Sustainable extraction of bioproducts from cactus pear waste: Economic viability and market opportunities in a green economy by Giuseppe Timpanaro, Vera Teresa Foti

“…Further research should explore alternative biomass sources and innovations in extraction efficiency to ensure continuous production and cost reductions.…”
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Meristic and morphometric comparison of an undescribed sucker of the Río Culiacán (Catostomus sp.) and Yaqui sucker (Catostomus bernardini) (Catostomidae, Teleostei) from the Sierr... by Gorgonio Ruiz-Campos, Sergio Sánchez-Gonzáles, Richard L. Mayden, Alejandro Varela-Romero

“…Likewise, the discrimination was associated with the lowest values for predorsal distance, soft posterior ocular margin to occiput, and number of anal rays. The standardized coefficients for canonical variables 1 and 2 accounted 82.6% of the total variation. …”
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Treatment of Pediatric Colchicine Poisoning with Single-Pass Albumin Dialysis: A Case Report by Atessa Bahadori, Rishil Patel, Cal Robinson, Steve Balgobin, Michael Zappitelli, Nithiakishna Selvathesan

“…The rationale for CVVHDF with SPAD was based on the high protein binding, variably high volume of distribution, previous reports showing a sieving coefficient of 0.2 with CVVH, and the high mortality risk. …”
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A Data-Driven Approach Based on Deep Neural Network Regression for Predicting the Compressive Strength of Steel Fiber Reinforced Concrete by Nhat-Duc Hoang, Van-Duc Tran

“…Experimental results show that the L1 regularization helps achieve the most desired performance, with a coefficient of determination (R2) of roughly 0.96. Notably, an asymmetric loss function is used along with Nadam to decrease the percentage of overestimated cases from 50.83% to 27.08%. …”
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Estimativa das temperaturas máximas e mínimas do ar para a região do Circuito das Frutas, SP Estimation of maximum and minimum air temperatures for the "Circuito das Frutas" region... by Ludmila Bardin, Mário J. Pedro Júnior, Jener F. L. de Moraes

“…Also, maps with the spacial variability of the maximum and minimum mean monthly and annual temperatures are presented for the region.…”
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The Effect of Vocal Rehabilitation on Patients with Vocal Cord Paralysis by Mila Bunijevac, Andrijana Mikić, Maša Đurišić

“…Measures of central tendency, measures of variability, one-factor analysis of variance, t-test for independent samples, chi-square test and interclass correlation coefficient were applied in statistical data processing. …”
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Assessing motor control and movement quality in patients with non-specific low back pain: a scoping review and development of an ICF-based conceptual framework by Kerstin Luedtke, Agnes Sturma, Georg Pfluegler, Meike Klinger, Clemens Ley, Beate Schüßler

“…A conceptual framework was constructed, consisting of five International Classification of Functioning, Disability and Health-based broad motor control functions and 10 movement quality domains, namely flexibility, stability, accuracy, symmetry, speed, smoothness, adaptability, variability, efficiency and coordination.Conclusion The provided conceptual framework for motor control functions and movement quality domains can serve as a structural foundation for future research on the content validity of assessment approaches in the context of LBP.…”
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Exploring restoration efforts from a social lens: statistical models reveal relationships between salmon habitat restoration efforts and ecological and social characteristics of th... by Brittany D King, Robert Fonner

“…We specified statistical models to explain the variation in the number of restoration worksites undertaken in subwatersheds as a function of environmental and social variables. Using a common set of explanatory variables, we fit four models to examine the distribution of worksites associated with particular types of restoration actions (instream, riparian, land acquisition, and fish passage) and a fifth model to examine the distribution of all aquatic-based restoration worksites across action types. …”
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Field Testing of a Smart Geomat Based on Fiber Optic Sensors and Sensor Fusion for Levee Monitoring by Manuel Bertulessi, Francesca Ceccato, Francesco Ioli, Federico Barbieri, Livio Pinto, Paolo Simonini, Giovanni Menduni

“…ABSTRACT Real‐time monitoring of the functionality of river embankments, especially during flood events, is an increasingly important topic in the new scenario outlined by climate change. …”
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Cumulative Distribution-Based Method for Pavement Performance Modeling by Chenhao Tu, Wenya Ye, Rui Zhang, Xudong Qian, Qun Yang

“…Predicting future pavement conditions accurately and efficiently helps determine the optimal maintenance time, select appropriate measures, and allocate rehabilitation funds effectively. …”
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Changes in AXL and/or MITF melanoma subpopulations in patients receiving immunotherapy by M. Willemsen, J. Bulgarelli, S.K. Chauhan, R.R. Lereim, D. Angeli, G. Grisendi, G. Krebbers, I. Davidson, J.A. Kyte, M. Guidoboni, R.M. Luiten, W.J. Bakker

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Bottom-up Biomaterial strategies for creating tailored stem cells in regenerative medicine by Brenda Cruz-Gonzalez, Ellie Johandes, Dominique Gramm, Donny Hanjaya-Putra, Donny Hanjaya-Putra, Donny Hanjaya-Putra, Donny Hanjaya-Putra

“…By replicating lineage-specific mechanical, chemical, and spatial cues, these tailored biomaterials enhance differentiation fidelity, reprogramming efficiency, and functional integration. This paradigm shift from passive scaffolds to dynamic, cell-instructive platforms bridges critical gaps between laboratory success and clinical translation, offering a transformative roadmap for regenerative medicine and tissue engineering.…”
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Evaluating Machine Learning Models for Predicting Hardness of AlCoCrCuFeNi High-Entropy Alloys by Uma Maheshwera Reddy Paturi, Muhammad Ishtiaq, Pasupuleti Lakshmi Narayana, Anoop Kumar Maurya, Seong-Woo Choi, Nagireddy Gari Subba Reddy

“…This study evaluates the predictive capabilities of various machine learning (ML) algorithms for estimating the hardness of AlCoCrCuFeNi high-entropy alloys (HEAs) based on their compositional variables. Among the ML methods explored, a backpropagation neural network (BPNN) model with a sigmoid activation function exhibited superior predictive accuracy compared to other algorithms. …”
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Elucidating the role of mind–body connection profiles in emotional reactivity and regulation amongst typically developed adults by Kristen Van Bael, Jessica Scarfo, Emra Suleyman, Michelle Ball

“…Abstract Background Adaptive emotional functioning necessitates a strong mind–body connection. …”
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Optimized Temporal Interference Stimulation Based on Convex Optimization: A Computational Study by Chao Geng, Yang Li, Long Li, Xiaoqi Zhu, Xiaohan Hou, Tian Liu

“…CVXTI leverages the distribution characteristics of the TI envelope electric field to optimize electrode configurations, enhancing the optimization efficiency.…”
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Process engineering by Ahmed Mohamed Farid Shaaban, Azza Ibrahim Hafez, Mona Amin Abdel-Fatah, Nabil Mahmoud Abdel-Monem, Mohamed Hanafy Mahmoud

“…The solution diffusion model was used to develop power correlations to calculate the permeate side solute mass transfer coefficient as a function of effective cross-flow Reynolds number. …”
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Multi-Scale Multi-Domain Hybrid Finite Element Modeling of Light Propagation by Jingwei Wang, Zhanwen Wang, Lida Liu, Yuntian Chen

“…We revisit finite element method of modeling multi-scale photonic/electromagnetic devices via the proposed beam basis function, in combination with domain decompositions. …”
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HEE-SegGAN: A holistically-nested edge enhanced GAN for pulmonary nodule segmentation. by Yong Wang, Seri Mastura Mustaza, Mohammad Syuhaimi Ab-Rahman, Siti Salasiah Mokri

“…Compared to traditional 3D methods, our approach extracted features more efficiently while preserving spatial information and reducing computational requirements. …”
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Forecasting water quality indices using generalized ridge model, regularized weighted kernel ridge model, and optimized multivariate variational mode decomposition by Marjan Kordani, Mohsen Bagheritabar, Iman Ahmadianfar, Arvin Samadi-Koucheksaraee

“…Statistical metrics confirmed that the proposed OMVMD-GRKR model, concerning the best efficiency in the Ahvaz (R = 0.987, RMSE = 0.761, and U95% = 2.108) and Molasani (R = 0.963, RMSE = 1.379, and U95% = 3.828) stations, outperformed the OMVMD and simple-based methods such as ridge regression (Ridge), least squares support vector machine (LSSVM), deep random vector functional link (DRVFL), and deep extreme learning machine (DELM). …”
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Smart Fermentation Technologies: Microbial Process Control in Traditional Fermented Foods by Chong Shin Yee, Nur Asyiqin Zahia-Azizan, Muhamad Hafiz Abd Rahim, Nurul Aqilah Mohd Zaini, Raja Balqis Raja-Razali, Muhammad Ameer Ushidee-Radzi, Zul Ilham, Wan Abd Al Qadr Imad Wan-Mohtar

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