bluuebunny/crossref_metadata_2025 huggingface dataset:
Interorganizational Relations and Destination Marketing in Anime-Induced Tourism: The Effect of Joint Dependence
Authors: Mori Hiroaki
Published: February 2025

Traveling to locations featured in anime has become a significant tourism behavior as the number and popularity of Japanese anime works have increased. The widespread phenomenon of anime-induced tourism has called for destination marketing that welcomes anime fans. This study focuses on the dyadic relationship between destination marketers and anime production teams, who hold definitive discretion over copyrights in anime-induced tourism. Using the concept of joint dependence derived from the theoretical assumptions of resource dependency theory, this research investigates how organizations with imbalanced power relations choose to collaborate. By comparing three qualitative cases that distinctly demonstrate temporal structural changes in anime tourism, this study reveals that joint dependence facilitates interorganizational cooperation through domain consensus between destination marketers and anime production teams. The current study makes a significant theoretical contribution to the fields of interorganizational relations, destination marketing studies, and anime-induced tourism research. Additionally, it provides highly practical insights into tourism development strategies for destination marketers and anime production companies.
A Small Cosmological Constant from a Large Number of Extra Dimensions
Authors: Gao Changjun
Published: February 2025

In this article, we consider the 4 + n dimensional spacetimes among which one is the four dimensional physical Universe and the other is an n-dimensional sphere with constant radius in the framework of Lanczos-Lovelock gravity. We find that the curvature of extra dimensional sphere contributes a huge but negative energy density provided that its radius is sufficiently small, such as the scale of Planck length. Therefore, the huge positive vacuum energy, i.e., the large positive cosmological constant is exactly cancelled out by the curvature of extra sphere. In the mean time the higher order of Lanczos-Lovelock term contributes an observations-allowed small cosmological constant if the number of extra dimensions is sufficiently large, such as n ≈ 69.
The Temperature-Associated Effects of Rift Valley Fever Virus Infections in Mosquitoes and Climate-Driven Epidemics: A Review
Authors: Azerigyik Faustus A. , Cagle Shelby M. , Wilson William C. , Mitzel Dana N. , Kading Rebekah C.
Published: February 2025

Rift Valley fever virus (RVFV) is a mosquito-borne zoonotic disease within the genus Phlebovirus. Symptoms of the disease in animals range from moderate to severe febrile illness, which significantly impacts the livestock industry and causes severe health complications in humans. Similar to bunyaviruses in the genus Orthobunyavirus transmitted by mosquitoes, RVFV progression is dependent on the susceptibility of the physical, cellular, microbial, and immune response barriers of the vectors. These barriers, shaped by the genetic makeup of the mosquito species and the surrounding environmental temperature, exert strong selective pressure on the virus, affecting its replication, evolution, and spread. The changing climate coupled with the aforementioned bottlenecks are significant drivers of RVF epidemics and expansion into previously nonendemic areas. Despite the link between microclimatic changes and RVF outbreaks, there is still a dearth of knowledge on how these temperature effects impact RVF transmission and vector competence and virus persistence during interepidemic years. This intricate interdependence between the virus, larval habitat temperatures, and vector competence necessitates increased efforts in addressing RVFV disease burden. This review highlights recent advancements made in response to shifting demographics, weather patterns, and conveyance of RVFV. Additionally, ongoing studies related to temperature-sensitive variations in RVFV–vector interactions and knowledge gaps are discussed.
Barriers and Benefits: Understanding Riders’ Views on Pooled Rideshare in the U.S.
Authors: Gangadharaiah Rakesh , Brooks Johnell , Boor Lisa , Kolodge Kristin , Jia Yunyi
Published: February 2025

This manuscript provides actionable recommendations to enhance user satisfaction and address existing barriers regarding pooled rideshare (PR) in the United States. Despite PR’s intended benefits, such as reduced traffic congestion and cost savings, its adoption remains limited. To identify these actionable items, a U.S. nationwide survey with 5385 participants explored transportation preferences, barriers, and motivators for PR use in the summer of 2021. First, two factor analyses were conducted. The first factor analysis identified the five factors associated with one’s willingness to consider PR (time/cost, traffic/environment, safety, privacy, and service experience). The second factor analysis revealed the four factors related to ways to optimize one’s PR experience (comfort/ease of use, convenience, vehicle technology/accessibility, and passenger safety). Privacy concerns, for instance, were found to reduce the likelihood of PR adoption by 77%, and convenience had the potential to increase it by 156%. A structural equation model evaluated the relationships among these nine key factors influencing PR usage to develop the Pooled Rideshare Acceptance Model (PRAM). The privacy, safety, trust service, and convenience factors each had a significant large effect (Cohen’s f2 > 0.35) on the model. PRAM was extended using multigroup analyses to reveal the nuanced impact of 16 demographics, including gender, generation, rideshare experience, etc., highlighting the need for tailored strategies to improve PR acceptance through the Pooled Rideshare Acceptance Model Multigroup Analyses (PRAMMAs). Multiple workshops were held with diverse audiences to translate the team’s findings to date into 84 actionable recommendations, categorized across topical areas like safety, routing, driver and passenger selection, user education, etc. These findings are a foundation for a future study to determine which items resonate with different user groups. In the meantime, the actional items serve as a user-driven resource for policymakers, transportation network companies, and researchers, offering a roadmap to potential improvements to PR services to address existing concerns with the goal of increasing the usage of PR.
Unveiling Tick Diversity in Cattle in Cameroon: Emergence of Rhipicephalus microplus, Replacing the Original Rhipicephalus spp.
Authors: Aziz Muhammad Umair , Zeb Jehan , Lontsi-Demano Michel , Almendros Angel , de la Fuente José , Sparagano Olivier Andre , Butaye Patrick
Published: February 2025

Ticks are well-known vectors of pathogens, posing considerable risks to livestock health and productivity. In Cameroon, where livestock production is vital, established tick species such as Amblyomma variegatum and Hyalomma truncatum are prevalent in key cattle-rearing areas. The recent introduction of the invasive, acaricide-resistant Rhipicephalus microplus further complicates control efforts. In this study, we deliver baseline data on the composition of tick species and their shifts within agroecological zone I (AEZ I) and agroecological zone III (AEZ III) of Cameroon, providing a foundation for targeted vector control strategies to ultimately reduce the risk of pathogen transmission. From 1100 ticks collected across two Cameroonian agroecological zones, H. truncatum (39.9%), A. variegatum (31%), and R. microplus (10.64%) were the most prevalent species, along with Rhipicephalus lunulatus (4.45%), Hyalomma rufipes (1.45%), Hyalomma marginatum (1.09%), Hyalomma dromedarii (0.45%), and Rhipicephalus sanguineus (0.9%). Molecular identification using cytochrome C oxidase subunit 1 (cox1) and 16s led to the identification of five additional species, Hyalomma nitidum (0.73%), Rhipicephalus simus (3.54%), Rhipicephalus sulcatus (2.64%), Rhipicephalus praetextatus (2.1%), and Rhipicephalus pusillus (1.1%). R. microplus emerged as the most dominant Rhipicephalus spp. in AEZ I, comprising 67.5% of the total Rhipicephalus ticks. In conclusion, we demonstrate the further spread of R. microplus, which represents a major source of vector-borne diseases, affecting both humans and animals.
Water Management Instructions as an Element of Improving the State of the Pakoski Reservoir (Central–Western Poland)
Authors: Nowak Bogumił , Dumieński Grzegorz , Ławniczak-Malińska Agnieszka
Published: February 2025

The management of reservoir dams in the context of observed climate changes and changing environmental conditions is becoming an increasingly significant challenge. Changes in the regimes of rivers feeding the reservoirs, sudden floods, long periods of drought, shallowing of reservoirs, water pollution, and algal blooms create unprecedented threats to the operation of these reservoirs. Among these challenges, the most crucial seems to be the proper management of available water resources, which condition the existence of the reservoir. The location of the reservoir has a significant impact on how water management is conducted. In the case of mountain and upland reservoirs created for flood protection of areas downstream, water management practices differ significantly from those for lowland reservoirs, which primarily serve to retain water for industrial and agricultural needs in the area, with an additional flood protection function. The aim of this study was to assess the factors determining the supply of lowland reservoirs using the example of the Pakoski Reservoir (Central–Western Poland) and to propose actions that would allow more efficient management of water resources in the catchment and reservoir, enabling the preservation of the current morphometric parameters in the face of climate change, adverse environmental phenomena, and increased anthropogenic pressure in the catchment area. This study focused on the Pakoski Reservoir, located in the southern part of the Kuyavian–Pomeranian Voivodeship. It was constructed fifty years ago as a result of damming water in the river systems of the Noteć and Mała Noteć Rivers. For decades, it served its functions, and its management posed no major issues. However, over the past decade, due to environmental changes and human activities in the catchment area, the reservoir has increasingly faced problems with filling.
Filling the Gap: Explaining Foreign Participation in China’s Water PPP Projects from a Local Government Perspective
Authors: Li Dan , Zhang Zhen , Zhao Zhirong Jerry
Published: February 2025

Foreign capital has dominated over half of the public–private partnership (PPP) projects in developing countries over the past three decades. As such, attracting and regulating foreign participation in water PPP projects presents a critical challenge for both practitioners and scholars. Using a dataset of 2024 water PPP projects from 1994 to 2021, this study investigates foreign participation and its fall in China’s water PPP projects. Our findings highlight three key points: First, the proportion of projects undertaken by foreign capital decreased from 100% to less than 0.5%, with Chinese domestic capital taking its place. Second, resource dependence on foreign capital and the local government’s need for control lead to four types of foreign participation: financing water plants under user-pays, financing and operating water utilities under government-pays, participating with mainly an O&M role, and nearly no participation. Third, a better balance between efficiency gains and control needs via cooperation with domestic capital by local governments had driven the decline in foreign participation. This study makes two key contributions: (1) it is one of the pioneer studies on systematically tracing the evolution of foreign participation in PPP projects, and (2) it explains the fall of foreign participation from a local government perspective, complementing market-based explanations.
Spatiotemporal Variability of Groundwater Quality for Irrigation: A Case Study in Mimoso Alluvial Valley, Semiarid Region of Brazil
Authors: Almeida Thayná A. B. , Montenegro Abelardo A. A. , de Lima João L. M. P. , Farias Carolyne W. L. A. , Carvalho Ailton A. , de Paiva Anderson L. R.
Published: February 2025

Alluvial aquifers are vital for agricultural communities in semiarid regions, where groundwater quality is often constrained by seasonal and spatial salinity variations. This study employed geostatistical methods to analyze the spatial and temporal variability of electrical conductivity (EC) and the sodium adsorption ratio (SAR) and elaborate an indicative quality map in the Mimoso Alluvial Aquifer, Pernambuco, Brazil. Groundwater samples were collected and analyzed for cations, total hardness (TH), and the percentage of sodium (PS). Moreover, the relation between EC and the SAR was used to determine the groundwater quality for irrigation. Cation concentrations followed the order Ca2+ > Mg2+ > Na+ > K+. EC and the SAR exhibited medium to high variability, with spatial dependence ranging from moderate to strong, and presented a strong cross-spatial dependence. Results showed that sequential Gaussian simulation (SGS) provided a more reliable groundwater classification for agricultural purposes compared to kriging methods, enabling a more rigorous evaluation. Based on the strong geostatistical cross correlation between EC and RAS, a novel water quality index was proposed, properly identifying regions with lower groundwater quality. The resulting spatial indicator maps classified groundwater as suitable (64.7%), restricted use (2.08%) and unsuitable (2.38%) for irrigation. The groundwater quality maps indicated that groundwater was mostly suitable for agriculture, except in silty areas, also corresponding to regions with low hydraulic conductivity at the saturated zone. Soil texture, rainfall, and water extraction significantly influenced spatial and temporal patterns of groundwater quality. Such correlations allow a better understanding of the groundwater quality in alluvial valleys, being highly relevant for water resources management in semiarid areas.
Is Industrial-Scale Wastewater Treatment Possible with a Commercially Available Atmospheric Pressure Plasma System? A Practical Study Using the Example of a Car Wash
Authors: Szulc Michał , Kirner Carmen , Götz Jörg , Schein Jochen
Published: February 2025

The topic of water reuse is becoming increasingly important. It might be possible to use the well-known antibacterial effect of atmospheric pressure plasma due to its special mixture of reactive species, UV, and electromagnetic fields in a scaled-up, industrially interesting area to remove bacteria from wastewater, and thus, make it usable again. To review this question, water volumes of 5L and of different qualities (turbidity and different degrees of hardness) were treated with a commercially available plasma system. The change in water-specific values such as pH, EC, ORP, nitrate, and nitrite content was determined. To test the antibacterial effect, both direct and indirect treatment of the test germ Pseudomonas aeruginosa was conducted. In the first case, the inoculated water samples were plasma-treated, while in the second case, the water samples were treated before inoculation with the germ. The viable bacteria were counted via the spread plate method. The best reduction rate of at least 6 log levels was achieved when inoculated deionized water samples were treated directly with plasma. A significant reduction in viability was also observed in directly treated clear tap water samples, whereby the different degrees of hardness did not influence the effectiveness of the plasma. The bacterial load remained almost unchanged when reused water samples from a car wash were treated. Based on the results, a possible application in a car wash was discussed including a cost estimation and possible limitations.
Simulating the Failure Mechanism of High-Slope Angles Under Rainfall-Mining Coupling Using MatDEM
Authors: Li Qihang , Wang Yunmin , Hou Di , Jiang Song , Gong Bin , Li Xiaoshuang
Published: February 2025

The safety production of gold, silver, copper, and other important metals is seriously threatened in the process of mining from open-pit to underground due to various factors such as infiltration caused by rainfall and unloading during mining. Furthermore, the current situation of open-pit mining in an increasing number of mines presents a high and steep terrain, which poses significant security risks. Accordingly, it is of great practical significance to investigate the failure mechanism of high-slope angles to ensure the long-term safe mining of mines, considering factors such as rainfall infiltration and excavation unloading. In this study, the slope failure of high-slope angles (45°, 55°, and 65°) under rainfall-mining coupling was analyzed using the discrete element MatDEM numerical simulation software. Herein, the stress distribution, failure characteristics, and energy conversion of the model were simulated under different slope angles to analyze the failure mechanism at each stage. The simulation results show that the damage scale is smallest at 55° and largest at 65°. This indicates that setting the slope angle to 55° can reduce the risk of slope instability. Moreover, the reduction of elastic potential energy during the mine room mining stage is similar to that of mechanical energy. During the pillar mining stage, stress is concentrated in each goaf, resulting in a greater reduction in mechanical energy compared to elastic potential energy. Finally, after the completion of the continuous pillar mining stage, stress becomes concentrated in the failure area, and the effect of the slope angle on mechanical energy reduction becomes evident after the complete collapse of the model.
Optimization of Scale Inhibitor Addition Scheme and Control of Phosphorus Content in External Cooling System of Synchronous Condenser
Authors: Gu Xiantao , Wu Yuquan , Xu Yunqing , Zhao Hongwei , Yang Lin , Chen Xiaochun , Fan Peipei , Zhang Junjie , Liu Zhikui , Zhu Tao , Gao Yuxiang , Dong Haosheng
Published: February 2025

Scaling is one of the common problems in circulating cooling water systems, which can significantly affect the cooling efficiency of equipment in severe cases. At present, the problem of scaling is usually controlled by adding water treatment agents. However, taking the external cooling system of the synchronous condenser in an ultra-high-voltage converter station as an example, due to the lack of scientific understanding of scale inhibitors, there is often a problem of excessive dosing, resulting in unsatisfactory scale inhibition effects and difficulties in wastewater treatment and discharge. In addition, the extensive use of phosphorus-containing agents has led to the enrichment of phosphorus elements in water bodies. Therefore, the optimal amount of AS-582 scale inhibitor used in the converter station with the best scale inhibition effect was determined through static calcium carbonate deposition experiments, with the scale inhibition rate of 91.4% at 90 mg/L. And the scale inhibition mechanism was explored, where the lattice distortion mechanism and threshold effect play important roles. The AS-582 scale inhibitor was mixed with two green scale inhibitors, PASP and PESA, to obtain a phosphorus reduction formula that combined excellent scale inhibition performance and low phosphorus content. When using the optimal composite scale inhibitor of n(AS-582):n(PASP):n(PESA) = 4:1:1, the scale inhibition rate is 91.8% and the phosphorus content is reduced by one-third. The effectiveness of the formula was tested using dynamic circulating water experimental equipment under practical application conditions, proving its practical value.
Hydrological Dynamics and Climate Variability in the Sava River Basin: Streamflow Reconstructions Using Tree-Ring-Based Paleo Proxies
Authors: Ramírez Molina Abel Andrés , Leščešen Igor , Tootle Glenn , Gong Jiaqi , Josić Milan
Published: February 2025

This study reconstructs historical streamflow in the Sava River Basin (SRB), focusing on hydrological variability over extended timescales. Using a combination of Machine Learning (ML) and Deep Learning (DL) models, streamflow patterns were reconstructed from self-calibrated Palmer Drought Severity Index (scPDSI) proxies. The analysis included nine ML models and two DL architectures, with a post-prediction bias correction applied uniformly using the RQUANT method. Results indicate that ensemble methods, such as Random Forest and Gradient Boosted Tree, along with a six-layer DL model, effectively captured streamflow dynamics. Bias correction improved predictive consistency, particularly for models exhibiting greater initial variability, aligning predictions more closely with observed data. The findings reveal that the 2000–2022 period ranks as the lowest 23-year flow interval in the observed record and one of the driest over the past ~500 years, offering historical context for prolonged low-flow events in the region. This study demonstrates the value of integrating advanced computational methods with bias correction techniques to extend hydrological records and enhance the reliability of reconstructions. By addressing data limitations, this approach provides a foundation for supporting evidence-based water resource management in Southeastern Europe under changing climatic conditions.
Impacts of Changing Temperatures on the Water Budget in the Great Salt Lake Basin
Authors: Affram Grace , Othman Jihad , Morovati Reza , Castellanos Saddy Pineda , Khoshnoodmotlagh Sajad , Dunn Diana , Dority Braedon , Diaz Katherine Osorio , Ratterman Cody , Zhang Wei
Published: February 2025

Quantifying the water budget in the Great Salt Lake (GSL) basin is a nontrivial task, especially under a changing climate that contributes to increasing temperatures and a shift towards more rainfall and less snowfall. This study examines the potential impacts of temperature thresholds on the water budget in the GSL, emphasizing the influence on snowmelt, evapotranspiration (ET), and runoff under varying climate warming scenarios. Current hydrological models such as the Variable Infiltration Capacity (VIC) model use a universal temperature threshold to partition snowfall and rainfall across different regions. Previous studies have argued that there is a wide range of thresholds for partitioning rainfall and snowfall across the globe. However, there is a clear knowledge gap in quantifying water budget components in the Great Salt Lake (GSL) basin corresponding to varying temperature thresholds for separating rainfall and snowfall under the present and future climates. To address this gap, the study applied temperature thresholds derived from observation-based data available from National Center for Environmental Prediction (NCEP) to the VIC model. We also performed a suite of hydrological experiments to quantify the water budget of the Great Salt Lake basin by perturbing temperature thresholds and climate forcing. The results indicate that higher temperature thresholds contribute to earlier snowmelt, reduced snowpack, and lower peak runoff values in the early spring that are likely due to increased ET before peak runoff periods. The results show that the GSL undergoes higher snow water equivalent (SWE) values during cold seasons due to snow accumulation and lower values during warm seasons as increased temperatures intensify ET. Projected climate warming may result in further reductions in SWE (~71%), increased atmospheric water demand, and significant impacts on water availability (i.e., runoff reduced by ~20%) in the GSL basin. These findings underscore the potential challenges that rising temperatures pose to regional water availability.
Ethno-adventure tourism: the synergy of ethnic, ethnographic and adventure tourism as a new driver of Russia s development
Authors:   Peoples Friendship University of Russia, Moscow, Zeveke O. Yu. , Kovalev G. A. ,   Peoples Friendship University of Russia, Moscow
Published: February 2025

The article considers the synergy of ethnic, ethnographic and adventure tourism as a single
ethno-adventure tourism, contributing to the development of the tourist potential of the territory of the Russian Federation. The hypotheses related to the unification of these three directions are analyzed, which opens up new horizons for the tourism industry. The definitions of each type of tourism and their
interaction are studied in detail, which makes it possible to create unique ethno-adventure routes. The
advantages of this approach for the economic growth of regions, preservation of cultural heritage and
improvement of the quality of life of local communities are discussed. The foreign experience of successful integration of these types of tourism is also presented, which can serve as a basis for the introduction of
similar practices in the regions of Russia. The conclusion highlights the need for an integrated approach to the development of tourism products, taking into account the interests of indigenous peoples and local communities.
Regional blood flow in dental patients with reduced interalveolar distance and auditory disorders (Part 2)
Authors: Gaivoronskaya A. A. , Tsimbalistov A. V. , Voityatskaya I. V. , Lopushanskaya T. A. , Gaivoronskaya M. G. , Chernogaeva E. A. , Solovykh E. A.
Published: February 2025

Relevance. Reduced interalveolar distance, resulting from increased wear of dental hard tissues, generalized periodontitis, and tooth loss, leads to morphofunctional changes not only in the masticatory muscles and temporomandibular joint (TMJ) but also in other structures of the maxillofacial region. These changes affect hemodynamics in the vascular regions of the face, neck, brain, TMJ, and upper cervical spine. Objective. To evaluate regional blood flow in dental patients with reduced interalveolar distance and auditory disorders.

Materials and methods. The study was conducted on a group of patients with signs of reduced interalveolar distance (n = 50), aged 34 to 73 years, with a mean age of 53.5 ± 2.4 years. The group comprised 22 men (44.0%) and 28 women (56.0%). The examination included the functional-physiological method for determining the central relationship of the jaws using the Apparatus for Determining Central Occlusion (AOTSO) and duplex ultrasound scanning of the head, neck, and TMJ vessels.

Results. In patients with reduced interalveolar distance in habitual occlusion, a high asymmetry coefficient of linear blood flow velocity was observed in the examined arteries, reaching up to 40%, along with signs of venous dysgemia. Using loading tests during the functional-physiological method achieved optimal positioning of the mandibular condyles in the mandibular fossa and optimized occlusion. This significantly reduced the blood flow asymmetry coefficient to 4%, with no signs of venous outflow disorders. These improvements indirectly influenced the hemodynamics of the peripheral auditory system, enhancing its function. Conclusion. reduced interalveolar distance, temporomandibular joint, auditory disorders.
Antibiotic use during the first episode of acute perianal sepsis: a still-open question
Authors: Blondin Stanislas , Lobo David , Egal Axel , Ysmail-Dahlouk Saliha , Taouk Milad , Bourguignon Josée , Blondeel David , Etienney Isabelle
Published: February 2025

Purpose: The role of antibiotics in preventing fistula formation following an initial abscess remains a subject of debate. This study compared the incidence of fistula in ano in patients experiencing their first episode of acute perianal sepsis, with and without antibiotic therapy, and evaluated the prevalence of fistula in ano necessitating surgical intervention at 1 year.Methods: This retrospective cohort study was conducted at a tertiary care hospital with a dedicated proctology department. All patients who presented to the emergency proctology unit with a first episode of acute perianal sepsis were eligible for inclusion.Results: This study included 276 patients. At 1 year, fistula formation was identified in 65.6% of all patients, 54.0% of those who had received antibiotics, and 75.0% of those who had not (P<0.001). This finding remained significant after weighted propensity analysis (odds ratio, 0.53; 95% confidence interval, 0.31–0.92; P=0.025).Conclusion: The rate of fistula formation was relatively high in this study. However, it was lower among patients with perianal sepsis who were treated with antibiotics, although a causal relationship could not be established. Prolonged follow-up is needed to clarify the role of antibiotic therapy in preventing or delaying fistula development in patients with acute perianal sepsis.
La evolución del nanografeno en el sector de la construcción
Authors: Rondos Chavez Jorge Cesar , Cahuana Zavala Pamela Maria
Published: February 2025

La nanotecnología, un campo en constante evolución, ha abierto nuevas fronteras en diversos sectores, y la construcción no es la excepción. El objetivo es explicar la evolución del nanografeno en el sector de la construcción. El enfoque es cuantitativo, tipo descriptivo-explicativo con diseño experimental. Se realizó una búsqueda en las bases de datos Scopus, ScienceDirect y Scielo. Se utilizaron los descriptores “nanografeno”, “concreto” y “resistencia a la compresión". Los resultados demuestran que, una de sus propiedades mecánicas es la resistencia a la compresión, se puede decir que los porcentajes dl nanografeno que oscilan entre 0.02% - 0.04% con relación al peso del cemento se incrementa desde un 10% - 12%. En conclusión, la optimización de la dosificación del nanografeno es un punto clave para obtener los mejores resultados, ya que al dosificar de manera excesiva puede generar aglomeraciones del nanomaterial, lo que puede afectar negativamente las propiedades del concreto.
Methodological aspects of the statistical analysis of entrepreneurial confidence in the sectors of the Russian economy
Authors: Shmarikhina E. S.
Published: February 2025

The article examines the sources of information on the entrepreneurial confidence of organizations and consumer expectations of the population collected by Rosstat. The features of programmatic, methodological and organizational issues of monitoring the conjuncture and business activity of organizations and consumer behavior of the population are summarized. The limitations of the statistical analysis of non-quantitative information (balances of evaluation of indicators as a difference in the frequency of responses) of marketoriented sample surveys are formulated. The dynamics and seasonality of the index of entrepreneurial confidence of enterprises extracting minerals, engaged in manufacturing, providing electric energy, gas and steam, air conditioning, construction, retail trade, services, and the index of consumer confidence of the Russian population for 2022-2024 are analyzed. The degree of influence of the components of the index of entrepreneurial (consumer) confidence in Russia on its dynamics for 2018-2024 was measured. The factors limiting the activities of Russian enterprises and organizations were analyzed, stable and unstable among them were identified, and structural shifts in respondents' responses about the impact of these factors for 2020-2024 were also assessed.
Uptake of Peritoneal Dialysis (PD) by Minoritized Patients
Authors: Arnaoudova Ivelina , Wilson Clara , Rizzolo Katherine , Shen Jenny , Ehtesham Nahian , Wilson Jennifer , Golestaneh Ladan
Published: February 2025

Background:

In a cohort of patients with late-stage kidney disease who completed dialysis modality education and who self-identified as racial ethnic minorities, we studied characteristics of those choosing PD, and perception of usefulness of the education session in modality selection.

Methods:

In this study of individuals with kidney failure cared for by nephrologists at Montefiore Medical Center, Bronx, NY, who were referred for modality education, we: 1-tested the association of patient characteristics with modality selection in 113 patients from 2021-2023, and 2-examined patient perception of the quality of modality education from 13 semi-structured interviews. We compared sociodemographic, clinical attributes, and patient responsiveness to attempts made by staff among those who selected and initiated PD to those who a-did not select PD, or b-initiated on HD urgently . We performed qualitative analysis of interviews to reach consensus on theoretical domain framework concepts and how they fit events in the kidney failure trajectory.

Results:

Compared to individuals who required urgent HD, those who selected, and were initiated on, PD were younger (54 yrs vs 66 yrs), had fewer comorbidities, and did not require as many attempts to schedule modality education. Qualitative analysis of interviews showed that experience with staff and quality of information conveyed during education was generally positive, but the following gaps were identified: lack of support for the emotional trauma of kidney failure diagnosis, inability to address structural barriers to PD specific to the patient population, and the lack of a deliberate program to lessen anxiety about the responsibility of PD.

Conclusions:

Incorporation of tailored content that addresses clinical comorbidity, structural barriers to care and emotional trauma constitute aspects of modality education that can be improved to increase PD uptake among minoritized patients.
Multi-criterion modeling in the conditions of non-homogeneous data uncertainty in the V. Skalozub papers
Authors: O. Kuropiatnyk
Published: February 2025

The problems of solving multi-criteria modeling tasks in conditions of heterogeneous data uncertainty are characteristic and relevant for many areas, in particular, transport and logistics, medical, and economic. This paper summarizes the approaches to solving these ar-eas tasks, including cases for data obtained during monitoring with uneven and unclear inter-vals. All the considered approaches were created under the guidance and with the direct par-ticipation of prof. Skalozub V. V. The author's team, with his participation, illustrated exam-ples of the use of models in the tasks of organizing multi-symbol sequences in transport (for-mation-dismantling of trains, order processing) and in the analysis and forecasting of states/events based on data on diabetes diseases. In this paper, the main approaches to modeling in conditions of heterogeneous data un-certainty based on multi-layer constructive-synthesizing, separable and relational-separable models are highlighted. Multi-layer constructive-synthesizing became new branch of develop constructive-synthesizing modeling. Their practical value currently lies in the possibility of obtaining a new form of implementation of the specified technological processes of railway transport. In the future, they can be applied to tasks that require step-by-step data processing with a clear demarcation of the relevant operations. The obtained results can be used for further development of the proposed ideas and ap-proaches. It is promising to develop the identified approaches, including by combining them, as well as supplementing constructive-production models with a formalized description of con-structive elements, including input data, by ontological means. The paper contains information about the figure and scientific work of V. Skalozub.
Application of machine learning methods for analysis of Twitter messages
Authors: P.V. Herasymchuk , T.A. Likhouzova , Y.O. Oliinyk
Published: February 2025

The paper investigates the problem of binary classification of text messages for the presence of bullying. Bullying on the Internet, in particular in social networks, is a serious threat to the mental health of users. Aggressive, offensive or humiliating messages can cause stress, anxiety, depression or other mental disorders. Because of this, identifying and prevent-ing cyberbullying is a priority for organizations developing communication platforms. A dataset with Twitter messages was prepared and pre-processed, including cleaning, tokenization, and lemmatization. 3 sets of input data for classification models were created: Bag-of-Words, TF-IDF matrix, word2vec matrix. Models based on various machine learning methods were built and tested: logistic re-gression, k nearest neighbors, random forest, support vector, naive Bayesian classifier meth-ods on each of the input data sets. Based on the results of testing the models, a comparative analysis of their effectiveness was carried out, logistic regression on Bag-of-Words input data was singled out as the most effective model for the task of binary classification of text messages from the selected set. The results obtained in the course of the study can be used for the development of sys-tems for automatic detection of signs of cyberbullying in the messages of users of social net-works and the prompt use of appropriate measures.
Analysis of approaches of electronic voting systems implementation
Authors: D. Ostapets , V. Motylenko
Published: February 2025

The work examines modern approaches to building electronic voting systems, such as blockchain, which promises to revolutionize the process due to its immutability and decen-tralization properties, as well as traditional cryptographic methods, including homomorphic encryption, which allows vote counting without the need to decrypt each individual vote. Blind signatures ensure the ability to confirm a vote without disclosing the user's identity, and zero-knowledge proofs allow voting without interacting with the server. The goal of the work is to select an approach for building electronic voting systems based on a comparative analy-sis of their key characteristics. The solved tasks include reviewing the requirements, general-ized structures, and main procedures of electronic voting systems; analyzing the existing types of electronic voting systems and their comparative characteristics. During the work, existing systems and other literature were thoroughly analyzed. The article provides a de-tailed analysis of the advantages and limitations of these technologies, as well as their suit-ability for different electoral systems, considering important aspects such as scalability, effi-ciency, and protection against potential threats. Throughout the work, a list of requirements for electronic voting systems was compiled, the main procedures present in electronic voting systems were outlined, a set of actors in typical electronic voting systems was defined, and the generalized structures of their main types were presented. A comparative analysis of the types of electronic voting systems based on compliance with the requirements was conducted. An approach was chosen for further system development.
Predicting the popularity of music tracks on Spotify based on numerical metrics
Authors: A.O. Bur , T.A. Likhouzova , Y.O. Oliinyk
Published: February 2025

In today's world, music plays an important role in the lives of millions of people, and music streaming platforms such as Spotify have become an integral part of modern culture. The popularity of music tracks is of great importance to the music industry, affecting artists' incomes and trends in the music world. Predicting the popularity of music tracks is an impor-tant task that can help artists, producers, and platforms better understand listener preferences and optimize their strategies. As part of this work, a data storage of music tracks on the Spotify platform has been de-veloped, based on a physical model of the database, the functionality of which is implemented using SQL scripts. Working with the database is presented through the implementation of software for the implementation of ETL processes and intelligent analysis of selected data. The software allows you to classify tracks by the level of popularity (0 - not at all popular, 1 - medium popularity, 2 - hit) using numerical track metrics such as acousticness, tempo, va-lence, liveness, etc. The role of the data storage management system is SQLite, the program-ming language for implementing the application is Python. Different machine learning models are used to predict track popularity, including KNeighbors, Decision Tree, Random Forest, and Extreme Gradient Boosting. Data mining software provides efficient track classification and graphical display, allowing users to easily interpret forecasting results. Libraries used in the work: pandas, numpy, seaborn, matplotlib, tabulate, xgboost, scipy, sqlite3. The overall analysis showed that the XGBoost and Random Forest models are the most effective for predicting the popularity of music tracks. They demonstrate high accuracy and resistance to changes in the set of attributes, which makes them suitable for use in real condi-tions.
Algorithms for data imputation based on entropy
Authors: O. Zemlianyi , O. Baibuz
Published: February 2025

Recent advancements in data imputation have focused on various machine learning techniques, including methods like mean, median, and mode imputation, along with more complex approaches like k-nearest neighbors (KNN) and multiple imputation by chained equations (MICE). Research into entropy-based methods offers a promising direction. This method minimizes uncertainty by selecting imputation values that reduce the overall entropy of the dataset. The goal of this work is to develop an algorithm that imputes missing data by minimiz-ing conditional entropy, thus ensuring that the missing values are filled in a way that pre-serves the relationships between the variables. The method is designed for both qualitative and quantitative data, including discrete and continuous variables, aiming to reduce uncer-tainty in classification tasks and enhance the performance of machine learning models. The proposed algorithm is based on conditional entropy minimization, using entropy as a measure of uncertainty in data. For each incomplete row, the algorithm computes the con-ditional entropy for possible imputation values. The value that minimizes conditional entropy is selected, as it reduces uncertainty in the target variable. This process is iterated for each missing value until all missing data is imputed. Three types of tests were performed on two datasets. The analysis showed that the pro-posed algorithms are quite slow compared to other methods and can be improved, for exam-ple, by multiprocessing, as described in our work [15]. The type 1 test showed that the pro-posed algorithms do not give a gain on the RMS deviation metric, but significantly reduce en-tropy (type 2 test). At the same time, these methods show an improvement in classification performance over the baseline models (type 3 test). Thus, the proposed entropy-based imputation methods have shown good results and can be considered by researchers as an additional tool to improve the accuracy of decision mak-ing, but further computational optimisation studies are needed to improve the performance of these methods. The algorithm shows promise in improving classification accuracy by selecting imputa-tion values that minimize conditional entropy. Future research will focus on optimizing the method for large datasets and expanding its application to various domains.
Methodology for the development of neuro-fuzzy automatic control systems with a function for identifying the parameters
Authors: V.S. Mykhailenko , H. Korenkova , V. Leshchenko , L. Martynovych
Published: February 2025

The article discusses a methodology for developing neuro-fuzzy automatic control systems (ACS) for marine steam turbine installations (MSTI) with a parameter identification function during their operation. The proposed methodology includes stages of MSTI dynamic modeling, the development of parameter identification algorithms based on neural networks, and their integration with fuzzy logic for decision-making. An analysis of the proposed approach's capabilities regarding the enhancement of reliability and stability of marine power plants has been conducted. The results obtained demonstrate that such a system can adjust model parameters in real-time, ensuring control accuracy and reducing the risk of emergency situations. The methodology can be implemented in real marine power systems that require automated control of complex processes.
Features of real-time modeling of steelmaking processes using unreal engine 5
Authors: D. Myrhorodskyi , T. Selivorstova
Published: February 2025

This paper explores the features of real-time modeling of steelmaking processes using Unreal Engine 5, focusing on the visualization and simulation of continuous casting machine (CCM) operations. The study highlights the advantages of interactive and virtual reality (VR) technologies in the training and optimization of metallurgical processes, providing a safer and more cost-effective alternative to traditional training methods. A detailed approach to 3D modeling of CCM components is presented, including the tundish, mold, secondary cooling system, and roller sections, with a focus on their realistic visualization and optimization for real-time performance. The implementation of physical simulations using Chaos Physics and Niagara in Unreal Engine 5 allows for an accurate rep-resentation of molten steel flow, solidification dynamics, and temperature gradients. Addi-tionally, gamification elements have been integrated to enhance user interaction, enabling students and engineers to explore various operational parameters in a controlled virtual envi-ronment. The research also assesses the efficiency of digital simulation techniques compared to conventional learning methods in metallurgical training programs. The use of VR-based in-teractive learning modules improves engagement and comprehension by allowing users to manipulate casting parameters and observe the impact on the final product in real-time. The paper concludes that Unreal Engine 5 provides an effective platform for modeling complex industrial processes, offering high-quality visual representation, dynamic interaction, and immersive training experiences for metallurgical professionals. Future work will focus on enhancing AI-driven adaptive learning, expanding the simu-lation scope to include additional steelmaking stages, and integrating augmented reality (AR) tools to bridge the gap between virtual training and real-world applications.
Changes in breast reconstruction over the COVID-19 pandemic: a single centre experience
Authors: Vinycomb Toby I , Shen Amanda Y , Hall Courtney , Keating Daniel , Ellis Lisa , Lo Cheng H , Tan Beryl
Published: February 2025

Introduction: Approximately 4000 Australians undergo mastectomy annually, yet there is a paucity of published Australian data on how the COVID-19 pandemic affected breast reconstruction services. The aim of this study is to determine the impact of the COVID-19 pandemic on the breast reconstructive service of a busy metropolitan hospital in Melbourne, Australia. Challenges in clinical service provision and surgical outcomes are discussed and compared with the published literature.
Methodology: A single centre retrospective review of breast reconstruction over a four-year period (April 2018 to March 2022 inclusive) was conducted. Data collected include patient demographics, oncological attributes, surgical management and outcomes. Data was compared before (April 2018 to March 2020, inclusive) and during the COVID-19 pandemic (April 2020 to March 2022, inclusive).
Results: Resection rates were comparable before and during the COVID-19 pandemic (240 versus 248 patients). There was an increase in the rate of mastectomies compared to breast-conserving operations between the two periods (30.4% versus 45.6%, p <0.001). Breast reconstruction post-mastectomy increased from 39.7 per cent to 46.0 per cent (not statistically significant, p = 0.68). The rate of immediate breast reconstruction (79% versus 81%) and autologous reconstruction (62% versus 70%) were statistically similar between the two periods. There was no difference in total pre-COVID-19 and post-COVID-19 complication rates.
Conclusion: Our experience demonstrates that acceptable oncological and reconstructive outcomes for breast cancer can be achieved in the middle of a pandemic without compromising outcomes.