Selection of memory clinic patients for CSF biomarker assessment can be restricted to a quarter of cases by using computerized decision support, without compromising diagnostic acc... by Hanneke F M Rhodius-Meester, Ingrid S van Maurik, Juha Koikkalainen, Antti Tolonen, Kristian S Frederiksen, Steen G Hasselbalch, Hilkka Soininen, Sanna-Kaisa Herukka, Anne M Remes, Charlotte E Teunissen, Frederik Barkhof, Yolande A L Pijnenburg, Philip Scheltens, Jyrki Lötjönen, Wiesje M van der Flier

“…Computer-supported prediction restricts CSF testing to only 26% of cases, without compromising diagnostic accuracy.…”
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Evaluating Radio Occultation (RO) Constellation Designs Using Observing System Simulation Experiments (OSSEs) for Ionospheric Specification by Nicholas Dietrich, Tomoko Matsuo, Chi‐Yen Lin, Brandon diLorenzo, Charles Chien‐Hung Lin, Tzu‐Wei Fang

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Optimization of ATIG Weld Based on a Swarm Intelligence Approach: Application to the Design of Welding in Selected Manufacturing Processes by Kamel Touileb, Sahbi Boubaker

“…Based on the numerical observations, linear and nonlinear models for describing the effect of the thermophysical parameters on the weld characteristics were tuned using a particle swarm optimization algorithm. While the linear model provided good prediction accuracy, the nonlinear exponential model outperformed the linear one for the depth yielding a mean absolute percentage error of 17%, a coefficient of determination of 0.8266, and a root mean square error of 0.9665 mm. …”
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Drone-Based Digital Phenotyping to Evaluating Relative Maturity, Stand Count, and Plant Height in Dry Beans (Phaseolus vulgaris L.) by Leonardo Volpato, Evan M. Wright, Francisco E. Gomez

“…The CNN-LSTM model showed high accuracy in RM prediction across various conditions, outperforming traditional image preprocessing approaches. …”
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FCB-YOLOv8s-Seg: A Malignant Weed Instance Segmentation Model for Targeted Spraying in Soybean Fields by Zishang Yang, Lele Wang, Chenxu Li, He Li

“…The results of ablation experiments revealed that the FCB-YOLOv8s-Seg model achieved a mean average precision of 95.18% for bounding box prediction and 96.63% for segmentation, marking an increase of 5.08% and 7.43% over the original YOLOv8s-Seg model. …”
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Grapes leaf disease dataset for precision agricultureMendeley Data by Madhuri Dharrao, Nilima Zade, R. Kamatchi, Rakesh Sonawane, Rabinder Henry, Deepak Dharrao

“…This High-quality annotated image dataset can help to design standard advanced AI models for automated disease detection, classification, and prediction. The dataset was validated through a transfer learning approach using the ResNet-18 algorithm and demonstrated the remarkable classification accuracy of 96 %. …”
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Analysis of Temperature Changes, Vegetation, Evapotranspiration, and Drought Based on Modeling of Landsat 5 and 8 Satellite Imagery and Meteorological Indicators by Mitra Sadat Fathifard, Abbas Rahdan, Mahsa Tohidfar

“…Evapotranspiration was then calculated using MODIS data and the Torrent-White method, incorporating the vegetation growth coefficient, and compared with evapotranspiration values derived from the SEBAL algorithm. Additionally, drought prediction was conducted using the Standardized Precipitation Index (SPI) (1-month, 3-month, 6-month, and 12-month) for the period from 2015 to 2044. …”
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Heterogeneity analysis provides evidence for a genetically homogeneous subtype of bipolar-disorder. by Caroline C McGrouther, Aaditya V Rangan, Arianna Di Florio, Jeremy A Elman, Nicholas J Schork, John Kelsoe, Bipolar Disorder Working Group of the Psychiatric Genomics Consortium

“…By investigating the subgroup's bicluster-informed polygenic-risk-scoring (PRS), we find that the disease-specific pattern highlighted by the bicluster can be leveraged to eliminate noise from our GWAS analyses and improve risk prediction. This improvement is particularly notable when using only a relatively small subset of the available SNPs, implying improved SNP replication. …”
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Cost-Efficient Fall Risk Assessment With Attention Augmented Vision Machine Learning on Sit-to-Stand Test Videos by Chunhua Pan, Boting Qu, Rui Miao, Xin Wang

“…Furthermore, a novel Attention-augmented Spatial-Temporal Graph Convolutional Network (AST-GCN) is developed for reliably identifying the action in each frame, enabling accurate computation of key kinematic features for fall risk prediction. Experimental evaluations on a dataset of 450 FSTS test videos demonstrate the high performance of <sc>FRAVM</sc>, with detection accuracy, F1 score, and ROC-AUC achieving 88.64%, 88.58%, and 98.86%, respectively. …”
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A Bit String Content Aware Chunking Strategy for Reduced CPU Energy on Cloud Storage by Bin Zhou, ShuDao Zhang, Ying Zhang, JiaHao Tan

“…The existing chunking algorithm greatly reduces the system performance when confronted with big data and it wastes a lot of energy. …”
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The Value of Morphologic Study (MRI) of the Median Nerve in Stadialization and Treatment of the Carpal Tunnel Syndrome by Florin Gabriel PANCULESCU, Raluca STEFANESCU, Ion BORDEIANU, Iulian Catalin BRATU

“…The criterion of diameter decrease can be a benchmark in order to establish a therapeutic algorithm in carpal tunnel syndrome.…”
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Automatic identification of hard and soft tissue landmarks in cone-beam computed tomography via deep learning with diversity datasets: a methodological study by Yan Jiang, Canyang Jiang, Bin Shi, You Wu, Shuli Xing, Hao Liang, Jianping Huang, Xiaohong Huang, Li Huang, Lisong Lin

“…To evaluate the accuracy of our algorithm, we determined the mean absolute error along the x-, y-, and z-axes and calculated the mean radial error (MRE) between the reference landmark and predicted landmark, as well as the successful detection rate (SDR). …”
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Topological Optimization of Dynamic Stiffness in Continuum Structure Based on Bidirectional Evolutionary Structural Optimization by JIANG Xudong, LIU Zheng, TENG Xiaoyan

“…By minimizing structural dynamic compliance, the programming scheme of optimal stiffness for continuum structure under dynamic load is proposed, by combination of Equivalent Static Loads with Bidirectional Evolutionary Structural Optimization To effectively decrease calculation scale for dynamic optimization in structural topology, the Equivalent Static Loads Method is applied to transforming dynamic optimization to static one that is solved by Bidirectional Evolutionary Structural Optimization in structural topology To enhance the optimal efficiency of the original BESO method to optimization of dynamic stiffness in continuum structure, a design domain reduction method is developed to establish a new volume control and a stop criterion in this study Numerical results show that the dynamic compliance is asymptotically convergent to optimal solution with volume constraint precisely 〖JP3〗satisfied, and optimal configuration can effectively inhibit the vibration induced by dynamic load Whereby the presented optimization algorithm is verified to be robust and adapt Consequently it is provided with theoretical significance to extend the original Evolutionary Structural Optimization Method to dynamic optimization in structural design…”
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Intelligent Energy Management in an Isolated DC Microgrid using Fuzzy Logic by Youssfi Abdelaziz, El Kadi Youssef Ait

“…The PV system is controlled by a MPPT method implementing the INC algorithm, while the storage system is managed by a PI controller to control battery charging and discharging. …”
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A Novel Method for Mechanical Fault Diagnosis Based on Variational Mode Decomposition and Multikernel Support Vector Machine by Zhongliang Lv, Baoping Tang, Yi Zhou, Chuande Zhou

“…A novel fault diagnosis method based on variational mode decomposition (VMD) and multikernel support vector machine (MKSVM) optimized by Immune Genetic Algorithm (IGA) is proposed to accurately and adaptively diagnose mechanical faults. …”
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Multi-Objective Robustness of Integrated Energy System Considering Source-Load Uncertainty by LI Jianlin, ZHANG Zedong, LIANG Ce, ZENG Fei

“…A grid-connected electric-thermal-hydrogen operation model including fuel cells and electrolytic cells is developed, and the source-load uncertainty is added by using the hierarchical Latin hypercube sampling and Euclidean distance scenario reduction methods, and solved by a two-stage robust optimization algorithm. …”
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Biomarker and clinical data–based predictor tool (MAUXI) for ultrafiltration failure and cardiovascular outcome in peritoneal dialysis patients: a retrospective and longitudinal st... by Eva María Arriero-País, María Auxiliadora Bajo-Rubio, Roberto Arrojo-García, Pilar Sandoval, Guadalupe Tirma González-Mateo, Patricia Albar-Vizcaíno, Gloria del Peso-Gilsanz, Marta Ossorio-González, Pedro Majano, Manuel López-Cabrera, Gloria del Peso-Gilsanz

“…Linear discriminant analysis (LDA) discerns among transfer to haemodialysis or death, predicts whether the cause of PD end is ultrafiltration failure (UFF) or cardiovascular disease (CVD) and anticipates the type of CVD (receiver operating characteristic curve under the area&gt;0.71).Discussion Our combination of longitudinal PD datasets, attribute shrinkage and gold-standard algorithms with overfitting testing and class imbalance ensures robust predictions in PD. …”
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Snow Depth Retrieval Using Detrended SNR From GNSS-R With Bidirectional GRU by Wei Liu, Zihui Lin, Yuan Hu, Aodong Tian, Xintai Yuan, Jens Wickert

“…Snow depth monitoring is crucial for hydrology, climate research, and avalanche prediction. While traditional global navigation satellite system (GNSS) reflectometer methods offer cost-effective snow thickness retrieval, they suffer from poor accuracy and robustness, especially in complex terrains and extreme weather. …”
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Vision-Guided Maritime UAV Rescue System with Optimized GPS Path Planning and Dual-Target Tracking by Suli Wang, Yang Zhao, Chang Zhou, Xiaodong Ma, Zijun Jiao, Zesheng Zhou, Xiaolu Liu, Tianhai Peng, Changxing Shao

“…Furthermore, a dual-target-tracking algorithm—integrating motion prediction with color-based landing zone recognition—achieves a 96% success rate in precision landings under dynamic conditions. …”
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Challenges, Difficulties, and Delayed Diagnosis of Multiple Myeloma by Tugba Zorlu, Merve Apaydin Kayer, Nazik Okumus, Turgay Ulaş, Mehmet Sinan Dal, Fevzi Altuntas

“…<b>Conclusions:</b> Multimodal tools for early diagnosis of MM. Educational campaigns to raise awareness of the disease, algorithms dedicated to routine care and novel technologies, including AI and big data analytics, and new biomarkers may serve this purpose, as well as genomic approaches to the premalignant MGUS stage.…”
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