Metastatic neuroendocrine tumor with extensive bone marrow involvement at diagnosis: Evaluation of response and hematological toxicity profile of PRRT with 177Lu-DOTATATE by Sandip Basu, Rohit Ranade, Pradeep Thapa

“…The selected patients were analyzed for the following: (i) Patient and lesional characteristics, (ii) associated metastatic burden, (iii) hematological parameters at diagnosis and during the course of therapy, (iv) response to PRRT (using a 3-parameter assessment: Symptomatic including Karnofsky/Lansky performance score, biochemical finding, and scan finding), (v) dual tracer imaging features [with somatostatin receptor imaging (SRI) and fluorodeoxyglucose-positron emission tomography/computed tomography (FDG-PET/CT)]. …”
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Global monopole in a Ricci-coupled Kalb–Ramond bumblebee gravity by Fernando M. Belchior, Roberto V. Maluf, Albert Yu. Petrov, Paulo J. Porfírio

“…This modified theory of gravity possesses the notable feature of incorporating local Lorentz symmetry breaking (LSB) via a spontaneous symmetry-breaking mechanism. …”
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Development and Validation of an Interpretable Machine Learning Model for Prediction of the Risk of Clinically Ineffective Reperfusion in Patients Following Thrombectomy for Ischem... by Hu X, Qi D, Li S, Ye S, Chen Y, Cao W, Du M, Zheng T, Li P, Fang Y

“…The final model included ten parameters: EVT attempts, diabetes mellitus, previous ischemic stroke, National Institutes of Health Stroke Scale (NIHSS score), preoperative infarction in the basal ganglia, baseline diastolic blood pressure, clot burden score (CBS)/basilar artery on computed tomography angiography (BATMAN) score, stroke cause, collateral grade, and MLS.Conclusion: We developed and validated the first interpretable machine learning model for CIR prediction after EVT, surpassing traditional methods. …”
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A Study of the Effect of Inflation and Exchange Rate on Stock Market Returns in Ghana by Charles Kwofie, Richard Kwame Ansah

“…The variables were tested for long memory and it was observed that such property did exist in these variables, making it a desirable feature of which investors can take advantage of. …”
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Finger Knuckle Print classification: Leveraging vision Mamba for low complexity and high accuracy by Chiron Bang, Ali Salem Altaher, Ahmed Altaher, Hawraa Moamin, Thamer Alshammari, Basmh Alkanjr, Hasan Altaher, Mohammed G. Al-Jassani, Hanqi Zhuang

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High-Performance Voltage-Boost Switched-Coupled-Inductor DC–DC Converters Deduced From Impedance Source Networks by Yuliang Ji, Lina Geng

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Enhancing State of Health Prediction Accuracy in Lithium-Ion Batteries through a Simplified Health Indicator Method by Dongxu Han, Nan Zhou, Zeyu Chen

“…This paper conducts an in-depth analysis of the incremental capacity (IC) curve and proposes a feature parameter based on the area under the IC curve. …”
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Identification of Alcoholism Based on Wavelet Renyi Entropy and Three-Segment Encoded Jaya Algorithm by Shui-Hua Wang, Khan Muhammad, Yiding Lv, Yuxiu Sui, Liangxiu Han, Yu-Dong Zhang

“…The wavelet Renyi entropy is proposed to provide multiresolution and multiscale analysis of features, describe the complexity of the brain structure, and extract the distinctive features. …”
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Dual-context enhanced knowledge representation learning method in hyper-relational knowledge graphs by Jiahang Li, Qilong Han, Dan Lu, Lijie Li

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Attention-Based Batch Normalization for Binary Neural Networks by Shan Gu, Guoyin Zhang, Chengwei Jia, Yanxia Wu

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GSPSO-LRF-ELM: Grid Search and Particle Swarm Optimization-Based Local Receptive Field-Enabled Extreme Learning Machine for Surface Defects Detection and Classification on the Magn... by Jun Xie, Jin Zhang, Fengmei Liang, Yunyun Yang, Xinying Xu, Junjie Dong

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Synchronization of Chaotic Systems with Huygens-like Coupling by Jonatan Pena Ramirez, Adrian Arellano-Delgado, Rodrigo Méndez-Ramírez, Hector Javier Estrada-Garcia

“…One of the earliest reports on synchronization of inert systems dates back to the time of the Dutch scientist Christiaan Huygens, who discovered that a pair of pendulum clocks coupled through a wooden bar oscillate in harmony. A remarkable feature in Huygens’ experiment is that different synchronous behaviors may be observed by just changing a parameter in the coupling. …”
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Surface-based morphometry of the cerebral cortex in cognitive impairments of varying severity in patients with age-related cerebral small vessel disease by Elena I. Kremneva, Larisa A. Dobrynina, Kamila V. Shamtieva, Victoria V. Trubitsyna, Zukhra S. Gadzhieva, Angelina G. Makarova, Maria M. Tsypushtanova, Marina V. Krotenkova

“…The assessment included the analysis of signs of cerebral small vessel disease based on the results of magnetic resonance imaging with the computation of general cerebral small vessel disease index and processing T1 multiplanar reconstruction images by surface-based morphometry to quantify general and regional brain parameters, including the thickness of the cerebral cortex. …”
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Evaluating Communication Performance in Rotating Electrical Machines Using RSSI Measurements and Artificial Intelligence by Sonia Ben Brahim, Samia Dardouri, Hanen Lajnef, Amel Ben Slimane, Ridha Bouallegue, Tan-Hoa Vuong

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LeafLaminaMap: Exploring Leaf Color Patterns Using RGB Color Indices by Péter Bodor-Pesti, Lien Le Phuong Nguyen, Thanh Ba Nguyen, Mai Sao Dam, Dóra Taranyi, László Baranyai

“…LeafLaminaMap was developed in Scilab with the Image Processing and Computer Vision toolbox, and the code is available freely at GitHub. …”
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Mobile Apps and Visual Function Assessment: A Comprehensive Review of the Latest Advancements by Caius Goh, Marilyn Puah, Zhi Hong Toh, Joewee Boon, Debbie Boey, Ryan Tay, Ashita A. Sule, Renee Liu, Xing-Er Ong, Aditya Kalra, Satvik Gupta, Andres Rousselot, William Rojas-Carabali, Bryan Ang, Rupesh Agrawal

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Horizon Wavefunction of Generalized Uncertainty Principle Black Holes by Luciano Manfredi, Jonas Mureika

“…This is likely due to a “dimensional reduction” feature of the model, where the black hole characteristics for sub-Planckian black holes mimic those in (1+1) dimensions and the horizon size grows as RH~M-1.…”
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Edge-Aware Dual-Task Image Watermarking Against Social Network Noise by Hao Jiang, Jiahao Wang, Yuhan Yao, Xingchen Li, Feifei Kou, Xinkun Tang, Limei Qi

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Value Chain Modeling in Digital Strategic Management by I. M. Stepnov, Yu. A. Kovalchuk

“…The analysis of existing approaches reveals the following unsolved problems: frst, the absence of direct interconnection between the expenses on digitalization and the results received with the use of digital platforms, and second, information is not singled out as a separate expense category in cost accounting, management and control regardless of the considerable percentage increase of an enterprise expenses on cloud computing service and technology. The authors model the newly created value in digital environment by a) defning a service (not fnished goods) as an integrating element which is typical of digital economy; b) singling out the variants of market cooperation with the use of platforms on the basis of traditional contracts, agreements “by default”, registered users of the platforms, smart contracts; c) choosing basic parameters — investments in the capital which is aggregated by the process and the costs of operating activity participants (by technological limits) supplemented by semi fixed costs; d) using the concept of limits to represent operating activity which is sensitive to special features and proportions among separate stages of a technological process and introducing two information limits (“Data collection, storage and processing” and “Digital representation and market design”) which resulted in creation of the information and communication costs accounting object. …”
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Road Event Detection and Classification Algorithm Using Vibration and Acceleration Data by Abiel Aguilar-González, Alejandro Medina Santiago

“…Traditional approaches often require complex feature engineering or the use of machine learning models, which can be computationally intensive, especially when dealing with real-time data from high-frequency vibration and acceleration sensors. …”
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