bluuebunny/crossref_metadata_2025 huggingface dataset:
“Neither of the East nor of the West”
Authors: Scharbrodt Oliver
Published: October 2024

What does it mean to do Islamic Studies within Religious Studies? Taking the cue from Thomas A. Tweed's intervention, this article discusses new theoretical and methodological approaches in Religious Studies and their relevance to researching Islam. Such approaches cross geographical, disciplinary, and intellectual boundaries while equally being emplaced in particular socio-cultural contexts that inform their perspectives. In order to overcome statist, normative, and essentialist understandings of Islam, the article explores three key themes: ambiguity, multi-locality, and aesthetics. When we approach the intellectual history of Islam, not only its diversity and plurality become obvious but also its culture of ambiguity, which is at ease with contradictions and inconsistencies. Recent reflections on diaspora religions decentre Islamic Studies from the Middle East and allow for exploring the multiple transnational connections between Muslim minority and majority contexts. Such approaches illustrate the multi-locality of Islam. Finally, the article explores what it means to approach Islam as an aesthetic formation in which rituals as embodied experiences and material sensory culture are central in forging and articulating Muslim individual and collective identities.
Sten Hidal, Esaias Tegnér: Skalden och biskopen
Authors: Sidenvall Erik
Published: October 2024

N/A
ESTIMASI KEBUTUHAN MATERIAL PADA PROSES FABRIKASI KAPAL TONGKANG 230x80x16 FEET BERDASARKAN SWC
Authors: Dani Ahmad , Hilmy Zakwan , Susilo Trisno , Tyas Adi Fajar
Published: October 2024

Provinsi kepulauan Riau memiliki wilayah laut yang cukup luas dan maka dengan itu perkembangan teknologi transportasi perairan yaitu kapal yang merupakan ladang bisnis yang cukup menjanjikan pada Industri Kontruksi kapal di Indonesia, Tujuan dari penelitian ini adalah Membuat Perhitungan berat material dan membuat perencanaan Estimasi kebutuhan material, dimana Perhitungan Berat kapal dan Perencanaan Estimasi Material Kapal menggunakan aplikasi CAD (Computer Aided Design) dan Excel diharapkan dari hasil penelitian Perhitungan berat kapal dan Estimasi kebutuhan material ini mampu mencapai efisiensi dan efektifitas produksi kapal untuk perusahaan. Hasil perhitungan didapatkan estimasi kebutuhan material sebesar 987.592 ton dalam pembuatan kapal kapal tongkang 230x80x16 feet berdasarkan swc
DESAFIOS E PERSPECTIVAS DA ENFERMAGEM ONCOLÓGICA FRENTE A COMUNICAÇÃO
Authors: Bezerra Ryan Bóris Braz , Lima Tamires Monteiro , Bezerra Thaís Alves , Medeiros Renata Lívia Silva Fônseca Moreira de , Souza Anne Caroline de , Bezerra Yuri Charllub Pereira
Published: October 2024

Introdução: O câncer, condição de crescimento desordenado de células, é uma das principais causas de mortalidade global, com um aumento constante na incidência. Apesar dos avanços médicos, enfrentam-se desafios significativos, afetando não apenas os pacientes, mas também suas famílias. A comunicação terapêutica é essencial, porém muitos profissionais de saúde carecem de habilidades nesse aspecto, o que pode levar a evitar interações delicadas. Os enfermeiros desempenham um papel crucial, não apenas na prestação de cuidados físicos, mas também na comunicação eficaz e no suporte emocional. A enfermagem oncológica, com sua abordagem personalizada, promove a humanização no cuidado, contribuindo para uma melhor qualidade de vida para pacientes e familiares. Objetivo: Analisar os principais desafios e perspectivas da enfermagem oncológica, na comunicação com pacientes e seus familiares. Metodologia: Trata-se de uma revisão integrativa, na qual se norteou a partir da pergunta: Quais foram os desafios e perspectivas na comunicação da enfermagem oncológica com pacientes com câncer e seus familiares? A revisão se deu por meio da BVS, utilizando as bases de dados: Scielo, Lilacs, Medline e BDENF, com os descritores controlados em saúde: câncer, comunicação e enfermagem, que foram combinados com os descritores booleanos “and” e “OR”. Foram escolhidos artigos científicos publicados nos últimos cinco anos, com foco nos anos de 2019 a 2024, que estavam completos e disponíveis gratuitamente na íntegra, em português, inglês e espanhol. Foram removidos artigos duplicados e que não atenderam ao objetivo predefinido. Todas as informações contidas nos artigos escolhidos para este estudo foram apresentadas em tabelas e analisadas à luz da literatura pertinente. Resultados e discussão: O câncer resulta de mutações genéticas que levam à proliferação descontrolada de células anormais. É a segunda causa de morte global, com cerca de 704 mil novos casos anuais no Brasil, onde os tipos mais comuns incluem câncer de pele não melanoma, próstata e mama. O diagnóstico envolve exames clínicos e complementares, enquanto o rastreamento ajuda a reduzir a morbidade e mortalidade. A Sistematização da Assistência de Enfermagem (SAE) é essencial para o cuidado ao paciente oncológico, permitindo diagnósticos precisos e intervenções adequadas, especialmente na gestão da dor e suporte emocional. Conclusão: Portanto a relevância do cuidado integral na enfermagem para pacientes com câncer, enfatizando a importância da gestão da dor e do suporte emocional para melhorar sua qualidade de vida.
Jeu et apprentissage
Authors: Sanchez Eric
Published: October 2024

Dans quelle mesure le jeu constitue-t-il une méthode d’apprentissage ? Comment peut-il être utilisé lors des différentes étapes de l’éducation, de la petite enfance jusqu’à l’université, en passant par la formation professionnelle, voire l’apprentissage informel dans les musées ?Jeu et apprentissage explore l’émergence des jeux et l’intérêt croissant qu’ils suscitent dans les contextes éducatifs. Jeux de plateau, jeux numériques, escape games ou encore jeux de rôle, de nombreux enseignants et formateurs intègrent désormais des outils ludiques dans leurs pratiques pédagogiques.Ce livre analyse les modalités des apprentissages rendus possibles par l’usage du jeu. Qu’apprend-on réellement en jouant ? Quels sont les enseignements tirés des travaux de recherche sur les méthodes d’apprentissage basées sur le jeu ? Destiné à un large public, cet ouvrage offre une synthèse des connaissances actuelles sur le sujet. Il s’adresse à tous ceux qui s’intéressent à l’innovation pédagogique.
Exploring the association between SLC11A1 and CARD15 gene polymorphisms and tuberculosis susceptibility in Holstein cattle
Authors: Bejaoui Safa , Fehri Nour Elhouda , Ferchichi Mohamed Amine , Jemmali Bayrem
Published: October 2024

Abstract. Bovine tuberculosis (bTB) is a contagious disease that has a socio-economic impact on familial and industrial farms. Genetic selection can improve resistance against bTB. This study aimed to characterize the links between SLC11A1 and CARD15 gene polymorphisms and tuberculosis (TB) susceptibility. In total 200 animals were used (50 cases and 150 controls). Polymorphisms in the SLC11A1 and CARD15 genes were identified and analyzed with the restriction fragment length polymorphism (PCR-RFLP) method. Our results report the PstI PCR-RFLP marker for the SLC11A1-SNP1 site and the StyI PCR-RFLP marker for the CARD51-SNP1 site in Tunisian Holstein cows. Statistical analysis showed a significant association between SLC11A1-SNP1, CARD15-SNP1 and susceptibility/resistance to TB (P < 0.05). Two SLC11A1-SNP1 genotypes were susceptible to tuberculosis, i.e., the heterozygote CG and the homozygote CC, while one SLC11A1-SNP1 genotype, i.e., the GG mutated homozygote, was less susceptible to infection. Concerning the CARD15 gene, two genotypes are highly sensitive to the incidence of bovine tuberculosis, i.e., AA and AG, while the GG genotype is more beneficial and more tolerant of Mycobacterium bovis. SLC11A1 and CARD15 are two useful candidate genes associated with tuberculosis, and this information can be used to improve the health status of domestic cattle and humans.
Investigating the vertical extent of the 2023 summer Canadian wildfire impacts with satellite observations
Authors: Zhang Selena , Solomon Susan , Boone Chris D. , Taha Ghassan
Published: October 2024

Abstract. Pyrocumulonimbus clouds (pyroCbs) generated by intense wildfires can serve as a direct pathway for the injection of aerosols and gaseous pollutants into the lower stratosphere, resulting in significant chemical, radiative, and dynamical changes. Canada experienced an extremely severe wildfire season in 2023, with a total area burned that substantially exceeded those of previous events known to have impacted the stratosphere (such as the 2020 Australian fires). This season also had record-high pyroCb activity, which raises the question of whether the 2023 Canadian event resulted in significant stratospheric perturbations. Here, we investigate this anomalous wildfire season using retrievals from multiple satellite instruments, ACE-FTS (Atmospheric Chemistry Experiment – Fourier transform spectrometer), OMPS LP (Ozone Mapping and Profiler Suite Limb Profiler), and MLS (Microwave Limb Sounder), to determine the vertical extents of the wildfire smoke along with chemical signatures of biomass burning. These data show that smoke primarily reached the upper troposphere, and only a nominal amount managed to penetrate the tropopause. Only a few ACE-FTS occultations captured elevated abundances of biomass-burning products in the lowermost stratosphere. OMPS LP aerosol measurements also indicate that any smoke that made it past the tropopause did not last long enough or reach high enough to significantly perturb stratospheric composition. While this work focuses on Canadian wildfires given the extensive burned area, pyroCbs at other longitudes (e.g., Siberia) are also captured in the compositional analysis. These results highlight that despite the formation of many pyroCbs in major wildfires, those capable of penetrating the tropopause are extremely rare; this in turn means that even a massive area burned is not necessarily an indicator of stratospheric effects.
Flow patterns, hotspots and connectivity of land-derived substances at the sea surface of Curaçao in the Southern Caribbean
Authors: Bertoncelj Vesna , Mienis Furu , Stocchi Paolo , van Sebille Erik
Published: October 2024

Abstract. The South Caribbean Island of Curaçao is abundant in coral reef communities, but they are declining. Land-derived nutrients and pollutants are a potential contributing factor to this decline, as these substances after entering the ocean, can be transported towards reef sites by ocean currents. To study the movement of the substances and their potential impact on coral reefs, we developed SCARIBOS, a fine-resolution hydrodynamic model of the South CARIBbean Ocean System, with a 1/100° resolution. SCARIBOS covers the period from April 2020 to March 2024 (excluding spin-up time) to analyse flow patterns within that period around the close proximity of Curaçao. Furthermore, SCARIBOS is used as hydrodynamic input for Lagrangian particle tracking analysis with the Parcels framework, where we assess the distribution of positively buoyant substances and explore connectivity within Curaçao’s coastlines as well as with nearby regions of Aruba, Bonaire, the Venezuelan islands, and a portion of the Venezuelan mainland. Results reveal two dominant processes: the northwest-directed Caribbean Current and weaker cyclonic eddies moving in the opposite direction. These flow patterns influence hotspot locations of higher substance concentrations observed during eddy events. Our analysis also highlights increased particle accumulation of land-derived substances in the northwest of Curaçao, corresponding to the prevailing currents. While the focus is on land-derived nutrients and pollutants, this methodology can be extended to study other particle types such as plastic debris and coral larvae, providing valuable insights for marine conservation efforts and environmental management.
Mechanistic insights into chloroacetic acid production from atmospheric multiphase VOC-chlorine chemistry
Authors: Li Mingxue , Xia Men , Lin Chunshui , Jiang Yifan , Sun Weihang , Wang Yurun , Zhang Yingnan , He Maoxia , Wang Tao
Published: October 2024

Abstract. Chlorine-containing oxygenated volatile organic compounds (Cl-OVOCs) are indicators of atmospheric chlorine chemistry involving volatile organic compounds (VOCs). However, their formation mechanisms are insufficiently understood. Herein, a strong diel pattern of chloroacetic acid (C2H3O2Cl) was observed with daytime peaks at 19 and 13 ppt (1-hour averages) in 2020 and 2021, respectively, at a coastal site in southern China. Ethene was previously proposed as the primary precursor responsible for daytime C2H3O2Cl levels, but a photochemical box model based on Master Chemical Mechanism (MCM) simulations indicates that ethene accounts for less than 1 %. Quantum chemical calculations suggest that other alkenes also can act as chloroacetic acid precursors. Using an updated gas-phase VOC-Cl chemistry model, we find that isoprene, the most abundant VOC at the sampling site, along with its oxidation products, accounts for 7 % of the observed C2H3O2Cl levels. Moreover, the simulation with the updated MCM produces appreciable levels of other Cl-OVOCs, especially chloro-acetaldehyde, a precursor of C2H3O2Cl. We proposed the multiphase reaction of Cl-OVOCs to reconcile the overestimation of Cl-OVOCs and the underestimation of C2H3O2Cl in our gas-phase model. The estimated reactive uptake coefficients for various Cl-OVOCs range from 3.63 × 10-5 to 2.34 × 10-2, according to quantum chemical calculations and linear relationship modeling. Box model simulation with multiphase chemistry reveals that the heterogeneous conversion of chloro-acetaldehyde to C2H3O2Cl is a more important source of C2H3O2Cl than gas-phase reactions. Our study thus proposes a formation mechanism of gaseous C2H3O2Cl and highlights the potential importance of multiphase processes in VOC-Cl chemistry.
Brief communication: Evidence of the impacts of climate extremes on power system outages in India
Authors: Verschuur Jasper , Balakrishnan Srijith
Published: October 2024

Abstract. Electricity systems are prone to climate extremes such as heatwaves and cold spells, precipitation, high winds, and flood inundation. Yet, the impacts of these climate extremes on the provision of electricity is scarce, in particular in the Global South context. Here, we combine four years of daily electricity outages data from 370 locations across India with temperature, wind, precipitation and flood inundation data to provide empirical evidence of their impacts of the electricity system. We find that outages minutes can increase 20–70 % during days with high wind speed (>50 m/s), 80–220 % during days of intense precipitation (>40 mm/day), and around 15–60 % during heatwaves (>40 degrees Celsius). In terms of flooding, we find that severe flood inundation in urban areas can increase daily outage minutes with a factor 2.1 to 5.5. Our findings highlight how high frequency data can help empirically validate how climate extremes can affect essential services to customers, and how these impacts differ across types of locations. This information is key for those countries that aim to meet universal access to energy in the coming decades, yet at the same time will experience more frequent and intense climate extremes.
A Copernicus-based evapotranspiration dataset at 100 m spatial resolution over four Mediterranean basins
Authors: Bartkowiak Paulina , Ventura Bartolomeo , Jacob Alexander , Castelli Mariapina
Published: October 2024

Abstract. Evapotranspiration (ET) is responsible for regulating the hydrological cycle, with a relevant impact on air humidity and precipitation that is particularly important in the context of acute drought events in recent years. With the intensification of rainfall deficits and extreme heat events, the Mediterranean region requires regular monitoring to enhance water resource management. Even though remote sensing provides spatially continuous information for estimating ET on large scales, existing global products with spatial resolutions ≥ 0.5 km are insufficient for capturing spatial detail at a local level. In the framework of ESA's 4DMED-Hydrology project, we generate an ET dataset at both high spatial and high temporal resolutions using the Priestley–Taylor Two-Source Energy Balance (TSEB-PT) model driven by Copernicus satellite data. We build an automatic workflow to generate a 100 m ET product by combining data from Sentinel-2 (S2) MultiSpectral Instrument (MSI) and Sentinel-3 (S3) land surface temperature (LST) with ERA5 climate reanalysis derived within the period 2017–2021 over four Mediterranean basins in Italy, Spain, France, and Tunisia (Po, Ebro, Hérault, and Medjerda). First, original S2 data are pre-processed before deriving 100 m inputs for the ET estimation. Next, biophysical variables, like leaf area index and fractional vegetation cover, are generated, and then they are temporally composited within a 10 d window according to S3 acquisitions. Consequently, decadal S2 mosaics are used to derive the remaining TSEB-PT inputs. In parallel, we sharpen 1 km S3 by exploiting the dependency between coarse-resolution LST and 100 m S2 reflectances using a decision tree algorithm. Afterwards, climate forcings are utilized to model energy fluxes and then for daily ET retrieval. The daily ET composites demonstrate reasonable TSEB-PT estimates. Based on the validation results against eight eddy covariance (EC) towers between 2017 and 2021, the model predicts 100 m ET with an average RMSE of 1.38 mm d−1 and a Pearson coefficient equal to 0.60. Regardless of some constraints mostly related to the high complexity of EC sites, TSEB-PT can effectively estimate 100 m ET, which opens up new opportunities for monitoring the hydrological cycle on a regional scale. The full dataset is freely available at https://doi.org/10.48784/b90a02d6-5d13-4acd-b11c-99a0d381ca9a, https://doi.org/10.48784/fb631817-189f-4b57-af6a-38cef217bad3, https://doi.org/10.48784/70cd192c-0d46-4811-ad1d-51a09734a2e9, and https://doi.org/10.48784/7abdbd94-ddfe-48df-ab09-341ad2f52e47 for the Ebro, Hérault, Medjerda, and Po catchments, respectively (Bartkowiak et al., 2023a–d).
City-wide Solar Radiation Potential Analysis by Coupling Physical Modelling and Machine Learning
Authors: Chen Xiana , Yu Junxian , Tu Wei , Chen Long
Published: October 2024

Abstract. Addressing the challenges posed by climate change and meeting urban energy demands is of utmost importance in today's world. Building Integrated Photovoltaics (BIPV) emerges as a crucial solution for energy conservation and carbon emissions reduction in urban environments. However, traditional methods of assessing solar radiation on buildings using physical models are often computationally intensive and time-consuming. This paper introduces a novel hybrid approach that integrates physical model-based solar radiation calculation with machine learning techniques to analyze Solar Radiation Potential (SRP) across city-wide building infrastructure. The proposed approach precisely evaluates the SRP of representative blocks by leveraging computing-intensive physical models integrated with 3D building data. Subsequently, two machine learning models are developed to effectively predict the SRP of building roofs and facades across the entire city. To validate the efficacy of this approach, an experiment was conducted in Shenzhen, China, yielding insightful results. The findings reveal that Shenzhen has a huge potential for BIPV solar power generation, with mean annual total building roof and facade solar radiation values of 9.22*107 kwh and 2.47*108 kwh, respectively. It can be further observed that relying solely on rooftop installations is insufficient to meet electricity demand. This study not only provides an innovative alternative for city-wide SRP estimation by combining physical modeling and machine learning but also offers valuable insights for fostering low-carbon urban environments and informing data-driven and model-driven urban planning and management strategies.
Energy Consumption-Driven UAV Dock Deployment Planning for Power Inspection
Authors: Fu Jing , Shao Guiwei , Wang Zhiye , Wu Shaolong , Cai Huanqing , Wu Huaxi , Chen Chi , Yang Bisheng
Published: October 2024

Abstract. As an important energy in modern society, the stable operation of electricity is the guarantee of social and economic operation, and the loss caused by the damage of power facilities is immeasurable, so the regular monitoring of power facilities is indispensable. UAVs, with flexible flight mode, have played an important role in power inspection. With the development of UAV docks, UAV inspection has entered a new stage. However, due to the fixed location of the docks and limited coverage, how to achieve the optimal deployment of the docks with the lowest cost and full coverage of power facilities through reasonable deployment is one of the important issues that need to be solved at this stage of dock construction. To solve this problem, this paper proposes an energy-driven adaptive optimization method for dock location by combining geospatial analysis with UAV performance index. The experiment results show that our method can achieve an efficient, reasonable and feasible optimal location for UAV dock deployment.
High-Precision Monitoring during the Installation of Large Steel Structures by UAV Nap-of-the-Object Photogrammetry
Authors: Liu Chuanyao , Wei Shuangfeng , Zhang Min , Yan Qiang , Yu Fan
Published: October 2024

Abstract. This paper proposes and validates a method based on UAV nap-of-the-object photogrammetry for refined 3D digital modeling to achieve high-precision monitoring during the installation of large steel structures, offering a comparative analysis with traditional oblique photogrammetry methods. Through field tests and data processing on the steel structure of a sports stadium in Zhejiang Province, the results demonstrate that nap-of-the-object photogrammetry can capture high-resolution images, offering significant advantages in detail representation and modeling of complex structures. Experimental data reveal that the model's root mean square error (RMSE) generated by nap-of-the-object photogrammetry is 14.56mm, markedly lower than the 51.99mm achieved by traditional methods, meeting the Level II accuracy standard specified in the "Technical Specifications for Nap-of-the-Object Photogrammetry." The study further shows that, when combined with optimized flight path planning, nap-of-the-object photogrammetry enhances both the efficiency and accuracy of data collection while improving operational safety. This technique is highly applicable and flexible, making it suitable for data acquisition of complex structures and high-rise buildings. In summary, the proposed method exhibits significant advantages in terms of accuracy, efficiency, safety, and applicability, providing a practical solution for high-precision, comprehensive digital modeling of large steel structures.
Back to the Future: Revisiting Barometric Levelling
Authors: Scarmana Gabriel
Published: October 2024

Abstract. Barometric levelling, traditionally employed in aviation, parachute jumping, and mountain climbing, has undergone a transformative shift with the technological advancement of state-of-the-art atmospheric pressure sensors. This evolution has rendered these sensors more accurate and affordable, broadening their applications within the realm of Intelligent Systems. The integration of barometric altimeter modules into electronic devices, coupled with GNSS and mapping systems, has significantly enhanced their versatility, making them complementary components in various consumer electronics like smartphones, watches, sports bands, bicycle computers, and motor vehicle tracking devices. Moreover, they play a pivotal role in emerging technologies such as drone mapping projects and modelling. This because of their capabilities of measuring elevations in GNSS denied areas such as caves, canyons, and tunnels. The significance of barometric levelling lies in its capacity to determine relative elevation between two points through the measurement of atmospheric pressure. This technique leverages the fact that atmospheric pressure decreases with increasing altitude, enabling the calculation of elevation differences by comparing pressure readings at different locations.In this study, 25 elevations within a 3 km radius were independently measured using barometric levelling, highlighting its practical usage. These elevations ranged from 2 m to 140 m. Readings of time of measurements, temperature, air pressure, and humidity were taken at each of these stations and were synchronized with the readings obtained from a fixed reference station of known elevation. The measurements at this reference station were carried out with an instrument with data logging capabilities, able to record relevant weather data at pre-established intervals of time without human intervention. The results of these measurements were compared to fixed reference stations of known elevation, and the subsequent differences were analysed. The study employed a portable weather monitoring instrumentation with data logging capabilities, emphasizing the importance of automated data collection practices. The comparison of the 25 elevation readings with true elevations, determined by conventional surveying methods, revealed an RMSE of +/- 0.49 meters, affirming the accuracy of barometric levelling.Additionally, a distance-dependent test demonstrated a predictable decrease in positional accuracy as the distance from a reference base station increased, providing valuable insights into the system's limitations. The barometric levelling tests presented here offer results that can inform future applications. The conclusions and recommendations derived from this study provide guidance for optimizing the use of barometric levelling within the broader landscape of Intelligent Systems.
Explaining Environmental Distribution of Aedes albopictus using Machine Learning
Authors: Singh Priyanka , Saran Sameer
Published: October 2024

Abstract. The Aedes albopictus mosquito, known for its role in transmitting diseases such as dengue fever, Zika virus, and chikungunya, poses a significant public health threat globally. Understanding its distribution patterns is crucial for effective disease surveillance and control. This study employs machine learning techniques, specifically MaxEnt modeling, to elucidate the relationship between environmental factors and the distribution of Aedes albopictus. Using presence-only data and a suite of environmental variables, we trained MaxEnt models to predict the potential distribution of Aedes albopictus across a geographical region. The models were validated using independent datasets and evaluated for their predictive accuracy and robustness. Our results reveal significant associations between Aedes albopictus presence and environmental factors such as temperature related variables. Furthermore, we employed spatial analysis techniques to identify areas at high risk of Aedes albopictus presence, aiding in targeted vector control strategies and disease prevention efforts. MaxEnt models demonstrated high predictive performance, effectively capturing the complex relationships between environmental variables and mosquito distribution in Nepal, India and Myanmar, along with Spain and Italy. By integrating machine learning algorithms with environmental data, this study provides valuable insights into the ecological drivers of Aedes albopictus distribution, enhancing our ability to mitigate the risk of mosquito-borne diseases in affected regions.
A Review of Existing Sources for the Design of an Archaeological Underwater Cultural Heritage Database of Puglia Region (Italy)
Authors: Spreafico Alessandra , Colucci Elisabetta , Chiabrando Filiberto , Auriemma Rita
Published: October 2024

Abstract. Underwater cultural heritage (UCH) in Italy is under-documented despite its significance. Creating a comprehensive UCH database is essential but faces challenges, such as complex documentation processes, data interoperability, and international standard adherence. This paper examines data models, standards, and the use of webGIS and databases for underwater cultural heritage documentation in Italy and globally. International documents like the 1996 ICOMOS Charter and the 2001 UNESCO Convention emphasize in-situ preservation. However, documentation efforts remain scattered, lacking a unified database. GIS technologies are vital for managing and analyzing UCH data but are underutilized for public access and tourism. Projects like Andar per Mare and Archim3des in the Puglia region aim to promote underwater cultural heritage using webGIS platforms. However, existing sources like CartaPulia face limitations, including a lack of standardization, specialized fields for underwater cultural heritage characteristics, and language barriers. The proposed solution involves creating a new data model based on standards, resulting in a bilingual geodatabase. This geodatabase will support scientific and tourism-focused webGIS applications, enhancing accessibility and promoting Italy's underwater cultural heritage. A unified database will prevent duplication, facilitate discoveries, and promote Italy's cultural heritage.
National Land Use Zoning Dashboard – Harnessing Geo-informatics Technology for Seamless Land Management and Conflict Resolution
Authors: Tashi Tashi , Tshering Chencho
Published: October 2024

Abstract. The National Land Use Zoning (NLUZ) exercise was conducted by the National Land Commission Secretariat (NLCS) in collaboration with other agencies of the Royal Government of Bhutan. The primary objective of this exercise was to harmonize all land uses on the ground and integrate spatial data across different agencies. Previously, such data had been created and archived separately within each agency. To accomplish this goal, a dedicated team was formed, and a baseline report was published in 2023. However, simply having a report did not fully support the objectives of the NLUZ. Therefore, an interactive dashboard was conceptualized to serve as a platform for integrating and visualizing all geospatial data. This dashboard will also provide analytical tools to guide decision-makers in the optimal utilization of the country's limited land resources. The development of the dashboard will utilize ArcGIS technology and will be customized using the ArcGIS Map SDK for JavaScript and the Calcite System Design.
Counting Cattle in Argentina with AI and Satellite Images
Authors: Torrusio Sandra , Gonzalez Juan , Errázquin Martin , Cereceda Abril , Cassano M. Julia , Morales Natalia , Saucedo Ricardo
Published: October 2024

Abstract. From a specific need of the national institution responsible for plant and animal health in Argentina, SENASA, this collaborative work between the public sectors together with academia arises. The objective was the development of a Deep Learning algorithm for the detection of livestock, cows in particular, in very high-resolution satellite images (provided by the Argentine Space Agency (CONAE)) and its subsequent counting. The basic elements involved in the development of artificial intelligence are detailed, such as the selection and acquisition of satellite images, their very thorough preprocessing and labelling, details of the training stage and some forms of error quantification. The image database is made up of about 320 scenes (based on very high resolution (VHR) satellite data from the Pleiades and Pleiades NEO sensors, ©Airbus 2022, distributed by CONAE) of the Pampas and Patagonian regions in Argentina. Around 8,000 labels of different types of animals were generated, the most common were cows and sheep. Also labels that did not represent animals to contribute to training. Finally, some very promising preliminary results are presented, such as the average error in the count that was achieved was ± four cows. The usefulness of these tools is reflected in better management of renewable natural resources linked to animal health issues, fiscal issues and within the framework of the 2030 Agenda and Sustainable Development Goals #12, #15 and #17.
Identification and Analysis of Peak Population Migration Patterns in the Beijing-Tianjin-Hebei Region Based on Complex Network Theory
Authors: Wen Zheng , Zhang Jianqin , Hu Chaonan
Published: October 2024

Abstract. As a vital economic and population agglomeration area in China, the Beijing-Tianjin-Hebei region has attracted considerable attention regarding population migration issues. Population migration not only directly affects the population size and structure of cities within the region but also has profound implications for economic development, social stability, and urban planning. This study extends the analysis to the "Spring Festival Travel Rush" period, using population migration data from January to March in the years 2020 to 2022 as the basis. By employing complex network theory and relevant statistical indicators, the study explores the peak period population migration patterns and their variations in the Beijing-Tianjin-Hebei region. The research firstly identifies significant changes in population migration patterns in the Beijing-Tianjin-Hebei region around 2021 and analyzes the changing patterns. Secondly, network statistical indicators indicate hierarchical population migration patterns based on city tiers. Furthermore, cities with unique migration patterns are identified. Finally, based on an in-depth exploration of population migration patterns and their variations in the Beijing-Tianjin-Hebei region, the study provides suggestions and prospects for future urban planning and development, offering important references for addressing the challenges posed by population migration in the region.
Explore to Mantai, the Ancient Port-city and the International Trade-hub of Maritime Silk Road in Northern Coast of Sri Lanka
Authors: Wijenayake Nelson , Du Mingyi , Jiang Jie
Published: October 2024

Abstract. Mantai Ancient Port City is located in Mannar, Northern Coast of Sri Lanka, archeological reserves declared by the Department of Archeology in Sri Lanka. In concern with historical international trades for almost 2000 years, Mantai had been an excellent port city as discovered by 1980s investigations. Today, this historically valued archeology reserves are being covered by various unauthorized constructions. The artifacts found in 1980s excavations figured out in further research directives to unveil the ancient cultural and social relations that had been experienced over two millennium around the globe. This research paper elaborates change detection of temporal aspects of unauthorized constructions within the respective geographical domain. Change detection researches are based on the historical maps, aerial photographs, satellite images and recent spatial data sources played over the application software. The investigation mission deployed in 1980 had unveiled evidences of civilization history and artifacts from many countries. However the archeological research and investigations were disrupted in 1983 with escalation of civil war in Northern Province. The Research elaborates visual facts and figures of the constructions erected after 1980 against their chronological measures. The research team further discusses about the tremendous variety of fields that Mantai opens to collaborate with the international research organizations.
Developing a Workflow for Transforming BIM Models into Immersive Virtual Reality Experiences
Authors: Wijerathna Ashirwada , Perera Srinath , Nanayakkara Samudaya , Zlatanova Sisi
Published: October 2024

Abstract. The integration of Extended Reality (XR) and Building Information Modelling (BIM) has emerged as a promising approach for enhancing interaction with spatial data in the built environment. While the potential of BIM for advanced visualization has been recognized, there remains a need for standardized workflows that facilitate the transformation of BIM models into immersive virtual reality (VR) experiences. This research contributes to the ongoing development of BIM-VR integration by presenting a workflow that leverages Revit, Twinmotion, and Datasmith to create visually rich and interactive VR environments. The established process focuses on enhancing textures, incorporating dynamic lighting and weather simulations, and populating the virtual space with realistic elements. The workflow also addresses the integration of interactable objects to elevate user engagement and the use of cutting-edge VR headsets for an immersive experience. By providing a structured approach to bridging complex BIM data with VR, this research aims to support architects, engineers, construction professionals, and clients in design collaboration, project review, and decision-making across the building lifecycle. The workflow's potential for facilities management and training applications is also explored. Through a case study, the research demonstrates the workflow's effectiveness in facilitating a deeper understanding of architectural spaces before construction, highlighting its potential for improving efficiency and reducing rework. The paper also discusses the challenges and opportunities associated with integrating BIM with GIS and sensor data to create comprehensive digital twins. This research contributes to the growing body of knowledge on BIM-VR integration and underscores the importance of continued development in this field to enhance the design, communication, and experience of the built environment.
Indoor Scene Intelligent Identification System Based on Spatial Topological Relationship Constraints
Authors: Xu Shenglei , Sun Yaqin
Published: October 2024

Abstract. Indoor scene identification can provide prior environmental information for indoor positioning applications, achieving positioning enhancement. Due to the similarity of wireless signals in adjacent spaces, it can lead to incorrect identification in neighbouring scenario units. To address this problem, this paper first employs a Naive Bayes classifier to train and classify wireless signal strength data from different scenes, constructing a scene identification algorithm. Secondly, a topological relationship adjacency matrix and adjacency list tailored for indoor positioning are constructed, imposing spatial topological constraints to assist scene identification. Finally, an indoor scene intelligent identification system is developed and implemented. The experimental results indicate that the scene identification method based on spatial topological relationship constraints can effectively improve identification accuracy. The overall accuracy for 8 scenario units is 98.2%, and the identification accuracy is increased by 1.1% compared with the original method.
Research on Spatial Data Aggregation Based on Aggregation Degree Function
Authors: Zeng Zhaoyang , Huo Liang , Zhu Wangzhang , Bao Peng , Li Yucai , Zhang Miao
Published: October 2024

Abstract. Restricted by the development level of hardware and software technology, computers cannot load massive data at one time, coupled with the fact that the three-dimensional linear scene is characterized by complicated lines, irregular shapes of features and a large number of features. Therefore, it is necessary to seek a three-dimensional spatial data organization and scheduling method applicable to the railroad scene to realize the display and interaction of the scene. In this paper, we propose a data organization method based on the aggregation degree function for the 3D model of features. The feature model is projected to generate an orthographic projection map, the cluster division rule is designed to divide the subsets, the feature model after clustering is aggregated using the feature model aggregation rule, and the aggregated model is displayed according to the aggregation degree function and viewpoint factor. The results of the test applied to the railroad scene show that the 3D spatial data aggregation based on the aggregation degree function can improve the loading speed of the 3D scene, and can effectively support the application of interactive visualization of the railroad 3D scene.
Leveraging cloud compute and open source software to generate 3D models from drone photography
Authors: Biegel Gregory
Published: October 2024

Abstract. Modern drone platforms provide the opportunity to capture large quantities of high quality, geotagged aerial imagery quickly and over large distances, at a relatively low cost. As organisations increasingly turn to digital twin technology to manage their operations, rich, photorealistic three dimensional (3D) models of their assets become increasingly important. This paper describes how cloud computing, and container based serverless compute in particular, can be used together with open source software to generate a 3D model, converted to 3D tiles for optimised transmission, from images of large outdoor assets captured by drone. This approach offers a flexible and cost effective way to processing drone imagery into 3D models whilst allowing you to maintain ownership and control of your data.
Rethinking Intergenerational Living as the Ideal Form of Senior Care: Life Course Research with Immigrant Families in Toronto
Authors: Carson Alexa
Published: October 2024

Canada’s care systems are ill-equipped to support its aging population, and this crisis intertwines with an acute shortage of affordable housing. Immigrants to Canada have a higher propensity to cohabitate multi-generationally, an arrangement that is sometimes romanticized as an ideal form of senior care. This article contributes to scholarship exploring intergenerational cohabitation as a practice of care, using life course research to consider how class and migration timing shape experiences of intergenerational living and senior care. Based on 19 in-depth interviews with immigrant seniors from Latin America and the Caribbean (n=10) and family caregivers (n=9) living in the Greater Toronto Area, this study uncovers two central findings. First, intergenerational living should not be viewed as an ideal form of senior care since (1a) some seniors resist intergenerational living, preferring independence and downtown residence nearer to culturally relevant communities and (1b) cohabitation does not always provide sufficient or better care. Second, access to smooth multigenerational cohabitation is inequitable, as housing arrangements are structured by class and migration timing, with middle-class families who have been in Canada longer facing fewer barriers to positive experiences of intergenerational living, compared to more recent migrants with lower incomes. This article challenges culturally essentializing assumptions about immigrant intergenerational cohabitation and argues that access to affordable housing is a senior care issue.
Teaching Interprofessional Collaboration through Experiential Learning with Behavioural Psychology, Business, and Engineering Students
Authors: Shea Pamela , Dogra Rajni , Shea Kaela , Bazylak Jason
Published: October 2024

Research has indicated that interprofessional collaboration improves client outcomes, enhances work life, optimizes costs, and allows professionals to tackle complex situations with increased knowledge and creativity. However, the inherent barriers and challenges of developing effective interprofessional teams have been documented in the literature. This research explores whether teaching interprofessional collaboration improves students’ perceptions of their own interprofessional collaborative competencies. This research provides two experiential learning projects to teach interprofessional collaboration among behavioural psychology, engineering, and business students. In Study 1, interprofessional teams were presented with complex cases, and teams created a functional assessment and developed a function-based treatment using technology developed by the engineering students. During Study 2, community stakeholders provided interprofessional teams with community-based challenges. Students worked collaboratively to analyze why the challenge existed and created innovative solutions based on behavioural economics. Significant increases in the Interprofessional Collaborative Competency Attainment Scale scores were found in both studies. Sentiment analysis results suggested that most students felt that the interprofessional collaboration project benefitted them in terms of communication, collaboration, and synergy. Findings support the effectiveness of IEP in increasing student perceptions of their interprofessional collaborative competency.
Crisis of Meaning: Compassion and Community Engaged Learning
Authors: Smeltzer Sandra , Poli Amala , Axenova Kristina
Published: October 2024

This research paper explores the relationship between compassion, meaning-making, and curricular community engaged learning (CEL) in a university setting. We contend that CEL, as a key form of community-focused experiential learning (EL), can play an important role in helping address the well-being of students, faculty, and staff by providing opportunities to engage in what they consider to be meaningful activities. Our critical examination of this relationship draws on primary research conducted in Winter and Spring 2022 with members of a large Canadian university and its affiliated colleges. This mixed-methods research includes a Qualtrics-based survey with over 2,500 respondents, combined with a series of interdisciplinary, online focus group discussions with faculty, staff, and students. Our findings reveal that many participants have experienced a “crisis of meaning” in their academic and work lives. They thus seek avenues to engage in meaningful, creative, compassionate, and community-focused activities that provide them with opportunities to foster their overall well-being. Participants emphasized the heightened importance of such endeavours after the COVID-19 pandemic as they pursue deeper connections with others and a stronger sense of purpose beyond utilitarian academic or employment performance.
Come Join the Party: Lessons Learned Fostering Inclusion in Online Learning
Authors: Schultz Christie , Thompson S. Anthony , De Lugt Jenn
Published: October 2024

This article invites scholars of teaching and learning in higher education to consider the ways in which instructors can use practices of inviting inclusion to create an environment in which students can feel—and be—included in online classrooms, especially since the onset of the COVID-19 pandemic. Using the analogy of a “block party” and to illustrate the practices envisioned, the authors explore their and others’ practices of teaching online in ways that foster inclusion, with attention to their experiences teaching during the pandemic. The authors conclude by reflecting upon what has been learned because of pandemic-informed teaching and learning experiences.