Chemical analysis of snus products from the United States and northern Europe. by Tameka S Lawler, Stephen B Stanfill, Hang T Tran, Grace E Lee, Patrick X Chen, J Brett Kimbrell, Joseph G Lisko, Carolina Fernandez, Samuel P Caudill, B Rey deCastro, Clifford H Watson

“…Reported means, standard errors, and differences are least-square (LS) estimates from bootstrapped mixed effects models, which accounted for correlation among repeated measurements. …”
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Modelling and Using Spatial Effects in Nationwide Historical Data Improve Genomic Prediction of Rice Heading Date in Japan by Shoji Taniguchi, Takeshi Hayashi, Hiroshi Nakagawa, Kei Matsushita, Hiromi Kajiya-Kanegae, Jun-Ichi Yonemaru, Akitoshi Goto

“…The spatial effects were heterogeneous and regional patterns were detected. These findings imply that spatial effects are important not only for improving prediction performance but also for dissecting the model itself to identify the factors contributing to model improvement.…”
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Improved somatic mutagenesis in zebrafish using transcription activator-like effector nucleases (TALENs). by Finola E Moore, Deepak Reyon, Jeffry D Sander, Sarah A Martinez, Jessica S Blackburn, Cyd Khayter, Cherie L Ramirez, J Keith Joung, David M Langenau

“…These designer nucleases bind to and cleave DNA at particular target sites, inducing error-prone repair that can result in insertion or deletion mutations. …”
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Real-Time System Prediction for Heart Rate Using Deep Learning and Stream Processing Platforms by Abdullah Alharbi, Wael Alosaimi, Radhya Sahal, Hager Saleh

“…The offline phase targets developing the model using different forecasting techniques to find the lowest root mean square error. The heart rate time-series dataset is extracted from Medical Information Mart for Intensive Care (MIMIC-II). …”
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A robust and adaptive framework for interaction testing in quantitative traits between multiple genetic loci and exposure variables. by Julian Hecker, Dmitry Prokopenko, Matthew Moll, Sanghun Lee, Wonji Kim, Dandi Qiao, Kirsten Voorhies, Woori Kim, Stijn Vansteelandt, Brian D Hobbs, Michael H Cho, Edwin K Silverman, Sharon M Lutz, Dawn L DeMeo, Scott T Weiss, Christoph Lange

“…Using extensive simulation studies, we demonstrate that RITSS controls the type 1 error rate in a wide range of scenarios, and we show how the screening strategy influences statistical power. …”
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Distribution and risk factors for childhood visual deficiency in Morocco: Case – control study by Loulidi Soukaina, Loukid Mohamed, Boussaa Samia

“…Results: The results showed the predominance of cataracts (43 %), followed by refractive error (26.4 %) and glaucoma (23.6 %). In youngsters, the primary cause of vision impairment is 63.2 % heredity. …”
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AI-Driven Global Disaster Intelligence from News Media by Fahim Sufi, Musleh Alsulami

“…The ARIMA (2, 1, 2) model achieved a mean squared error (MSE) of 823,761, demonstrating high predictive accuracy. …”
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Near-infrared hyperspectral imaging and robust statistics for in vivo non-melanoma skin cancer and actinic keratosis characterisation. by Lloyd A Courtenay, Innes Barbero-García, Saray Martínez-Lastras, Susana Del Pozo, Miriam Corral de la Calle, Alonso Garrido, Diego Guerrero-Sevilla, David Hernandez-Lopez, Diego González-Aguilera

“…The analysis revealed that the spectral regions between 900.66-1085.38 nm, 1109.06-1208.53 nm, 1236.95-1322.21 nm, and 1383.79-1454.83 nm showed the highest differences in this regard, with <1% probability of these observations being a Type I statistical error. Our findings demonstrate that hyperspectral imagery in the near-infrared spectrum is a valuable tool for analyzing, diagnosing, and evaluating non-melanoma skin lesions, contributing significantly to skin cancer research.…”
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Improving the accuracy of fatty liver index to reflect liver fat content with predictive regression modelling. by Hykoush A Asaturyan, Nicolas Basty, Marjola Thanaj, Brandon Whitcher, E Louise Thomas, Jimmy D Bell

“…The results obtained for FLI+ outperform the original FLI by delivering a lower mean absolute error by approximately 47%, a lower standard deviation by approximately 20%, and an increased adjusted R2 statistic by approximately 49%, reflecting a more accurate representation of liver fat content.…”
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Tracking Poultry Drinking Behavior and Floor Eggs in Cage-Free Houses with Innovative Depth Anything Model by Xiao Yang, Guoyu Lu, Jinchang Zhang, Bidur Paneru, Anjan Dhungana, Samin Dahal, Ramesh Bahadur Bist, Lilong Chai

“…Additionally, we evaluate DAM’s accuracy in detecting disparity within cage-free facilities. The accuracy of the model in estimating physical depth was assessed using root mean square error (RMSE) between predicted and actual perch frame depths, yielding an RMSE of 0.11 m, demonstrating high precision. …”
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Fundus screening for peripheral retinal lesions in myopic patients before refractive surgery using ultra-wide field scanning laser ophthalmoscopy by Amr M Elhady, Osama R Elnaggar

“…The mean spherical equivalent of the refractive error was −4.83±1.38 D (range=−1.50 to −7.75 D). …”
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Application of Deep Learning to the Classification of Stokes Profiles: From the Quiet Sun to Sunspots by Ryan J. Campbell, M. Mathioudakis, Carlos Quintero Noda, P. H. Keys, D. Orozco Suárez

“…In the sunspot simulation, the 630.25 nm line produces “double” profiles in the penumbra, likely a manifestation of magneto-optical effects in horizontal fields; these are rarer in the 1564.85 nm line. We find the 1564.85 nm line detects more reverse polarity magnetic fields in the penumbra, in contradiction to observations. …”
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The impact of study size on meta-analyses: examination of underpowered studies in Cochrane reviews. by Rebecca M Turner, Sheila M Bird, Julian P T Higgins

“…<h4>Background</h4>Most meta-analyses include data from one or more small studies that, individually, do not have power to detect an intervention effect. The relative influence of adequately powered and underpowered studies in published meta-analyses has not previously been explored. …”
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A Case of Posterior Communicating Artery Aneurysm Combined With an Atypical Origin of the Ipsilateral Ophthalmic Artery by D. V. Litvinenko, A. E. Gerasyuta, I. N. Sever, E. I. Zyablova, T. N. Trofimova, V. V. Tkachev

“…The patient was discharged in satisfactory condition with a stable neurological status.Conclusions: The combination of abnormal anatomy of arteries at the base of the brain and cerebral aneurysms increases the risk of tactical errors and perioperative complications. Each such case requires a careful comparison of the clinical, imaging, and intraoperative findings. …”
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Prospects for Gamma-Ray Emission from Magnetar Regions in CTAO Observations by M. F. Sousa, R. Costa Jr., Jaziel G. Coelho, R. C. Dos Anjos

“…Our findings indicate that CTAO will detect gamma-ray emissions from these three magnetar regions with significantly reduced emission flux errors compared to current instruments. …”
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Intracellular spatial transcriptomic analysis toolkit (InSTAnT) by Anurendra Kumar, Alex W. Schrader, Bhavay Aggarwal, Ali Ebrahimpour Boroojeny, Marisa Asadian, JuYeon Lee, You Jin Song, Sihai Dave Zhao, Hee-Sun Han, Saurabh Sinha

“…Abstract Imaging-based spatial transcriptomics technologies such as Multiplexed error-robust fluorescence in situ hybridization (MERFISH) can capture cellular processes in unparalleled detail. …”
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A hybrid compound scaling hypergraph neural network for robust cervical cancer subtype classification using whole slide cytology images by Pooja Govindaraj, Sasikaladevi Natarajan, Pradeepa Sampath, Akilesh Thimma Suresh, Rengarajan Amirtharajan

“…Manual cytological examination is time-consuming, error-prone and subject to inter-observer variability. …”
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Correlation Between Emergency Department Crowding and Adverse Occurrences in an Academic Hospital: A Retrospective Cohort Study by Alassaf W, Albrahim R, Abukhaled JK, Aldhaif M, Mohammed MA, Al Baiz A, Aljahany M

“…Our findings provide evidence of increased errors in medication, care coordination, and medical care due to emergency department (ED) crowding. …”
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Cephalic measures in normal pre-school children 3 to 7-years of age Medidas cranianas em crianças pré-escolares normais de 3 a 7 anos by A. J. Diament, F. W. Rodrigues

“…The statistical analysis consisted in determining means and standard errors for each measure. For the new cephalic index it was shown through the Kruskal-Wallis test that there were no significant difference between age and sex. …”
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Psychometric evaluation of the Persian version of the adult chronic kidney disease self-management instrument in the Iranian population by Simin Alasvand, Mehrnaz Ahmadi, Hamid Sharif-Nia, Marziyeh Asadizaker

“…The absolute reliability, as determined by Standard Error of Measurement results, was 3.16. Additionally, the Minimum Detectable Change was estimated to be 8.75. …”
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