bluuebunny/crossref_metadata_2025 huggingface dataset:
Quantitative Modeling and Predictive Analysis of Chemical Oxygen Demand in Wastewater Treatment Systems Utilizing Long Short-Term Memory Neural Network
Authors: Meng Xuanzhen , Zhang Yan
Published: November 2024

In the realm of water resource management, meticulous monitoring and control methodologies are quintessential to the refinement of wastewater treatment processes. This research elucidates an avant-garde methodology for forecasting the Chemical Oxygen Demand (COD), an instrumental indicator of water quality, by harnessing the capabilities of long short-term memory (LSTM) neural networks in conjunction with Internet of Things (IoT) paradigms. The efficacy of the LSTM model is juxtaposed with that of an advanced Deep Belief Network (DBN), as well as contemporary models like a Convolutional Neural Network–Long Short-Term Memory (CNN-LSTM) hybrid model and a Transformer-based model, employing data sourced from a wastewater treatment facility located in Changsha. The empirical findings show that notwithstanding the comparable training durations used, the LSTM model exhibits a preeminent error rate of merely 7%, thus surpassing the DBN model (which has an error rate of 35%), the CNN-LSTM model (registering a 22% error rate), and the Transformer-based model (with a 17% error rate) in its predictive precision. This research underscores the potential of integrating an astute wastewater control system with IoT and LSTM models, thereby hinting at prospective enhancements in the sustainability and operational efficacy of wastewater treatment installations.
Chemical Composition and Decomposition of Litter in Signal Grass Pastures Fertilized with Increasing Nitrogen Doses or Intercropped with Calopo
Authors: Chaves Carla Silva , Coutinho Danielle Nascimento , dos Anjos Albert José , Alves Wagner Sousa , da Silveira Tâmara Chagas , Ribeiro Karina Guimarães
Published: November 2024

Knowledge about the decomposition of litter in signal grass pastures is still limited, especially in pastures managed under deferred grazing. Thus, we aimed to evaluate the chemical composition, carbon/nitrogen (C/N) ratio, and decomposition rate of litter in signal grass (Urochloa decumbens cv. Basilisk) pastures not fertilized with N (U0), fertilized with 50 kg·N·ha−1 (U50), fertilized with 100 kg·N·ha−1 (U100), and intercropped with calopo (Calopogonium mucunoides Desv.) (UC), managed under deferred grazing at different incubation times for two experimental periods (2017–2018 and 2018–2019). Data were analyzed using a randomized block experimental design with four management systems and two blocks, each containing two replicates per treatment. Nitrogen sources increased the N concentrations in the litter before incubation. Nitrogen concentrations in the incubated litter were affected by the incubation times and periods, increasing over time, mainly for U50 and U100. U100 litter samples exhibited higher acid detergent insoluble nitrogen (ADIN) levels than the U0 litter samples only in period 2. Notably, the C/N ratio did not differ with the different management systems; however, it decreased with increasing incubation times and periods, with final values of 24:1 and 26:1 in periods 1 and 2, respectively. Overall, litter samples from pastures fertilized with chemical or biological N sources exhibited higher N concentrations, but their incubated litter samples exhibited higher ADIN concentrations. However, management systems did not affect C/N ratios and no differences in litter biomass decomposition were observed among the systems, possibly due to the grazing period occurring prior to litter sampling.
ESG Performance and Enterprise Value in Chinese Tourism Companies: The Chained Mediating Roles of Media Attention and Green Innovation
Authors: Xue Yiping , Lakkanawanit Pankaewta , Suttipun Muttanachai , Huang Shi-Zheng
Published: November 2024

This study explores the relationship between environmental, social, and governance (ESG) performance and enterprise value in Chinese tourism companies, with differing degrees of media attention and green innovation as the multiple-chained mediating factors. In this study, we adopted a quantitative approach to collect survey data from 804 samples selected from China’s A-level tourist attractions, star-rated hotels, and travel agencies. Through rigorous statistical analysis and hypothesis testing, our results reveal a significant positive relationship between ESG performance and enterprise value in tourism companies. Media attention and green innovation demonstrate crucial chained mediating effects in this relationship. The findings expand the understanding of ESG performance’s influence on enterprise value in the tourism sector, highlighting how media visibility and innovation initiatives amplify ESG’s positive effects. This study offers practical implications for tourism companies, emphasizing the importance of integrating ESG principles into core business strategies, engaging with media, and investing in green innovation to enhance firm value. In addition, it suggests that policymakers create incentive structures to promote sustainable practices and encourage media–tourism company collaborations to communicate ESG efforts effectively.
Assessing Drought Risk and the Influence of Climate Projections in Sri Lanka for Sustainable Drought Mitigation via Geospatial Techniques
Authors: Dissanayake S. D. Sachini Kaushalya , Jing Yuanshu , Laksith Tharana Inu
Published: November 2024

Sri Lanka is highly vulnerable to climatic change, making drought risk assessment an essential tool for the development of effective mitigation strategies. This study addresses existing gaps by employing geospatial techniques to evaluate drought risk in Sri Lanka and focusing on future trends in temperature and precipitation. The observed meteorological data, projected climate variables, and environmental factors were analyzed using the standardized precipitation evapotranspiration index (SPEI). Key findings show that the northwestern and southern regions of Sri Lanka are particularly susceptible to increased drought hazards, while the southwestern region, characterized by the highest density of built-up areas, is also more vulnerable. A combination of hazard and vulnerability data reveals that the northwestern, upper–central, and southern regions exhibit relatively high drought risk. The spatial distributions of the predicted meteorological variables align closely with current patterns, and significant increasing trends were observed under the SSP 2.6 and SSP 8.5 scenarios. Precipitation and temperature correlate with drought, indicating an elevated risk of future drought events. This study provides a comprehensive understanding of the interplay between climate change and drought risk in Sri Lanka, offering valuable insights for policymakers and resource managers to develop sustainable drought mitigation plans.
Intelligent Manufacturing and Green Innovation—Evidence from China’s Listed Manufacturing Firms
Authors: Xu Xiaoshu , Pan Jiangpei , Meng Xuechen
Published: November 2024

The realization of intelligent and green manufacturing represents two core challenges currently faced by manufacturing enterprises. The “Intelligent Manufacturing Pilot Demonstration List” issued by the Ministry of Industry and Information Technology (MIIT) of the People’s Republic of China provides a sample of firms that have undergone stringent selection processes, demonstrating secure and controllable technological capabilities, with no intellectual property disputes. Using data from manufacturing firms listed on the Shanghai and Shenzhen stock exchanges from 2011 to 2020, we identify those that implemented intelligent manufacturing based on the aforementioned pilot list from 2015 to 2019 as the treatment group and the remaining firms as the control group to investigate whether intelligent manufacturing increases the number of green patent applications. The findings indicate that the implementation of intelligent manufacturing significantly increases green patent applications by 3.676% through three main pathways: reducing the level of financing constraints, improving resource utilization efficiency, and increasing R&D investment. Heterogeneity analysis reveals that state-owned enterprises exhibit a significantly stronger promotion effect on green innovation post-implementation of intelligent manufacturing compared to non-state-owned enterprises, with enterprises in the western region demonstrating the most pronounced enhancement in green innovation. Based on these findings, we propose corresponding recommendations from the perspectives of policy support and enterprise strategy.
Defining the Total CSR Z-Score: A Methodological Approach Using Regulations, Standards and Guidelines Through Application to the Greek Market
Authors: Pagkalou Foteini I. , Liapis Konstantinos I. , Thalassinos Eleftherios I.
Published: November 2024

Corporate responsibility is a complex and multidimensional concept, and this is what makes it difficult to quantify. The main purpose of this article is to construct a composite, but easily applicable and interpretable index for measuring the corporate social responsibility of companies. By combining existing legislation, reporting and measurement standards, as well as reward criteria, we have created 44 variables which cover all dimensions of CSR, including sustainability, and apply to the whole range of business activities. In order to collect values for the remaining qualitative variables, a prototype questionnaire was drawn up and completed by the 100 largest companies operating in Greece for a period of 3 fiscal years. Through the categorical principal components analysis procedure, we converted the above variables from the increasing categorical type to quantitative. We then performed the elbow technique to find the optimal number of clusters in which the companies and organizations in the sample could be integrated, and then we applied a hierarchical cluster. The above is a necessary procedure to be able to perform discriminant analysis, and through it, to calculate the Total CSR (ESG and Internal CSR) z-score for each new company. The equation generated by the discriminant analysis to calculate the z-score can calculate the “Total CSR Z-Score” for the companies. The contribution of our work is to establish the variables that shape corporate social responsibility and, through them, to determine a comprehensive summary index for its calculation. The practical value of the article is that it proposes a quantitative measurement of the level of corporate responsibility of each company, allowing comparisons between companies.
Physical Characterization of Ecological Briquettes Based on Vertisols and Sorghum Bicolor CS54 Fibers
Authors: Falama Abba , Kaoutoing Maxime Dawoua , Souaibou  , Falama Ruben Zieba , Dumbrava Virgil , Raidandi Danwé
Published: November 2024

The aim of this work is to perform the physical characterization of ecological briquettes based on vertisols and fibers of Sorghum bicolor CS54 from the city of Maroua located in the Far North of Cameroon, a country of Sub-Saharan Africa. Three sites of study have been identified and investigated, namely ZL (Zokok Laddeo), Ngassa (NG), and KG (Kongola). Different percentages of added plant fibers have been realized, including 0%; 2%; 6%; and 8% of fiber additions for each site considered. The experimental tests have revealed that the plasticity of clays is between 16.56% and 25.96%; it is higher in the Zokok Laddéo site (25.96%); and it is between 16.56 and 23.78% for Ngassa and Kongola. The main aggregates observed in the three sites are gravel, which varies between 1.90% and 16.12%, sand between 4.99 and 53.12%, silt, which varies between 2.30 and 36.10%, and clay which fluctuates between 20 and 38.77%. The coefficient of resistance to abrasion varies between 7.19% and 24.35 for the three sites. The highest rates are those of the samples from the Ngassa site (24.35%). The linear shrinkage of the samples varies between 2.9 and 13.04%. The apparent density of the briquettes are between 1587.30 kg/m3 and 2138.13 kg/m3; they are higher for the sites of Zokok Laddéo and Ngassa. The overall coefficient of the capillary rise value is between 0.42% and 16.85%. The interval variation in the obtained results for the different parameters are for most cases and depending on the sites studied in accordance with the defined international standards. These results have proven that the addition of bicolor Sorghum fibers CS54 in vertisols could improve the performance of constructions based on local and eco-friendly materials.
Artificial Intelligence Literacy Competencies for Teachers Through Self-Assessment Tools
Authors: Tenberga Ieva , Daniela Linda
Published: November 2024

This study investigates the key components of teachers’ self-assessed artificial intelligence (AI) literacy competencies and how they align with existing digital literacy frameworks. The rapid development of AI technologies has highlighted the need for educators to develop AI-related skills and competencies in order to meaningfully integrate these technologies into their professional practice. A pilot study was conducted using a self-assessment questionnaire developed from frameworks such as DigiCompEdu and the Selfie for Teachers tool. The study aimed to explore the relationships between AI literacy competence and already defined digital skills and competencies through principal component analysis (PCA). The results revealed distinct components of AI literacy and digital competencies, highlighting competence overlaps in some areas, for example, digital resource management, while also confirming that AI literacy competencies form a separate and essential category. The findings show that although AI literacy aligns with other digital skills and competencies, focused attention is required to professionally develop AI-specific competencies. These insights are key elements of future research to refine and expand AI literacy tools for educators, providing targeted professional development programs to ensure that teachers are ready for the opportunities and challenges of AI in education.
Detecting Soil Tillage in Portugal: Challenges and Insights from Rules-Based and Machine Learning Approaches Using Sentinel-1 and Sentinel-2 Data
Authors: Morais Tiago G. , Domingos Tiago , Falcão João , Camacho Manuel , Marques Ana , Neves Inês , Lopes Hugo , Teixeira Ricardo F. M.
Published: November 2024

Monitoring soil tillage activities, such as plowing and cultivating, is essential for aligning agricultural practices with environmental standards for soil health. Detecting these activities presents significant challenges, especially when relying on remotely sensed data. This paper addresses these challenges within the framework of the Common Agricultural Policy (CAP), which requires EU countries to enhance their environmental monitoring and climate action efforts. We used remote sensing data from Sentinel-1 and Sentinel-2 missions to detect soil tillage practices in 73 test farms in Portugal. Three approaches were explored: a rule-based method and two machine learning techniques based on XGBoost (XGB). One machine learning approach utilized the original imbalanced dataset, while the other employed a SMOTE (Synthetic Minority Oversampling Technique) approach to balance underrepresented soil tillage operations within the training set. Our findings highlight the inherent difficulty in detecting soil tillage operations across all methods, though the XGB-SMOTE approach demonstrated the most promising results, achieving a recall of 67% and an AUC-ROC (area under the receiver operating characteristic curve) of 74%. These results underscore the need for further research to develop a fully automated detection model. This work has potential applications for monitoring compliance with CAP mandates and informing environmental policy to better support sustainable agricultural practices.
The Path to Urban Sustainability: Urban Intelligent Transformation and Green Development—Evidence from 286 Cities in China
Authors: Zhong Yangyang , Zhong Yilin , Zhang Longpeng , Tang Zhiwei
Published: November 2024

Urban intelligence is reshaping urban innovation patterns, accelerating urban transformation, and significantly influencing green and sustainable development. By applying the non-radial directional distance function and an improved entropy method, this study measures the green development efficiency and levels across 286 Chinese cities from 2006 to 2020. The objectives of this study are twofold: first, to examine the impact of urban intelligence transformation on green development, and second, to investigate how urban intelligence influences common prosperity. The analysis employs a double/debiased machine learning model, with the “Smart City Pilot” policy as the focal point. The findings indicate that (1) urban intelligence transformation enhances both the level and efficiency of green development in Chinese cities; (2) this transformation fosters green development by driving urban innovation, upgrading industrial structures, and promoting green finance; and (3) the impact of urban intelligence varies across cities with different sizes, resource endowments, and marketization levels. Furthermore, the study constructs a common prosperity index to assess how urban intelligence contributes to residents’ well-being and social equity. The results suggest that urban intelligence transformation not only advances green development but also contributes to improving residents’ quality of life, thereby promoting a more equitable and prosperous society. These insights offer crucial policy guidance for China and other countries facing environmental and economic challenges in the digital age.
Chemical Assessment of Real Driving Tire and Road Wear Particles in Urban and Suburban Seoul, Korea
Authors: Mun Sunhee , Chong Hwansoo , Lim Yunsung , Kwon Sangil
Published: November 2024

Extensive research about non-exhaust fine particles from tires and brakes in vehicles has been reported, focusing on the significant effects on air pollution and human harm. Significant investigations are still needed in determining the cause of influence on the environment and human health. The regulations on emissions have been discussed in earnest, starting with the introduction of brake wear particle emission standards in Euro 7. Various indoor and outdoor experiments have been conducted, such as analysis of the amount of wear on tires and brakes, and analysis of the physical and chemical properties of fine particles, and the effect of non-exhaust fine wear particles on the atmosphere and human health, as fundamental data for the introduction of emission standards and the development of low-wear tires and brakes to meet regulations. Recently, international standardized indoor experimental methods for brakes have been announced, and indoor and outdoor experimental methods for tires have been continuously studied to develop international standardized methods. In particular, tire and road wear particles, including brake wear particles, are usually mixed with each other in the non-exhaust particles from a vehicle driving on real roads, and in-depth research is being performed on their accurate classification and characteristic analysis. In this study, the characteristics of the volatile organic compounds and marker substances for tire and tire and road wear particles were analyzed. A system was installed on the vehicle to collect non-exhaust wear fine particles from the vehicle running on two different roads, urban and suburban, of the Seoul area, and the proving ground road. The specific findings are as follows: (1) From the chemical analysis of the volatile organic compounds, high n-hexane and n-dodecane were measured in the tire–road-wear particles. (2) The volatile organic compound species in the PM2.5 (aerodynamic diameter ≤ 2.5 µm) increased as the vehicle velocity increased. (3) For the PM10 (aerodynamic diameter ≤ 10 µm), high volatile organic compound species were recorded at 40 km/h of the vehicle velocity. (4) This study also revealed that higher vinylcyclohexene and dipentene were measured in the particle size below 10 μm than those in PM2.5.
A Stakeholder-Related Procedure Model for Social Sustainability Assessment
Authors: Götze Uwe , Richter Fanny , Döring Julia
Published: November 2024

The importance of assessing the sustainability of companies and their activities is increasing. Especially since the implementation of the new Corporate Social Reporting Directive, even more companies are committed to reporting on the impacts of their businesses on sustainability. This is a challenge especially concerning the social dimension of sustainability. Some frameworks present various relevant social criteria that can be used as a basis for assessment. However, these do not provide detailed suggestions for handling the numerous methodological challenges of such a multi-criteria assessment: identification and selection of the relevant stakeholders, categories and indicators to measure the impacts on social sustainability, weighting and aggregation of these criteria, etc. Therefore, this paper contributes to the methodology of social sustainability assessment by presenting a procedure model for this specific assessment task. The novelty of the model results from its foundation by a review of methods for selection, normalisation, weighting and aggregation of social criteria, existing decision theory-based procedure models, as well as a stakeholder-oriented catalogue of criteria. The procedure model is structured hierarchically by subdividing the overall social sustainability-assessment task into different levels: stakeholders, categories, and indicators. Furthermore, appropriate methods are suggested for the single steps of the procedure model.
Research on Sustainable Design of Smart Charging Pile Based on Machine Learning
Authors: Liu Zongming , Liang Xinan , Li Linwei , Li Xinyu , Ou Wenwen
Published: November 2024

With the rapid growth of the electric vehicle market, the importance of the user experience and product sustainability requirements for intelligent charging stations has become increasingly significant. However, accurately capturing the complex associations between design features and sustainability elements remains challenging. Therefore, this study aims to balance user needs and environmental standards in designing smart charging piles, ensuring adherence to symmetry principles. This balance addresses the growing demand for personalization and ensures sustainability. In this paper, the semiotic approach to product construction (SAPAD) model is introduced to analyze the user behavioral process in depth and clarify the core needs of users. Subsequently, these core needs are translated into specific technical requirements for products, and a correlation matrix linking user needs with product technical requirements is constructed using fuzzy quality function deployment (FQFD) to identify design features that fulfill the user requirements. The sustainability factors are then comprehensively evaluated and prioritized based on three dimensions: economic, environmental, and social, i.e., the triple bottom line (TBL). Furthermore, a mapping matrix is developed to connect the design features and sustainability factors, which is combined with the particle swarm optimization–random forest (PSO-RF) algorithm to predict the sustainability factors associated with design features that meet users’ needs. The number of branches m and the maximum depth d of the random forest (RF) algorithm are optimized using the particle swarm optimization (PSO) method. The results indicate that the SAPAD-FQFD model effectively identifies the user needs and relevant product design features. In contrast, the PSO-RF model adeptly manages the nonlinear relationships between charging pile design features and various sustainability factors, e.g., aesthetics and material selection, ensuring that the intelligent charging pile meets users’ core needs in terms of form and function, while embodying the principles of design symmetry. This integrated approach effectively bridges the gap between user needs analysis and product functional design, ensuring the sustainability of the design solution. This study contributes a sustainable framework for the development and design of smart charging piles and related products, further promoting the adoption of green design principles and symmetry design concepts within the supporting infrastructure of new energy vehicles.
Decomposition and Symmetric Kernel Deep Neural Network Fuzzy Support Vector Machine
Authors: El Moutaouakil Karim , Roudani Mohammed , Ouhmid Azedine , Zhilenkov Anton , Mobayen Saleh
Published: November 2024

Algorithms involving kernel functions, such as support vector machine (SVM), have attracted huge attention within the artificial learning communities. The performance of these algorithms is greatly influenced by outliers and the choice of kernel functions. This paper introduces a new version of SVM named Deep Decomposition Neural Network Fuzzy SVM (DDNN-FSVM). To this end, we consider an auto-encoder (AE) deep neural network with three layers: input, hidden, and output. Unusually, the AE’s hidden layer comprises a number of neurons greater than the dimension of the input samples, which guarantees linear data separation. The encoder operator is then introduced into the FSVM’s dual to map the training samples to high-dimension spaces. To learn the support vectors and autoencoder parameters, we introduce the loss function and regularization terms in the FSVM dual. To learn from large-scale data, we decompose the resulting model into three small-dimensional submodels using Lagrangian decomposition. To solve the resulting problems, we use SMO, ISDA, and SCG for optimization problems involving large-scale data. We demonstrate that the optimal values of the three submodels solved in parallel provide a good lower bound for the optimal value of the initial model. In addition, thanks to its use of fuzzy weights, DDNN-FSVM is resistant to outliers. Moreover, DDNN-FSVM simultaneously learns the appropriate kernel function and separation path. We tested DDNN-FSVM on several well-known digital and image datasets and compared it to well-known classifiers on the basis of accuracy, precision, f-measure, g-means, and recall. On average, DDNN-FSVM improved on the performance of the classic FSVM across all datasets and outperformed several well-known classifiers.
Exclusion of Superinfection or Enhancement of Superinfection in Pestiviruses—APPV Infection Is Not Dependent on ADAM17
Authors: Geranio Francesco , Affeldt Sebastian , Cechini Angelika , Barth Sandra , Reuscher Carina M. , Riedel Christiane , Rümenapf Till , Lamp Benjamin
Published: November 2024

Some viruses can suppress superinfections of their host cells by related or different virus species. The phenomenon of superinfection exclusion can be caused by inhibiting virus attachment, receptor binding and entry, by replication interference, or competition for host cell resources. Blocking attachment and entry not only prevents unproductive double infections but also stops newly produced virions from re-entering the cell post-exocytosis. In this study, we investigated the exclusion of superinfections between the different pestivirus species. Bovine and porcine cells pre-infected with non-cytopathogenic pestivirus strains were evaluated for susceptibility to subsequent superinfection using comparative titrations. Our findings revealed significant variation in exclusion potency depending on the pre- and superinfecting virus species, as well as the host cell species. Despite this variability, all tested classical pestivirus species reduced host cell susceptibility to subsequent infections, indicating a conserved entry mechanism. Unexpectedly, pre-infection with atypical porcine pestivirus (APPV) increased host cell susceptibility to classical pestiviruses. Further analysis showed that APPV can infect SK-6 cells independently of ADAM17, a critical attachment factor for the classical pestiviruses. These results indicate that APPV uses different binding and entry mechanisms than the other pestiviruses. The observed increase in the susceptibility of cells post-APPV infection warrants further investigation and could have practical implications, such as aiding challenging pestivirus isolation from diagnostic samples.
Characterization and Fluctuations of an Ivermectin Binding Site at the Lipid Raft Interface of the N-Terminal Domain (NTD) of the Spike Protein of SARS-CoV-2 Variants
Authors: Lefebvre Marine , Chahinian Henri , La Scola Bernard , Fantini Jacques
Published: November 2024

Most studies on the docking of ivermectin on the spike protein of SARS-CoV-2 concern the receptor binding domain (RBD) and, more precisely, the RBD interface recognized by the ACE2 receptor. The N-terminal domain (NTD), which controls the initial attachment of the virus to lipid raft gangliosides, has not received the attention it deserves. In this study, we combined molecular modeling and physicochemical approaches to analyze the mode of interaction of ivermectin with the interface of the NTD-facing lipid rafts of the host cell membrane. We characterize a binding area that presents point mutations and deletions in successive SARS-CoV-2 variants from the initial strain to omicron KP.3 circulating in many countries in 2024. We show that ivermectin has exceptional flexibility, allowing the drug to bind to the spike protein of all variants tested. The energy of interaction is specific to each variant, allowing a classification according to their affinity for ivermectin in the following ascending order: Omicron KP.3 < Delta < Omicron BA.5 < Alpha < Wuhan (B.1) < Omicron BA.1. The binding site of ivermectin is subject to important variations of the NTD, including the Y144 deletion. It overlaps with the ganglioside binding domain of the NTD, as demonstrated by docking and physicochemical studies. These results suggest a new mechanism of antiviral action for ivermectin based on competitive inhibition for initial virus attachment to lipid rafts. The current KP.3 variant is still recognized by ivermectin, although with an affinity slightly lower than the Wuhan strain.
Smart Water Management with Digital Twins and Multimodal Transformers: A Predictive Approach to Usage and Leakage Detection
Authors: Syed Toqeer Ali , Muhammad Munir Azam , AlShahrani Abdul Aziz , Hammad Muhammad , Naqash Muhammad Tayyab
Published: November 2024

Effective water management is crucial in urban and rural settings, requiring efficient usage and timely detection of issues like leakages for sustainability. This paper introduces an integrated framework that combines Digital Twin technology with a multimodal transformer-based model for accurate water usage prediction and leakage detection. The system synchronizes real-time data from various sensors including flow meters, pressure sensors, and thermal imaging devices with a Digital Twin of the water network. Advanced transformer models, specifically the Informer model for long-term time-series prediction and a Water Multimodal Transformer for anomaly detection, process these data to capture complex patterns and dependencies. Experimental results demonstrate the framework’s effectiveness: the Informer model achieved an R2 score of 0.9995 and a Mean Squared Error (MSE) of 2.2, outperforming traditional models. For leakage detection, the model attained 98.4% accuracy and precision, an F1 score of 97.6%, a low False Positive Rate of 0.0019, and an Area Under the Curve (AUC) of 0.984. By fusing diverse sensor data and utilizing advanced transformer architectures, the framework provides a comprehensive view of the water network, enabling real-time decision-making, enhancing forecasting accuracy, and reducing water waste. This scalable solution supports sustainable water management practices in both urban and industrial contexts.
Dialogical interaction of literature and music as one of the productive ways of forming general cultural competence
Authors:   Municipal Budgetary Educational Institution «Secondary School No. 49» of Kursk, Metalichenko Rimma Kamilevna
Published: November 2024

The relevance and social and pedagogical significance of the dialogical interaction
of literature and music is important in the formation of general cultural competence of students
in a modern school. One of the main tasks facing a modern school is to increase the
level of personal culture. This is not only mastering social and cultural knowledge, but also
implementing activities that contribute to the transformation of this knowledge into moral
and ethical convictions, into the skills and abilities of creative activity, the ability to navigate in
the cultural space and the ability to apply aesthetic standards as evaluation criteria. The solution
to this problem is carried out within the framework of the formation of general cultural
competence in students. The process of forming a personal culture continues throughout a
person’s life. An important period of its formation is school years, and it is at this time that
students should gain tremendous experience in the field of national and universal culture. In
the process of learning, schoolchildren must achieve a certain level of general cultural competence.
General cultural competence in pedagogical theory is defined as a level of education
sufficient for self-education, self-knowledge, independent and well-founded judgments
about phenomena in various areas of culture, dialogue with representatives of other cultures.
Currently, as practice shows, most students have insufficiently developed knowledge, skills
and abilities in the field of literature, culture and art: children read little, acquaintance with
literary works and works of art is limited to the school curriculum. But every teacher wants to
educate a harmoniously developed, creatively gifted and competent person not only in the
field of literature, but also in art. Of course, the solution to this problem is the use of a dialogue
between literature and music in lessons in a modern school. This approach to the study of
literature in school is now becoming increasingly relevant, as it allows each student to perceive
the world as a whole. In this article, the author analyzes the role of dialogical interaction
between literature and music as one of the ways to form general cultural competence.
A systematic process-oriented approach to the implementation of the enterprise's information security management system
Authors: Tupkalo Viltalii , Cherepkov Serhii , Yarmolatii Andrii
Published: November 2024

In the context of ensuring information security (cybersecurity) of enterprises and critical infrastructure institutions, which include state enterprises (institutions) providing services for metrological support, conformity assessment, and standardization, the development of systemology and the implementation of an information security management system (ISMS) based on the principles of system process-oriented approach is a highly relevant task. The article concludes with the need for further substantiated research in this direction based on a critical analysis of well-known scientific studies (publications) of domestic and foreign scientists. First of all, this concerns the solution to the problem of identifying a set of information security objects in enterprises' managerial and technological processes systems. Since this system belongs to the «complex system» category, it becomes relevant to study the systemology of the enterprise ISMS as a systematic combination of its information and organizational resources. In this regard, the basis of the conducted research is the conceptual system statement that ISMS is an integral part of the enterprise's general management system. In the context of this statement, the author's vision for implementing the requirements of the current DSTU standard ISO/IEC 27001:2023 regarding the construction of ISMS based on the principles of system and process approach is outlined. For this, a number of system definitions and corresponding models are proposed, making it possible to implement the specified requirements of the standard within the framework of the proposed pyramid model of process-oriented enterprise management. Within the framework of the specified model, the author's interpretation of the definition of the concept «Enterprise Information field» is formulated, on the basis of which a structural task-solving staging model of ensuring enterprise information security is proposed.
Integrating Network Pharmacology and Molecular Docking to Identify the Active Substances and Mechanisms of Chrysanthemum against Dry Eye
Authors: Yanxue Zhang , Yu Tang , Kai Wu , Xiaolei Yao
Published: November 2024

Background: Dry eye is the most common ocular surface disease and is widely treated with chrysanthemum, an herbal medicine known for its anti-inflammatory mechanism. However, the active ingredients, potential targets, and pathways of chrysanthemum in treating dry eye have not been clearly identified.
Objective: The objective of this study is to explore the bioactive components and potential mechanism of chrysanthemum on dry eye using network pharmacology and molecular docking. Methods: We used the TCMSP database to search and screen the active ingredients of chrysanthemum and their related targets. Targets associated with dry eye were collected and screened using the Genecards database.
Biofield Energy - Health Effects of Solar Flares by Seema Bhattessa MR Pharms
Authors: Bhattessa Seema
Published: November 2024

Space weather is the term used to describe events, or storms, in space that affect humans. These events, including solar flares, coronal mass ejections, and their associated electromagnetic effects, are primarily attributed to magnetic shifts occurring on the Sun. These events intensify during solar maximum, the phase of the 11-year solar cycle leading up to the Sun’s polar shift, during which the Sun’s magnetic north and south poles switch. The resulting geomagnetic storms reach and affect Earth’s atmosphere, with impacts on electrical systems, including power infrastructure, communications systems, and biological systems. Epidemiological studies show correlations between solar activity and increased severity of neurologic symptoms, increased rates of cardiovascular events, and behavioural, immune, and other effects. Currently, the Sun is approaching solar maximum, which will peak in 2025, bringing an increased frequency and intensity of geomagnetic storms.
PREECLAMPSIA CARE (A WEB-BASED INFORMASTION SYSTEM) EFFECTIVE FOR DETECTING THE RISK OF PREECLAMPSIA IN PREGNANT WOMEN
Authors: Fajaria Nur Aini  , Zuhriyatun Fitria , Yuliani Diki Retno , Hapsari Wanodya
Published: November 2024

One of the leading causes of maternal and newborn fatalities worldwide is preeclampsia. Only healthcare professionals can now detect the risk of preeclampsia, and they still do so manually. Pregnant women can't know if they have preeclampsia risk factors or not. Preeclampsia risk detection is significant because it can determine a pregnant woman's preeclampsia risk, allowing for early diagnosis and prevention. A web-based information system can be used to identify pregnant women who are at risk of preeclampsia. Women who are expecting can utilize laptops or smartphones linked to the internet. Numerous research studies have demonstrated that information technology solutions can enhance health services regarding data transmission, health outcomes, prescription adherence, and patient monitoring compliance. This descriptive study explained its usefulness; live sampling was used as the sampling method, and 33 pregnant women served as the study's subjects. Web-based information systems and questionnaires are used to collect data. Pregnant women's ability to independently recognize preeclampsia risk can be enhanced by employing a web-based information system to identify different levels of preeclampsia risk. Of these, 51.5% have no risk of preeclampsia, 18.2% have a moderate risk, and 24.24% have a high risk. The effectiveness rate used in the Technology Acceptance Model (TAM) questionnaire is 92%.
Современные возможности хирургической невротизации роговицы. Обзор литературы
Authors: Д.А. Кумыкова , В.В. Бржеский , Е.Л. Ефимова
Published: November 2024

Нейротрофическая кератопатия – дегенеративное заболевание, сопровождающееся снижением или полной утратой чувствительности роговицы вследствие поражения ее нервов. Трудности в достижении стойкого удовлетворительного эффекта, несмотря на многообразие консервативных и хирургических подходов к лечению, связаны с отсутствием прямой патогенетической направленности большинства применяемых методик. Одним из действенных способов решения рассматриваемой проблемы явилась хирургическая невротизация роговицы – операция, используемая для восстановления ее чувствительности путем пересадки интактного сенсорного нерва непосредственно к пораженной роговице или опосредованно – при помощи интерпозиционного нервного трансплантата (для восстановления без натяжения). Несмотря на техническую сложность операции и необходимость междисциплинарного подхода, достичь восстановления чувствительности роговицы и ее реэпителизации удается в большинстве случаев. Совершенствование методик хирургической невротизации роговицы имеет большие перспективы в лечении нейротрофической кератопатии благодаря их прямой патогенетической направленности.

Neurotrophic keratopathy is a degenerative disease accompanied by decreased or complete loss of corneal sensitivity due to damage to corneal nerves. Difficulties in achieving a persistent satisfactory effect, despite the variety of conservative and surgical approaches to treatment, are associated with the lack of direct pathogenetic orientation of most of the methods used. One of the effective ways to solve the problem in question was surgical corneal neurotization – an operation used to restore corneal sensitivity by transplanting an intact sensory nerve directly to the affected cornea or indirectly, using an interposition nerve graft (for tension-free repair). Despite the technical complexity of the operation and the need for an interdisciplinary approach, restoration of corneal sensitivity and reepithelialization can be achieved in most cases. Improvement of techniques of surgical corneal neurotization has great prospects in the treatment of neurotrophic keratopathy because of their direct pathogenetic orientation.
РАЗРАБОТКА АЛГОРИТМА СОСТАВЛЕНИЯ СТАНДАРТНОЙ ОПЕРАЦИОННОЙ ПРОЦЕДУРЫ (СОП) В УСЛОВИЯХ ПРОИЗВОДСТВЕННЫХ АПТЕК
Authors: И.А. Савченко , И.Н. Корнеева , Е.А. Лукша , М.А. Шмальц
Published: November 2024

В статье представлен алгоритм создания стандартной операционной процедуры (СОП) для аптечных организаций, осуществляющих контроль качества изготовленных лекарственных препаратов. Актуальность разработки СОПов определена внедрением международных отраслевых стандартов в фармацевтическую деятельность. С целью обеспечения единообразия системы документации аптечной организации предложена общая структура стандартной операционной процедуры для контроля качества лекарственных форм, изготовленных в аптеке. Приведены основные этапы разработки СОП, даны рекомендации по оформлению документа, его актуализации, внесению изменений и дополнений. Разработка шаблонов стандартных операционных процедур позволит аптекам создавать собственные СОПы, учитывающие особенности конкретной организации.

The article presents the algorithm for creating a standard operating procedure (SOP) for pharmacy organizations that carry out quality control of manufactured medicines. The relevance of developing SOPs is determined by the implementation of international industry standards in pharmaceutical field. In order to ensure the uniformity of the documentation system of the pharmacy organization, we suggested the general structure of the standard operating procedure for the quality control of dosage forms manufactured at the pharmacy. The main stages of the development of the SOP are given, recommendations are given on the design of the document, it’s updating, making changes and additions. The development of templates for standard operating procedures will allow pharmacies to create their own SOPs that take into account the characteristics of a particular organization.
КОЛИЧЕСТВЕННЫЙ СПЕКТРОФОТОМЕТРИЧЕСКИЙ АНАЛИЗ ЛЕКАРСТВЕННОГО ПРЕПАРАТА «МЕТРОКЕТОКОНАЗОЛЬ»
Authors: А.И. Замараева , Н.С. Бессонова , Т.А. Кобелева , А.И. Сичко
Published: November 2024

Приведены результаты опытов по анализу метронидазола и кетоконазола в новом лекарственном препарате «Метрокетоконазоль», изготовленного на титансодержащей основе (гель «Тизоль»). Представлены ультрафиолетовые спектры поглощения этанольных растворов ингредиентов мази. Установлено, что для количественного определения необходимо использовать длины волн 241 нм и 312 нм. Выбраны оптимальные условия и разработан способ анализа соединений в модельной смеси с относительной погрешностью ±1,47-1,73%. Предложена методика количественного спектрофотометрического определения метронидазола и кетоконазола в исследуемой мягкой лекарственной форме с ошибкой, не превышающей пределов допустимых норм и отклонений.

The results of experiments on the analysis of metronidazole and ketoconazole in a new drug "Metroketoconazole" made on a titanium-containing basis ("Tizol" gel) are presented. Ultraviolet absorption spectra of ethanol solutions of ointment ingredients are presented. It is established that for quantitative determination it is necessary to use the wavelengths of 241 nm and 312 nm. Optimal conditions were selected and a method was developed for analyzing compounds in a model mixture with a relative error of ±1.47-1.73%. A method for quantitative spectrophotometric determination of metronidazole and ketoconazole in the studied soft dosage form with an error not exceeding the limits of permissible norms and deviations is proposed.
РАЗРАБОТКА И ВАЛИДАЦИЯ МЕТОДИКИ ОПРЕДЕЛЕНИЯ СИБУТРАМИНА В ЛЕКАРСТВЕННЫХ ПРЕПАРАТАХ
Authors: А.М. Суханова , И.Б. Перова , К.И. Эллер , Г.М. Родионова
Published: November 2024

Данная работа посвящена разработке и валидации методики определения сибутрамина в лекарственных препаратах для осуществления их контроля качества с целью дальнейшей разработки нормативной документации на территории Российской Федерации. Подобраны экстрагент, хроматографические условия разделения для оптимального определения сибутрамина в лекарственных препаратах методом высокоэффективной жидкостной хроматографии (ВЭЖХ) с использованием ультрафиолетового детектора (УФ). Доказаны специфичность, линейность, правильность методики; относительная ошибка единичного определения не превышает 1,5% (0,70%), коэффициент вариации (RSD) меньше 1% (0,93%), проведена внутрилабораторная прецизионность, относительная ошибка которой = 0,16%. Определен предел обнаружения на уровне 0,004 мг/мл; предел количественного определения - 0,01 мг/мл. Методика является правильной, систематическая ошибка отсутствует, следовательно, методика пригодна для дальнейшего использования и включения в нормативную документацию.

This research is devoted to the development and validation of a method for the determination of sibutramine in drugs for their quality control in order to further develop regulatory documentation in the Russian Federation. Solvent and chromatographic separation conditions were selected for the optimal determination of sibutramine in drugs by high performance liquid chromatography (HPLC) using an ultraviolet detector (UV). The specificity, linearity, correctness of the method have been proved, the relative error of a single determination does not exceed 1.5% (0.70%), the calculated value of the Student's test tcalc (2.14) is less than the tabular ttable (2.36), the coefficient of variation (RSD) does not exceed 1% (0.93%), the intralaboratory precision was carried out, the relative error of which = 0.16%. The detection limit was determined at the level of 0.004 mg/ml; the limit of quantitative determination is 0.1 mg/ml. The methodology is correct, there is no systematic error, therefore, it is suitable for further inclusion in the regulatory documents.