The Effects of Active Galactic Nuclei Feedback on the Lyα Forest Flux Power Spectrum by Megan Taylor Tillman, Blakesley Burkhart, Stephanie Tonnesen, Simeon Bird, Greg L. Bryan

“…Using the Simba cosmological-hydrodynamic simulations, we examine the impact that adding different AGN feedback modes has on the predicted P1D. We find that, for Simba , the impact of AGN feedback is most dramatic at lower redshifts ( z  < 1) and that AGN jet feedback plays the most significant role in altering the P1D. …”
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Cavitation and erosion effects on hydraulic performances of a submersible drainage pump by Md Rakibuzzaman, Sang-Ho Suh, Hyoung-Ho Kim, Md. Didarul Islam, Ling Zhou, Mahmoud A. El-Emam

“…The Reyleigh-Plesset cavitation model was considered for interphase mass transfer to predict and find the cavitation characteristics. Additionally, the discrete phase model (DPM) was adopted as an Eulerian-Eulerian approach combined with Grant and Tabakoff's erosion model to capture the erosion effects in the pump numerically. …”
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Forecasting insect abundance using time series embedding and machine learning by Gabriel R. Palma, Rodrigo F. Mello, Wesley A.C. Godoy, Eduardo Engel, Douglas Lau, Charles Markham, Rafael A. Moral

“…A possible solution to enhance decision-making is to apply forecasting methods to predict insect abundance. However, another layer of complexity is added when other covariates are considered in the forecasting, such as climate time series collected along the monitoring system. …”
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The mirror preference test: A reverse translational approach to study anomalous subjective experience in rats by Daria Chestnykh, Liubov S. Kalinichenko, Stephan von Hörsten, Johannes Kornhuber, Christian P. Müller

“…In humans, a Mirror-Gazing test is used to examine abnormal self-experience and to predict the risk of schizophrenia. To address this, we developed a task to evaluate anomalous subjective experiences in rats using a Mirror-Preference test. …”
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Mortality Related Risk Factors in High-Risk Pulmonary Embolism in the ICU by Begüm Ergan, Recai Ergün, Taner Çalışkan, Kutlay Aydın, Murat Emre Tokur, Yusuf Savran, Uğur Koca, Bilgin Cömert, Necati Gökmen

“…In high-risk PE, admission APACHE II score and need for invasive mechanical ventilation may predict death in ICU. Thrombolytic therapy seems to be beneficial in these patients.…”
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Association between prognostic nutritional index and all-cause mortality and cardiovascular disease mortality in American adults with non-alcoholic fatty liver disease by Yuqing Lei, Shaohong Tao, Yubo Yang, Fang Xie, Weining Xie

“…Time-dependent ROC analysis highlighted the strong predictive performance of PNI across various time points.ConclusionPNI played a significant role as an effective predictor of prognosis in individuals diagnosed with NAFLD.…”
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Analysis of the correlation between the serum triglyceride glucose index and the risk of death in patients on maintenance hemodialysis: a retrospective cohort study by Xiaokeng Chi, Shuxin Chen, Zhe Huang, Rong Zhou, Zhicheng Su, Qiujun Mai, Yilin Xu, Jianxin Wan

“…Compared with MHD patients with low TyG index levels, the risk of all-cause mortality and cardiovascular mortality in MHD patients with high TyG index levels increased by 1.790 and 1.735 times, respectively (P = 0.006 & P = 0.022). The predictive time-AUC values of the TyG index for all-cause and cardiovascular death in MHD patients were between 0.698 to 0.819. …”
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PET-Assessed Metabolic Tumor Volume Across the Spectrum of Solid-Organ Malignancies: A Review of the Literature by Anusha Agarwal, Chase J. Wehrle, Sangeeta Satish, Paresh Mahajan, Suneel Kamath, Shlomo Koyfman, Wen Wee Ma, Maureen Linganna, Jamak Modaresi Esfeh, Charles Miller, David C. H. Kwon, Andrea Schlegel, Federico Aucejo

“…MTV may be used in conjunction with several existing and established clinical parameters to help inform risk stratification and treatment strategies and predict outcomes in cancer. Optimizing such volumetric parameters is paramount for advancing efforts to advance cancer care for our patients. …”
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Impact of surrounding tissue-type and peri-electrode gap in stereoelectroencephalography guided (SEEG) radiofrequency thermocoagulation (RF-TC): a computational study by Santiago Collavini, Juan J. Pérez, Enrique Berjano, Mariano Fernández-Corazza, Silvia Oddo, Ramiro M. Irastorza

“…The computer model was first validated by an ex vivo model based on liver fragments and later used to study the impact of three different factors on the coagulation zone size: 1) the difference in the tissue surrounding the electrode (gray/white matter), 2) the presence of a peri-electrode gap occupied by cerebrospinal fluid (CSF), and 3) the energy setting used (power-duration).Results The model built for the experimental validation was able to predict both the evolution of impedance and the short diameter of the coagulation zone (error < 0.01 mm) reasonably well but overestimated the long diameter by 2 − 3 mm. …”
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Effect of recycling on the time- and temperature-dependent mechanical properties of PP/MWCNT composite liner materials by Attila Bata, Péter Gerse, Krisztián Kun, Emese Slezák, Ferenc Ronkay

“…A novel method was applied in physical-mechanical measurements to evaluate MWCNT efficiency, predicting its effect across the temperature range typical for hydrogen-powered vehicles and determining the optimal filler content for maximum reinforcement efficiency. …”
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Skin Lesion Classification Through Test Time Augmentation and Explainable Artificial Intelligence by Loris Cino, Cosimo Distante, Alessandro Martella, Pier Luigi Mazzeo

“…Grad-CAM is used to generate heatmaps that highlight the regions of input images that influence the model’s predictions. Our findings reveal that Test Time Augmentation enhances the balanced multi-class accuracy of CNN models by up to 0.3%, achieving a balanced accuracy rate of 97.58% on the International Skin Imaging Collaboration (ISIC 2019) dataset. …”
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Unravelling the multi-scale structure of vertebrate scavenger communities: The role of beta-diversity in livestock carcass consumption by María Eugenia Cabrera-García, Patricia Mateo-Tomás, José Hernán Sarasola, Juan I. Zanón Martínez, Beatriz Martínez-Miranzo, Pedro P. Olea

“…Understanding the structure of communities across multiple scales is useful for predicting impacts on biodiversity and ecosystem functioning. …”
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Polymorphisms in immunosuppression-related genes are associated with AML by Mingying Li, Mingying Li, Jingjing Ye, Jingjing Ye, Mengyuan Chang, Mengyuan Chang, Lei Feng, Lei Feng, Tingting Liu, Tingting Liu, Di Zhang, Di Zhang, Yuyan Wu, Yuyan Wu, Yuechan Ma, Yuechan Ma, Guangqiang Meng, Guangqiang Meng, Chunyan Ji, Chunyan Ji, Tao Sun, Tao Sun

“…Lastly, expressions of CD163, CIITA, LILRB4, and CD200 were higher in AML patients than that in normal controls.ConclusionsOur findings on SNP associations in AML immunosuppression-related genes provide important reference points for predicting treatment outcomes in AML patients.…”
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Spatiotemporal range dynamics and conservation optimization for endangered medicinal plants in the Himalaya by Fu-Lv Liu, Winnie Wanjiku Mambo, Jie Liu, Guang-Fu Zhu, Raees Khan, Abdullah, Shujaul Mulk Khan, Lu Lu

“…In this study, we used the biomod2 ensemble model to predict the potential habitats of ten medicinal species using 497 occurrence points and 26 environmental variables under the past, present, and two future scenarios (2090; SSP126 and SSP585). …”
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Fluorescence Lifetime Imaging of NAD(P)H in Patients’ Lymphocytes: Evaluation of Efficacy of Immunotherapy by Diana V. Yuzhakova, Daria A. Sachkova, Anna V. Izosimova, Konstantin S. Yashin, Gaukhar M. Yusubalieva, Vladimir P. Baklaushev, Artem M. Mozherov, Vladislav I. Shcheslavskiy, Marina V. Shirmanova

“…In this regard, the selection of an appropriate in vitro model and the choice of cellular response assay are critical for reliable predictions. Fluorescence lifetime imaging microscopy (FLIM) is a powerful, non-destructive tool that enables direct monitoring of cellular metabolism on a label-free basis with a potential to resolve metabolic rearrangements in immune cells associated with their reactivity. …”
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Analytical hierarchy process as a tool supporting a decision-making for assessment of the risk of transboundary infectious animal disease introduction to the Russian Federation an... by N. V. Lebedev, A. S. Igolkin, K. N. Gruzdev, D. G. Spirin, M. A. Farukh, N. V. Ermilov, G. G. Eremin

“…The article assesses the validity of the possibilities and use of modern methods of analyzing and predicting the spread of animal morbidity, identifying cause-and-effect relationships and the extent of the spread of particularly dangerous animal diseases. …”
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Dentin-Derived Inorganic Minerals Promote the Osteogenesis of Bone Marrow-Derived Mesenchymal Stem Cells: Potential Applications for Bone Regeneration by Gang Lei, Yanqiu Wang, Yan Yu, Zehan Li, Jiamin Lu, Xingyun Ge, Na Li, Ana Gloria Cuba Manduca, Jinhua Yu

“…DIM could promote BMMSC osteogenic differentiation via triggering the ERK and p38 MAPK signaling pathways and might be a novel predictable material for facilitating bone formation.…”
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Ironing out differences in attenuation and blooming artifact in acute stroke thrombi by Aglae Velasco Gonzalez, Dennis Görlich, Boris Buerke, Cristina Sauerland, Norbert Meier, Manfred Fobker, Ray McCarthy, Astrid Jeibmann, Walter Heindel, Andreas Faldum, Harald Kugel

“…The cut-off value of 1242 µg/g of iron predicted blooming artifacts with high sensitivity and specificity. …”
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Synthetic Modeling of Polarized Dust Emission in Intermediate-mass YSOs. I. Constraining the Role of Iron Inclusions and Inelastic Relaxation on Grain Alignment with ALMA Polarizat... by Nguyen Chau Giang, V. J. M. Le Gouellec, Thiem Hoang, A. J. Maury, P. Hennebelle

“…Moreover, inelastic relaxation is predicted to dominate over Barnett relaxation in driving the IA of micron-sized grains and very large grains (VLGs) above 10 μ m. …”
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DeepRetention: A Deep Learning Approach for Intron Retention Detection by Zhenpeng Wu, Jiantao Zheng, Jiashu Liu, Cuixiang Lin, Hong-Dong Li

“…Further, we show that IRs predicted by DeepRetention are biologically meaningful on an RNA-seq dataset from Alzheimer’s Disease (AD) samples. …”
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