Subtypes detection of papillary thyroid cancer from methylation assay via Deep Neural Network by Andrea Colacino, Andrea Soricelli, Michele Ceccarelli, Ornella Affinito, Monica Franzese

“…When applied to the thyroid independent dataset, the proposed Neural Net architecture successfully discriminates tumor versus normal samples (AUC = 0.91 +/- 0.05) and follicular versus classical PTC subtypes (AUC = 0.80 +/- 0.05), outperforming traditional machine learning algorithms. Conclusions: In conclusion, the study highlights the effectiveness of CNNs in the methylation based classification of thyroid tumors and their subtypes, demonstrating its ability to capture subtle epigenetic differences with minimal preprocessing.This versatility makes the model adaptable for classifying other tumor types. …”
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Advances in Light Field Spatial Super-Resolution: A Comprehensive Literature Survey by Wenqi Lyu, Hao Sheng, Wei Ke, Xiao Ma

“…Our experimental findings indicate substantial differences in robustness and adaptability among methods: approaches such as DistgSSR and DPT perform exceptionally well at high magnifications, while others, like HLFSR, exhibit comparatively poorer performance in complex scenes. …”
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Enhancing Sustainable Manufacturing in Industry 4.0: A Zero-Defect Approach Leveraging Effective Dynamic Quality Factors by Rouhollah Khakpour, Ahmad Ebrahimi, Seyed Mohammad Seyed Hosseini

“…<a href="#_ENREF_10">Leit&atilde;o et al. (2018)</a> apply multi-agent system (MAS) infrastructure, which combines with data analysis, provides early and real time detection of deviations, prevents defects occurrence and their propagation to downstream processes, and finally enables the system to be predictive by early detection of defects and to be proactive through self-adaptation with different situations.</p> <p style="text-align: left;"><a href="#_ENREF_12">Magnanini, Colledani, and Caputo (2020)</a> propose applying the manufacturing execution system (MES) for real time data gathering and data analysis to be exploited in ZDM strategies. …”
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Root-Zone Salinity in Irrigated Arid Farmland: Revealing Driving Mechanisms of Dynamic Changes in China’s Manas River Basin over 20 Years by Guang Yang, Xuejin Qiao, Qiang Zuo, Jianchu Shi, Xun Wu, Alon Ben-Gal

“…The approach demonstrated high predictive accuracy (<i>R</i>² = 0.96 ± 0.01, root mean squared error <i>RMSE</i> = 0.19 ± 0.03 g kg⁻¹, maximum absolute error <i>MAE</i> = 0.14 ± 0.02 g kg⁻¹) in evaluating <i>SSC</i> drivers. Factors such as initial <i>SSC</i>, crop type distribution, duration of film mulched drip irrigation implementation, normalized difference vegetation index (NDVI), irrigation amount, and actual evapotranspiration (<i>ET_a</i>), with mean (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mfenced close="|" open="|"><mrow><mrow><mi>SHAP</mi><mo> </mo><mi>value</mi></mrow></mrow></mfenced></mrow></semantics></math></inline-formula>) ≥ 0.02 g kg⁻¹, were found to be more closely correlated with root-zone <i>SSC</i> variations than other factors. …”
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Surgical thyroid pathology in Crimea and Sevastopol: the way COVID-19 pandemic altered the frequency and structure of diseases by O. R. Khabarov, D. V. Zima, O. F. Bezrukov, E. Yu. Zyablitskaya, E. R. Asanova, P. E. Maksimova

“…These findings highlight the importance of adapting healthcare systems to global crises, including reserving resources for oncology care and developing early diagnostic algorithms.…”
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