Fault Detection Algorithm for Gaussian Mixture Noises: An Application in Lidar/IMU Integrated Localization Systems by Penggao Yan, Zhengdao Li, Feng Huang, Weisong Wen, Li-Ta Hsu

“…The relationship between GMM-distributed noises and the measurement residual is rigorously established through error propagation, which is utilized to construct the test statistic for a chi-squared test. …”
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Female pseudohermaphroditism due to classical 21-hydroxylase deficiency and insulin resistance in a girl with Turner syndrome by M Emre Atabek, Selim Kurtoğlu, Mehmet Keskin

“…We conclude that chronic hypersecretion of androgen precursors due to an inborn error of metabolism can induce a reduction in insulin sensitivity. …”
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Efficient on-shell matching by Mikael Chala, Javier L. Miras, José Santiago, Fuensanta Vilches

“…The standard off-shell approach to matching requires the use of a Green's basis that includes redundant and evanescent operators. The reduction of such a basis to a physical one is often highly non-trivial, difficult to automate and error prone. …”
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Adaptive Spatial Modulation Based Visible Light Communications: SER Analysis and Optimization by Jin-Yuan Wang, Jian-Xia Zhu, Sheng-Hong Lin, Jun-Bo Wang

“…In the system, the analysis of the average SER is divided into two aspects: the error probability of the spatial domain and the error probability of the signal domain when the spatial domain is correctly estimated. …”
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Dyadic Probabilistic Shaping of PAM-4 and PAM-8 for Cost-Effective VCSEL-MMF Optical Interconnection by Lin Sun, Chang Wang, Jiangbing Du, Chenyu Liang, Wenjia Zhang, Ke Xu, Fan Zhang, Zuyuan He

“…Energy efficient signaling can be achieved with up to 46% theoretical power reduction by PS. Experimentally, we obtained 16% reduction of optical power for the VCSEL-MMF optical link. …”
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Carbon emission prediction method of steel plants based on long short-term memory network by Fengyun LI, Zehui DOU, Peng LI, Wei GUO

“…As the second largest carbon emitter in China, iron and steel enterprises have great potential for carbon emission reduction.In order to facilitate the supervision and control of carbon emissions by relevant departments, carbon emission prediction research is carried out.Taking a steelmaking plant as the research object, firstly, the carbon dioxide emissions in the steelmaking process were analyzed, and 10 energy substances that caused carbon emissions were determined.The basic energy data of the steelmaking plant from 2001 to 2023 were collected, and the carbon emissions were calculated from the basic energy data according to the carbon emission accounting method.Secondly, based on the long short-term memory network to predict the carbon emissions in the next 7 years, the training error and test error were close to 0.01, and the actual error was 1 323 307.46 tons of carbon dioxide.Then, the Mann-Kendall trend test was used to evaluate the overall carbon emission trend of the steelmaking plant.Finally, some reasonable suggestions were put forward for steelmaking plants in order to actively respond to the goal of low-carbon environmental protection.…”
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A Near-Infrared Imaging System for Robotic Venous Blood Collection by Zhikang Yang, Mao Shi, Yassine Gharbi, Qian Qi, Huan Shen, Gaojian Tao, Wu Xu, Wenqi Lyu, Aihong Ji

“…Results show that, compared to U-Net, the BYOL+U-Net+ResNet18 method achieves an 8.31% reduction in Binary Cross-Entropy (BCE), a 5.50% reduction in Hausdorff Distance (HD), a 15.95% increase in Intersection over Union (IoU), and a 9.20% increase in the Dice coefficient (Dice), indicating improved image segmentation quality. …”
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A deep neural network framework for estimating coastal salinity from SMAP brightness temperature data by Yidi Wei, Qing Xu, Qing Xu, Xiaobin Yin, Xiaobin Yin, Yan Li, Yan Li, Kaiguo Fan

“…The framework leverages machine learning interpretability tools (Shapley Additive Explanations, SHAP) to optimize input feature selection and employs a grid search strategy for hyperparameter tuning.Results and discussionSystematic validation against independent in-situ measurements demonstrates that the baseline DNN model constructed for the entire region and time period outperforms conventional algorithms including K-Nearest Neighbors, Random Forest, and XGBoost and the standard SMAP SSS product, achieving a reduction of 36.0%, 33.4%, 40.1%, and 23.2%, respectively in root mean square error (RMSE). …”
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Mine cable partial discharge denoising method based on multivariate variational mode decomposition and improved wavelet threshold by Jiyuan CAO, Yanwen WANG, Peng CHEN, Xuan ZHOU, Weixiong ZHU, Yihe ZHANG, Le WANG

“…The partial discharge characteristic signal is classified as gross error by 3σ criteria, and the Gaussian white noise and narrow-band interference signal in the noise dominant component are inversely suppressed. …”
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Impact of Low-dose Imaging on PET Quantitative Accuracy and Image Quality by SU Xuesong, GENG Jianhua, ZHENG Rong, WANG Xuejuan

“…The PBV and BCV exhibit an increase with a reduction in the injected dose, while the CNR of the spheres exhibits a decrease. …”

Association of prognostic nutritional index with all-cause and cardiovascular mortality in adults with depression: NHANES 2005–2018 by Haiyan Ding, Xinchun Zou

“…Each 1-unit increase in PNI was associated with a 12% reduction in the risk of all-cause mortality (HR, 0.88; 95% CI, 0.84–0.93; p < 0.001) and a 12% reduction in the risk of CVD mortality (HR, 0.88; 95% CI, 0.80–0.96; p = 0.006). …”
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Effectiveness of Dietary Guidelines for Reducing Free Sugar Intakes: A Randomised Controlled Trial by Lucy Boxall, Katherine M. Appleton, Emily Arden-Close, Janet James

“…Participants achieving a ≥ 2% reduction in %FS from baseline or <5% %FS intakes and those that did not, were classified as adherent or non-adherent, respectively. …”
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Coordinated Design of Power System Stabilizer and Virtual Inertia Control Using Modified Harris Hawk Optimization for Improving Power System Stability by Mohamad Almas Prakasa, Imam Robandi, Alberto Borghetti, Muhammad Ruswandi Djalal, Waseda Himawari

“…With the optimal damping ratios of 9.94% to 9.96% achieved by HHO-MSS, the overall power system stability improvements, including both local and interarea responses across 38 simulations involving sudden load changes, varying inertia, and different RES levels, are as follows: 41.17% to 70.89% frequency nadir improvement, 25.9% to 67.38% power angle deviation improvement, 84.83% to 85.26% settling time reduction, and 51.57% to 89.73% average error reduction calculated with performance indices. …”
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A new validated Lymphoedema-specific Patient Reported Outcome Measure (LYMPROM) for adults with Lymphoedema. by Melanie Thomas, Marie Gabe-Walters, Ioan Humphreys, Alan Watkins

“…LYMPROM© showed good responsiveness, with strong, positive correlations between total and domain initial and repeat (between four weeks and seven months later) scores, with a slight reduction in scores (-3.8 to -2.0 units) and some indication of relationships between reduction and time interval (Total: p = 0.025; Physical health domain: 0.034; Social health domain: 0.181; Emotional health domain: 0.009).…”
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ADEPNET: A Dynamic-Precision Efficient Posit Multiplier for Neural Networks by Aditya Anirudh Jonnalagadda, Uppugunduru Anil Kumar, Rishi Thotli, Satvik Sardesai, Sreehari Veeramachaneni, Syed Ershad Ahmed

“…This becomes especially useful for performing error-tolerant tasks like deep learning inference computation where low latency and area are a priority. …”
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Modeling Short-Term Drought for SPEI in Mainland China Using the XGBoost Model by Fanchao Zeng, Qing Gao, Lifeng Wu, Zhilong Rao, Zihan Wang, Xinjian Zhang, Fuqi Yao, Jinwei Sun

“…Key findings reveal spatiotemporal prediction patterns: temporal-scale dependencies show all models exhibit limited capability at SPEI-1 (R²: 0.32–0.41, RMSE: 0.68–0.79) but achieve progressive accuracy improvement, peaking at SPEI-12 where CPSO-XGBoost attains optimal performance (R²: 0.85–0.90, RMSE: 0.33–0.43) with 18.7–23.4% error reduction versus baselines. Regionally, humid zones (South China/Central-Southern) demonstrate peak accuracy at SPEI-12 (R² ≈ 0.90, RMSE < 0.35), while arid regions (Northwest Desert/Qinghai-Tibet Plateau) show dramatic improvement from SPEI-1 (R² < 0.35, RMSE > 1.0) to SPEI-12 (R² > 0.85, RMSE reduction > 52%). …”
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Initialization improvement and clustering quality evaluation of K-means algorithm by HE Xuansen, HE Fan, YU Hailan

“…The simulation results show that the average λ test statistic of other algorithms is 2.72 times that of this scheme, and the improved clustering error is reduced by 6.04%.…”
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Limb Body Wall Complex: First Trimester Ultrasonographic Diagnosis of a Case with Exencephaly and Megacystis by Mert Turğal, Aslıhan Yazıcıoğlu, Özgür Özyüncü, M. Sinan Beksaç

“…Despite the anomaly arises from an error occuring during the embryonic folding, the exact pathophysiological mechanisms are poorly understood. …”
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Forecasting Forex EUR/USD Closing Prices Using a Dual-Input Deep Learning Model with Technical and Fundamental Indicators by Abolfazl Saghafi, Maryam Bagherian, Farhad Shokoohi

“…The model outperforms the second-best model, achieving a 29% reduction in mean absolute error (MAE) and root mean squared error (RMSE) in the training set and reductions of 24% and 23% in MAE and RMSE, respectively, in the test set. …”
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An Oracle Normalized Least Mean Square (NLMS) Algorithm and a Simple Bayesian Detection NLMS Algorithm Robust to Impulse Noise by Hadi Zayyani, Yaser Attar

“…Initially, to have a fast algorithm, an optimization problem is introduced and then an oracle NLMS algorithm is devised. It has the largest reduction in misalignment error at each iteration with respect to the previous iteration. …”
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