Effect of Poverty and Child Prostitution in Kamuganguzi Sub¬-county Kabale District. by Katusiime, Marvellous

“…Based on the results from the study, 100% of the respondents agreed that the role poverty plays in child prostitution in the Kamuganguzi sub-county includes Poverty is the primary driving force behind women becoming prostitutes, limited and extremely scarce opportunities for women Leads to prostitution, populations experiencing extreme poverty leads to prostitution, families suffering from poverty are purposely targeted by traffickers as a means of exploitation resulting to poverty, some parents sell their children. …”
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Multiscale wildfire and smoke detection in complex drone forest environments based on YOLOv8 by Wenyu Zhu, Shanwei Niu, Jixiang Yue, Yangli Zhou

“…Abstract Global climate change has triggered frequent extreme weather events, leading to a significant increase in the frequency and intensity of forest fires. …”
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Transformasi Kota Cerdas dalam Mitigasi Banjir: Pemodelan Curah Hujan DKI Jakarta dengan Pendekatan Spatial Vector Autoregressive (SpVAR) dan Pemetaan Bobot Queen Contiguity by Rinda Lolita Melanwati, Eni Sumarminingsih, Henny Pramoedyo

“…However, time series data often have spatial dimensions. Therefore, a Spatial Vector Autoregressive (SpVAR) model has been developed considering both spatial and temporal dimensions. …”
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The Flowering Characters Variation Among Floral Variants and Landraces Along Geographical Gradients in Gunung Sewu by Yeni Widyana Nurcahyani Cahyaningrum, Sapto Indrioko, Eny Faridah, Atus Syahbudin

“…Sandalwood flowered twice a year in all of land-races and variants, however, the onset and duration varied. …”
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Elliptical Fourier analysis of molar outlines in Late Pliocene Parapapio whitei from Makapansgat Limeworks, South Africa by Alexander C. Kim, Frank L’Engle Williams

“…Conclusion: MP 221 and MP 223 likely belong to a single species with no clear affinity to any of the extant taxa examined. …”
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Tunnel squeezing prediction based on partially missing dataset and optimized machine learning models by Peng Guan, Guangzhao Ou, Feng Liang, Weibang Luo, Qingyong Wang, Chengyuan Pei, Xuan Che

“…The parameters of these 6 ML models were optimized using the Whale Optimization Algorithm (WOA) in conjunction with five-fold cross-validation. A total of 305 tunnel squeezing sample data were collected to train and test the models. …”
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Impact of Cyclonic Storm “Sitrang” over the Bay of Bengal on Heavy Rain and Snow in Eastern Tibet by Xiaotao Zhao, Lunzhu Danzeng, Qu Chi, Xulin Ma, Yuting Tan, Luozhu Duodian, Ranzhen Danzeng

“…Rainstorms and blizzards are common extreme weather events occurring in the eastern Tibet region. …”
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Interpretable Machine Learning Model for Predicting Postpartum Depression: Retrospective Study by Ren Zhang, Yi Liu, Zhiwei Zhang, Rui Luo, Bin Lv

“… Abstract BackgroundPostpartum depression (PPD) is a prevalent mental health issue with significant impacts on mothers and families. …”
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Exploring Early Learning Challenges in Children Utilizing Statistical and Explainable Machine Learning by Mithila Akter Mim, M. R. Khatun, Muhammad Minoar Hossain, Wahidur Rahman, Arslan Munir

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An ultrasonic-AI hybrid approach for predicting void defects in concrete-filled steel tubes via enhanced XGBoost with Bayesian optimization by Shuai Wan, Shipan Li, Zheng Chen, Yunchao Tang

“…Based on 3600 ultrasonic measurement samples, an Extreme Gradient Boosting (XGBoost) model was enhanced through oversampling and hyperparameter optimization via Bayesian optimization (BO-XGBoost). …”
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Airport Arrival Flow Prediction considering Meteorological Factors Based on Deep-Learning Methods by Zhao Yang, Yifan Wang, Jie Li, Liming Liu, Jiyang Ma, Yi Zhong

“…This study presents a combined Long Short-Term Memory and Extreme Gradient Boosting (LSTM-XGBoost) method for flight arrival flow prediction at the airport. …”
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Exploration and comparison of the effectiveness of swarm intelligence algorithm in early identification of cardiovascular disease by Tiantian Bai, Mengru Xu, Taotao Zhang, Xianjie Jia, Fuzhi Wang, Xiuling Jiang, Xing Wei

“…Subsequently, the selected feature subsets were integrated into ten classification models, and a comprehensive weighted evaluation was performed based on the accuracy, precision, recall, F1 score, and AUC value of the model to determine the optimal model configuration. …”
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Effects of COVID-19 Emergency Response Levels on Air Quality in the Guangdong-Hong Kong-Macao Greater Bay Area, China by Jie Li, Haotian Yang, Shuping Zha, Nu Yu, Xingang Liu, Ruofei Sun

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Features of the anatomical structure of leaves depending on the high-altitude growth of apricot in Dagestan by D. M. Anatov, Z. M. Asadulaev, Z. R. Ramazanova, R. M. Osmanov

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First-Principles-Based Structural and Mechanical Properties of Al₃Ni Under High Pressure by Chuncai Xiao, Baiyuan Yang, Zhangli Lai, Zhiquan Chen, Huaiyang Yang, Hui Wang, Yunzhi Zhou, Xianshi Zeng

“…This current research systematically elucidated the stability of Al₃Ni under high-pressure conditions and the law of the transformation of it mechanical behavior, providing a theoretical foundation for its application under extreme circumstances.…”
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Evaluating the Accuracy of the ERA5 Model in Predicting Wind Speeds Across Coastal and Offshore Regions by Mohamad Alkhalidi, Abdullah Al-Dabbous, Shoug Al-Dabbous, Dalal Alzaid

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An optimized data analytics pipeline for improving healthcare diagnosis using ensemble learning by Lomat Haider Chowdhury, Shaira Tabassum, Swakkhar Shatabda, Ashir Ahmed

“…Outliers in a medical dataset represent extreme cases and rare conditions, or they may even be generated due to data entry errors. …”
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L’autre scène dans The Three Birds de Joanna Laurens (2000) : enjeux dramatiques de la réécriture d’un mythe by Solange Ayache

“…Mirroring and enacting the characters’ evolution from innocence to barbarism, language is distorted and altered to an extreme through a creative process involving word coinage (i.e. barbarisms), syntactic irregularities, and ‘babelisation,’ thus bringing out and performing the violence of the myth. …”
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Impacts of climate change on the suitable habitat of Angelica sinensis and analysis of its drivers in China by Shaoyang Xi, Xudong Guo, Xiaohui Ma, Ling Jin

“…Diels (A. sinensis). Despite its importance in traditional herbal medicine, there is limited research on adaptation of A. sinensis to climate challenges. …”
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Exploitation of the genetic potential of <i>Thinopyrum</i> and <i>Agropyron</i> genera to protect wheat from diseases and environmental stresses by L. Ya. Plotnikova, V. V. Knaub

“…The tertiary gene pool, including Thinopyrum spp., is a valuable resource for increasing genetic diversity and wheat resistance to fungal diseases and abiotic stresses. …”
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