El Nino Southern Oscillation and Indian Ocean Dipole teleconnection to the wetness and drought trend of Bhutan using time series (1983-2022) PERSIANN rainfall data by Dibyendu Dutta, Manoj Kumar Nanda, Ramprasad Kundu, Saurabh Tewari, Pragyan Jain, Bidyut Kumar Bhadra, Tanmay Khemka, Ankur Naik, Angshu Chakraverty

“…The majority of the districts witnessed higher levels of wetness in 1987, 1988, 2012, 2015, and 2017, while severe to extreme droughts were found over varying time periods in 1984–86, 1990–93, 1996, 1999, and 2019. …”
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Stress can be detected during emotion-evoking smartphone use: a pilot study using machine learning by Lydia Helene Rupp, Akash Kumar, Misha Sadeghi, Lena Schindler-Gmelch, Marie Keinert, Bjoern M. Eskofier, Bjoern M. Eskofier, Matthias Berking

“…XGBoost showed to be more reliable for prediction, with lower error for both training and test data.DiscussionThe findings provide further evidence that non-invasive video recordings can complement standard objective and subjective markers of stress.…”
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Clinical Features of Juvenile Open-angle Glaucoma by A. V. Malyshev, A. S. Apostolova, A. A. Sergienko, A. F. Teshev, G. Yu. Karapetov, M. K. Ashhamahova, B. N. Hatsukova

“…When comparing the level of IOP, no differences were found between JOAG and healthy eyes. The DA ratio and IR parameters did not differ between JOAG and healthy eyes, SP-A1 was higher in JOAG compared to a healthy eye, but this difference was not reliable p = 0.384. …”
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Stratified allocation method for water injection based on machine learning: A case study of the Bohai A oil and gas field by Changlong Liu, Pingli Liu, Qiang Wang, Lu Zhang, Zechao Huang, Yuande Xu, Shaojiu Jiang, Le Zhang, Changxiao Cao

“…First, according to the basic parameters of block B in the Bohai A oil and gas field, a reservoir numerical simulation model was established, and historical fitting was carried out. The calculation found that the natural gas production of the A oil field would increase over time, although its oil production showed a decreasing trend. …”
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A framework for modelling whole-lung and regional transfer factor of the lung for carbon monoxide using hyperpolarised xenon-129 lung magnetic resonance imaging by Jemima H. Pilgrim-Morris, Laurie J. Smith, Helen Marshall, Bilal A. Tahir, Guilhem J. Collier, Neil J. Stewart, Jim M. Wild

“…Results Coefficients of the physiological model were found to differ from previously reported values. …”
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A Novel Forest Dynamic Growth Visualization Method by Incorporating Spatial Structural Parameters Based on Convolutional Neural Network by Linlong Wang, Huaiqing Zhang, Kexin Lei, Tingdong Yang, Jing Zhang, Zeyu Cui, Rurao Fu, Hongyan Yu, Baowei Zhao, Xianyin Wang

“…The results show that: first, spatial structural parameters C and U have a certain contribution to the forest growth, and C and U can explain 21.5&#x0025;, 15.2&#x0025;, and 9.3&#x0025; of the variance in DBH, H, and CW growth models, respectively; second, CNN model outperformed machine learning algorithms SVR, MARS, Cubist, RF, and XGBoost in terms of prediction performance; third, based on FDGVM-CNN-SSP, we simulated Chinese fir plantations at individual tree level and stand level from 2018 to 2022 and found that DBH and H&#x0027;s fitting performance in measured and predicted data was highly consistent with <italic>R</italic>² and root-mean-square error (RMSE) of 86.8&#x0025;, 2.06 cm in DBH and 79.2&#x0025;, 1.11 m in H, but CW&#x0027;s <italic>R</italic>² and RMSE of 72.2&#x0025;, 0.65 m caused crowding (C) inconsistency.…”
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Human-Annotated Label Noise and Their Impact on ConvNets for Remote Sensing Image Scene Classification by Longkang Peng, Tao Wei, Xuehong Chen, Xiaobei Chen, Rui Sun, Luoma Wan, Jin Chen, Xiaolin Zhu

“…To fill this research gap, this article, for the first time, collected real-world labels from 32 participants and explored how their annotated label noise affects three representative ConvNets (VGG16, GoogleNet, and ResNet-50) for remote sensing image scene classification. We found that 1) human-annotated label noise exhibits significant class and instance dependence; 2) an additional 1&#x0025; of human-annotated label noise in training data leads to a 0.5&#x0025; reduction in the overall accuracy of ConvNets classification; and 3) the error pattern of ConvNet predictions was strongly correlated with that of participant&#x0027;s labels. …”
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Differences in abundance of Thaumatotibia leucotreta and its natural enemies between organic and conventionally farmed citrus ecosystems by Luke Cousins, Mellissa Peyper, Tamryn Marsberg, Sean Moore, Martin Hill

“…No significant difference was found in spider abundance between organic and conventional citrus orchards. …”
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Integrated soil moisture fusion for enhanced agricultural drought monitoring in China by Aifeng Lv, Xianglei Yang, Wenxiang Zhang, Yan Han

“…Spatially, 58.25 % of China's territory experienced a decrease in drought intensity, especially in the Qinghai-Tibetan Plateau, North China Plain, and southern regions, while certain areas in northern and southwestern China recorded an intensification of drought conditions. (4) The correlation between meteorological drought and agricultural drought was found to be stronger during the summer (R = 0.68) and autumn (R = 0.63) compared to winter and spring. …”
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Validity and reliability of the Manchester Oxford Foot Questionnaire (MOXFQ) in one-year postoperative ankle fracture patients—a validation study by Michael Quan Nguyen, Marjolein Memelink Iversen, Knut Harboe, Ingvild Dalen, Aksel Paulsen

“…The PROM has three domains: (1) Pain; (2) Walking/Standing; and (3) Social Interaction. One study found sufficient content validity for the Pain and Walking/Standing domains when used in the evaluation of ankle fracture patients. …”
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Structural validity of the Brazilian version of the quality care questionnaire-palliative care for use in individuals with diabetes mellitus eligible for palliative care by Abraão Albino Mendes-Júnior, Aldair Darlan Santos-de-Araújo, Leonel Richard de Oliveira Silva Santos, Lorena Lúcia Costa Ladeira, Meire Coelho Ferreira, Louise Aline Romão Godim, Mariana Campos Maia, Marinete Rodrigues de Farias Diniz, Almir Vieira Dibai-Filho, Daniela Bassi-Dibai

“…Results Of the 100 participants included in the study, 66% were female, 54% were single, with a median age of 64 years, 44% were overweight (44%), 77% were on polypharmacy, and 70% were physically inactive. We found that one domain is the most appropriate for use of the QCQ-PC in individuals with DM eligible for palliative care, according to the parallel analysis implemented in the EFA. …”
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Assessing the measurement properties of PROMIS Computer Adaptive Tests, short forms and legacy patient reported outcome measures in patients undergoing total hip arthroplasty by C. Braaksma, N. Wolterbeek, M. R. Veen, R. W. Poolman, Y. Pronk, A. D. Klaassen, R. W. J. G. Ostelo, C. B. Terwee

“…The construct validity of PROMIS CAT and short forms were found sufficient, except for the PROMIS-PI short form. …”
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Safe Use of Butorphanol–Azaperone–Medetomidine to Immobilize Free‐Ranging White‐tailed Deer by Joseph R. McDermott, Wendy Leuenberger, Caleb A. Haymes, Garrett B. Clevinger, Jonathan K. Trudeau, Tim C. Carter, John T. Hast, Gabriel S. W. Jenkins, Will E. Bowling, John J. Cox

“…First signs of induction were observed on average at 4.4 ± 0.2 (standard error) minutes post–intramuscular administration, and deer reached lateral recumbency at 8.6 ± 0.4 minutes. …”
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Process-based modeling of solar-induced chlorophyll fluorescence with VISIT-SIF version 1.0 by T. Miyauchi, T. Miyauchi, M. Saito, H. M. Noda, A. Ito, T. Kato, T. Matsunaga

“…We also found that the mean seasonal variability in the simulated SIFs was mostly consistent with the GOSAT SIF retrievals at the subcontinental scale. …”
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Bangladeshi Vehicle Classification and Detection Using Deep Convolutional Neural Networks With Transfer Learning by Farid, Proshanta Kumer Das, Monirul Islam, Ebna Sina

“…The proposed system can detect and classify low-speed and high-speed vehicles with an average 93% detection rate and 98% accuracy, while facing challenges that include issues with image annotation tools like poor label visibility, lack of error checking, and limited guidance, as well as difficulties in setting up the NVIDIA Jetson Nano embedded device for efficient model deployment.…”
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Clinical characteristics and prediction model of re-positive nucleic acid tests among Omicron infections by machine learning: a real-world study of 35,488 cases by Ying Cao, Tianhua Yao, Ronghao Li, Liang Tan, Zhixiong Zhang, Junsheng Qi, Rui Zhang, Yazhou Wu, Zhiqiang Chen, Changlin Yin

“…Interpretation Higher TR risk was found in infected cases who were underage or with underlying diseases; vaccine brand and inoculation status were not significantly associated with TR. …”
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Comparative validity assessment of three android step counter applications; a semi-structured laboratory-based study by Uchechukwu Martha Chukwuemeka, Arinze Damian Nnalue, Sochima Johnmark Obiekwe, Fatai Adesina Maruf, Anthony Chinedu Anakor, Monday Omoniyi Moses, Chinedum Amaechi, Uchenna Prosper Okonkwo, Ifeoma Adaigwe Amaechi

“…The Spearman’s correlation was used for a relationship, while Mean Absolute Percentage Error (MAPE) and Bland plot were for validity testing at an Alpha level of 0.05. …”
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Addressing ORPD problem in a standard IEEE power network accompanied with RESs and FACTs appliances by COMMKE under volatile load scenarios by Susanta Dutta, Tushnik Sarkar, Chandan Paul, Sabbir Reza Tarafdar, Provas Kumar Roy, Ghanshyam G. Tejani, Seyed Jalaleddin Mousavirad

“…To make this comparison more lucid, statistical records are produced, box plots are presented, error bar plots are used and moreover one way ANOVA test has been performed over the results generated through the different optimization approaches.…”
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Predicting biomass transportation costs: A machine learning approach for enhanced biofuel competitiveness by Ali Omidkar, Razieh Es’haghian, Hua Song

“…Conversely, the impact of distance on transportation costs was found to be minimal. In the more robust random forest model, vehicle type, distance, and load factor were identified as the most significant predictors, contributing 31 %, 25 %, and 12 % to the overall cost variation, respectively. …”
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The genetic structure and diversity of smallholder dairy cattle in Rwanda by Oluyinka Opoola, Felicien Shumbusho, Innocent Rwamuhizi, Isidore Houaga, David Harvey, David Hambrook, Kellie Watson, Mizeck G. G. Chagunda, Raphael Mrode, Appolinaire Djikeng

“…Asides well-established genes in cattle, we found evidence for a variety of novel and less-known genes under selection to be associated with fertility, milk production, innate immunity and environmental adaptation. …”
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