Monte Carlo-Based Strategy for Assessing the Impact of EEG Data Uncertainty on Confidence in Convolutional Neural Network Classification by Pierre Sedi Nzakuna, Vincenzo Gallo, Vincenzo Paciello, Aime Lay-Ekuakille, Angelo Kuti Lusala

“…We introduce robust evaluation metrics, including the proportion of area under the curve (AUC) of probability density functions (PDFs) <inline-formula> <tex-math notation="LaTeX">$\geq 70$ </tex-math></inline-formula>% accuracy, overlap coefficients, and percentile-based thresholding, which provide a more comprehensive assessment of model performance, capturing not only accuracy but also confidence and ambiguity in predictions. …”
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Predicting Wastewater Characteristics Using Artificial Neural Network and Machine Learning Methods for Enhanced Operation of Oxidation Ditch by Igor Gulshin, Nikolay Makisha

“…This study investigates the operational efficiency of the lab-scale oxidation ditch (OD) functioning in simultaneous nitrification and denitrification modes, focusing on forecasting biochemical oxygen demand (BOD₅) concentrations over a five-day horizon. …”
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Comparative Pacing Profile and Chronometric Performance in Elite Swimmers with Intellectual Impairments and Able-Bodied Athletes by Luca Puce, Piotr Zmijewsk, Nicola Luigi Bragazzi, Carlo Trompetto

“…Performance metrics were assessed using 50 m split times, and within-group variability was evaluated through coefficients of variation. …”
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Influences of Gait Training with Knee–Ankle–Foot Orthosis on Gait Ability and Independence in Severe Hemiplegia and Pusher Behavior with Unilateral Spatial Neglect Following Stroke... by Kota Sawa, Miko Tamura, Saori Arai

“…Onset days and SPV variability errors influenced severe hemiplegia cases, whereas SPV‐EO variability errors impacted USN cases, with moderate regression coefficients (p < 0.05). …”
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Development of a High-Cell-Density Production Process for a Biotherapeutic Yeast, <i>Saccharomyces cerevisiae</i> var. <i>boulardii</i>, for Use as a Human Probiotic by Ghaneshree Moonsamy, Sarisha Singh, Yrielle Roets-Dlamini, Koketso Kenneth Baikgaki, Santosh Omrajah Ramchuran

“…Once the optimised batch was validated in the replicate batches, the statistical analysis indicated a high level of reproducibility, with low variability across key performance indicators such as biomass concentration (unit), CFU production (CFU.mL⁻¹), and substrate utilization efficiency (g.g⁻¹). …”
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Learning compositional sequences with multiple time scales through a hierarchical network of spiking neurons. by Amadeus Maes, Mauricio Barahona, Claudia Clopath

“…The hierarchical model redistributes the variability: it achieves high motif fidelity at the cost of higher variability in the between-motif timings.…”
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Analysis of Surface Roughness and Machine Learning-Based Modeling in Dry Turning of Super Duplex Stainless Steel Using Textured Tools by Shailendra Pawanr, Kapil Gupta

“…One of the most critical aspects of turning, and machining in general, is the surface roughness of the finished product, which directly influences the performance, functionality, and longevity of machined components. …”
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Deep learning algorithm on H&E whole slide images to characterize TP53 alterations frequency and spatial distribution in breast cancer by Chiara Frascarelli, Konstantinos Venetis, Antonio Marra, Eltjona Mane, Mariia Ivanova, Giulia Cursano, Francesca Maria Porta, Alberto Concardi, Arnaud Gerard Michel Ceol, Annarosa Farina, Carmen Criscitiello, Giuseppe Curigliano, Elena Guerini-Rocco, Nicola Fusco

“…The DL model exhibited high accuracy in tissue quantification and TP53 status prediction, outperforming traditional methods in terms of precision and efficiency. DL-based approaches offer significant promise for enhancing biomarker testing and precision oncology by reducing intra- and inter-observer variability, but further validation is required to optimize their integration into real-world clinical workflows. …”
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Measuring and estimation of suspended sediment variation using sediment rating curve approach in Mereg River by Sohila Aghabeigi Amin, Heidar Mirzaei

“…Therefore, recognizing the variability of rivers is essential to manage water resources and environmental issues. …”
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Acute Effects of Two Different Species of Amyloid-β on Oscillatory Activity and Synaptic Plasticity in the Commissural CA3-CA1 Circuit of the Hippocampus by Cécile Gauthier-Umaña, Jonathan Muñoz-Cabrera, Mario Valderrama, Alejandro Múnera, Mauricio O. Nava-Mesa

“…Soluble Aβ microinjection increased cCA3-to-CA1 synaptic variability without significant changes in synaptic efficiency. …”
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Genetic characterisation of Germanata Veneta and Mignon local duck breeds (Anas platyrhynchos) using whole-genome sequencing by Francesco Perini, Enrico Bortoletto, Filippo Cendron, Umberto Rosani, Emiliano Lasagna, Maristella Baruchello, Martino Cassandro, Mauro Penasa

“…Both breeds showed low genetic variability and high inbreeding (GER: FHOM = 0.305 ± 0.184; MIG: FHOM = 0.369 ± 0.163). …”
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Absorbing Aerosol Effects on Hyperspectral Surface and Underwater UV Irradiances from OMI Measurements and Radiative Transfer Computations by Alexander Vasilkov, Nickolay Krotkov, Matthew Bandel, Hiren Jethva, David Haffner, Zachary Fasnacht, Omar Torres, Changwoo Ahn, Joanna Joiner

“…The output underwater products include the hyperspectral diffuse attenuation coefficients of the planar and scalar irradiances. Effects of the seasonal variability of AAOD on the UV index and the deoxyribonucleic acid (DNA) damage dose rates are considered. …”
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Fate-tox: fragment attention transformer for E(3)-equivariant multi-organ toxicity prediction by Sumin Ha, Dongmin Bang, Sun Kim

“…To address these challenges with multiple strategies, we developed FATE-Tox, a novel multi-view deep learning framework for multi-organ toxicity prediction. For variability of substructures, we used three fragmentation methods such as BRICS, Bemis-Murcko scaffolds, and RDKit Functional Groups to formulate fragment-level graphs so that diverse substructures can be used to identify toxicity for different organs. …”
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A Mimetic Assay of Neutrophil Extracellular Trap Degradation Using YOYO-1-Stained DNA-Histone Surface Webs by Katherine H. Nguyen, Midori L. Wasielewski, Srilakshmi Yalavarthi, Xianggui Qu, Jason S. Knight, Shuichi Takayama

“…This paper describes a simplified, lower variability mimetic assay with DNA–histone structures, referred to as surface webs, that performs functionally similarly to traditional NET degradation assays with increased scalability, ease of use, shorter preparation time, and lowered costs. …”
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Beyond the interface: benchmarking pediatric mobile health applications for monitoring child growth using the Mobile App Rating Scale by Anggi Septia Irawan, Arie Dwi Alristina, Arie Dwi Alristina, Rizky Dzariyani Laili, Nuke Amalia, Arief Purnama Muharram, Adriana Viola Miranda, Bence Döbrössy, Edmond Girasek

“…MARS assessed applications from multiple domains, including engagement, functionality, aesthetics, and information quality. Inter-rater reliability was ensured using the Intraclass Correlation Coefficient (ICC). …”
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Combined analysis of 16S rRNA gene sequencing data reveals core vaginal bacteria across livestock species by Lucille C. Jonas, Lucille C. Jonas, Curtis R. Youngs, Stephan Schmitz-Esser, Stephan Schmitz-Esser

“…Recent publications have uncovered a high degree of variability of the livestock vaginal microbiota, making it difficult to focus functional research on individual microorganisms. …”
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RNAtango: Analysing and comparing RNA 3D structures via torsional angles. by Marta Mackowiak, Bartosz Adamczyk, Marta Szachniuk, Tomasz Zok

“…Such an analysis has been made possible by RNAtango, a web server introduced in this paper, that provides a trigonometric perspective on RNA 3D structures, giving insights into the variability of examined models and their alignment with reference targets. …”
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Psychophysiological and Performance Effects of Biofeedback and Neurofeedback Interventions in a Top 100 Female Chess Player by Juan Pedro Fuentes-García, Santos Villafaina

“…Specifically, the sensorimotor rhythm stimulation (12–15 Hz) can enhance cognitive functions such as selective attention and working memory. …”
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Influence of Customer Intimacy Strategy on Organisations’ Competitiveness in Tier III Category of Commercial Banks in Kenya by Alfayo Odongo Wamburi, Lucy Kibe, Henry Yatich

“…Proportionate stratified random sampling ensured representativeness based on management staff functions. Regression analysis revealed a strong positive correlation (R = 0.822) between the Customer Intimacy Strategy and Organisational Competitiveness, explaining 67.5% of the variability. …”
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UDDER MEASUREMENTS AT "ALBA DE BANAT" AND "CARPATINA" GOATS BREEDS by Rodica CHETROIU

“…The primary data obtained was statistically processed using statistical functions available in Microsoft Excel and the main statistical parameters were determined: arithmetic mean, standard error of mean and variability coefficient. …”
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