bluuebunny/crossref_metadata_2025 huggingface dataset:
Reliability and Detectability of Emergency Management Systems in Smart Cities under Common Cause Failures
Authors: Jesus Thiago C. , Portugal Paulo , Costa Daniel G. , Vasques Francisco
Published: May 2024

Urban areas are undergoing significant changes with the rise of smart cities, with technology transforming how cities develop through enhanced connectivity and data-driven services. However, these advancements also bring new challenges, especially in dealing with urban emergencies that can disrupt city life and infrastructure. The emergency management systems have become crucial elements for enabling cities to better handle urban emergencies, although ensuring the reliability and detectability of such system remains critical. This article introduces a new method to perform reliability and detectability assessments. By using Fault Tree Markov chain models, this article evaluates their performance under extreme conditions, providing valuable insights for designing and operating urban emergency systems. These analyses fill a gap in the existing research, offering a comprehensive understanding of emergency management systems functionality in complex urban settings.
Integration of Smart City Technologies with Advanced Predictive Analytics for Geotechnical Investigations
Authors: Cong Yuxin , Inazumi Shinya
Published: May 2024

This paper addresses challenges and solutions in urban development and infrastructure resilience, particularly in the context of Japan’s rapidly urbanizing landscape. It explores the integration of smart city concepts to combat land subsidence and liquefaction, phenomena highlighted by the 2011 Great East Japan Earthquake. Additionally, it examines the current situation and lack of geoinformation and communication technology in the concept of smart cities in Japan. Consequently, this study employs advanced technologies, including smart sensing and predictive analytics through kriging and ensemble learning, with the objective of enhancing the precision of geotechnical investigations and urban planning. By analyzing data in Setagaya, Tokyo, it develops predictive models to accurately determine the depth of bearing layers that are critical to urban infrastructure. The results demonstrate the superiority of ensemble learning in predicting the depth of bearing layers. Two methods have been developed to predict undetected geographic data and prepare ground reality and digital smart maps for the construction industry to build smart cities. This study is useful for real-time analysis of existing data, for the government to make new urban plans, for construction companies to conduct risk assessments before doing their jobs, and for individuals to obtain real-time geographic data and hazard warnings through mobile phones and other means in the future. To the best of our knowledge, this is the first instance of predictive analysis of geographic information being conducted through geographic information, big data technology, machine learning, integrated learning, and artificial intelligence.
To Retire or Not to Retire? A Comprehensive Examination of Retirement Decision Dynamics in Italy
Authors: Fabiani Michele
Published: May 2024

The concept of active aging has become central to the public debate in many Western countries, given the increasing aging of the population and the future challenges associated with it. This phenomenon is tightly intertwined with choices regarding the retirement period, which can be postponed for different reasons by individuals in a society. The purpose of this paper is to understand the personal and family characteristics that influence future choices about retirement date in Italy. Utilizing data provided by the Bank of Italy in the Survey on Household Income and Wealth (SHIW), a logistic regression is performed to observe the impact of different covariates on the hypothesized retirement date of individuals close to retirement, i.e., over the age of 50 who are still in working status. The results show that the decision to delay retirement has increased in recent years, and is influenced by personal (e.g., matrimonial status), work, and economic factors. In addition, these factors have different impacts between males and females.
Generalizability Theory in the Evaluation of Psychological Profile in Track and Field
Authors: Sanz-Fernández Cristina , Morales-Sánchez Verónica , Castellano Julen , Mendo Antonio Hernández
Published: May 2024

Generalizability theory (GT) has been used throughout the scientific literature to ensure validity, reliability, and generalizability in different sport contexts. However, there is a small number of studies examining the measurement of psychological profiles in sport from this perspective. Therefore, this study’s main goal is the sources of variability and the optimal measurement design estimation for a good assessment of the psychological profile in track and field. The sample consisted of 470 participants (age: Average= 32.1; Standar Desviation = 13.5). The analysis of variance and generalizability component analysis has been performed in order to test the reliability and generalizability of the sample. The profile included the following variables: flow, motivation (from Self-Determination Theory and Achievement Goals), self-confidence, and psychological skills. Results confirm that the sample has a high degree of reliability and generalizability in all the tested models. So, a detailed study on the validity, reliability, and generalizability of samples and measures should be an inherent element in the practice of psychological counseling in sports.
Scientific and Practical Challenges for the Development of a New Approach to the Simulation of Remanufacturing
Authors: Pawlewski Pawel
Published: May 2024

This article explores the scientific and practical challenges associated with developing simulation modeling methods for remanufacturing within a circular economy framework. It aims to define this concept and identify the key hurdles that need to be overcome for its successful implementation. According to the six principles of sustainable development, the key pillar is remanufacturing. Remanufacturing helps the environment in several different ways, including: saving energy, the conservation of raw materials, the conservation of space, landfills, the reduction of air pollution, and greater fuel efficiency. This process closes the loop in the supply chain, exemplifying the principles of a circular economy. The research methods used are primarily the analysis and criticism of literature, document examination—especially in relation to existing simulation programs and analysis—the logical construction method, and the heuristic method, used to define concept of simulation modelling. In response to scientific and practical challenges, the concept of a new modeling method was defined and presented. This concept uses the legacy of Lean and the author’s original ideas regarding the structuring of the remanufacturing factory and processes. The main contribution of this study is integration, embedding this concept into the simulation software. A comparison with existing solutions and the advantages of the new concept are also included in the article.
Always with the Best Intentions? Interrogating the Use of Sustainable Building Assessment Systems in Developing Countries: Kenya
Authors: Chelang’at Faith Ng’eno , Lawrence Ranald
Published: May 2024

Assessment methodologies such as BREEAM and LEED allocate points based on prescribed interventions that promote design features or strategies considered to be more sustainable than others. A focus on accumulating numerical scores, however, often fails to address pertinent contextual issues, particularly within developing countries. This paper examines the use of four assessment systems in Kenya—two international systems, LEED-US and Green Star SA-Kenya; and two locally developed systems, Green Mark Kenya and the Safari Green Building Index. The paper compares the relative weighting of different categories under each system, and assesses their appropriateness to a Kenyan context, with reference to the suitability of active technology versus passive design approaches. The paper examines selected examples of ‘green’ buildings in Nairobi, reflecting on the influence of different methods of assessment on the adopted design approaches. The paper argues that international rating systems, such as LEED, often focus on a Western construct of sustainability featuring a systematic bias towards global rather than local perspectives, with an emphasis on physical environmental factors. In pursuit of objectivity, the measurement of non-contextual parameters untailored to local circumstances (e.g., energy performance) is prioritised at the expense of those contingent on local conditions or climate.
Characterizing Land Surface Temperature (LST) through Remote Sensing Data for Small-Scale Urban Development Projects in the Gulf Cooperation Council (GCC)
Authors: Ahmed Maram , Aloshan Mohammed A. , Mohammed Wisam , Mesbah Essam , Alsaleh Naser A. , Elghonaimy Islam
Published: May 2024

In the context of global climate change, there is a projected increase in land surface temperature (LST) worldwide, amplifying its impacts. This poses a particular concern for countries with hot climates, including the Kingdom of Bahrain as an example for the Gulf Cooperation Council countries (GCC), which are countries with a hot climate. With a surge in population growth, there is a heightened demand for land to accommodate additional residential developments, creating an opportunity to investigate the influence of land use changes on LST variations. To achieve this goal, a residential development project spanning from 2013 to 2023 was undertaken. Landsat 8 OLI/TIRS remote sensing datasets were selected for four climate seasons, each set comprising images before and after development. The analysis involved extracting the LST, Normalized Difference Vegetation Index (NDVI), and Normalized Difference Built-Up Index (NDBI) on various dates, followed by correlation and regression analyses to explore their interrelationships. The results revealed a significant increase in the mean LST during spring and autumn post-development. A consistent positive association between the LST and NDBI was observed across all seasons, strengthening after development completion. Conversely, there was a pre-development negative correlation between the LST and NDVI, shifting to a positive relationship post-development. These findings empirically support the idea that small-scale residential developments contribute to notable LST increases, primarily due to expanded impervious surfaces. These insights have the potential to inform localized adaptation strategies for small-scale residential development projects, crucial for managing the impacts of rising land surface temperatures.
Developing a Measurement Framework for Ethiopian Dry Port Sustainability: An Empirical Study
Authors: Beyene Zellalem Tadesse , Nadeem Simon Peter , Jaleta Matiwos Ensermu
Published: May 2024

In the context of a dry port, sustainable operations involve developing and implementing policies and procedures that reduce adverse effects on the environment, advance economic viability, and strengthen social responsibility. Several factors contribute to achieving environmental, economic, and social sustainability, making it critical to identify the factors influencing the sustainability of dry port operations. This research aims to identify decisive factors associated with economic, social, and environmental sustainability, and to develop a framework for measuring sustainability in dry port operations. The research utilises exploratory factor analysis (EFA) and the analytical hierarchical process (AHP) to develop a measurement framework for assessing the sustainability of Ethiopian dry ports. EFA is an effective method with which to identify factors that contribute to sustainable dry port operations. To provide a frame for the critical sustainability performance metrics for dry ports, the AHP approach was used. Data were collected from 300 stakeholders using surveys to identify key factors, and 20 senior experts were involved in validating and rating the most influential factors determining dry port sustainability. This research asserts the most pertinent factors guiding dry port sustainability operations, resource allocation, and decision-making. From an environmental sustainability perspective, critical factors include minimising business-partner impacts, reducing waste, addressing climate change, providing environmental planning education to teams, and implementing measures to protect the national environment. From a social perspective, the factors identified include a resettlement policy, employment opportunities for the community, workplace safety, stakeholder consultation, and top-management guidance. From an economic standpoint, critical factors include value-added services, reduced transportation costs, decreased time, enhanced productivity in the trade supply chain, and profit orientation. The research provides valuable insights with which to guide the development of practices and policies aimed at ensuring sustainable dry port operations, a critical domain of the trade supply chain.
Lattice-Boltzmann-Method-Based Numerical Simulation for Heavy Metal Migration Process during Deep-Sea Mining
Authors: Yin Lei , Chen Dongdong , Yang Yunqi , Wei Xuedan , Dai Houping , Zeng Juan , Huo Hanxin
Published: May 2024

During deep-sea mining, heavy metal pollutants can cause contamination in the marine environment. In this paper, the multiphasic coupling model is established to describe the heavy metal migration process during deep-sea mining, which takes the effects of the convection–diffusion, adsorption–desorption, and sedimentation–resuspension of heavy metals in the aquatic environment into full consideration. Due to the advantages of the Lattice Boltzmann method, it is adopted to numerically solve the multiphasic coupling model and achieve the simulation of the heavy metal migration process during deep-sea mining. In addition, taking cadmium as an example, the concentration variations are discussed and analyzed in detail. Based on the established model and Lattice Boltzmann method, the concentration distribution of heavy metals can be accurately described to provide the reasonable bases for the evaluation of marine environmental protection.
Exploring the Dynamics of Dark and Singular Solitons in Optical Fibers Using Extended Rational Sinh–Cosh and Sine–Cosine Methods
Authors: Muniyappan Annamalai , Manikandan Kannan , Saparbekova Akbota , Serikbayev Nurzhan
Published: May 2024

This investigation focuses on the construction of novel dark and singular soliton solutions for the Hirota equation, which models the propagation of ultrashort light pulses in optical fibers. Initially, we employ a wave variable transformation to convert the physical model into ordinary differential equations. Utilizing extended rational sinh–cosh and sine–cosine techniques, we derive an abundant soliton solution for the transformed system. By plugging these explicit solutions back into the wave transformation, we obtain dark and singular soliton solutions for the Hirota equation. The dynamic evolution of dark soliton profiles is then demonstrated, with a focus on varying physically significant parameters such as wave frequency, strength of third-order dispersion, and wave number. Furthermore, a comprehensive analysis is examined to elucidate how the dark and singular soliton profiles undergo deformation in the background influenced by these arbitrary parameters. The findings presented in this study offer valuable insights that could potentially guide experimental manipulation of dark solitons in optical fibers.
Fractional Stochastic Partial Differential Equations: Numerical Advances and Practical Applications—A State of the Art Review
Authors: Moghaddam Behrouz Parsa , Babaei Afshin , Dabiri Arman , Galhano Alexandra
Published: May 2024

This article aims to provide a comprehensive review of the latest advancements in numerical methods and practical implementations in the field of fractional stochastic partial differential equations (FSPDEs). This type of equation integrates fractional calculus, stochastic processes, and differential equations to model complex dynamical systems characterized by memory and randomness. It introduces the foundational concepts and definitions essential for understanding FSPDEs, followed by a comprehensive review of the diverse numerical methods and analytical techniques developed to tackle these equations. Then, this article highlights the significant expansion in numerical methods, such as spectral and finite element methods, aimed at solving FSPDEs, underscoring their potential for innovative applications across various disciplines.
Assessment of Non-Coplanar Maneuver Parameters and Perturbing Accelerations Using the Minimal Number of Observations
Authors: Baranov Andrey
Published: May 2024

The algorithms for determining the active space object maneuver parameters in the conditions of near-circular orbits are presented in the paper. The right ascension and declination angles are used to determine the parameters of a single maneuver with transversal and lateral components (the application moment and the velocity impulse magnitude). Two pairs of angles are used to determine the parameters of the maneuver with only a lateral component. Two pairs of angles are needed for the determination of the parameters of the long-duration maneuver performed by a low-thrust engine (moments of the maneuver start and finish, and components of the acceleration delivered by the engine). The essential detail that makes it possible to determine the parameters of long-duration maneuvers is their symmetry relative to the center of the engine operating interval. Considerable perturbing accelerations, which are not accounted for by traditional perturbing models, affect passive objects, especially membranous objects with a big and variable area-to-mass ratio. This decreases dramatically the accuracy of these objects’ motion propagation. In this paper, the magnitude of perturbing acceleration is determined with the assumption that it is constant and is active throughout the whole time interval from the moment of the last orbit determination to the moment of the new measurement used. Examples of the assessment of maneuvers performed by an object in the geostationary orbit are presented.
A Geometric Approach to the Sundman Transformation and Its Applications to Integrability
Authors: Cariñena José F.
Published: May 2024

A geometric approach to the integrability and reduction of dynamical systems, both when dealing with systems of differential equations and in classical physics, is developed from a modern perspective. The main ingredients of this analysis are infinitesimal symmetries and tensor fields that are invariant under the given dynamics. A particular emphasis is placed on the existence of alternative invariant volume forms and the associated Jacobi multiplier theory, and then the Hojman symmetry theory is developed as a complement to the Noether theorem and non-Noether constants of motion. We also recall the geometric approach to Sundman infinitesimal time-reparametrisation for autonomous systems of first-order differential equations and some of its applications to integrability, and an analysis of how to define Sundman transformations for autonomous systems of second-order differential equations is proposed, which shows the necessity of considering alternative tangent bundle structures. A short description of alternative tangent structures is provided, and an application to integrability, namely, the linearisability of scalar second-order differential equations under generalised Sundman transformations, is developed.
Sustainability under Active Inference
Authors: Albarracin Mahault , Ramstead Maxwell , Pitliya Riddhi J. , Hipolito Ines , Da Costa Lancelot , Raffa Maria , Constant Axel , Manski Sarah Grace
Published: May 2024

In this paper, we explore the known connection among sustainability, resilience, and well-being within the framework of active inference. Initially, we revisit how the notions of well-being and resilience intersect within active inference before defining sustainability. We adopt a holistic concept of sustainability denoting the enduring capacity to meet needs over time without depleting crucial resources. It extends beyond material wealth to encompass community networks, labor, and knowledge. Using the free energy principle, we can emphasize the role of fostering resource renewal, harmonious system–entity exchanges, and practices that encourage self-organization and resilience as pathways to achieving sustainability both as an agent and as a part of a collective. We start by connecting active inference with well-being, building on existing work. We then attempt to link resilience with sustainability, asserting that resilience alone is insufficient for sustainable outcomes. While crucial for absorbing shocks and stresses, resilience must be intrinsically linked with sustainability to ensure that adaptive capacities do not merely perpetuate existing vulnerabilities. Rather, it should facilitate transformative processes that address the root causes of unsustainability. Sustainability, therefore, must manifest across extended timescales and all system strata, from individual components to the broader system, to uphold ecological integrity, economic stability, and social well-being. We explain how sustainability manifests at the level of an agent and then at the level of collectives and systems. To model and quantify the interdependencies between resources and their impact on overall system sustainability, we introduce the application of network theory and dynamical systems theory. We emphasize the optimization of precision or learning rates through the active inference framework, advocating for an approach that fosters the elastic and plastic resilience necessary for long-term sustainability and abundance.
Digitalization as a Factor of Production in China and the Impact on Total Factor Productivity (TFP)
Authors: Li Pei , Liu Jinyi , Lu Xiangyi , Xie Yao , Wang Ziguo
Published: May 2024

In the digital transformation era, digitalization integrates deeply into production, bolstering output efficiency and economic value. Through stochastic frontier analysis (SFA), this research positions digitalization as an input in the production function, dissecting its elasticity impact on capital, labor, and output. The effect of digitalization on total factor productivity change (TFPC) is explained by comparing TFPC with and without digitalization. Findings reveal that digitalization’s integration into economic growth displays a U-shaped trajectory, with initial productivity setbacks transitioning to long-term benefits as industries adapt. The periodic complementarity and substitution between digitalization and labor, along with a weak substitution relationship with capital, illustrate that, as a production factor, digitalization dynamically interacts with other factors, both complementing and substituting them. This dynamic interplay highlights the intricate role that digitalization plays within the production function. Furthermore, digitalization has played a crucial role in China’s TFP growth, which also highlights the lack of other technological progress. Meanwhile, the pace of digital transformation presents scalability challenges, evident in the fluctuating scale efficiency change (SEC). Policymakers are advised to address these early stage challenges through supportive measures, ensuring smoother digital transitions. Concurrently, industries should embrace this non-linear transformation, emphasizing adaptability to maximize digitalization’s long-term advantages.
Transforming Cybersecurity into Critical Energy Infrastructure: A Study on the Effectiveness of Artificial Intelligence
Authors: Govea Jaime , Gaibor-Naranjo Walter , Villegas-Ch William
Published: May 2024

This work explores the integration and effectiveness of artificial intelligence in improving the security of critical energy infrastructure, highlighting its potential to transform cybersecurity practices in the sector. The ability of artificial intelligence solutions to detect and respond to cyber threats in critical energy infrastructure environments was evaluated through a methodology that combines empirical analysis and artificial intelligence modeling. The results indicate a significant increase in the threat detection rate, reaching 98%, and a reduction in incident response time by more than 70%, demonstrating the effectiveness of artificial intelligence in identifying and mitigating cyber risks quickly and accurately. In addition, implementing machine learning algorithms has allowed for the early prediction of failures and cyber-attacks, significantly improving proactivity and security management in energy infrastructure. This study highlights the importance of integrating artificial intelligence into energy infrastructure security strategies, proposing a paradigmatic change in cybersecurity management that increases operational efficiency and strengthens the resilience and sustainability of the energy sector against cyber threats.
Biological Monitoring of Glyphosate Exposure among Knapsack Sprayers in Khon Kaen, Thailand
Authors: Chaiklieng Sunisa , Uengchuen Kodchakorn , Gissawong Netsirin , Srijaranai Supalax , Autrup Herman
Published: May 2024

Sprayers’ exposure to glyphosate was analyzed through detection of its biomarker in spot urine biological monitoring, and the health risk was assessed using the biomatrix model. Urine samples were collected from 15 sprayers after spraying, and the glyphosate concentration was determined by using the DLLME-HPLC method with a UV detector. The calibration curve for glyphosate was linear in the range of 0.4–100 µg/L, while the limits of detection and quantification were 0.1 µg/L and 0.4 µg/L, respectively. The human health risk was estimated using the hazard quotient (HQ) and the biomatrix of risk assessment. The internal dose ranged from 0.0001 to 0.0021 mg/kg b.w./day. The non-cancer HQ showed no potential health risk concerns (HQ < 1). The biomatrix of health risk assessment, based on urinary glyphosate concentration, exhibited a strong correlation with the health risk matrix model. This correlation was determined by considering the likelihood of exposure, calculated from the quantity of glyphosate used and the usage of personal protective equipment (r = 0.854, p < 0.001). Although low risk was observed in sprayers, proper PPE use and the application of more knowledge are required. The simplified health risk assessment can be used for easy self-assessment of risk in preventive action regarding health risk awareness among sprayers.
Droplet Digital RT-PCR (dd RT-PCR) Detection of SARS-CoV-2 in Honey Bees and Honey Collected in Apiaries across the Campania Region
Authors: Mancusi Andrea , Proroga Yolande Thérèse Rose , Maiolino Paola , Marrone Raffaele , D’Emilio Claudia , Girardi Santa , Egidio Marica , Boni Arianna , Vicenza Teresa , Suffredini Elisabetta , Power Karen
Published: May 2024

Coronaviruses (CoVs), a subfamily of Orthocoronavirinae, are viruses that sometimes present a zoonotic character. Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is responsible for the recent outbreak of COVID-19, which, since its outbreak in 2019, has caused about 774,593,066 confirmed cases and 7,028,881 deaths. Aereosols are the main route of transmission among people; however, viral droplets can contaminate surfaces and fomites as well as particulate matter (PM) in suspensions of natural and human origin. Honey bees are well known bioindicators of the presence of pollutants and PMs in the environment as they can collect a great variety of substances during their foraging activities. The aim of this study was to evaluate the possible role of honey bees as bioindicators of the prevalence SARS-CoV-2. In this regard, 91 samples of honey bees and 6 of honey were collected from different apiaries of Campania region (Southern Italy) in four time periods from September 2020 to June 2022 and were analyzed with Droplet Digital RT-PCR for SARS-CoV-2 target genes Orf1b and N. The screening revealed the presence of SARS-CoV-2 in 12/91 in honey bee samples and in 2/6 honey samples. These results suggest that honey bees could also be used as indicators of outbreaks of airborne pathogens such as SARS-CoV-2.
Vaccine Effectiveness against GP-Attended Symptomatic COVID-19 and Hybrid Immunity among Adults in Hungary during the 2022–2023 Respiratory Season Dominated by Different SARS-CoV-2 Omicron Subvariants
Authors: Horváth Judit Krisztina , Túri Gergő , Krisztalovics Katalin , Kristóf Katalin , Oroszi Beatrix
Published: May 2024

Hungary provides the opportunity to evaluate the effectiveness of COVID-19 vaccination in a setting where naturally acquired immunity and hybrid immunity are likely to play a greater role due to suboptimal vaccination coverage. Methods: A test-negative study was conducted during the 2022–2023 respiratory season at the primary care level to determine the effectiveness of at least one COVID-19 booster dose in preventing medically attended symptomatic RT-PCR-confirmed SARS-CoV-2 infection in adults. Unvaccinated patients were used as a reference group. Results: A total of 247 cases and 1073 controls were included in the analysis. CVE was 56.8% (95% CI: 11.9–78.8%) in the population aged 60 years and older and 2.3% (95% CI: −50.0–36.3%) in the younger adults against COVID-19 caused by Omicron subvariants, mainly BA.5, BQ.1, and XBB.1. Self-reported COVID-19 in the 60–365 days prior to the current illness did not confer protection against reinfection without vaccination, but together with booster vaccination, it reduced the risk of COVID-19 by 63.0% (95% CI: −28.0–89.3%) and 87.6% (95% CI: 26.4–97.9%) among the 18–59 and 60+ age groups, respectively. Conclusions: CVE against COVID-19 was moderately high in the 60+ age groups. Because of the benefit of hybrid immunity, persons with previous SARS-CoV-2 infection should still be considered for vaccination campaigns.
Numerical Analysis of the Stress Shadow Effects in Multistage Hydrofracturing Considering Natural Fracture and Leak-Off Effect
Authors: Song Jinxin , Qiao Qing , Chen Chao , Zheng Jiangtao , Wang Yongliang
Published: May 2024

As a critical technological approach, multistage fracturing is frequently used to boost gas recovery in compact hydrocarbon reservoirs. Determining an ideal cluster distance that effectively integrates pre-existing natural fractures in the deposit creates a fracture network conducive to gas movement. Fracturing fluid leak-off also impacts water resources. In our study, we use a versatile finite element–discrete element method that improves the auto-refinement of the grid and the detection of multiple fracture movements to model staged fracturing in naturally fractured reservoirs. This computational model illustrates the interaction between hydraulic fractures and pre-existing fractures and employs the nonlinear Carter leak-off criterion to portray fluid leakage and the impacts of hydromechanical coupling during multistage fracturing. Numerical results show that sequential fracturing exhibits the maximum length in unfractured and naturally fractured models, and the leak-off volume of parallel fracturing is the smallest. Our study proposes an innovative technique for identifying and optimizing the spacing of fracturing clusters in unconventional reservoirs.
Advanced Uncertainty Quantification for Flood Inundation Modelling
Authors: Aitken Gordon , Beevers Lindsay , Christie Mike A.
Published: May 2024

Flood hazards present a significant risk to the UK, with homes, businesses and critical infrastructure exposed to a mixture of fluvial, surface water and coastal flooding. Climate change is expected to influence river flows, changing the frequency and magnitude of future flood events. Flood hazard assessments are used by decision-makers to implement policies and engineering interventions to reduce the impacts of these flood events. Probabilistic flood modelling can explore input and parameter uncertainties in flood models to fully quantify inundation uncertainty. However, probabilistic methods require large computational costs—limiting their application. This paper investigates a range of advanced uncertainty quantification methods (traditional Monte Carlo (FMC), Kriging and multi-fidelity Monte Carlo (MFMC)) to reduce the dichotomy between accuracy and costs. Results suggest that Kriging can reduce computational costs by 99.9% over FMC. The significantly increased efficiency has the potential to improve future policy and engineering decisions, reducing the impacts of future flood events.
Cladocera and Geochemical Variables from Core Sediments Show Different Conditions of Hungarian Lakes
Authors: Gyulai István , Korponai János , Wamugi Sheila Mumbi A. , Jakab Jázmin , Kawu Umar Abba , Soltész Andor G. , Karches Tamás , Tumurtogoo Uyanga
Published: May 2024

Studies on the sediments of lakes with varying trophic status are of particular importance when considering changes in the natural environment. In this study, our objective was to examine subfossil remains of Cladocera species and the relationship between the sedimental Cladocera assemblages and geochemical variables during 11 years of sediment records from northern Hungarian lakes. To achieve this, we compared sedimental cladoceran communities and the geochemistry of the sediment layers among lakes. Among the studied lakes, one was an intermittent lake (KMT: the Kis-Morotva Lake) which dried out in 2012 but was subsequently naturally refilled in 2013 by groundwater affected by the high-water level of the River Tisza. The other type consisted of permanent lakes (SZA: the Szabolcs oxbow lake, TI: the Timár Morotva Lake) that never dried out. The results of the beta diversity analysis show that the deposition of Cladocera communities was similar among the sediment layers of lakes, while the abundance differences contributed significantly to replacement. Subsequently, core sediment samples of the three lakes were compared based on the remains of Cladocera communities and geochemical variables using Adonis (PERMANOVA). The core sediment samples indicate variations in Cladocera communities alongside disparities in geochemical variables across the same lakes. In conclusion, the significance of sediment cores containing the remains of the Cladocera community has grown significantly in the reconstruction of historical ecological and climatic changes.
Dr. Stone
Authors: Magaldi Carolina Alves , Mendes Lucas Alves
Published: May 2024

O presente artigo conduz uma discussão acerca dos enlaces entre letramento, construção de conhecimento científico e arte, a partir do mangá e anime Dr. Stone. Na obra japonesa, um grupo de pessoas, petrificadas no momento atual, desperta no ano 5738, voltando a habitar uma nova realidade do planeta Terra, desprovida de tecnologias ou recursos científicos modernos. Em nosso estudo, apresentaremos o desenvolvimento da narrativa, analisando-a a partir de pressupostos teóricos do campo do letramento (SOARES, 1998, 2014), do letramento científico (PITRELLI, 2003; SANTOS, 2020) e de suas relações com a arte e as relações interpessoais (KAHN e ZEIDLER, 2016). A discussão dos quatro grandes experimentos realizados no primeiro arco narrativo da obra nos permite problematizar como o mangá explora os elementos artísticos e as conexões linguístico-sociais entre os personagens como elementos indissociáveis da construção de conhecimento científico.
Achados audiológicos de frentistas expostos a combustíveis
Authors: Zucki Fernanda , Duarte Josilene Luciene , Morata Thais Catalani , Jacob Lilian Cássia Bórnia , Roggia Simone Mariotti , Tsunemi Miriam Harumi , Alvarenga Kátia de Freitas
Published: May 2024

Introdução. O histórico de exposição ocupacional geralmente é mal documentado. Os dados fisiológicos apontam para uma combinação de processos de cocleotoxicidade e neurotoxicidade subjacentes aos efeitos auditivos observados nas exposições a solventes. Assim, a caracterização do risco de exposição a solventes é necessária para desenvolver e implementar medidas diagnósticas e preventivas eficazes. Objetivo. Avaliar o sistema auditivo periférico e central de frentistas expostos a combustíveis. Método. Este estudo transversal utilizou uma bateria de testes que incluiu audiometria tonal liminar (ATL), imitância acústica, potencial evocado auditivo de tronco encefálico (PEATE) e potencial evocado auditivo cognitivo (P300). Um grupo não exposto incluiu 23 participantes sem exposições conhecidas a ruído, combustíveis ou solventes. O grupo exposto a combustíveis incluiu 21 frentistas que foram expostos a combustível e solventes. Resultados. Apenas 2 dos 24 frentistas apresentaram audição normal em todos os testes. Individualmente, o reflexo acústico estapediano apresentou o maior número de alterações, com diferenças significativas entre os grupos, para os resultados do reflexo acústico estapediano ipsilateral da orelha direita e contralateral da orelha esquerda para o grupo não exposto. Resultados anormais do PEATE e reflexo acústico estapediano podem ser detectados antes das anormalidades de P300 e ATL. Conclusão. Foram observadas alterações auditivas caracterizadas por comprometimento do sistema auditivo periférico e/ou central, sugerindo ação tóxica da exposição aos combustíveis. Mais pesquisas são necessárias para melhor caracterizar os danos às vias auditivas centrais induzidos por combustíveis e para identificar uma bateria de testes audiológicos ideal para uso com este grupo de indivíduos.
Ar-CM-ViMETA: Arabic Image Captioning based on Concept Model and Vision-based Multi-Encoder Transformer Architecture
Authors: Osman Asmaa , Shalaby Mohamed , Soliman Mona , Elsayed Khaled
Published: May 2024

Image captioning is a major artificial intelligence research field that involves visual interpretation and linguistic description of a corresponding image. Successful image captioning relies on acquiring as much information as feasible from the original image. One of these essential bits of knowledge is the topic or the concept that the image is associated with. Recently, concept modeling technique has been utilized in English image captioning for completely capturing the image contexts and make use of these contexts to produce more accurate image descriptions. In this paper, a concept-based model is proposed for Arabic Image Captioning (AIC). A novel Vision-based Multi-Encoder Transformer Architecture (ViMETA) is proposed for handling the multi-outputs result from the concept modeling technique while producing the image caption. BiLingual Evaluation Understudy (BLEU) and Recall-Oriented Understudy for Gisting Evaluation (ROUGE) standard metrics have been used to evaluate the proposed model using the Flickr8K dataset with Arabic captions. Furthermore, qualitative analysis has been conducted to compare the produced captions of the proposed model with the ground truth descriptions. Based on the experimental results, the proposed model outperformed the related works both quantitatively, using BLEU and ROUGE metrics, and qualitatively
Impact of mobile apps in higher education: Evidence on learning
Authors: Palshkov Kostiantyn , Shetelya Natalia , Khlus Nataliia , Vakulyk Iryna , Khyzhniak Inna
Published: May 2024

The article reveals the main advantages of using mobile applications in the educational process and shows their significance in increasing the level of knowledge and skills of higher education students; elements of the content of mobile learning are revealed; didactic principles are singled out and factors that educational mobile applications must meet are grouped; didactic features of mobile applications are shown in the educational process of a higher school. The methodological basis of the study is the general theoretical and methodological provisions of philosophy regarding the relationship between theory and practice of the Impact of mobile applications on higher education. The results of the conducted research testify to the fact that the use of mobile applications in the educational process to increase the level of knowledge and skills of students has a positive effect on increasing the level of skills and motivation of students to study, significantly facilitates the educational process based on the implementation of a personalized approach outside classroom time, allows you to organize productive independent work in higher education.
Insurance of virtual assets: problems of theory and practice
Authors: Biletska Liudmyla , Kulyk Oleh , Shumak Ihor
Published: May 2024

Many companies use large volumes of virtual assets to run their business, but traditional insurance products are not effective enough to address the unique challenges of virtual assets. In addition, legal regulation in this area is dynamic and ambiguous. This shows that the study of the insurance of virtual assets is an urgent task, as it responds to the modern challenges associated with digital technologies and creates a basis for the development of effective strategies and tools in the field of insurance.

The purpose of the study is to clarify problematic issues in the theory and practice of insurance of virtual assets. The research methodology consists of the following methods: legal analysis method, empirical method, historical method, concept analysis method and argumentation analysis method, system method, analogy method, induction and deduction method.

It is concluded that classic insurance products may be inadequate to solve the unique risks of virtual assets, while there is a need to develop new insurance products that take into account digital threats and losses, becoming a necessity. In addition, the lack of a clear legal framework in the field of insurance of virtual assets creates a consequential gap, and, therefore, the need to develop and implement standards and regulations has become an urgent task for the diversification of legal regulation.
PTSD in military personnel: diagnosis, treatment and support
Authors: Klymenko Ivan , Tverdokhlib Nataliia , Zlobin Oleksandr , Karachynskyi Oleksii , Kononenko Oksana
Published: May 2024

Posttraumatic stress disorder (PTSD) in military personnel demands urgent attention for enhanced diagnosis, treatment, and support, addressing mental health challenges in this crucial demographic. The main goal is to offer a detailed comprehension of how PTSD is diagnosed, treated, and supported among military personnel. This research utilizes established such methodology as surveys from respected sources, such as Hill & Ponton and the Center for Advancing Health. The criteria for including scientific sources underwent a rigorous selection process using academic. In the results it was discussed the treatments for PTSD in the military, such as psychotherapy, pharmacotherapy, and other approaches aimed at reducing stress and alleviating distress. Special attention is paid to support for service members with PTSD, which may include social support, rehabilitation programs and other interventions for their return to normal life after a traumatic experience. It was found that effective diagnosis and treatment of PTSD in military personnel can significantly improve their quality of life and reduce the risk of mental deterioration. The conclusions emphasize the need for further improvement of the support system for military personnel with PTSD and spreading awareness about this problem in order to improve the quality of life of this group of people.
An Overview of Research Methodologies for Metaphor Identification: A Case Study of the Georgian EFL Essay Corpus
Authors: Narimanishvili Tamari
Published: May 2024

This paper provides a compact overview of several linguistic metaphor identification methodologies, including MIV, MIP, and MIPVU. It offers a comparative analysis of their frameworks and applications in prior studies. The evaluation of these methodologies involves delving into their underlying principles and highlighting their respective advantages and weaknesses in terms of accuracy, practicality, and applicability for different research questions. Moreover, by presenting a case study based on a Georgian EFL essay corpus, the paper reveals the nuanced nature and challenges of identifying metaphors in learner English. The study concludes with a brief discussion of limitations and suggests directions for future research in metaphor identification. By analyzing different approaches, this paper aims to guide researchers in selecting strategies that closely align with their specific research objectives and ensure optimal metaphor identification in L2 contexts.
PENGARUH SPESIALISASI AUDITOR DAN UKURAN K.A.P TERHADAP KUALITAS AUDIT DENGAN KOMITE AUDIT SEBAGAI VARIABEL PEMODERASI
Authors: Tahang Moh. , Sarwoko Haris , Asmanah Siti
Published: May 2024

Audits can mitigate the opportunistic actions of agents by ensuring that a company's profits are accurately reflected through the quality of the audit. The aim of this research is to explore and evaluate the impact of KAP size and auditor specialization on audit quality. This study employs a quantitative methodology using secondary data, with data collection through the documentation method obtained indirectly. The study's population and samples consist of financial statements from manufacturing companies covering the years 2018 to 2022. The analytical approach involves the use of the ANOVA application to perform several analyses, including descriptive statistical tests, classical assumption tests, normality tests, heteroscedasticity tests, and hypothesis tests. The findings of this research indicate that for Hypotheses 1 and 2, which concern the size of the KAP and the specialization of auditors, both resulted in a p-value of 0.336 > 0.05, suggesting that both the size of KAP and auditor specialization influence the quality of the audit. Recommendations for future researchers include using a broader time span for data, incorporating more varied variables, and utilizing data from companies beyond the manufacturing sector

Key words: KAP Size, Auditor Specialization, Audit Quality
ON THE EXISTENCE OF OPTIMAL CONTROL FOR STOCHASTIC FUNCTIONAL DIFFERENTIAL EQUATIONS UNDER THE INFLUENCE OF EXTERNAL DISTURBANCES
Authors:   Yuriy Fedkovych Chernivtsi National University, Chernivtsi, Ukraine, v.yasynskyy@chnu.edu.ua, Yasynskyy V.K. , Yurchenko I.V. ,   Yuriy Fedkovych Chernivtsi National University, Chernivtsi, Ukraine, i.yurchenko@chnu.edu.ua
Published: May 2024

The article discusses the comparison theorem for solutions of stochastic functional differential equations under the influence of external disturbances and its application to one stochastic control problem. Keywords: comparison theorem, stochastic control, stochastic functional differential equations.
INCREASING THE FAULT TOLERANCE IN MICROSERVICE ARCHITECTURE
Authors:   National University of Kyiv-Mohyla Academy, Kyiv, Ukraine, a.glybovets@ukma.edu.ua, Hlybovets A. , Paprotskyi I. ,   National University of Kyiv-Mohyla Academy, Kyiv, Ukraine, i.paprotskyi@ukma.edu.ua
Published: May 2024

Microservice architecture is widely used in the development of distributed applications. Many problems present at the beginning of using this approach have already been solved. However, one of the fundamental problems that seriously affects the system’s fault tolerance remains unsolved. This fundamental problem is known as guaranteed delivery of messages between services. The article analyzed standard approaches to solving this problem. Based on the analysis, the Circuit Breaker pattern was isolated, and its modification was carried out, which reduced the delay in the transition between states and, accordingly, the sending of messages by the service. The efficiency of the proposed modification has been confirmed experimentally. The result of the modification is presented in the form of a quick configuration for Spring Boot. Keywords: microservice architecture, fault tolerance, microservice, programming pattern, Circuit Breaker.