bluuebunny/crossref_metadata_2025 huggingface dataset:
Risk of Major Cardiovascular Events in Offshore Oil and Gas Industry Workers in Qatar
Authors: Mochtar Iqbal , Modjo Robiana
Published: November 2024

Introduction: Oil and gas workers are exposed to various hazards in the workplace, which increases their risk factors and risk of major adverse cardiovascular events (MACE). There have been limited studies on the risk of MACE in workers within the oil and gas industry. Methods: We utilized a cross-sectional approach to analyze data spanning a decade for offshore and onshore workers of an oil and gas corporation in Qatar. By utilizing the Framingham Risk Score (FRS), we evaluated the risk of MACE within both groups. Data was retrieved from the corporation’s electronic medical record. The corporation had 736 offshore workers and 1,041 onshore workers. A sample calculation determined that 48 data samples were required for the offshore workers, which were then rounded up to 50. Similarly, 50 data samples were obtained from the onshore workers for comparison. The samples were selected using a computer-generated random sampling method. Two sets of data, namely the first profile (2009) and the second profile (2019), were collected in each sample. The available data were used to compute the risk of MACE. Results: Over a ten-year period, both offshore and onshore workers experienced increased risks of MACE. For offshore workers, the risk escalated from 9.2(8.0)% to 20.4(15.2)%, whereas for onshore workers, the risk increased from 10.0(7.6)% to 17.0(11.0)%. The risk of MACE was found to be significantly greater among offshore workers compared to onshore workers (p=0.011). Conclusion: The deterioration in the risk of MACE was more pronounced among offshore workers in comparison to onshore workers.
MyPlate: A Diet Monitoring and Recommender Application
Authors: Achuthan Anusha , Hui Yii Shu , Ali Alkhafaji Ali Fawzi Mohammed
Published: November 2024

Introduction: Diet monitoring is of great interest in practicing a healthy diet to ensure good health by keeping track of the type and amount of food consumed. The food recommender system could provide personalized suggestions about food choices that best suit user preferences, making diet monitoring a valuable tool for maintaining good health, preventing diseases, and achieving a balanced lifestyle. Methods: This article presents a diet monitoring and recommender Android mobile application utilizing a Mask Region-based Convolutional Neural Network (Mask-RCNN) and portion analysis with a content-based filtering recommender algorithm. The application, named MyPlate, will provide a daily calorie limit and nutrition guidelines based on the user profile record, such as current and ideal weight. At the same time, MyPlate can also perform food image recognition and portion analysis from the picture captured and estimate the total calories. Finally, MyPlate provides a personalized food intake recommendation based on the previous intake record. Results: The developed MyPlate application can achieve accurate food image recognition, with the mean average precision at 0.825. Besides that, the proposed MyPlate application can perform portion analysis and provide food recommendations based on intake history at 80% similarity. Conclusion: The proposed MyPlate Android application has shown the effectiveness of incorporating machine intelligence into a diet monitoring technique that can promote healthy eating habits in the community.
Modelling the Future Malaysian Clinician Dental Workforce using System Dynamics
Authors: Che Musa Muhd Firdaus , Jennifer Morgan , Paul Harper , Eduardo Bernabé , Jennifer E. Gallagher
Published: November 2024

Introduction: The aim of this operational research workforce project was to build, and test, a clinical dental workforce model for Malaysia to address population need/demand with a view to informing health policy. Methods: A system dynamics (SD) model was developed to take account of population oral health needs and demands and dental workforce supply nationally from 2010 to 2040. This involved building two sub-models: population need/demand; and dental workforce supply, drawing on evidence from two previous studies (student survey and interviews of key-stakeholders) supported by government data. The two sub-models were integrated in relation to clinical time to explore potential of over- or under-supply of clinical hours; were latter converted to clinical workforce numbers. The SD model was tested and validated as an acceptable baseline model for Malaysia using existing workforce data. Results: A SD model was developed to model the need, supply and demand for dental care in two sectors from 2010 to 2040. There is a short-term need for an expanded dental workforce to meet the needs of the population but there is a potential oversupply of dentists and therapists from 2040, or earlier. The level of public demand for both primary and secondary dental care is expected to increase respectively from the year 2010 to 2040, varying in relation to demographic and health trends across public and private sectors. Conclusion: The study suggests there is are current requirements for an expanded dental workforce to serve the population needs/demand and potential for oversupply from 2040, or earlier.
Migliorare Autostima e Autoefficacia per ridurre lo Stress attraverso la tecnica energetico-meditativa detta Espansione di Coscienza del Metodo Cosmo. Lo studio si è svolto su 100 corsisti
Authors: Sanna Antonio , Columbano Teresa , Ondradu Katya , Puddori Mariangela , Molinari Claudio G. , Barontini Melissa , Cittanti Giuliana
Published: November 2024

L’espansione di Coscienza è una tecnica bioenergetica del Metodo Cosmo (ampliamento del più conosciuto Metodo Summa Aurea di cui è erede) (Fabbroni R., Columbano T., 2024) che è in grado di agire a livello Psicologico, a livello mentale, a livello fisiologico (Fabbroni R., Molinari C., Sanna A., Columbano T., et Alt.) e ovviamente a livello energetico, per migliorare qualitativamente lo stato di benessere della persona in autotrattamento (Fabbroni R., Sanna A., 2022). Può essere vista come una meditazione energetica la cui peculiarità principale è l’utilizzo dell’Energia Scalare (Fabbroni R., 2024) tipica del Metodo. Scopo dello studio è la valutazione degli effetti che si producono sul livello di Autostima e Sicurezza di sé grazie all’utilizzo frequente della Tecnica Energetico-Meditativa chiamata Espansione di Coscienza del Metodo Cosmo. Lo studio qualitativo è basato su 100 partecipanti ai corsi del Metodo Cosmo di cui oltre il 50% Operatori in ambito Medico sanitario. Attraverso un questionario con 3 item si è sondato i cambiamenti dei praticanti. I risultati ottenuti hanno pienamente confermato le ipotesi della ricerca.
İbtidai siniflərin Azərbaycan dili dərslərində şagirdlərin humanizm tərbiyəsinin formalaşdırılması imkanları
Authors: M. Könül
Published: November 2024

Məqalədə ibtidai siniflərdə tədris olunan Azərbaycan dili dərslərində şagirdlərdə humanizm tərbiyəsinin aşılanması yollarından bəhs olunur. Humanizm insan cəmiyyətinin məhsuludur. Belə ki, bu cəmiyyətdə yaranmış tələbatlar əmək prosesində meydana gəlmişdir. Davranış normaları adi vaxtlarda, əmək prosesində, eləcə də istirahət zamanı müəyyən qaydaların yerinə yetirilməsinə ehtiyac olan dövrdən yaranmağa başlamışdır. Bu normalar insanın ictimaiyyət, kollektiv, eləcə də ayrı-ayrı insanlarla münasibətini müəyyənləşdirir. Müs
Early prediction of placenta accreta spectrum by evaluation of risk factors and ultrasound
Authors: Hu Caihong , Zhang Weishe , Pei Chenlin , Liu Yuelan , Fu Yiran , Peng Qiaozhen , Wang Biaobiao , Li Qi , Huang Jingrui
Published: November 2024

Introduction

We explored the predictive utility of clinical risk factors and first-trimester pregnancy ultrasound signs for severe placenta accreta spectrum.

Material and methods

Patients with placenta accreta spectrum treated in our institution between March 1, 2017 and December 31, 2022 were analyzed. The patients were divided into those with mild and those with severe conditions. Univariate analysis was used to determine the clinical risk factors and first trimester ultrasound signs associated with severe placenta accreta spectrum. Receiver operating characteristic curves were drawn and the areas under the curves calculated.

Results

Univariate analysis revealed significant between-group differences between the groups in the number of cesarean sections, scar pregnancy, low gestational sac position, abnormal placental position, focal exophytic mass and abnormal placental lacunae in placental parenchyma (p < 0.05). The number of cesarean sections and first trimester ultrasound signs predicted severe placenta accreta spectrum, with areas under the curves of 0.66 and 0.75. When the number of cesarean sections was combined with low gestational sac position, the placenta position and related ultrasound signs, the areas under the curves for predicting severe placenta accreta spectrum were 0.78, 0.73, and 0.89, respectively.

Conclusions

Clinical risk factors and first-trimester ultrasound signs predicted severe placental accreta spectrum and their combinations had even greater clinical utility.
Integration of Augmented Reality and Artificial Intelligence: A Review of Framework for Immersive Learning in Oman Vision 2040
Authors: Naidu Vikas Rao , Gupta Rajani Rani , Al Rubaii Thuraiya , Dattana Vishal
Published: November 2024

Technological breakthroughs are driving a rapid transition of the educational landscape. Among these, artificial intelligence (AI) and augmented reality (AR) stand out as being crucial in changing how knowledge is transmitted and gained. The Oman Vision 2040 seeks to use these technologies to support a creative and forward-thinking educational system. This article presents a thorough framework for immersive learning that is in line with Vision 2040 and examines the integration of AR and AI in higher education institutions (HEIs) in Oman.
Perspectivas de la fiscalidad de la energía nuclear en el derecho tributario ambiental en la Unión Europea: el reglamento de taxonomía de la Unión Europea y el Plan Industrial del Pacto Verde
Authors: Díez Moreno María de los Ángeles
Published: November 2024

La energía nuclear representa aproximadamente el 26 % de la electricidad producida en la UE y cada uno de los Estados miembros es soberano a la hora de decidir su inclusión en sus respectivos sistemas energéticos. El reglamento sobre taxonomía de la Unión Europea reconoce el importante papel que desempeñará esta tecnología para afrontar el reto de la descarbonización, llegando incluso a impulsar programas de desarrollo de nuevos reactores, lo cual supone nuevas perspectivas para el sector nuclear. Este nuevo horizonte plantea la necesidad unas bases comunes para configurar un régimen de imposición apropiado que reconozca la contribución de esta tecnología baja en carbono a la vista de los principios del derecho tributario ambiental de la Unión Europea y la finalidad que persigue la Propuesta de Directiva del Consejo por la que se reestructura el régimen de la Unión de imposición de los productos energéticos y de la electricidad, que no es otra que garantizar la coherencia entre la fiscalidad de la energía y los objetivos climáticos de este Pacto Verde. Siendo verdes las inversiones nucleares que se lleven a cabo cumpliendo con los requisitos europeos de una gestión responsable de los residuos, al igual que las renovables, la carga fiscal que se deberá asignar a la energía nuclear será el tipo mínimo de 0,15 €/GJ, tipo que se aplicará a la electricidad, a los biocombustibles y biogás sostenible avanzados y a los combustibles renovables de origen no biológico, como el hidrógeno renovable. Este tipo mínimo deberá complementarse con los tributos que se establezcan sobre el riesgo asociado a esta tecnología de forma adecuada y, sobre todo, teniendo en cuenta que todas las centrales europeas cumplen las normas de seguridad en su operación, así como respecto a la gestión de los residuos que establece la Unión Europea para así evitar el establecimiento de tributos que lo graven repetida y acumulativamente sin ninguna finalidad extrafiscal, como ha ocurrido en España.
Transaksi Bitcoin dalam Perspektif Ekonomi Syariah
Authors: Fitri Riska Julia , Ismail M. Syukri
Published: November 2024

Cryptocurrency adalah uang digital, yang beredar di dunia maya tidak memiliki wujud fisik, awal kemunculannya tahun 2008 oleh Satoshi Nakamoto, keamanan Crypto dilindungi oleh teknologi blokchain, namun tidak ada lembaga yang bertanggung jawab dan tidak memiliki asset yang mendasar, segala problem yang muncul, menimbulkan pro dan kontra dikalangan pakar ekonomi dan para ulama, crypto belum memenuhi beberapa unsur dan kriteria sebagai mata uang khususnya dalam prinsip Ekonomi Islam, dalam konteks uang digital tidak ada underlying yaitu aset dijadikan sebagai dasar transaksi, uang digital bukan mata uang, ada unsur ketidak jelasan gharar, harga tidak terkendali dan fungsi mata uang digital telah berkembang sekedar alat tukar menjadi komoditas investasi. penelitian ini bertujuan untuk mengetahui bagaimana Transaksi Bitcoin dalam perspektif ekonomi syariah dan pandangan hukum islam terhadap transaksi bitcoin, teori yang digunakan adalah teori transaksi ekonomi  dan penelitian ini bersifat studi pustaka (Library Research), Dari penelitian ini dapat disimpulkan bahwa dalam Islam transaksi yang dilakukan harus jelas, wujud, barang, dan maanfaatnya, dan tidak ada pihak yang saling dirugikan, bitcoin haram dan tidak memenuhi syarat sil’ah secara syar’i, selain itu bitcoin juga bertentangan dengan Undang- Undang Nomor 7 Tahun 2011 dan Peraturan Bank Indonesia Nomor 17 Tahun 2015, Di Indonesia alat tukar yang sah hanya satu rupiah.
Influence of technology on the performance of community development non-governmental organisations-governmental NGOs in Kenya
Authors: Oira Justus Amenya , Muriuki Jenifer Wanjiru
Published: November 2024

The aim of this study was to find out the influence of technology on the performance of community development non-governmental organisations (NGOs) in Nairobi County, Kenya. The research was anchored by two theories: strategic fit theory and Ansoff strategic success theory. The research employed a descriptive research design focusing on a target population of the senior management team, social workers and caseworkers comprising 300 employees of SHOFCO located in Kibera Nairobi County, Kenya. The study selected a sample using a stratified random sampling technique, using a sample size of 90 individuals. The study used a structured questionnaire containing open-ended questions to collect data. Questionnaires were administered individually and collected after respondents had fully filled them. The results were analysed thereafter using a statistical package for social sciences (SPSS), regression analysis and presentation using figures and tables for ease of interpretation and understanding. The findings showed that technology had a positive and significant relationship with the performance of community development NGOs in Kenya. This study concluded that technology was the last predictor of the strategic performance of community development non-governmental organisations in Kenya.
Participation of rural women to rice-based farming system: A Study of North Bihar, India
Authors:   SMS, KVK, Begusarai, Dr. Rajendra Prasad Central Agricultural University, Pusa, Samastiipur, Bihar, India, Kumari Mala
Published: November 2024

Rural women in Bihar play a crucial role in agriculture and related activities, participating extensively in tasks from pre-harvest to post-harvest. Despite their significant contributions, these women often remain unrecognized, commonly referred to as “invisible farmers.” This study was conducted in the Samastipur district of North Bihar to examine the extent of rural women’s involvement in various agricultural activities. Two rice-growing blocks were randomly selected from a total of 20, with two villages chosen at random from each block, resulting in a sample of four villages. A total of 160 respondents were selected from 40 farm families in each village using a proportionate stratified random sampling technique based on landholding size. The study highlights that women’s independent participation in farm and allied activities within rice-based farming systems was 50.05 percent, surpassing men’s independent participation of 31.28 percent, while joint participation was recorded at 18.87 percent. This research underscores the essential yet often overlooked role of rural women in agriculture in Bihar.
ЦИФРЛЫҚ ПЛАТФОРМАЛАР КӚМЕГІМЕН ЖОҒАРЫ СЫНЫПОҚУШЫЛАРЫНА ҚАЛЫПТАСТЫРУШЫ БАҒАЛАУ ТАПСЫРМАЛАРЫН ҚҦРАСТЫРУДЫҢ ТӘСІЛДЕРІ
Authors: Рахимқанова Ж.Т. , Усенов Н.Е.
Published: November 2024

Мақалада жоғары сынып оқушыларының цифрлық ортада ӛзара мұғаліммен қарым-қатынастарының ӛнімді жолдары мен қалыптастырушы бағалау тапсырмаларын цифрлық платформалар кӛмегімен құрастырылу жолдары қарастырылған. Жоғары сынып оқушыларының оқу іс-әрекеттері, қалыптастырушы бағалау тапсырмаларын құрастырудағы алғышарттары мен цифрлық ресурстардың маңыздылығы туралы шетелдік және отандық ғалымдардың дереккӛздерімен жұмыс жасалынды. Оқытудағы бірқатар мәселелердің бастамасы республика деңгейінде алынған еркін формадағы мұғалімдер арасындағы сауалнамада анықталды. Алынған сандық ақпараттар статистикалық және сипаттамалық тәсілдермен ұсынылды. Ғылыми жұмыстың ӛзектіліктері талқылау сұрақтары арқылы негізделіп, шешімдері айқындалды. Зерттеу жұмысының басты мақсаты –жоғары сынып оқушыларының география сабақ-тарында, теориялық білімдерінің практикада қолданылуында мұғалімнің цифрлық ресурстар кӛмегімен ұсынылған қалыптастырушы бағалау тапсырмасының тиімділігін анықтау. Жаңашылдық әрекеттермен құрастырылған тәсілдер мен тәжірибелер, дамыту қолданбалары оқушылардың қызығушылығын оятып, оқуды жеңілдетуге кӛмектеседі.Мұғалім оқу мақсаттарына сай ұсынылатын қалыптастырушы бағалау тапсырмаларын оқушының болашақ жоғары оқу орнының білім алушы, кәсіби маман болатынын ескеріп, әдістемелік қорын ұлғайтуда цифрлық ресурстардың кӛмегімен сабақтастырып отыру қажет. Нәтижесінде мұғалім ӛзін-ӛзі кәсіби дамытып, болашақ түлек атанатын оқушы үшін географиялық білімінің жетілуі мен оқу мақсатына толық жете алуына кӛмектеседі.
O IMPACTO DA DIETA NA SAÚDE BUCAL: UMA REVISÃO DE LITERATURA
Authors: Oliveira Neto João Venâncio , Machado Valesca Rovana Carvalho , Borba Márcia Socorro da Costa , Linhares Helton Diego Dantas , Melo Neto José Pereira de , Verde Giselle Maria Ferreira Lima
Published: November 2024

Este estudo aborda a relação entre a dieta alimentar e a saúde bucal, destacando como certos alimentos podem influenciar no surgimento de problemas como cáries, erosões dentárias e doenças periodontais. A cavidade oral, por estar em contato direto com o meio externo e fazer parte do sistema digestivo, tem seus tecidos e estrutura dental diretamente impactados pelo que é consumido. Dietas ricas em açúcares e alimentos ácidos são prejudiciais, pois danificam o esmalte dos dentes e alteram a microbiota oral, aumentando a vulnerabilidade a problemas dentários. Em contrapartida, alimentos ricos em cálcio e vitaminas, como laticínios, são essenciais para a manutenção da saúde de dentes e gengivas. O objetivo deste estudo é analisar o impacto da alimentação na saúde bucal. O estudo foi conduzido por meio de uma revisão integrativa de literatura, focada em artigos disponíveis nas bases de dados Lilacs e PubMed, no período entre 2020 e 2024. Foram estabelecidos critérios de inclusão para selecionar artigos relevantes ao tema, publicados em português e inglês, enquanto foram excluídos estudos como monografias, dissertações, teses e artigos duplicados. Dos 180 artigos encontrados inicialmente, apenas 10 atenderam a todos os critérios de inclusão e foram analisados detalhadamente. Os resultados reforçam a correlação entre a dieta e a saúde bucal. Alimentos ricos em açúcares e ácidos são fatores determinantes para o aumento do risco de cáries e erosões dentárias. Em contrapartida, alimentos ricos em cálcio, como leite e queijos, protegem o esmalte dental e contribuem para uma microbiota oral equilibrada, sendo aliados na prevenção de doenças bucais. A conclusão do estudo ressalta a importância de integrar hábitos alimentares saudáveis à rotina diária como forma de prevenir patologias bucais. O acesso a informações claras e eficazes sobre nutrição pode ser uma ferramenta poderosa na promoção da saúde oral e geral, mostrando que mudanças simples na dieta podem ter efeitos significativos na prevenção de doenças.
A EDUCOMUNICAÇÃO COMO AGENTE DE SENSIBILIZAÇÃO NA PRÁTICA SOCIOAMBIENTAL
Authors: Chagas Daniel Alves Caitano , Coutinho Diogenes José Gusmão
Published: November 2024

A pesquisa aborda a Educomunicação como um agente de sensibilização nas práticas socioambientais, enfatizando sua relevância no contexto educacional contemporâneo. Utilizando uma metodologia bibliográfica, o estudo analisa conceitos fundamentais, histórico e práticas exemplares, permitindo uma compreensão crítica do tema. A seleção de fontes inclui livros, artigos acadêmicos e documentos institucionais, garantidos pela sua credibilidade. A coleta de dados será realizada por meio de leitura crítica e fichamento, facilitando a organização e análise das informações. Os resultados esperados incluem a identificação de tendências, convergências e divergências nas abordagens de Educomunicação e sua relação com a sustentabilidade. A pesquisa também visa destacar as limitações do campo e a importância de metodologias ativas na educação. Por fim, este trabalho contribuirá para a formação de cidadãos críticos e engajados nas questões socioambientais, promovendo um futuro mais sustentável.
A IMPORTÂNCIA DA PRESUNÇÃO DE INOCÊNCIA NO PROCESSO PENAL BRASILEIRO: O DILEMA DA DECISÃO PROFERIDA NAS ADCS 43, 44 E 54, QUE DECLAROU A CONSTITUCIONALIDADE DO ART. 283 DO CPP
Authors: Lima Régen Costa , Silva Elizelton Costa da
Published: November 2024

Este trabalho tem como objetivo analisar o impacto do princípio da presunção de inocência, previsto no artigo 5º, inciso LVII, da Constituição Federal de 1988, no âmbito do direito penal e processual penal brasileiro. Esse princípio estabelece que ninguém será considerado culpado até o trânsito em julgado de sentença penal condenatória, o que representa uma das principais garantias constitucionais no Estado Democrático de Direito.
Hourly surface nitrogen dioxide retrieval from GEMS tropospheric vertical column densities: Benefit of using time-contiguous input features for machine learning models
Authors: Gödeke Janek , Richter Andreas , Lange Kezia , Maaß Peter , Hong Hyunkee , Lee Hanlim , Park Junsung
Published: November 2024

Abstract. Launched in 2020, the Korean Geostationary Environmental Monitoring Spectrometer (GEMS) is the first geostationary satellite mission for observing trace gas concentrations in the Earth’s atmosphere. Observations are made over Asia. Geostationary orbits allow for hourly measurements, which leads to a much higher temporal resolution compared to daily measurements taken from low Earth orbits, such as by the TROPOspheric Monitoring Instrument (TROPOMI) or Ozone Monitoring Instrument (OMI). This work estimates the hourly concentration of surface NO2 from GEMS tropospheric NO2 vertical column densities (tropospheric NO2 VCDs) and additional meteorological features, which serve as inputs for Random Forests and linear regression models. With several measurements per day, not only the current observations but also those from previous hours can be used as inputs for the machine learning models. We demonstrate that using these time-contiguous inputs leads to reliable improvements regarding all considered performance measures, such as Pearson correlation or Mean Square Error. For Random Forests, the average performance gains are between 4.5 % and 7.5 %, depending on the performance measure. For linear regression models, average performance gains are between 7 % and 15 %. For performance evaluation, spatial cross validation with surface in-situ measurements is used to measure how well the trained models perform at locations where they have not received any training data. In other words, we inspect the models’ ability to generalize to unseen locations. Additionally, we investigate the influence of tropospheric NO2 VCDs on the performance. The region of our study is Korea.
Time Series approach to map areas of Agricultural Plastic Waste generation
Authors: de Souza Marlon F. , Lamparelli Rubens A. C. , Werner João P. S. , de Oliveira Murilo H. S. , Franco Telma T.
Published: November 2024

Abstract. The escalating presence of plastics in agriculture has raised concerns regarding Agricultural Plastic Waste (APW). Hitherto, a lack of comprehensive plasticulture data impedes effective waste management strategies, potentially resulting in plastic pollution and contributing to microplastic formation. APW locations and quantities are pivotal for territorial planning and the formulation of public policies on waste management and land use. Remote detection of agri-plastics has garnered increased consideration, particularly in mapping plastic-mulched farmlands (PMFs) dispersed in extensive regions. This study investigates whether the use of satellite image time series can map PMFs accurately. We assessed pixel-based classification using a 16-day composite time series of Sentinel-2 imagery (S2-16D) obtained from the Brazil Data Cube project. The Plastic-Mulched Landcover Index (PMLI) was joined into S2-16D bands because it is an index focused on PMF detection. Four classifiers (RF, MLP, L-TAE, and TCNN) were compared through agreed classification metrics. The most promising outcome showed an overall accuracy of 100% employing L-TAE but with visible noise in the map. The time series enhanced accuracy while minimizing background confusion, offering a viable solution for PMF detection. The PMF map presented herein represents an initial stride toward fostering circularity in plasticulture throughout South America.
Temporal ViT-U-Net Tandem Model: Enhancing Multi-Sensor Land Cover Classification Through Transformer-Based Utilization of Satellite Image Time Series
Authors: Heidarianbaei Mohammadreza , Kanyamahanga Hubert , Dorozynski Mareike
Published: November 2024

Abstract. Semantic segmentation is essential in the field of remote sensing because it is used for various applications such as environmental monitoring and land cover classification. Recent advancements aim to collectively classify data from diverse sensors and epochs to improve predictive accuracy. With the availability of vast Satellite Image Time Series (SITS) data, supervised deep learning methods, such as Transformer models, become viable options. This paper introduces the Temporal Vision Transformer(ViT), designed to extract features from SITS. These features, capturing the temporal patterns of land cover classes, are integrated with features derived from aerial imagery to improve land cover classification. Drawing inspiration from the success of transformers in Natural language processing (NLP), Temporal ViT concurrently extracts spatial and temporal information from SITS data using tailored positional encoding strategies. The proposed approach fosters comprehensive feature learning across both domains, facilitating seamless integration of encoded data from SITS into aerial images. Furthermore, a training strategy is proposed that supports the Temporal ViT to focus on classes with a changing appearance over the year. Extensive experiments carried out in this work indicate the enhanced classification performance of Temporal ViT compared to existing state-of-the-art techniques for multi-modal land cover classification. Our model achieves a 3.8% increase in the mean IoU compared to the network solely relying on aerial images.
XGBOOST and Multitemporal DETER Data for Deforestation Forecasting
Authors: La Rosa Laura E. Cué , Ferrari Felipe , Bezerra Francisco Gilney Silva , de Souza Rodrigo Antônio , Maretto Raian Vargas , de Aguiar Ana Paula Dutra , Vinhas Lubia , Happ Patrick Nigri , Feitosa Raul Queiroz
Published: November 2024

Abstract. This paper reports research that is part of a project to combat deforestation in the Brazilian Amazon rainforest by developing an online system designed to forecast deforestation risk over the short term, spanning 2 to 4 weeks. This online platform aims to empower stakeholders with timely data, facilitating proactive conservation and intervention strategies to safeguard the Amazon rainforest. We built a multitemporal database that compiles weekly deforestation alerts from the DETER project, forming our analysis’s backbone. Utilizing the XGBOOST regression algorithm, we have crafted a predictive model that identifies areas within the Amazon at imminent risk of more intensive deforestation. Preliminary results reveal an RMSE of 0.29 for predicting areas under deforestation risk, as validated against early alert data from 2020 to 2023. Our work advances environmental monitoring by focusing on a spatial resolution of 25 km × 25 km, providing accessible, near real-time information on deforestation risks.
Crop Yield Mapping with ARC using only Optical Remote Sensing
Authors: Lewis Philip E. , Yin Feng , Gómez-Dans Jose Luis , Weiß Thomas , Adam Elhadi
Published: November 2024

Abstract. ARC is a new method to generates time series of a full set of biophysical parameters derived from optical EO. Here, we examine relationships between this ‘full’ set and maize yield. 15 Parameters per pixel are estimated over the US corn belt using ARC, to fully describe the phenology, soil, and crop status over time for typical behaviour. ARC is tested for a new model over an area of irrigated and rain-fed winter crop in South Africa. We find that care must be taken for episodic events, and robust filtering methods should be developed for ARC, but average magnitude and timing is well-expressed. We find that a robust yield model (over time and space) can be created at the county-level for maize using only EO parameters with RMSE of 704-938 kg/ha using a non-linear model, but the results are only slightly poorer if a linear model is used. It compares well to a model that also includes weather data, showing that a model can be driven by optical EO data alone.
Evaluating the Effectiveness of ICESat-2 ATL03 Data for Georeferencing Satellite Images
Authors: Li Heyi , Qin Wei , Zhou Dan , Jing Quan , Zhang Xiao , Tao Pengjie
Published: November 2024

Abstract. ICESat-2 laser points, as a kind of public geographic data, have high ranging accuracy and have great potential in improving the geometric positioning accuracies of satellite images. This paper aims to evaluate the effectiveness of ICESat-2 ATL03 data for georeferencing satellite image. Our study combines ATL03 laser points with an image basemap processed using open-source data positioning to construct digital control photo (DCP), facilitating the rapid transformation of laser points into laser control points for image georeferencing. Through a comprehensive analysis involving comparison with traditional georeferencing methods using ground control points (GCPs), our findings indicate a significant enhancement in accuracy and efficiency in georeferencing, showcasing the potential of ICESat-2 data in improving the quality and reliability of remote sensing images. Experiments using the extracted laser points and GeoEye-1 images to construct DCP for georeferencing IKONOS images in Hobart, Australia demonstrate that the proposed method improved the horizontal accuracy from 2.33 meters to 0.97 meters and the vertical accuracy from 3.44 meters to 0.59 meters, compared to the georeferencing method without GCPs.
Multiscale assessment of land use efficiency in functional urban areas of Munich and Augsburg
Authors: Mann Deepika , Prexl Jonathan , Schmitt Michael , Sommer Felicitas
Published: November 2024

Abstract. This study aims to understand the spatio-temporal variations in land use efficiency (LUE) estimations at different scales of assessment, focusing on the per-capita built-up area within the Functional Urban Areas (FUAs) of Munich and Augsburg, Germany. The analysis is done for the time epochs 1985, 1995, 2005, 2015 and 2020. FUAs are defined as the economic area of influence in each urban area, making the study of land consumption in FUAs crucial for spatial planning and policy analysis. Land use efficiency is computed using built up surface and population data extracted from the Global Human Settlement Layer. This is done at municipal level and 100 m grid level. Furthermore, the effects of using high resolution building footprints for LUE computations are assessed. The analysis shows that urban cores and the adjacent regions are densifying with lower per capita built surface consumption while smaller urban areas utilise more per capita built surface leading to inefficent land use. It is also observed that higher resolution assessments helps in identifying varying intra-regional LUE estimates for a focused urban planning strategy development. Our study concludes that land use efficiency has generally decreased over time in the commuting zones of FUAs while the urban cores have remained efficient.
Evaluating the Spatio-Temporal Distribution of Nitrogen Dioxide, Land Surface Temperature and NDVI in Nairobi City County
Authors: Mwangi Patricia
Published: November 2024

Abstract. Cities are becoming larger and it is estimated that by the year 2050, more than 6 billion people will be living in cities. As cities expand and grow, the quality of life and conditions will also transform. An integral part of environmental studies has been statistical analysis in modelling the spatial dynamics of land use changes. The research involved the use of satellite imagery to determine yearly averaged values of LST and NDVI from Landsat 8 OLI/TIR and monthly mean values of Nitrogen Dioxide (NO2) from Sentinel 5-Precursor (Sentinel-5P) across Nairobi City County. The datasets covered the period 2019, 2020, 2021, 2022 and 2023 and were analysed in Google Earth Engine. Results indicated that the yearly mean values in NO2 and LST in 2020 reduced by 2% and 12% respectively from 2019, while the mean NDVI value significantly increased by 28% in 2020 from 2019. NO2 has a negative correlation with LST in all years and a positive correlation with NDVI. Pearson correlation with population densities in constituencies in Nairobi in 2019 and 2023 indicate a negative correlation with NDVI and a positive correlation with NO2 and LST. Constituencies that have higher population densities tend to have lower vegetation densities and higher NO2 concentrations and temperature. Vegetation therefore plays a crucial role in air quality and that climatic factors such as precipitation and temperature influence the concentration of pollutants.
Do greener childhoods mean fewer eating disorders? Using satellite imagery to uncover insights
Authors: Rivadeneyra Perla , Favaro Angela , Meneguzzo Paolo , Pirotti Francesco
Published: November 2024

Abstract. The benefits of natural environments on mental health have been documented in numerous studies. In spite of this, the underlying mechanisms by which different elements of natural environments affect mental health, and especially eating disorders, are still largely unknown. In this study, we use remote sensing time series from the Landsat missions to associate a degree of exposure to natural vs urban environment of 659 individuals with diagnosed eating disorders (ED), such as anorexia, bulimia, purging, binge (BED), who constitute our cases. We also obtain data from 39 individuals not affected by eating disorders that comprise our control group. We explore associations between growing up surrounded by areas with a higher NDVI to individuals affected by ED. A Cox regression model was used to estimate rates as relative risk ratios and then adjusted for potential confounding from other known risk factors. The results of the Cox regressions show that the relative risk of developing ED is lower for children growing up in environments with a higher NDVI. Rates did not notably change by adjustment for GDP (a proxy for socioeconomic status), elevation, CO2 and population. In conclusion, we found that growing up surrounded by greener settings may lower the risk of eating disorders by some 33%. According to our findings, ensuring access to natural environments is crucial for improving public health and creating not only more sustainable but also more livable cities.
Assessing climatic change impacts on mangrove structural dynamics on the northern coasts of the Persian Gulf
Authors: Shirmohammadi Mahdieh , Mafi-Gholami Davood , Pirasteh Saied , Youssefi Fahimeh , Shen Jie , Li Weilian , Li Jonathan
Published: November 2024

Abstract. Monitoring long-term trends in structural changes within mangrove ecosystems is essential for understanding their response to climate change and devising effective adaptation strategies in coastal regions. This study examines changes in mangrove patchiness within the Hara Biosphere Reserve (HBR) along the northern coasts of the Persian Gulf (PG) over a 31-year period (1986-2017), focusing on variations in rainfall patterns and drought occurrences. Employing a 35-year time series of monthly Standardized Precipitation Index (SPI) values alongside satellite imagery analysis, trends in both the number of patches (NP) and the Largest Patch Index (LPI) were assessed at the mangrove stand level. The analysis reveals a significant correlation between structural changes in mangroves and drought events. Pre-1998, characterized by wetter conditions, witnessed a decrease in both NP and LPI, indicating patch expansion and habitat extension. Conversely, post-1998, during drought periods, both indices increased, indicating habitat degradation due to heightened drought intensity. Pre-1998 structural changes in the HBR signify habitat expansion, with increased patch extent and core areas reflecting enhanced structural integrity. However, post-1998, a concerning trend of habitat degradation emerged, with increased NP and LPI attributed to intensified droughts. These findings highlight a transitional period marked by favourable conditions for mangrove growth followed by habitat degradation linked to increased drought intensity. This underscores the vulnerability of mangrove ecosystems to climate change impacts, particularly exacerbated droughts, necessitating urgent efforts for conservation and management to preserve biodiversity and ecosystem services in coastal regions.
TopoSense: agent driven topological graph extraction from remote sensing image
Authors: Zhang Mi , Yang Bingnan , Gong Jianya , Hu Xiangyun
Published: November 2024

Abstract. Automatic topological graph extraction is critical for intelligent remote sensing image interpretation and cartographic representation. However, existing approaches neither adopt segmentation-based post-processing nor directly predict the graph, thereby suffering from limited scalability and poor adaptability to complex spatial structures. To address these issues, we introduce TopoSense, an innovative framework for extracting topological graphs from remote sensing images through an agent-driven approach. By employing a novel combination of reinforcement learning and neural network architectures, TopoSense autonomously navigates through pixel-level data, efficiently constructing topological representations. It not only enhances the accuracy of spatial feature detection, but also significantly reduces processing time. Experiments on the TOP-BOUNDARY and REALSCENE demonstrate its superiority in capturing intricate spatial relationships compared to traditional methods.
Terrain analysis in forested areas: consequences of using DSM instead of DTM
Authors: Caldeira Carlos Rodrigo Tanajura , El Hage Mhamad , Polidori Laurent
Published: November 2024

Abstract. Relief mapping through dense tropical forest is a challenge, which can be met by processing radar images. Various global digital elevation models (DEMs) are available, either free or paid, the most widely used methods for producing them at global scale being photogrammetry and short wavelength radar interferometry. However, the resulting DEMs do not directly represent the ground surface but rather the canopy or something in between. Since most users need terrain models for a variety of applications in geoscience, water management etc. but use such canopy models for lack of anything better, it was relevant to assess the consequences of this inappropriate but unavoidable choice. This paper presents a study carried out in the Brazilian Amazon, where an airborne P-band radar interferometric DEM was used as a reference based on its accuracy assessed in previous studies. A well-established DEM (SRTM) and newer ones (Copernicus and Fabdem), as well as a DEM obtained from aerial X-bands radar data, were compared to the reference according to different criteria related to elevation (accuracy and a typical application, i.e., dam filling simulation) and to slope at different scales (accuracy and a typical application, i.e., terrain classification). The results highlighted the risks of using short wavelengths to represent the terrain and emphasized the importance of slope in different resolution scales.
TRUST-DART: Land Surfaces Temperature and Emissivity Nonlinear Mapping from Nonisothermal Mixed Pixels of Satellite Images with the DART 3D Radiative Transfer Model
Authors: Zhen Zhijun , León-Tavares Jonathan , Kallel Abdelaziz , Wang Yingjie , Regaieg Omar , Chavanon Eric , Lauret Nicolas , Guilleux Jordan , Hedman Johan , Yin Tiangang , Demoulin Romain , Gastellu-Etchegorry Jean-Philippe
Published: November 2024

Abstract. Coarse spatial resolution of Thermal Infrared (TIR) satellites hampers measuring the temperature and emissivity of scene elements from space that improves our understanding of land surfaces' thermal behavior. The stringent conditions of current TIR unmixing methods hinder the production of extensive component temperature and emissivity products. To address this, we designed a gradient-based multi-pixel physical model, TRUST-DART, to derive the temperature and emissivity of urban features from non-isothermal mixed pixels of satellite images using the DART 3D radiative transfer model. Unlike traditional TIR unmixing methods, TRUSTDART is not constrained by issues related to spatial, spectral, temporal resolution, angular, scene, field measurement requirements, or manual operations. Its inputs include an at-surface radiance image, downwelling sky irradiance, a 3D urban mock-up with feature information, and DART input parameters such as spatial resolution. It generates maps of emissivity and temperature per urban feature. Its accuracy is validated for two vegetation and urban scenes and two types of images (DART simulated pseudo satellite and ASTER observed images). The accuracy of the TRUST-DART depends heavily on the fraction of components. TRUST-DART proves robust for high-fraction components. However, its accuracy decreases with decreasing fractions. TRUST-DART is distributed with DART and is available for education and research via Toulouse III University (https://dart.omp.eu).
Optimum Combination of Spectral Variables for Crop Mapping in Heterogeneous Landscapes based on Sentinel-2 Time Series and Machine Learning
Authors: de Oliveira Júnior José Galdino , Esquerdo Júlio César Dalla Mora , Lamparelli Rubens Augusto Camargo
Published: November 2024

Abstract. This article aimed to determine a workflow for more efficient large-scale crop mapping using a time series of images from the Sentinel-2 Satellite, statistical methods of attribute selection, and machine learning. The proposed methodology explores the best possible combination of spectral variables related to vegetation (16 vegetation indices in the RGB, NIR, SWIR, and Red Edge regions) to characterize different spectro-temporal profiles of Land Use and Land Cover (LULC) in spatially heterogeneous landscapes. First, we applied a data dimensionality reduction analysis using the PCA (Principal Component Analysis) method. Subsequently, the variables that showed the highest statistical correlation between each other were used in the spectro-temporal classification process, using the Random Forest, TempCNN, and LightTAE algorithms, following three different strategies: C1 (ALL), C2 (BE + IV (Red Edge)) and C3 (BE + IV (without Red Edge)), where ALL – All variables; BE – Spectral Bands; IV – Vegetation Indices. Given the results found, the C2 classification scenario (with bands B3, B4, B5, B6, B7, B8, and B8A and the NDRE1, RESI, and MSR indexes) demonstrated the best LULC classification accuracy at the crop pattern level, compared to the other scenarios, with average values of 0.91, 0.88, 0.91, 0.89, and 0.89 (Global Accuracy, Producer Accuracy, User Accuracy, Kappa index, and F1-Score, respectively, for the TempCNN model), the which emphasized the importance of both qualitative and quantitative variability of sampling data and variables based on the Red Edge region for improving LULC classification processes in large-scale heterogeneous landscapes.
Evaluating rainfall erosivity index from CHIRPS and INMET data in southeast region of Goiás (Brazil)
Authors: de Souza Silva Izaias , Silva Guilherme Cardoso da , Nascimento Diego Tarley Ferreira
Published: November 2024

Abstract. Soil erosion is a form of land degradation commonly observed in different regions of the world, especially in tropical regions. In Brazil, soil erosion caused by rainwater (pluvial erosion) is the most common and worrying form of erosion, causing various environmental, economic and social damage. The main aim of this work was to evaluate the Erosivity Index (EI) relationships based on CHIRPS and INMET data in the municipality of Catalão-GO, that is located in one of the world's largest agricultural frontiers, the Brazilian Cerrado. The results found indicated that the CHIRPS data it is an alternative for calculating EI in the context of municipality of Catalão, southeast region of Goiás state, from a previous stage for statistical validation.
Abordaje endoscópico transpterigoideo para papiloma invertido del seno esfenoidal: Informe de un caso
Authors: Serrano Candelaria , Redivo Micaela , Minghera María del Pilar , Ruggeri Carlos S.
Published: November 2024

Se describe el caso clínico de una mujer que tuvo un papiloma invertido en el seno esfenoidal.El esfenoides fue muy neumatizado y el papiloma invertido se extendió a un receso lateral del seno, más allá de la arteria carótida interna paraclival, que fue procidente.Se hizo un abordaje endonasal unilateral, combinando una esfenoidotomía bilateral con septectomía posterior con un abordaje transpterigoideo, para exponer el receso lateral neumatizado del esfenoides localizado detrás de la pared posterior del maxilar.El papiloma invertido fue resecado en forma completa, sin evidencia de recurrencias.
O SONHO DOS OMBROS DE MARFIM: MARCO AURÉLIO FRENTE À MISSÃO DO GOVERNAR ROMA
Authors: Dinucci Aldo
Published: November 2024

Analiso duas versões que nos chegaram do sonho de Marco Aurélio antes de ser indicado como sucessor de Antonino Pio, sonho no qual Marco tem ombros de marfim. Examino o sonho metaforicamente e passo a um sumário da vida de Marco, de sua infância ao império, terminando por compreender o sonho como uma prescrição onírica sobre qual atitude seria favorável a Marco no comando de Roma, bem como uma antecipação sobre sua capacidade de suportar grandes desafios durante o seu governo.