Relationship between Cognitive Impairment and Behavioural Disturbances in Alzheimer’s Disease Patients by Laura Serra, Roberta Perri, Lucia Fadda, Alessandro Padovani, Sebastiano Lorusso, Carla Pettenati, Carlo Caltagirone, Giovanni A. Carlesimo

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Long-term effect of island industrial construction on groundwater health risk by Yong Huang, Daqing Wang, Haoli Xu, Zhao Lu, Zijian Cheng, Zhibin Ding, Yi Wang, Yue Shi, Huiru Cui, Xiaoying Lian

“…However, the health risk in the center of the park reached Level 1 and above, and the risk area of Level 2 and above covered an area of up to 94,613 m2, accounting for 0.0039 of the entire study area. Finally, Monte Carlo simulations were used to conduct uncertainty and sensitivity analyses to reflect the objective reality of groundwater health risks under the combined influence of various uncertainty factors. …”
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Nuclear Data Uncertainty Quantification and Propagation for Safety Analysis of Lead-Cooled Fast Reactors by Ishita Trivedi, Jason Hou, Giacomo Grasso, Kostadin Ivanov, Fausto Franceschini

“…The impact of nuclear data uncertainties based on ENDF/B-VII.0 covariances is quantified on lattice level using the generalized perturbation theory implemented with the Monte Carlo code Serpent and the deterministic code PERSENT of the Argonne Reactor Computational (ARC) suite. …”
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Ion beam induced secondary electron tomography of acrylonitrile-styrene-acrylate/polycarbonate polymer blends for fused filament fabrication and injection moulding by J. Hernández-Saz, D. Moreno-Sanchez, L. M. Valencia, Y. Gómez, S. I. Molina, M. Herrera

“…For this, ion beam induced secondary electron (iSE) images show the capability to distinguish unequivocally the two phases in the blend, providing enough contrasts to perform the 3D experiment. Additionally, Monte Carlo simulations show that the lateral spread for incident electrons in PC is 61.7 nm and for Ga+ ions of 26.2 nm, evidencing a better spatial resolution in iSE imaging. …”
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Uniform Quantization for Multi-Antenna Amplify–Quantize–Forward Relay by Gangsan Jeong, Xianglan Jin

“…Furthermore, we propose a USL method with Monte Carlo (USL-MC), leveraging an approximated loss function to address the heightened complexity observed in multi-antenna systems. …”
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Host-symbiont-gene phylogenetic reconciliation by Menet, Hugo, Trung, Alexia Nguyen, Daubin, Vincent, Tannier, Eric

“…Given three phylogenetic trees, we devise a Monte Carlo algorithm which samples evolutionary scenarios of symbionts and genes according to an approximation of their likelihood in the model. …”
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Uncertainty analysis in river quality management considering failure probability: controllable and uncontrollable input pollutants by Mohsen Dehghani Darmian, Britta Schmalz

“…This study integrates a finite volume approach, called SEF (symmetric exponential function), with Monte Carlo simulations in MATLAB to solve the advection-dispersion equation, focusing on evaluating river quality protection tools by considering failure probability (Pf). …”
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Mobility Aware Spectrum Handoff in 6G-Enabled Cognitive Radio Vehicular Centralized and Ad-Hoc Networks by Shanidul Hoque, Hemanta Kumar Sahu, Mohammed Nazibul Hasan, Rajesh Saha

“…We also perform Monte-Carlo simulation for the performance measuring metrics to validate the proposed integrated SH model in CRCNs.…”
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Event-by-Event Particle Ratio Fluctuations at LHC Energies by Shaista Khan, Bushra Ali, Anuj Chandra, Shakeel Ahmad

“…A Monte Carlo study of identified particle ratio fluctuations at LHC energies is carried out in the framework of HIJING model using the fluctuation variable νdyn. …”
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The Measurement of Neutron Contamination in High Energy X-Ray Radiotherapy Using a He-3 Gas Dosimeter by Alireza Vejdani, Mehdi Momennezhad, Sara Mohammadi, Vajiheh Vejdani Noghreiyan, Atefeh Rostami

“…Both the neutron and Farmer dosimeters were applied in the presence and absence of acrylic plates at the same point. In this study, Monte Carlo (MC) code was utilized to prepare the correct proportion of neutron dose. …”
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A comparison of Bayesian and frequentist confidence intervals in the presence of a late Universe degeneracy by Eoin Ó. Colgáin, Saeed Pourojaghi, M. M. Sheikh-Jabbari, Darragh Sherwin

“…We explain mathematically why this non-Gaussianity arises and show, using observational Hubble data (OHD), that Markov chain Monte Carlo (MCMC) marginalisation leads to 1D posteriors that fail to track the $$\chi ^2$$ χ 2 minimum at $$68\%$$ 68 % confidence level in high redshift bins. …”
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Septuple XBi2Te4 (X=Ge, Sn, Pb) intercalated MnBi2Te4 for realizing interlayer ferromagnetism and quantum anomalous hall effect by Ruixia Yang, Xiaoxiao Man, Jiahui Peng, Jingjing Zhang, Fei Wang, Fang Wang, Huisheng Zhang, Xiaohong Xu

“…Using first-principles calculations, we demonstrate that the p z orbital of the X atom mediates interactions between interlayer Mn atoms, enabling FM coupling. Monte Carlo simulations predict a magnetic transition temperature of 38 K for the MnBi2Te4/PbBi2Te4/MnBi2Te4 heterostructure. …”
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Assessing the Dark Matter Content of Two Quasar Host Galaxies at z ∼ 6 through Gas Kinematics by Qinyue Fei, John D. Silverman, Seiji Fujimoto, Ran Wang, Luis C. Ho, Manuela Bischetti, Stefano Carniani, Michele Ginolfi, Gareth Jones, Roberto Maiolino, Wiphu Rujopakarn, N. M. Förster Schreiber, Juan M. Espejo Salcedo, L. L. Lee

“…We find relatively large dark matter fractions within their effective radii ( f _DM ( R  <  R _e ) = ${0.61}_{-0.08}^{+0.08}$ and ${0.53}_{-0.23}^{+0.20}$ , respectively), which are significantly larger than those extrapolated from lower redshift studies and remain robust under different input parameters verified by Monte Carlo simulations. The large f _DM ( R  <  R _e ) corresponds to halo masses of ∼10 ^12.5 −10 ^12.8 M _⊙ , thus representative of the most massive halos at these redshifts. …”
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Methane hydrate systems off South Makassar Basin, Indonesia by Feisal Dirgantara, Susilohadi Susilohadi, Mohammad Andri Syahrir Iskandar, Yudha Arisandhy Sintuwardhana

“…A first-order estimation of methane resources via petrophysical approach and Monte Carlo simulation suggests approximately 105 trillion cubic feet (TCF) of methane resources.…”
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Computational design of potent dimeric phenylthiazole NS5A inhibitors for hepatitis C virus by Wissal Liman, Mehdi Oubahmane, Nouhaila Ait Lahcen, Ismail Hdoufane, Driss Cherqaoui, Rachid Daoud, Achraf El Allali

“…In this context, a set of 82 phenylthiazole derivatives was employed to construct a QSAR model using the Monte Carlo optimization technique. This model offers valuable insights into the specific structural characteristics that either enhance or reduce the inhibitory activity. …”
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Improvement in the Flux Uniformity of the Solar Dish Concentrator System through a Concave Quartz Window by Du-zhong Nie, You-duo Peng, Jian Yan, Cheng-ji Mi, Yong-xiang Liu, Yong Tian

“…For each concave quartz window, 36 structural schemes were offered. Based on the Monte Carlo ray-tracing method, the results showed that the nonuniformity coefficient of the receiver was 0.68 and the peak concentration ratio was 1320.21 by using a plane quartz window. …”
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Comparing predictive risk to actual presence of coronary atherosclerosis on coronary computed tomography angiography by Emma Playford, Simon Stewart, Gerard Hoyne, Geoff Strange, Girish Dwivedi, Christian Hamilton-Craig, Gemma Figtree, David Playford

“…Overall, 23 % of males and 31 % of females had CAD predicted by CVRS (Monte Carlo: females, p = 0.024; males, p < 0.001), but there was little to no agreement between CVRS and atherosclerosis burden (Cohen's kappa: males, κ = 0.149; females, κ = 0.096). …”
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Secondary flow characteristics and their relationship with thermal performance inside the absorber under non-uniform heat flux by Meihong Ye, Weili Gu, Yifan Hou, Xin Xiang, Jiayong Liu

“…This study combines the Monte Carlo Ray Tracing method (MCRT) and the Finite Volume Method (FVM) to investigate the fluid flow and heat transfer characteristics inside the absorber under non-uniform thermal boundary conditions. …”
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IMAGE PROCESSING AT ELLIPSOIDAL PHOTOMETRY by M. A. Bezuglyi, N. V. Bezuglaya, A. B. Samilyak

“…That confirmed by comparing results of the numerical (direct Monte Carlo simulation) and the real experiment for samples different thickness of muscle porcine tissue in vitro. …”
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A New Method of Central Axis Extracting for Pore Network Modeling in Rock Engineering by Xiao Guo, Kairui Yang, Haowei Jia, Zhengwu Tao, Mo Xu, Baozhu Dong, Lei Liu

“…Firstly, digital core was reconstructed by using the Markov Chain Monte Carlo (MCMC) method based on the binary images of a rock cutting plane taken from heavy oil reservoir sandstone. …”
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