bluuebunny/crossref_metadata_2025 huggingface dataset:
InsNet-CRAFTY v1.0: Integrating institutional network dynamics powered by large language models with land use change simulation
Authors: Zeng Yongchao , Brown Calum , Byari Mohamed , Raymond Joanna , Schmitt Thomas , Rounsevell Mark
Published: October 2024

Abstract. Understanding and modelling environmental policy interventions can contribute to sustainable land use and management but is challenging because of the complex interactions among various decision-making actors. Key challenges include endowing modelled actors with autonomy, accurately representing their relational network structures, and managing the often-unstructured information exchange. Large language models (LLMs) offer new ways to address these challenges through the development of agents that are capable of mimicking reasoning, reflection, planning, and action. We present InsNet-CRAFTY (Institutional Network – Competition for Resources between Agent Functional Types) v1.0, a multi-LLM-agent model with a polycentric institutional framework coupled with an agent-based land system model. The numerical experiments simulate two competing policy priorities: increasing meat production versus expanding protected areas for nature conservation. The model includes a high-level policy-making institution, two lobbyist organisations, two operational institutions, and two advisory agents. Our findings indicate that while the high-level institution tends to avoid extreme budget imbalances and adopts incremental policy goals for the operational institutions, it leaves a budget deficit in one institution and a surplus in another unresolved. This is due to the competing influence of multiple stakeholders, which leads to the emergence of a path-dependent decision-making approach. Despite errors in information and behaviours by the LLM agents, the network maintains overall behavioural believability, demonstrating error tolerance. The results point to both the capabilities and challenges of using LLM agents to simulate policy decision-making processes of bounded rational human actors and complex institutional dynamics, such as LLM agents’ high flexibility and autonomy, alongside the complicatedness of agent workflow design and reliability in coupling with existing programmed land use systems. These insights contribute to advancing land system modelling and the broader field of institutional analysis, providing new tools and methodologies for researchers and policy-makers.
Mixing state, spatial distribution, sources and photochemical enhancement to sulfate formation of black carbon particles in the Arctic Ocean during summer
Authors: Wang Longquan , Yan Jinpei , Chen Afeng , Jiang Bei , Yue Fange , Yu Xiawei , Xie Zhouqing
Published: October 2024

Abstract. Black carbon heats the atmosphere by absorbing solar radiation and regulates the radiation balance of the Earth. Specifically in the Arctic region, black carbon accelerates Arctic warming by simultaneously altering surface albedo. Nonetheless, assessing the climatic impacts of black carbon aerosols in the Arctic is challenging due to their considerable variability in temporal and spatial distribution, sources, and chemical composition. Black carbon particles (0.2–2 μm) in the Arctic Ocean were investigated using a ship-based single particle aerosol mass spectrometer from July to August 2017. In the central Arctic Ocean, near the Norwegian Sea-Iceland and the North Atlantic, biomass combustion is the predominant source of black carbon particles, constituting over 50 %, with a particularly high contribution exceeding 70 % in the central Arctic Ocean. Within the Chukchi Sea region, terrestrial transport from mid and low latitudes emerges as the primary source of black carbon particles, representing over 50 %, with biomass combustion and anthropogenic pollution sources each contributing around 25 %. Near Svalbard, biomass combustion sources and terrigenous transport stand out as the primary sources of black carbon particles, with their contributions being comparable. Furthermore, the ratio of sulfate to nitrate in black carbon particles was notably higher compared to that in sea salt particles. This ratio increased with elevated black carbon content and sunlight intensity, suggesting that Arctic black carbon particles substantially facilitated sulfate formation through photochemical processes. Such interactions could potentially modify the mixing state of Arctic black carbon particles and their radiative impacts.
The ACCESS-AM2 climate model strongly underestimates aerosol concentration in the Southern Ocean, but improving it could be problematic for the modelled climate system
Authors: Fiddes Sonya L. , Woodhouse Matthew T. , Mallet Marc D. , Lamprey Liam , Humphries Ruhi S. , Protat Alain , Alexander Simon P. , Hayashida Hakase , Putland Samuel G. , Miljevic Branka , Schofield Robyn
Published: October 2024

Abstract. The interaction of natural marine aerosol with clouds and radiation is a significant source of climate model uncertainty. The Southern Ocean represents a key area to understand these interactions, and a region where significant model biases exist. Here we provide an evaluation of the Australian Community Climate and Earth System Simulator atmosphere model which includes a double-moment aerosol scheme. We evaluate against condensation nuclei (N10) and cloud condensation nuclei (CCN) from seven ship campaigns and three terrestrial locations, spanning the years 2015–2019. We find that N10 is heavily underestimated in the model across all regions and seasons by more than 50 % and in some cases by over 80 % at higher latitudes. CCN is also strongly underestimated over marine and Antarctic regions, often by more than 50 %. We then perform seven sensitivity tests to explore different aerosol configurations. We find that updating the dimethyl sulfide climatology and turning on the primary marine organic aerosol flux marginally improves marine CCN by between 4–9 %. N10 however was reduced by between 3–9 %, resulting in worse model performance. The Southern Ocean radiative bias is also reduced by this combination of changes, with limited adverse effects. We also test altering the sea spray flux to use wind gust instead of mean wind speed, which significantly improved CCN in the marine regions, but resulted in detrimental impacts on the radiation budget. Our results indicate significant problems in the model’s microphysical processes and with over tuning. We suggest this needs to be addressed in a holistic way.
Intraseasonal variability of North Pacific Intermediate Water induced by mesoscale eddies
Authors: Qiang Ren , Liu Yansong , Nan Feng , Wang Ran , Diao Xinyuan , Yu Fei , Chen Zifei , Wang Jianfeng , Liu Xinchuan
Published: October 2024

Abstract. The North Pacific Intermediate Water (NPIW) is one of the most crucial water masses in the global ocean, significantly impacting physical, biological, chemical, and ecological processes. The challenges inherent in direct continuous observation of NPIW have been limiting the understanding of its short-term variability. Utilizing 14 months of data from three moorings (146° E, 25° N, M1; 122.6° E, 22.3° N, M2; 126° E, 18° N, M3), this study reveals the characteristics of the NPIW and its consistent intraseasonal variability from 60 to days across a range of latitudes and spatiotemporal scales. Direct measurement show depth variations at 700 m, 600 m, and 550 m for M1, M2, and M3, respectively. The analysis reveals a significant association between NPIW variation and mesoscale eddies, evidenced by lead-lag coefficients of 0.6, 0.5, and 0.55 for SLA and salinity at M1, M2, and M3. During anticyclonic (cyclonic) eddies, a positive (negative) SLA corresponds to relatively warm (cooler) and saline (fresh) characteristics of NPIW. Further analysis has shown that due to the inverse S-shaped structure of salinity in the North Pacific region, the vertical movement of water masses within mesoscale eddies leads to inverse phase changes between the NPIW and deeper water. Also the circulation and water masses near the western boundary are relatively complex, mesoscale eddies also induce mixing of the surrounding water masses and thus modify the NPIW properties. The result found that under the influence of the eddy, the change in salinity in the intermediate layer can reach to 0.3 psu, and the depth of the low-salt core can vary by hundreds of meters. Therefor studying the variability of NPIW is crucial for accurately predicting mesoscale eddy transport of heat and energy to ocean's intermediate layer, and understanding its response to climate change, its role in the global carbon cycle, and its impact on marine ecosystems.
Elevation Change of the Greenland Ice Sheet and its Peripheral Glaciers: 1992–2023
Authors: Nilsson Johan , Gardner Alex S.
Published: October 2024

Abstract. The integration of data from multiple satellite altimetry missions, each offering unique observational characteristics, has enabled us to discern both short-term variability and long-term climate trends affecting Greenland’s peripheral glaciers and the Greenland Ice Sheet (GrIS). Our methodology, adapted and informed by lessons learned from our similar efforts in Antarctica, ensures the consistency and reliability of the derived elevation change dataset. The data covers the years 1992–2023 and is made publicly available as part of the NASA's Making Earth System Data Records for Use in Research Environments (MEaSUREs) Inter-Mission Time Series of Land Ice Velocity and Elevation (ITS_LIVE) project. Our analysis of the dataset reveals significant patterns of mass loss across the GrIS. We find that the ice sheet and peripheral glaciers have experienced an average mass loss of -173 ± 19 Gt a-1 and -23 ± 5 Gt a-1 respectively over the 1992–2022 time period (given temporal availability of selected firn models), with notable variations over time. Specifically, the early years of the record exhibit a positive mass balance, likely due to anomalously positive surface mass balance. However, this trend shifts in subsequent years, with a pronounced increase in mass loss rates, highlighting the accelerating impact of a changing climate on ice sheet dynamics and surface mass balance. Moreover, our analysis underscores the importance of considering peripheral glaciers in addition to the continental ice sheet when assessing overall mass trends. By incorporating data from peripheral glaciers, we provide a more comprehensive understanding of Greenland’s total contributions to global sea level rise. Our findings reveal not only the magnitude of mass loss but also its evolution over time, emphasizing the need for continued monitoring and research to better understand the impacts of climate change on Earth's cryosphere.
Global high-resolution fire-sourced PM2.5 concentrations for 2000–2023
Authors: Hu Yonghang , Tian Chenguang , Yue Xu , Lei Yadong , Cao Yang , Xu Rongbin , Guo Yuming
Published: October 2024

Abstract. Fires are a significant disturbance in Earth’s systems. Smoke aerosols emitted from fires can cause environmental degradation and climatic perturbations, leading to exacerbated air pollution and posing hazards to public health. However, research on the climatic and health impacts of fire emissions is severely limited by the scarcity of air pollution data directly attributed to these emissions. Here, we develop a global daily fire-sourced PM2.5 concentration ([PM2.5]) dataset at a spatial resolution of 0.25° for the period 2000–2023, using the GEOS-Chem chemical transport model driven with two fire emission inventories, the Global Fire Emissions Database version 4.1 with small fires (GFED4.1s) and the Quick Fire Emission Dataset version 2.5r1 (QFED2.5) . Simulated all-source [PM2.5] are bias-corrected using a machine learning algorithm, which incorporates ground observations from over 9000 monitoring sites worldwide. Then the simulated ratios between fire- and all-source [PM2.5] at individual grids are applied to derive fire-sourced [PM2.5]. Globally, the average fire-sourced [PM2.5] is estimated to be 1.94 μg m-3 with GFED4.1s and 3.74 μg m-3 with QFED2.5. Both datasets show consistent spatial distributions with regional hotspots in central Africa and widespread decreasing trends over most areas. While the mean levels of fire-sourced [PM2.5] are much larger at low latitudes, fire episodes at the boreal regions can cause comparable PM2.5 levels as in the tropics. This dataset serves as a valuable tool for exploring the impacts of fire-related air pollutants on climate, ecosystems, and public health, enabling accurate assessments and supports for decision-making in environmental management and policy.
Review of methodological considerations and recommendations for mapping remote glaciers from aerial photography surveys in suboptimal conditions
Authors: Medrzycka Dorota , Copland Luke , Thomson Laura , Kochtitzky William , Smeda Braden
Published: October 2024

Abstract. Structure from motion (SfM) photogrammetry coupled with multiview stereo (MVS) techniques are widely used for generating topographic data for monitoring change in surface elevation. However, study sites on remote glaciers and ice caps often offer suboptimal conditions, including large survey areas, complex topography, changing weather and light conditions, poor contrast over ice and snow, and reduced satellite positioning performance. Here, we provide a review of methodological considerations for conducting aerial photography surveys under challenging field conditions. We generate topographic reconstructions, outlining the entire workflow, from data acquisition to SfM-MVS processing, using case studies focused around two small glaciers in Arctic Canada. We provide recommendations for the selection of photographic and positioning hardware and guidelines for flexible survey design using direct measurements of camera positions, thereby removing the need for ground control points. The focus is on maximising hardware performance despite inherent limitations, with the aim of optimising the quality and quantity of the source data, including image information and control measurements, despite suboptimal conditions.
Data-driven rolling model for global wave height
Authors: Wang Xinxin , Wang Jiuke , Lu Wenfang , Dong Changming , Qin Hao , Jiang Haoyu
Published: October 2024

Abstract. Significant Wave Height (SWH) is crucial for many human activities, such as marine navigation, offshore operations, and coastal management. Traditionally, SWH is modeled using numerical wave models, which, while accurate, are computationally intensive and constrained by incomplete physical representations of wave spectral evolution. This study introduces a simple global deep learning-based model for SWH, which uses the current SWH field and the wind field at the next time step as inputs to predict the SWH field at the next time step. This approach mirrors the rolling prediction strategy of numerical wave models. After training on a re-analysis dataset, the errors of the model diverge lightly with time when given a good initial field because no spectral information is used. However, after diverging for ~200 hours, the errors stabilize, remaining comparable to those of state-of-the-art numerical wave models. Additionally, the error divergence can be mitigated through the assimilation of altimeter measurements. This deep learning model can not only serve as an efficient surrogate for traditional numerical wave models but also provide a baseline for statistical modeling of global SWH due to its simplicity in inputs and outputs.
Towards a Robust Hydrologic Data Assimilation System for Hurricane-induced River Flow Forecasting
Authors: Abbaszadeh Peyman , Gavahi Keyhan , Moradkhani Hamid
Published: October 2024

Abstract. The Hybrid Ensemble and Variational Data Assimilation framework for Environmental Systems (HEAVEN) is a method developed to enhance hydrologic model predictions while accounting for different sources of uncertainties involved in various layers of model simulations. While the effectiveness of this data assimilation in forecasting streamflow have been proven in previous studies, its potential to improve flood forecasting during extreme events remains unexplored. This study aims to demonstrate this potential by employing HEAVEN to assimilate streamflow data from USGS stations into a conceptual hydrologic model to enhance its capability to forecast hurricane-induced floods across multiple locations within three watersheds in the Southeastern United States. The SAC-SMA hydrologic model is driven by two variables: precipitation and Potential Evapotranspiration (PET), collected from phase 2 of the North American Land Data Assimilation System (NLDAS-2) and MODIS (Moderate Resolution Imaging Spectroradiometer) satellite data, respectively. We have validated the probabilistic streamflow predictions during five instances of hurricane-induced flooding across three regions. The results show that this data assimilation approach significantly improves hydrologic model’s ability to forecast extreme river flows. By accounting for different sources of uncertainty in model predictions—in particular model structural uncertainty in addition to model parameter uncertainty, and atmospheric forcing data uncertainty, the HEAVEN emerges as a powerful tool for enhancing flood prediction accuracy.
Spatial Analysis of Land Use Land Cover Dynamics in the Madurai District Using Sentinel-2 Data and Supervised Learning Algorithms
Authors: Raguraman Naren , Bhardwaj Ashutosh
Published: October 2024

Abstract. LULC, or Land Use and Land Cover, refers to the classification and description of different types of land and its usage patterns, including urban areas, forests, agricultural land, etc. In remote sensing, satellite imagery for LULC mapping is becoming more widespread. Numerous studies examine various approaches to improve mapping efficiency and accuracy, highlighting the significance of various data sources, machine learning algorithms, and categorization techniques. This study employs machine learning classifiers, namely Random Forest (RF), Support Vector Machine (SVM), Gradient Boosted Trees (GTB), Classification and Regression Trees (CART), and K-Nearest Neighbors (KNN) for land use and land cover (LULC) classification of Madurai district utilizing Google Earth Engine. The findings reveal the impressive performance of Random Forest, boasting an overall accuracy of 99.01 percent coupled with a commendable Kappa coefficient of 98.68. Conversely. However, amidst these commendable achievements, it’s noteworthy to highlight the nuanced variations observed between the accuracy of training and validation sets. This discrepancy is attributed to the intrinsic intricacies of the learning processes inherent within the algorithms, underscoring the nuanced nature of algorithmic methodologies and their implications on accuracy assessment within spatial analysis frameworks. The generated land use and land cover (LULC) map allows for a comparison between the ground truth data and the surveys conducted to assess issues such as water scarcity and the drying of natural and man-made water bodies.
Reviewing Open Data Semantic 3D City Models to Develop Novel 3D Reconstruction Methods
Authors: Wysocki Olaf , Schwab Benedikt , Beil Christof , Holst Christoph , Kolbe Thomas H.
Published: October 2024

Abstract. Structured semantic 3D city models are pivotal in creating urban 3D digital twins. The wide adoption of such models has been primarily enabled by robust, model-based, and automatic 3D reconstruction methods. However, these methods impose requirements on the reconstruction, mainly restricting the solution space to several model types and relying on accurate 2D footprints. Recent research shows that deep-learning-based methods promise highly generic solution space and are footprint-free. Yet, the current training and test datasets are limited, hindering the methods’ development. In this work, we analyze the ubiquity of already existing, open 3D city model datasets and their potential to serve as a large-scale training and test set for 3D reconstruction, where 27 potential dataset collections have been identified. Our review shows that more than 215 million building models are readily available. We firmly believe that this review will facilitate further research on robust automatic 3D city model reconstruction and serve as a reference for benchmarking 3D city models.
Voxel Size Performance in 3D Indoor Model Creation for 3D Evacuation Simulations
Authors: Xie Ruihang , Zlatanova Sisi , Lee Jinwoo Brian
Published: October 2024

Abstract. 3D voxel models facilitate simulating 3D pedestrian motions within indoor environments with diverse furniture, equipment, and complex room layouts featuring stairs and ramps. Reasonable voxel sizes enable the effective identifications of indoor spaces, navigable surfaces, and vertical links from voxel models for the simulations. However, the performance of different voxel sizes on these identifications has yet to be thoroughly investigated. The choice of appropriate voxel sizes for various 3D evacuation scenarios has to be clarified to avoid unreliable simulation outcomes. Therefore, this paper aims to assess the performance of different voxel sizes on the identifications of the spaces, surfaces, and links. Firstly, we introduce three key metrics for the assessment: accuracy, robustness, and efficiency. Then, three IFC models are selected based on predefined criteria for the tests. Experimental procedures are elaborated to include data preparation, collection, and analysis. The primary findings of this investigation are: 1) with increasing voxel sizes, accuracy decreases, robustness changes, and efficiency increases; 2) larger indoor spaces exhibit smaller changes in accuracy across different voxel sizes, while smaller indoor spaces show more significant changes in accuracy. 3) when the voxel size is tiny, it becomes challenging to complete identifications. Conversely, with relatively larger voxel sizes, some indoor spaces and vertical links cannot be identified. 4) Indoor spaces with complex and non-orthogonal geometries require more identification time. This work is expected to advance the creation of 3D indoor model to facilitate 3D evacuation simulations.
Energy transfer from internal solitary waves to turbulence via high-frequency internal waves: seismic observations in the northern South China Sea
Authors: Meng Linghan , Song Haibin , Guan Yongxian , Yang Shun , Zhang Kun , Liu Mengli
Published: October 2024

Abstract. The shoaling and breaking of internal waves (IWs) are critical processes in the ocean's energy cascade and mixing. Using seismic data, we observed high-frequency internal waves (HIWs), which were primarily distributed in the depth range of 79–184 m. Their amplitude scale is O (10 m), with half-height widths ranging from 154 to 240 m. The shoaling thermocline and gentle slope with a low internal Iribarren number suggest that observed high-frequency internal waves are likely a result of fission. The remote sensing data support this point. Instability estimations showed that, due to the strong vertical shear, the Richardson number (Ri) in the range of 20–30 km was less than 0.25, and Kelvin–Helmholtz (KH) billows can be found in the seismic transect, suggesting that these waves were unstable and might dissipate rapidly. We used the seismic data to estimate diapycnal mixing, and we found that the HIWs can enhance diapycnal mixing, averaging 10−4 m2 s−1. The maximum mixing value is up to 10−3 m2 s−1, and it is associated with the breaking of IWs caused by the strong shear. The results show a new energy cascade route from shoaling internal solitary waves (ISWs) to turbulence, i.e., the fission of ISWs into HIWs, which improves our knowledge of ISW energy dissipation and their roles in improved mixing in the northern South China Sea.
Obesidade e Doença Pancreática Gordurosa não Alcoólica (Esteatose Pancreática)
Authors: Spezani Renata , Souza Marinho Thatiany , Melo Fabiano Matheus , Alves Sales Thamyres , Reis-Barbosa Pedro Henrique , Akemi Nagagata Brenda , Imazio Osorio Caterine , Barbosa Aguila Marcia , Mandarim-de-Lacerda Carlos Alberto
Published: October 2024

Indivíduos com obesidade e acúmulo de gordura no corpo, podem ter inflamação crônica do tecido adiposo com risco aumentado de resistência à insulina e diabetes mellitus do tipo 2. Os adipócitos servem para armazenar o excesso de energia na forma de triacilglicerol e secretam adipocinas (adiponectina e leptina). Com isso, o tecido adiposo regula outros tecidos e modula o metabolismo energético.
Microglia: Os Arquitetos Do Sistema Nervoso Central
Authors: A. Quagliato Laiana , Egidio Nardi Antonio
Published: October 2024

A busca pelo substrato biológico dos trans¬tornos mentais é um pré-requisito para o desenvolvimento de terapias mais eficazes e, sobretudo, para estratégias preventivas por meio do diagnóstico oportuno dessas con¬dições. Tentativas experimentais de identifi¬car marcadores específicos para os diferentes transtornos continuam sem sucesso. Esses resultados negativos resultam, pelo menos em parte, de uma provável falta de especi-ficidade das mudanças globais na biologia cerebral para certas condições clínicas. Evi-dências recentes mostram que as células mi¬crogliais atuam na plasticidade e função das sinapses, modificando os circuitos neuronais, e há associações entre os níveis de biomar-cadores inflamatórios e ativação microglial com diversos transtornos mentais. Assim, a elucidação dos mecanismos pelos quais as células microgliais podem contribuir para a migração neuronal anômala e consequente processamento cognitivo e emocional altera¬do poderia contribuir para a identificação de indivíduos com alto risco para o desenvol-vimento de transtornos mentais, bem como para o diagnóstico e tratamento oportuno e adequado dos mesmos. O objetivo desta revisão é abordar como as células micro¬gliais estão intimamente ligadas ao neuro¬desenvolvimento, mostrando evidências de seu impacto na migração neural, formação de sinapses e suas amplas implicações para transtornos psiquiátricos.
Produção científica brasileira sobre situações de aprendizagem para desenvolver Alfabetização Científica
Authors: Sobrinho Elizimari de Queiroz , Leão Marcelo Franco
Published: October 2024

Este estudo teve como objetivo investigar teses e dissertações brasileiras sobre ações pedagógicas realizadas para desenvolver Alfabetização Científica (AC) aos estudantes dos anos iniciais do Ensino Fundamental. Trata-se de uma pesquisa bibliográfica, do tipo estado do conhecimento, de abordagem qualitativa, cujo recorte temporal limitou-se entre 2011 a 2020. Buscou-se a produção sobre o assunto, contida na Biblioteca Digital Brasileira de Teses e Dissertações (BDTD), para estabelecer relações, no nível epistemológico e empírico, entre essas práticas de AC com a ênfase dada ao conteúdo na construção de habilidades e competências. A análise revelou que as ações pedagógicas contribuem com o processo de AC dos estudantes. As metodologias mais recorrentes foram: ensino por investigação, rodas de leitura, intervenção de ensino, abordagem Ciência, Tecnologia e Sociedade (CTS) e aulas dialogadas. Portanto, o ambiente investigativo construído em aula demonstrou ser um fator potencializador da AC, ou seja, algo necessário para ocorrer nos primeiros anos.
Effectiveness of Planned Teaching Programme on Knowledge regarding Blood Donation among Degree students
Authors: Kulkarni Shilpa , Kamble Ajaykumar , Dhage Krishna , Palwade Kavita , Ghuge Vaishnavi , Sanap Rahul , Sonawane Kajal
Published: October 2024

A study to evaluate the effectiveness of planned teaching programme on knowledge regarding blood donation among students studying in Selected Degree Colleges, Aurangabad. OBJECTIVES OF THE STUDY: To assess the knowledge regarding blood donation among students before planned teaching programme. To prepare and administer planned teaching programme regarding blood donation among students. To assess the knowledge regarding blood donation among students after planned teaching programme. To evaluate the effectiveness of planned teaching programme regarding blood donation among students. To find out the association between post test knowledge scores with selected demographic variables. MATERIAL AND METHODS: This pre experimental one group pre test post test study was conducted to evaluate the effectiveness of planned teaching programme on knowledge regarding blood donation among the students studying in selected degree colleges. Non – probability convenient sampling technique was used for the sample collection of 50 students studying in Maharashtra Institute of Technology college, Aurangabad. Structured knowledge questionnaire was used to evaluate effectiveness of planned teaching programme. The present study was evaluative in nature. The conceptual framework used for the study was based on ‘MODIFIED VON BERTTLANFFY’S’ theory. RESULT: In the comparison between pre test and post test the knowledge score of students was more in post test than pre test. In pre test 3[6%] subjects had good knowledge regarding blood donation, 5[10%] subjects had poor knowledge and 42[84%] subjects had average knowledge regarding blood donation. Whereas in post test, 49[98%] subject had good knowledge and only 01[2%] subject had average knowledge regarding blood donation. The mean difference of pre test and post test was 10.22 and paired t value was 55.72. CONCLUSION: This study revealed that planned teaching program was helpful to increase knowledge regarding blood donation among degree students.
Temperature selection and activity of the Norwegian Lemming Lemmus lemmus (L.) in a temperature gradient apparatus
Authors: Østbye Eivind
Published: October 2024

Tested in a temperature gradient apparatus the Norwegian lemming seemed to show a seasonal trend in temperature selection ranging from 21.6°C ±10.5 in summer, over 18.6°C ±10.9 in autumn to 15.9°C ±12.8 in winter. Different activities such as voiding, grooming, attacking and resting were recorded during the experiments. Possible relationships between the selected temperature (ST) and the selected temperature zone (STZ) found experimentally and the natural habitat of the Norwegian lemming, together with some physiological aspects, are discussed. Both ST and STZ are higher than the temperature regime prevailing in lemming habitats during the year. The coincidence of such physiological parameters as the critical temperature and the temperature pertaining to the lowest and most stable rate of oxygen consumption seems to indicate that ST is in the temperature zone with the lowest energy expenditure for maintenance of a constant body temperature.
Life history variables of resident Brown trout Salmo trutta L. in a coastal stream in northern Norway
Authors: Hesthagen Trygve
Published: October 2024

This study focused on the population structure and life history of resident Brown trout in the lower parts of a coastal stream in northern Norway. An uneven age distribution was strongly evidenced by the low number of young fish. There was a high frequency of sexually mature males, while only a few females were sexually mature. Males mature sexually at ages between 2 - 8 years, compared with 4 - 5 years for females. Females had a significantly higher mortality rate than males, and were fewer in number amongst older fish. There were no differences between the sexes in growth rates or in the length/weight relationship. It is suggested that the low number of spawning females, as well as density-independent mortality in young stages caused by environmental catastrophes, are important factors affecting the present structure of the Brown trout population in the study area. The population is probably maintained by immigration of older specimens into the area.
Density and yield of the noble crayfish Astacus astacus in the River Skotsbergelva, SE Norway
Authors: Vollestad Leif Asbjørn , Dervo Børre Kind
Published: October 2024

The population density and yield of the noble crayfish Astacus astacus was estimated on two localities in the River Skotsbergelva in the Halden river system, SE Norway, in August 1989. The estimated densities of catchable crayfish (>70 mm; caught in baited traps) varied between localities and with method of estimation. Mark - recapture estimates were much higher than comparable Leslie-estimates. Estimated densities varied from 0.47 to 0.93 crayfish m-2. Yield of legal size crayfish varied from 2.4 to 23.6 kg ha-1. Fishing mortality was estimated to 28 - 66%, being highest at the locality with the highest yield and exploitation.
PROPHETIC PRACTICES IN HUMAN RESOURCE MANAGEMENT
Authors: Bangash Faisal Mohammed Musaddiq Kamal , Yamin Muhammad Ali Yusef
Published: October 2024

Traditionally, the main motive behind focusing on human resources is organizations’ striving to achieve the maximum profits possible. While the Islamic motives are focusing on caring about the human resource as a human being whom was created to be Allah's deputy on earth. Prophet Mohammed PBUH came with a message that made working have a religious value. Separating work from its Islamic values stopped it from being the biggest motive for human’s development in organizations. Prophet Mohammed PBUH came with a message that honored humans and made their practical development a great concern, motivating them to building values, behaviors, improving performance, achieving and managing goals. The Prophet PBUH came with great values that would advance the idea of human resources management and enhance the human being in the organization, which would reflect on his performance and achieving the goals and objectives of organizations. This research claims that the impact of the prophetic applications on human resources is more comprehensive, spacious in scope and has greater impact than traditional human resources management. This research can be a scientific and practical reference to highlight the mechanisms and practices found from Prophet’s sayings, actions, or from the Sharia he brought in.
Deteksi Objek Video Bahasa Isyarat Untuk Anak Tuna Rungu dan Tuna Wicara Menggunakan YOLOv8
Authors: Maheza Fresmanda Muhammad , Istiadi  , Syahroni Wahyu Iriananda
Published: October 2024

Penelitian ini bertujuan untuk mengimplementasikan keberhasilan model algoritma YOLOv8 dalam mendeteksi abjad bahasa isyarat Indonesia (BISINDO) berbasis video. BISINDO merupakan adaptasi American Sign Language (ASL) yang disesuaikan dengan budaya Indonesia agar lebih mudah digunakan. Itu bergantung pada gerakan dua tangan untuk komunikasi. Model YOLOv8 mampu mendeteksi dan mengklasifikasikan bahasa isyarat Indonesia dengan tingkat akurasi yang cukup baik, mencapai precision 93,35%, recall 70,25%, mAP50 64,05% dan mAP50-95 45,88%. Temuan ini diharapkan dapat memberikan kontribusi positif dalam pendidikan dan komunikasi untuk anak tunarungu dan tunawicara
An interactive and adaptive learning resource for teaching first-year human anatomy
Authors: Linden Kelly , Teakel Sarah
Published: October 2024

Anatomy is a particularly challenging unit in many first-year university courses, however adaptive learning resources provide an opportunity to engage students in practical-based units such as anatomy. Here, the impact on student engagement, student learning and exam preparedness of implementing 21 interactive online adaptive lessons was evaluated. A total of 276 first-year students, enrolled in allied health undergraduate degrees from 2016 to 2020, consented to participate in this mixed methods study. Our findings suggest a positive correlation between the number of lessons a student completed and a positive performance in each of the three assessment items in the unit (p<0.05). We also identify an increase in students perceived understanding of anatomy after completing the lesson (p<0.0001). Students worldwide appreciate individualised, flexible and engaging nature of learning technologies. Here, we evidence that students appreciated online adaptive lessons to learn anatomy and exhibited a high level of satisfaction.
Dynamic performance enhancement of DFIG wind turbine using an active disturbance rejection control -based sliding mode control
Authors: Boureguig Kada , Ouagueni Fayssal , Soued Salah
Published: October 2024

The present paper proposes a hybrid control law that combines the active disturbance rejection control (ADRC) and the sliding mode control (SMC) to improve the decoupled control of the active and reactive power stator applied to a doubly-fed induction generator (DFIG) integrated into a wind energy conversion system. The stator is directly connected to the electric grid, while the rotor is connected to the electric grid via a back-to-back converter. The Lyapunov theory proves the stability of nonlinear control. The performance of the proposed strategy is compared with that of traditional ADRC and proportional-integral control (PI). The simulation results in MATLAB/SIMULINK environment using a 1.5MW wind system model show the proposed approach. The proposed algorithm shows an excellent dynamic performance that reduces the time response, overshoot, and steady-state error compared to the conventional controllers.Considering parametric variation, applying a novel controller results in fewer oscillations in stator powers, outperforming the PI regulator and classic ADRC.
A Study on the Influence of Language Environment on English Writing Ability in Universities-Based on the Theory of Second Language Acquisition
Authors: Jin Zi
Published: October 2024

Based on the theory of second language acquisition, this study employs a mixed-method approach to investigate the impact of language environment on English writing proficiency in higher education institutions. In the quantitative study, data were collected from 184 students with diverse English language learning backgrounds via the online questionnaire platform "Wenjuanxing" at several universities in China and in-depth interviews were conducted to gain qualitative insights. The findings indicate that the frequency and depth of writing practice, parents' education level, and early exposure to English have a notable impact on English writing ability. Students in the advanced training group demonstrated superior performance due to their increased exposure and practice opportunities, whereas students in the standard study group necessitated more structured instruction and writing practice to enhance their proficiency. The study offers a theoretical foundation and practical guidance for teaching English writing, such as the creation of a rich language environment to facilitate students' English writing abilities.
An Analysis and Comparison Between the Chinese GaoKao System and the A-Level System in the UK: Challenges and Improvements
Authors: Gao Xudong
Published: October 2024

The majority of students in China, who need to attend Gaokao to be admitted by universities, are not facing the same opportunities. They are strictly required to study specific subjects, no matter students are good and interested at or not. In addition, universities are not admitting students purely according to their talents, instead factors like region, family, which field they want to study in the future do matter. This study will discuss such situation of Chinese Gaokao and make a comparison with the education system in the UK. It also mentions current government policies for extra points that are originally for higher fairness, but they are not fair anymore in current circumstances. This study also gives advices to government and universities on how to make improvement on current education system. The results of this study provides a scientific basis for decision makers to make more rational and effective decisions. It is of great significance to the government, related departments and most importantly, Chinese students.
Preparing Translators for the Age of Generative AI: Revising Educational Curricula to Prioritize Essential Skills in an AI-Dominated Landscape
Authors: Wang Ying
Published: October 2024

The recent ability of machines to generate text and images that are fluent, coherent, and culturally nuanced is already causing major upheavals in the translation sector. Machine translation tools have exploded in number, sophistication, and quality, and the profession of human translator needs to adapt to work within this new environment and avoid being replaced by it. This paper examines the major changes that have taken place, and which could take place in the near future, and suggests ways of revising translator-training curricula to adapt to these challenges. This is essential at a time when the profession is undergoing profound changes and when all translators and future translators need to be prepared for new skills in the field of post-editing, machine-reading, machine-cultures and multidisciplinarity. After outlining the challenges that AI is causing to the profession and to the norms and values of the translation sector in its current state, the author suggests that translator training should adapt to the new reality of the profession and not to what it used to be. The profession is undergoing profound changes, and all translators and future translators need to find new skills and knowledge in order to continue to work with AI. The article concludes with recommendations on how to design AI-friendly translation programmes that can train students for the post-AI era.
Comparison of Multi-Armed Bandit Algorithms in Advertising Recommendation Systems
Authors: Zhao Junyi
Published: October 2024

In today's rapidly evolving online environment, advertising recommendation systems utilize multi-armed bandit algorithms like dynamic collaborative filtering Thompson sampling (DCTS), upper confidence bound based on recommender system (UCB-RS), and dynamic -greedy algorithm (DEG) to optimize ad displays and enhance click-through rates (CTR). These algorithms must adapt to limited information and update strategies based on immediate feedback.This study employs an experimental comparison to assess the performance of the DCTS, UCB-RS, and DEG algorithms using the click-through rate prediction database from Kaggle. Five experimental sets under varied parameter settings were analyzed, employing the Receiver Operating Characteristic (ROC) curve, accuracy, and area under the curve (AUC) metrics.Results show that the DEG algorithm consistently outperforms the others, achieving higher AUC values and demonstrating robust sample identification capabilities. DEG also exhibits superior precision at high recall levels, showcasing its potential in dynamic advertising environments. Its dynamic adjustment strategy effectively balances exploration and exploitation, optimizing ad displays.The findings suggest that DEG's adaptability and stability make it particularly suitable for dynamic ad recommendation scenarios. Future research should focus on optimizing DEG's parameter settings and possibly integrating UCB-RS's exploration mechanisms to enhance performance and develop more effective strategies for advertising recommendation systems.
Strategy Selection Using Multi-Armed Bandit Algorithms in Financial Markets
Authors: Guo Yushi
Published: October 2024

This paper aims to evaluate the effectiveness of Multi-Armed Bandit (MAB) algorithms in choosing the optimal trading strategy among the sub optimal ones within financial markets. The research aims to addresses the challenge of adapting to dynamic market conditions. By introducing a Composite Trading Strategy that integrates trend-following, mean reversion, and momentum strategies, the study investigates whether increased trading frequency enhances the performance of profitability of various MAB algorithms, including UCB, Thompson Sampling, and epsilon-greedy. The experimental results indicate that while the introduction of complex strategies greatly improves returns in favorable market conditions, MAB algorithms still face limitations in adverse market environments. The findings highlight the potential of MAB algorithms in financial strategy selection and suggest directions for future research to enhance their adaptability in adverse markets.
Interdisciplinary Brain-based Learning Strategies in Addressing Liver Fluke Disease and Cultural Dietary Practices among Early Childhood Students
Authors: Tungkasamit Angkana , Meekaew Nattapon , Boonmee Somkamon , Jantaburom Prapaporn , Silanoi Ladda
Published: October 2024

Liver fluke disease remains a critical public health issue in Southeast Asia, driven by cultural dietary practices involving raw or undercooked freshwater fish. This study evaluates the impact of an interdisciplinary brain-based learning intervention aimed at increasing awareness and modifying dietary behaviors among early childhood students in Central Northeast Thailand. A quasi-experimental design was employed, involving 122 students from four provinces. The intervention incorporated brain-based learning activities such as storytelling, songs, and visual aids to enhance engagement. Pre- and post-tests, behavioral observations, and attitudinal surveys were conducted to assess the program’s effectiveness. Post-intervention results indicated significant improvements in knowledge about liver fluke transmission, symptoms, and prevention, alongside positive changes in behavior, such as increased avoidance of raw fish consumption and improved hygiene practices. Attitudinal surveys showed a shift in preferences toward safer eating habits. These findings suggest integrating brain-based learning with culturally relevant health education can foster sustainable behavior change in early childhood populations. Further research is recommended to explore this approach’s long-term impacts and scalability.
‘This is not a ghetto’: Residents’ resistance and re-negotiation of neighbourhood narratives
Authors: Söderberg Rebecka
Published: October 2024

Over the past few decades, there has been a wave of urban renewal of multi-ethnic neighbourhoods across cities in the Global North, and movements for housing justice have emerged. The literature on housing struggles has mainly focussed on collective acts of resistance, neglecting mundane and individual forms of resistance. Building on ethnographic fieldwork in Mjølnerparken—a multi-ethnic public housing neighbourhood in Copenhagen, Denmark, targeted by the ‘ghetto legislation’—this article highlights residents’ various forms of resistance. Combining the ‘ABC of resistance’ framework with conceptions of place as continuously becoming, the analysis shows how residents enact a homeplace and re-negotiate the hegemonic narrative of their neighbourhood as a ‘ghetto’. Thus, the article contributes to the literature on housing struggles by broadening the understanding of resistance using ethnographic methods and an analytical framework from resistance studies. Simultaneously, it adds to the ABC framework by underscoring the place-making dimension of resistance.
Single Mothers Association of Kenya (SMAK) and the Fight to Stay Put on the Ziwani Estate in Nairobi
Authors: Manyasi Daniel , Lees Loretta , West Ashley
Published: October 2024

This Reflection discusses the fight to stay put on the Ziwani Estate in Nairobi, in the face of the redevelopment (gentrification) of one of the first East African public housing projects developed in Kenya under colonial rule. The Single Mothers Association of Kenya (SMAK), a community-based organization founded on the Ziwani Estate, is leading the fight for/with Ziwani residents. SMAK is focused on land and housing rights, capacity building for the community on these rights, advocating against illegal eviction, and fighting against gentrification, densification, and homelessness. Under immediate threat SMAK found local and global allies in academia, civil society, and in UN bodies. They have had some important wins on the preservation and conservation of Ziwani historic places and people based on unexpected academic collaborations and on their own activism which they believe requires civic education, domestic and international lobbying, and possibly legal struggle.