Exploring the drivers of irregular spending in the EU cohesion policy by Francesco Foglia, Francesco Molica, Anabela M. Santos

“…Overall, the analysis finds that the more complex the programmes (e.g., in terms of number of priorities, multi-fund focus), the higher the risk of irregularities and the more difficult is for programme authorities to detect them. …”
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Probabilistic linkages of propagation from meteorological to agricultural drought in the North African semi-arid region by Younes Dahhane, Victor Ongoma, Abdessamad Hadri, Mohamed Hakim Kharrou, Oualid Hakam, Abdelghani Chehbouni

“…Statistical measures such as Spearman correlation (R), root mean square error (RMSE), and mean absolute error (MAE), are utilized to assess the performance of the meteorological drought index to detect the agricultural drought. …”
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Experimental Study of Smart Steel Cables with Tubular Spot-Welded Grating Sensors by Nianchun Deng, Zhongqing Han, Zhiqian Chen, Zhaotao Chen

“…The measured cable force is compared with the standard load. The maximum error is 0.5% F.S. The discrepancy between the measured cable force and the acceleration sensor value is 1.5% in one instance involving an arch bridge employing six smart suspension cables to detect cable forces onsite. …”
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Inference in skew generalized t-link models for clustered binary outcome via a parameter-expanded EM algorithm. by Chénangnon Frédéric Tovissodé, Aliou Diop, Romain Glèlè Kakaï

“…In addition, empirical standard errors and information criteria proved useful for detecting spurious skewness and avoiding complex models for probit data. …”
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Evaluating the impact of internal control systems on corporate performance of Ghanaian banks: The moderating role of information technology by Samuel Asante Gyamerah, Gifty Laar, Clement Asare

“…It also highlights the significance of monitoring activities in detecting and preventing fraudulent activities, errors, and inefficiencies. …”
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Microstructural characterization and hardness prediction of AlCuCrFeNi high entropy alloys using Transformer-based Physics-Informed Neural Networks (T-PINN) by Mohamed Yasin Abdul Salam, Enoch Nifise Ogunmuyiwa, Victor Kitso Manisa, Abid Yahya, Irfan Anjum Badruddin

“…The T-PINN model demonstrated high accuracy, with a Root Mean Square Error (RMSE) - 0.048, Mean Absolute Error (MAE) of- 0.036, and R-square (R2) - 0.97 values, respectively. …”
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Diffusion models enable zero-shot pose estimation for lower-limb prosthetic users. by Tianxun Zhou, Muhammad Nur Shahril Iskandar, Keng-Hwee Chiam

“…The zero-shot approach achieved substantial reductions in keypoint coordinate errors of 37% for transtibial and 76% for transfemoral prosthetic limbs compared to OpenPose on the original videos. …”
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Children's Misconceptions: Opinions and Practices of Preschool Teachers by Rabia Nimet Gülmez, Ensar Yıldız

“…The majority of teachers evaluated children's readiness to detect their misconceptions. Children made misconceptions by mixing similar concepts, making semantic errors, making linguistic problems and making generalizations. …”
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Revision and validation of the Chinese version of the interpersonal reactivity index for couples for expectant couples by Juju Huang, Tengfei Liang, Jinzhi Li, Qiankun Liu, Jiaxue Pang, Yang Xu, Hui Xie

“…In the sample of pregnant women, the confirmatory factor analysis results indicated that the fit indices for the bi-factor model were satisfactory (Chi-square/degrees of freedom ( $\chi^2$χ2 /df) = 1.331, comparative fit index (CFI) = 0.993, Tucker-Lewis index (TLI) = 0.987, normal fit index (NFI) = 0.972, goodness of fit index (GFI) = 0.958, root mean square error of approximation (RMSEA) = 0.041, standardized root mean square residual (SRMR) = 0.038). …”
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Study on soil moisture estimation using a three-frequency combination of observations integrated with robust estimation and machine learning by Yintao Liu, Chao Ren, Hongjuan Shao

“…Unlike traditional methods that require separating direct and reflected signals, these approaches leverage carrier phase and pseudorange multipath errors to improve accuracy. The new methods eliminate the impact of geometrical factors and atmospheric delays. …”
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Reliability and Accuracy of Ultrasonographic Muscle Thickness Measurements: Evaluating Key Postural Stabilisers in Rehabilitation by Arkadiusz Żurawski, Natalia Barańska, Aleksandra Tomala, Edyta Majorczyk, Joanna Macierzyńska

“…The transversus abdominis demonstrated the highest measurement precision, with the lowest Standard Error of Measurement (SEM = 0.79-1.05 mm) and Minimal Detectable Change (MDC = 2.19-2.91 mm). …”
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Provide a Solution Based on Teacher and Student Learning Algorithm to Reduce Regression Test Cases by Mahmood Deypir, Amirhossein Mohammadpour

“…The aim of selecting test items is to choose a subset that has the potential to detect errors due to changes within the software. …”
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Efficiency Analysis of Turkish Container Ports: SFA or DEA? by İsmail Yenilmez

“…Capacity utilization and operational performance were analyzed in detail through ratio analysis.Methodology: Two efficiency measurement techniques were employed: SFA evaluates efficiency by accounting for random errors and external factors, while DEA assesses relative efficiency by comparing ports to the best performers. …”
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Cephalic measures in normal pre-school children 3 to 7-years of age by A. J. Diament, F. W. Rodrigues

“…The statistical analysis consisted in determining means and standard errors for each measure. For the new cephalic index it was shown through the Kruskal-Wallis test that there were no significant difference between age and sex. …”
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Causal Inference for Spatial Constancy across Saccades. by Jeroen Atsma, Femke Maij, Mathieu Koppen, David E Irwin, W Pieter Medendorp

“…Results showed different localization errors of the three targets, depending on the viewing time of the postsaccadic stimulus and its spatial separation from the presaccadic location. …”
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Meta-Reinforcement Learning reconciles surprise, value, and control in the anterior cingulate cortex. by Tim Vriens, Eliana Vassena, Giovanni Pezzulo, Gianluca Baldassarre, Massimo Silvetti

“…., comparing expectations with outcomes, detecting errors, tracking surprise). A consensus on which theoretical perspective best explains dACC contribution to behaviour is still lacking, as two distinct sets of studies report dACC activation in tasks requiring surprise tracking for performance monitoring and cognitive control without involving surprise monitoring, respectively. …”
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Identification and Correction for Sun Glint Contamination in Microwave Radiation Imager-Rainfall Mission Global Ocean Observations Onboard the FY-3G Satellite by Qiumeng Xue, Xuanyuan Yang, Qiang Zhang, Zhenxing Liu

“…Microwave radiometers are vital for global ocean observations, yet they are prone to errors from radio frequency interference, sun glint, and other contamination. …”
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H and D ∕ H analysis in olivine and wadsleyite with a multi-analytical approach combining Raman spectroscopy and ion and nuclear probes by A. Gautier, N. Bolfan-Casanova, B. Moine, H. Bureau, H. Khodja, A. C. Withers, L. Piani

“…Then we compared the <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M8" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><mi mathvariant="normal">D</mi><mo>/</mo><mi mathvariant="normal">H</mi></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="24pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="c78995d3f67856633c35697a267d9112"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="ejm-37-305-2025-ie00007.svg" width="24pt" height="14pt" src="ejm-37-305-2025-ie00007.png"/></svg:svg></span></span> ratios determined by SIMS to the <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M9" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><mi mathvariant="normal">OD</mi><mo>/</mo><mi mathvariant="normal">OH</mi></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="41pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="2cc1e29e7cbb5e6250616346ce803788"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="ejm-37-305-2025-ie00008.svg" width="41pt" height="14pt" src="ejm-37-305-2025-ie00008.png"/></svg:svg></span></span> intensity ratio determined by Raman spectroscopy for three wadsleyite samples, finding a conversion factor of 0.85 (error of <span class="inline-formula">∼2</span> %). …”
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The JCMT Legacy Release: SCUBA-2 850 μm Coadds and Catalogs by Sarah F. Graves, Jessica T. Dempsey, Graham S. Bell, David S. Berry, Iain M. Coulson, Malcolm J. Currie, Per Friberg, Tim Jenness, Doug Johnstone, Junhao Liu, Steven Mairs, Harriet A. L. Parsons, Harold Pena, Mark G. Rawlings, Holly S. Thomas, Jan G. A. Wouterloot

“…We then examined the accuracy of this calibration for our data set by calculating self-derived FCF values for our two most-used standard sources, finding a result within the expected errors but with a larger standard deviation of 9%. …”
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Relationship between ocular motility and motor skills by Carmen López de la Fuente, Eider Eider Bereau Iridoy, Paula Pardo Sofín, José Luis Cebrián Lafuente, Víctor Berdejo, Cristina Ruiz-Garros, María José López-de-la-Fuente

“…The group with typical motor performance had higher percentiles for both vertical and horizontal time, fewer errors, number of saccades, fixations, and regressions, and faster test performance. …”
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