoned shafts and analysis of the nature of artisanal mining operations in the Sutherland goldfield revealed that artisanal mining involving digging around collars of sealed shafts is a major threat to the stability of the shafts and their sealing structures. In addition, artisanal mining operations have increased the safety risks of the abandoned shafts in the area. This has also been worsened by the fact that a large number of people, especially women and children, are exposed to the hazards of the abandoned mine sites. This article emphasises an urgent need for the development of holistic and cohesive strategies for dealing with the problems of abandoned gold mine shafts wherever they exist in the country as opposed to simply closing them up.
The cause-effect relationships between performance dimensions were assessed using a multivariate linear regression. The author analyzes the strategic behavior of Russian football clubs using the profit/win maximization classification. The causality tests allowed the author to form a conceptual model of the main performance dimensions of professional football clubs in Russia. The results help better understand the managerial pitfalls in Russian club football. The article contributes to the literature on organizational performance of professional football clubs by focusing on the Russian context, which has not been done previously. The findings of the paper confront the managerial fallacies of Russian club football and broaden the understanding of club football management practices in general.
Today, innovation is perceived as a source of competitive advantage for firms, playing a vital role in both the survival and growth of firms. A general look at the existing literature on innovation points toward a lack of studies that explore the risk and reward topic in the conformation of innovation portfolios in a firm. Hence, the main purpose of the present paper is to analyse the relationship between investment in innovation and the gain of the process and how this relationship is affected by the type of industry in which the firm operates and by the intervention of the authorities (legal protection of innovation). Among others, results indicate that, contrary to what could be expected, firms would tend to invest in disruptive innovation projects in hard innovative industries, wherein the potential, disruptive innovation is much harder to generate given the natural protection against potential competition that characterizes these industries. On the other hand, investment in disruptive innovation in soft innovative industries would require a framework of legal protection in accordance with the level of natural innovativeness of the industry. In terms of practical implications, the management of the legal protection would be socially desirable for achieving a balanced innovation development framework in the economy, as well as for resource allocations in disruptive innovation in industries where, although it is easier to be successful, its usufruct is difficult.