bluuebunny/crossref_metadata_2025_split huggingface dataset:
Surveying the Motivation of Pre-service Teachers and the Performance of Nigerian Primary School Pupils
Authors: Okeke Tobechukwu Ebele 
Published: January 2024

This study investigates the crucial interplay between the motivation of pre-service teachers and the academic performance of primary school pupils in basic science and technology subjects within the Oyi Local Government Area of Anambra State, Nigeria. A descriptive survey method was used. The sample comprised 200 pre-service teachers and primary six students in government primary schools in Oyi Local Government Area. The researchers also constructed questionnaires and administered them to the sampled population in Oyi Local Government Area of Anambra State. Preliminary findings underscore the significance of pre-service teacher motivation in shaping the academic success of primary school pupils. These attributes contribute to a more conducive and effective learning environment, ultimately benefitting the academic performance of primary school pupils. However, challenges persist in providing consistent settlements, recognition, instructional materials, and retraining opportunities for pre-service teachers. Addressing these challenges is crucial for sustaining teacher motivation, improving teaching quality, and enhancing the educational experience for students.

Received: 10 November 2023 | Revised: 29 December 2023 | Accepted: 25 January 2024

Conflicts of Interest
The author declares that she has no conflicts of interest to this work.

Data Availability Statement
Data sharing is not applicable to this article as no new data were created or analyzed in this study.

Author Contribution Statement
Tobechukwu Ebele Okeke: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Resources, Data curation, Writing - original draft, Writing - review & editing, Visualization.
Analysis of the Operational Performance of International Aviation Institutions with the EIFTOPSIS Method
Authors: ÖZDEMİR Mustafa 
Published: January 2024

Purpose: The main goal of this study is to rank the operational performance variables used in aviation according to their importance levels and to measure the operational performance of international aviation institutions.
Methodology: An extended intuitionistic fuzzy TOPSIS method with maximum deviation is used in criterion weighting and performance measurement, which is relatively new and has no use case in aviation.
Findings: According to the results obtained in the study, it is understood that the total airport movements controlled among the variables used in the operational performance evaluation are the criterion with the highest importance. DSNA (France), ENAIRE (Spain), and DHMI (Türkiye) are in the top three in the best operational performance rankings.
Originality: The operational performance variables offered by EUROCONTROL have been tested for the first time with the extended intuitionistic fuzzy TOPSIS method.
Radiative effect of thin cirrus clouds in the extratropical lowermost stratosphere and tropopause region
Authors: Spang Reinhold , Müller Rolf , Rap Alexandru 
Published: January 2024

Abstract. Cirrus clouds play an important role in the radiation budget of the Earth; nonetheless, the radiative effect of ultra-thin cirrus clouds in the tropopause region and in the lowermost stratosphere remains poorly constrained. These clouds have a small vertical extent and optical depth and are frequently neither observed even by sensitive sensors nor considered in climate model simulations. In addition, their short-wave (cooling) and long-wave (warming) radiative effects are often in approximate balance, and their net effect strongly depends on the shape and size of the cirrus particles. However, the CRyogenic Infrared Spectrometers and Telescopes for the Atmosphere instrument (CRISTA-2) allows ultra-thin cirrus clouds to be detected. Here we use CRISTA-2 observations in summer 1997 in the Northern Hemisphere midlatitudes together with the Suite Of Community RAdiative Transfer codes based on Edwards and Slingo (SOCRATES) radiative transfer model to calculate the radiative effect of observed ultra-thin cirrus. Using sensitivity simulations with different ice effective particle size and shape, we provide an estimate of the uncertainty in the radiative effect of ultra-thin cirrus in the extratropical lowermost stratosphere and tropopause region during summer and – by extrapolation of the summer results – for winter. Cloud top height and ice water content are based on CRISTA-2 measurements, while the cloud vertical thickness was predefined to be 0.5 or 2 km. Our results indicate that if the ice crystals of these thin cirrus clouds are assumed to be spherical, their net cloud radiative effect is generally positive (warming). In contrast, assuming aggregates or a hexagonal shape, their net radiative effect is generally negative (cooling) during summer months and very likely positive (warming) during winter. The radiative effect is in the order of ±(0.1–0.01) W m−2 for a realistic global cloud coverage of 10 %, similar to the magnitude of the contrail cirrus radiative forcing (of ∼ 0.1 W m−2). The radiative effect is also dependent on the cloud vertical extent and consequently the optically thickness and effective radius of the particle size distribution (e.g. effective radius increase from 5 to 30 µm results in a factor ∼ 6 smaller long- and short-wave effects, respectively). The properties of ultra-thin cirrus clouds in the lowermost stratosphere and tropopause region need to be better observed, and ultra-thin cirrus clouds need to be evaluated in climate model simulations.
Investigating the differences in calculating global mean surface CO2 abundance: the impact of analysis methodologies and site selection
Authors: Wu Zhendong , Vermeulen Alex , Sawa Yousuke , Karstens Ute , Peters Wouter , de Kok Remco , Lan Xin , Nagai Yasuyuki , Ogi Akinori , Tarasova Oksana 
Published: January 2024

Abstract. The World Meteorological Organization (WMO) Global Atmosphere Watch (GAW) coordinates high-quality atmospheric greenhouse gas observations globally and provides these observations through the WMO World Data Centre for Greenhouse Gases (WDCGG) supported by Japan Meteorological Agency. The WDCGG and the National Oceanic and Atmospheric Administration (NOAA) analyse these measurements using different methodologies and site selection to calculate global annual mean surface CO2 and its growth rate as a headline climate indicator. This study introduces a third hybrid method named GFIT, which serves as an independent validation and open-source alternative to the methods described by NOAA and WDCGG. We apply GFIT to incorporate observations from most WMO GAW stations and 3D modelled CO2 fields from CarbonTracker Europe (CTE). We find that different observational networks (i.e. NOAA, GAW, and CTE networks) and analysis methods result in differences in the calculated global surface CO2 mole fractions equivalent to the current atmospheric growth rate over a 3-month period. However, the CO2 growth rate derived from these networks and the CTE model output shows good agreement. Over the long-term period (40 years), both networks with and without continental sites exhibit the same trend in the growth rate (0.030 ± 0.002 ppm yr−1 each year). However, a clear difference emerges in the short-term (1-month) change in the growth rate. The network that includes continental sites improves the early detection of changes in biogenic emissions.
The effect of different Climate and Air Quality policies in China on in situ Ozone production in Beijing
Authors: Nelson Beth S. , Liu Zhenze , Squires Freya A. , Shaw Marvin , Hopkins James R. , Hamilton Jacqueline F. , Rickard Andrew R. , Lewis Alastair C. , Shi Zongbo , Lee James D. 
Published: January 2024

Abstract. In recent years, clean air policies have led to reductions in air pollution across China. Alongside this, emerging carbon neutrality (CN) policies that aim to address the impacts of climate change may also deliver air quality (AQ) co-benefits or climate penalties. Different CN policies will lead to different changes in volatile organic compound (VOC), NOx, and particulate matter (PM) emissions, which will in-turn impact the photochemical production of secondary pollutants such as ozone (O3). It is currently unclear how different combinations of AQ and CN policies may impact in situ O3 production across China in the future. A detailed chemical box model incorporating the Master Chemical Mechanism was developed to investigate the impact of combined AQ and CN policies on O3 formation in Beijing. The Multi-resolution Emission Inventory model for Climate and air pollution research (MEIC) and the Dynamic Projection model for Emissions in China (DPEC) were used to estimate future pollutant mixing ratios, relative to ambient observations of 35 VOCs, NOx, CO and aerosol surface area (ASA) during the APHH-Beijing 2017 summer campaign. The most ambitious policy scenario, “Ambitious Pollution 1.5D goals", led to the largest reduction in O3 production by 2060, but was not the most impactful scenario for reducing O3 production between 2030–2045. Larger reductions were observed under the “Ambitious Pollution Neutral goals” policy which focuses on achieving net zero by 2060. O3 production was found to be most sensitive to changes in the OLE2 group of VOCs (alkenes where kOH > 7 x 104 ppm-1 min-1; a 5 % increase in OLE2 increased simulated O3 production by 1.12 %). However, reducing less reactive but higher concentration species in Beijing (including methanol and short-chain alkanes) led to larger reductions in O3 production under all scenarios. O3 production was not sensitive to changes in ASA, with a 69 % decrease in ASA leading to a change of < 1 % in O3. However, doubling biogenic VOCs in the model further increased O3 production in 2060 under all future scenarios by up to 18 %, indicating that the influence of future climate-induced changes in biogenic emissions may have a significant impact on in situ O3 formation in Beijing. This study highlights that the emission trajectories of certain specific VOCs are highly influential in determining possible future O3 air quality effects that may arise from increasing ambient temperatures and decarbonisation in Beijing.
Morphometric studies of the skin of adult cows
Authors: Shafiev A. P. , Kudryashov A. A. , Safronov D. I. 
Published: January 2024

Relevance. The skin of cattle consists of the epidermis and dermis. The dermis, or the skin itself, in turn consists of papillary and mesh layers. However, in the literature we have not found studies on the morphometry of different topographic areas of the skin of cattle. The aim of the study is to conduct comparative morphometric studies of the skin of various topographic zones in adult cows.Methods. For morphometric studies, histological preparations prepared according to the generally accepted method from skin samples of different topographic areas in adult cows were used. The research was carried out at the of the St. Petersburg State University of Veterinary Medicine Department of Pathological Anatomy and Forensic Veterinary Medicine and at the Department of Biology, Ecology and Histology. Morphometric studies of histological preparations were used to study the thickness of the dermis proper, as well as bundles of collagen fibers of the mesh layer of the dermis. The results of the studies were processed using the "Biostat" program.Results. Morphological features of the skin of different topographic areas in adult cows have been established, which are manifested by differences in the thickness of the skin layers and bundles of collagen fibers of the dermis. The morphometry performed allows us to expand the data on the morphological structure of the skin of adult cows.
3D Interior Design System Model Based on Computer Virtual Reality Technology
Authors: Yu Dai Yu Dai 
Published: January 2024

Globally, data volume is increases exponentially with increase in the proliferation with Cloud Computing. MapReduce is emerged as the prominent solution for the unprecedented growth in the efficient manner as it process both structured and unstructured data. The dynamic landscape of Virtual Reality has seen a significant shift towards technology-driven approaches, with data analytics and personalized learning becoming increasingly important. This paper introduces an innovative framework that leverages the power of Hadoop and MapReduce to elevate 3D virtual reality experiences within diverse VR Cloud settings. This paper presents the development of an efficient Cache-Based MapReduce framework (CMF) where Cache algorithms are effectively used to process queries on large-scale cloud-based data. The Hadoop System processes data in single-node Hadoop Clusters (Pseudo-distributed) as well as heterogeneous Hadoop Clusters (fully distributed nodes) within Amazon Web Services (AWS). The Hadoop System process the data in the single node Hadoop Cluster (Pseudo-distributed) heterogeneous Hadoop Cluster (fully distributed node) in the Amazon Web Services (AWS). The experimental analysis is evaluated for the SmallGutenberg and LargeGutenberg database. The developed model achieves the average reduction in job of 48.01% with reduction in execution time of 51.99%. The CMF of 7-node, 9-node, 15-node and 20-node reduction in execution time is measured as 49.91%, 51.38%, 54.71% and 45.29% respectively.
Improve the Bi-LSTM Model of University Financial Information Management Platform Construction
Authors: Fang Liu Fang Liu 
Published: January 2024

Information Management Systems are vital tools for businesses and organizations to manage their data effectively, make informed decisions, ensure data security and compliance, and enhance operational efficiency. This paper presents a robust approach to information management through the utilization of the Optimized Probabilistic Bidirectional Long Short-Term Memory (OP_Bi-LSTM) model. The study developed into the architecture and application of Simulated Annealing (SA) for hyperparameter optimization, emphasizing the impact of fine-tuning on model performance. OP_Bi-LSTM, rooted in Bidirectional Long Short-Term Memory, exhibits superior sequential data processing capabilities, making it well-suited for a variety of information management tasks. The proposed OP_BI-LSTM hierarchical architecture further enhances its pattern recognition capabilities in the information management system. Results from extensive experimentation demonstrate the model's versatility and adaptability in various applications, such as sentiment analysis, fraud detection, and time-series forecasting. The proposed OP_BI-LSTM model performance analysis is evaluated for the consideration of the different customers and product data. The propsoed OP_Bi-LSTM model achieves the classification accuracy of 0.98. It is stated that OP_Bi-LSTM emerges as a powerful tool for information management, offering exceptional performance and adaptability. As the field of deep learning and information management continues to evolve, this model holds great promise for addressing complex data challenges and facilitating data-driven decision-making in a variety of industries.
Evaluation model of English Informatization Teaching Quality in Universities Based on Particle Swarm Algorithm
Authors: Miao Tian Miao Tian 
Published: January 2024

Teaching quality in the field of English education plays a crucial role in shaping students' language proficiency, communication skills, and overall understanding of the language. One of the most significant contributions of deep learning to English education is its ability to personalize instruction. Deep learning algorithms analyze individual students' learning patterns, strengths, and weaknesses. This paper designed a framework for enhancing teaching quality in English education by implementation of Non-Convex Particle Swarm Optimization and Optimization (NC-PSOO) with a Generative Adversarial Network (GAN). The proposed model NC-PSOO with GAN, presents the information related to the teaching and learning process. The features are computed based on the utilization of the non-convex estimation for the analysis of the variables. Through the implementation of an effective process of data pre-processing using the Fejer filter, feature selection and extraction with NC-PSOO, and classification with GAN, this model aims to improve student performance, elevate the quality of teaching materials, increase student participation, enhance homework quality, and balance exam difficulty. The performance of NC-PSOO with GAN is compared with conventional optimization techniques like Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) to demonstrate its superior efficacy. The findings highlight the model's capability to achieve higher accuracy, precision, recall, and F1 score, ultimately improving teaching quality in English education.
Predictive Resource Allocation Strategies for Cloud Computing Environments Using Machine Learning
Authors: Torana Kamble Et al. 
Published: January 2024

Cloud computing revolutionizes fast-changing technology. Companies' computational resource use is changing. Businesses can quickly adapt to changing market conditions and operational needs with cloud-based solutions' adaptability, scalability, and cost-efficiency. IT operations and service delivery have changed due to widespread computational resource access. Cloud computing efficiently allocates resources in cloud environments, making it crucial to this transformation. Resource allocation impacts efficiency, cost, performance, and SLAs. Users and providers can allocate cloud resources based on workloads using elasticity, scalability, and on-demand provisioning. IT economics and operational effectiveness have changed due to rapid and flexible resource allocation. Proactive versus reactive resource allocation is key to understanding cloud resource management challenges and opportunities. Reactive strategies allocate resources only when shortages or surpluses occur at demand. This responsive strategy often leads to inefficiencies like over- or under-allocation, which raises costs and lowers performance. Predictive analysis and workload forecasting predict resource needs in proactive resource allocation. Optimize resource use to avoid shortages and over-provisioning. Attention has been drawn to proactive predictive resource allocation. These methods predict resource needs using historical data, machine learning, and predictive analytics. Predictive strategies optimize resource allocation by considering future decisions. Reduced bottlenecks boost user satisfaction and lower operational costs. Matching resource distribution to workloads optimizes cloud resource management. Resource allocation prediction improves with deep learning. CNN, LSTM, and Transformer cloud resource forecasting algorithms are promising. New tools for accurate and flexible workload predictions have come from their ability to spot intricate patterns in historical data. This paper compares CNN, LSTM, and Transformer deep learning algorithms for cloud computing resource allocation forecasting. This study determines the best predictive accuracy and workload ada[1]ptability algorithm using Google Cluster Data (GCD). The study evaluates upgrading cloud computing resource allocation with the Transformer model. This study advances predictive resource allocation strategies, which can help cloud service providers and organizations improve resource utilization, cost-effectiveness, and performance in the face of rapid technological change.
Bell Hooks, Paulo Freire e Wilhelm Reich: um diálogo possível?
Authors: Calaça Lilian , Macedo Eunice 
Published: January 2024

Este artigo propõe um diálogo entre a Pedagogia Crítica freiriana, a perspectiva pedagógica feminista de bell hooks e o princípio do ser energético de Wilhelm Reich, com vistas a uma formação docente voltada à educação humanizada e emancipadora. Com isso, delineamos os pensamentos conforme a figura humana representada pelos três autores, com ideias e ações permeadas por (desejo de) liberdade, ação política e preocupação com outras pessoas, numa relação mediatizada pelo mundo. Aprofundamos a reflexão a partir de uma pesquisa que se desenvolve no contexto de um curso de Pedagogia, em uma universidade pública com base freiriana, para analisarmos as implicações do Círculo de Cultura na formação docente para promover uma educação emancipadora na atualidade.
Educação em saúde e atenção básica: a interseção entre políticas públicas e o Programa Saúde na Escola
Authors: Cardoso Beatryz de Oliveira , Da Costa Názara Katarina Alves , Da Silveira Rodrigo Euripedes , Fernandes Jefferson Douglas Lima , Cheffer Maycon Hoffmann , De Oliveira Valquíria Magalhães , Loureiro Nina Rosa Gomes de Oliveira , Monteiro Jéssica Vanessa Menezes , Miyadaira Celenir Teló , Freitas Mayara Kaline 
Published: January 2024

O Programa Saúde na Escola (PSE) é uma iniciativa desenvolvida no âmbito das políticas públicas no Brasil, resultado da parceria entre os Ministérios da Saúde e da Educação. O programa atua em diversos eixos, como a promoção da saúde, prevenção de doenças, avaliação oftalmológica, combate ao mosquito Aedes aegypti, entre outros. Este estudo pretende analisar de que maneira a integração do PSE, aliada às políticas públicas e à atenção básica, atua de forma cooperativa na promoção da saúde. A pesquisa ocorreu dentro das bases de dados PubMed, BVS, Scielo e Google academico, no periodo entre agosto e dezembro de 2023, os Descritores em Ciências da Saúde (DeCS) usados foram "Políticas Públicas de Saúde", "Programa Saúde na Escola", "Atenção Básica" e "Educação em Saúde". Como critério de inclusão, apenas estudos na língua portuguesa, gratuitos e publicados entre 2016 e 2023. Os critérios de exclusão foram estudos incompletos, repetidos entre as bases de dados, fora do escopo, trabalhos de conclusão de curso, resumos ou capítulos publicados em anais e livros. Ao final, apenas 11 artigos foram selecionados para compor o estudo. O programa é crucial ao integrar-se com a saúde básica, pois fortalece a prevenção e o acesso aos serviços essenciais desde a infância. Essa colaboração permite a identificação precoce de problemas de saúde, promovendo a continuidade do cuidado e estabelecendo uma base sólida para a formação de hábitos saudáveis. O PSE desempenha um papel vital na promoção da saúde entre crianças e adolescentes, implementando diversas ações tangíveis que abrangem desde avaliações de saúde e vacinações até orientações sobre higiene e promoção da atividade física. O PSE, ao integrar-se às políticas públicas, beneficia-se das diretrizes estratégicas e do suporte financeiro, enquanto a atenção básica oferece a base operacional e o suporte prático para a implementação eficaz no nível local.